Latest Articles Include:
- Integrating addiction research
- Nat Neurosci 14(5):533 (2011)
Nature Neuroscience | Editorial Integrating addiction research Journal name:Nature NeuroscienceVolume: 14,Page:533Year published:(2011)DOI:doi:10.1038/nn0511-533Published online26 April 2011 Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Neuroscience for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. A recent proposal to integrate addiction research portfolios from across the National Institutes of Health into a single institute makes scientific sense, but the implementation will require care. View full text Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Neuroscience for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data - The ups and downs of seizure activity
- Nat Neurosci 14(5):535-536 (2011)
Nature Neuroscience | News and Views The ups and downs of seizure activity * Matthew C Walker1Journal name:Nature NeuroscienceVolume: 14,Pages:535–536Year published:(2011)DOI:doi:10.1038/nn.2811Published online26 April 2011 Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Neuroscience for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. A study this issue by Truccolo et al. analyzing extended recordings of single-neuron activity in human neocortical epilepsy, demonstrates that, even in areas remote from the seizure focus, neuronal firing patterns alter minutes before seizure onset, are heterogeneous during seizures, and change homogeneously at seizure offset. View full text Author information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Matthew C. Walker is at the University College London Institute of Neurology, University College London, London, UK. Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Matthew C Walker Author Details * Matthew C Walker Contact Matthew C Walker Search for this author in: * NPG journals * PubMed * Google Scholar Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Neuroscience for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data - Calcium channels put synapses in their place
- Nat Neurosci 14(5):536-538 (2011)
Nature Neuroscience | News and Views Calcium channels put synapses in their place * Justin R Fallon1Journal name:Nature NeuroscienceVolume: 14,Pages:536–538Year published:(2011)DOI:doi:10.1038/nn.2822Published online26 April 2011 Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Neuroscience for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Synapse density and patterning must be tightly regulated to ensure proper circuit formation and function. A new report finds that postsynaptic L-type calcium channels control the pattern and differentiation of developing synapses. View full text Author information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * The author is in the Department of Neuroscience, Brown University, Providence, Rhode Island, USA. * Justin R Fallon Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Justin R Fallon Author Details * Justin R Fallon Contact Justin R Fallon Search for this author in: * NPG journals * PubMed * Google Scholar Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Neuroscience for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data - Hanging by the tail: progenitor populations proliferate
- Nat Neurosci 14(5):538-540 (2011)
Nature Neuroscience | News and Views Hanging by the tail: progenitor populations proliferate * Zoltán Molnár1 * Navneet A Vasistha1 * Fernando Garcia-Moreno1 * Affiliations * Corresponding authorJournal name:Nature NeuroscienceVolume: 14,Pages:538–540Year published:(2011)DOI:doi:10.1038/nn.2817Published online26 April 2011 Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Neuroscience for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. A study now identifies a new progenitor subtype in the developing mouse cortex, similar to the outer radial glia progenitors described previously in human, ferret and other mammals with larger, folded brains. View full text Author information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Zoltán Molnár, Navneet A. Vasistha and Fernando Garcia-Moreno are in the Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Zoltán Molnár Author Details * Zoltán Molnár Contact Zoltán Molnár Search for this author in: * NPG journals * PubMed * Google Scholar * Navneet A Vasistha Search for this author in: * NPG journals * PubMed * Google Scholar * Fernando Garcia-Moreno Search for this author in: * NPG journals * PubMed * Google Scholar Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Neuroscience for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data - Scratching the surface: a role of pain-sensing TRPA1 in itch
- Nat Neurosci 14(5):540-542 (2011)
Nature Neuroscience | News and Views Scratching the surface: a role of pain-sensing TRPA1 in itch * Bailong Xiao1 * Ardem Patapoutian2 * Affiliations * Corresponding authorJournal name:Nature NeuroscienceVolume: 14,Pages:540–542Year published:(2011)DOI:doi:10.1038/nn.2813Published online26 April 2011 Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Neuroscience for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. The molecular mechanisms of itch, particularly histamine-independent itch, are unclear. Wilson et al. report that TRPA1, an ion channel critical for pain sensation, also functions as an essential component of itch transduction. View full text Author information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Bailong Xiao and Ardem Patapoutian are in the Department of Cell Biology and Dorris Neuroscience Center, The Scripps Research Institute, La Jolla, California, USA * Ardem Patapoutian is also at the Genomics Institute of the Novartis Research Foundation, San Diego, California, USA. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Ardem Patapoutian Author Details * Bailong Xiao Search for this author in: * NPG journals * PubMed * Google Scholar * Ardem Patapoutian Contact Ardem Patapoutian Search for this author in: * NPG journals * PubMed * Google Scholar Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Neuroscience for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data - The visual attention network untangled
- Nat Neurosci 14(5):542-543 (2011)
Nature Neuroscience | News and Views The visual attention network untangled * Sander Nieuwenhuis1 * Tobias H Donner2 * Affiliations * Corresponding authorsJournal name:Nature NeuroscienceVolume: 14,Pages:542–543Year published:(2011)DOI:doi:10.1038/nn.2812Published online26 April 2011 Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Neuroscience for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Goals are represented in prefrontal cortex and modulate sensory processing in visual cortex. A new study combines TMS, fMRI and EEG to understand how feedback improves retention of behaviorally relevant visual information. View full text Author information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Sander Nieuwenhuis is at the Leiden Institute for Brain and Cognition, Leiden University, Leiden, The Netherlands * Tobias H. Donner is in the Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Sander Nieuwenhuis or * Tobias H Donner Author Details * Sander Nieuwenhuis Contact Sander Nieuwenhuis Search for this author in: * NPG journals * PubMed * Google Scholar * Tobias H Donner Contact Tobias H Donner Search for this author in: * NPG journals * PubMed * Google Scholar Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Neuroscience for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data - Aβ1–42 inhibition of LTP is mediated by a signaling pathway involving caspase-3, Akt1 and GSK-3β
- Nat Neurosci 14(5):545-547 (2011)
Nature Neuroscience | Brief Communication Aβ1–42 inhibition of LTP is mediated by a signaling pathway involving caspase-3, Akt1 and GSK-3β * Jihoon Jo1, 5 * Daniel J Whitcomb1, 5 * Kimberly Moore Olsen2 * Talitha L Kerrigan1 * Shih-Ching Lo2 * Gilles Bru-Mercier1 * Bryony Dickinson1 * Sarah Scullion1, 3 * Morgan Sheng2 * Graham Collingridge3, 4 * Kwangwook Cho1, 3 * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 14,Pages:545–547Year published:(2011)DOI:doi:10.1038/nn.2785Received13 December 2010Accepted18 February 2011Published online27 March 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Amyloid-β1–42 (Aβ) is thought to be a major mediator of the cognitive deficits in Alzheimer's disease. The ability of Aβ to inhibit hippocampal long-term potentiation provides a cellular correlate of this action, but the underlying molecular mechanism is only partially understood. We found that a signaling pathway involving caspase-3, Akt1 and glycogen synthase kinase-3β is an important mediator of this effect in rats and mice. View full text Figures at a glance * Figure 1: Identification of a role for caspases in Aβ inhibition of LTP. (,) A pairing protocol induced LTP in control cultured slices (n = 6, ), but not following a 2-h Aβ pretreatment (n = 6, ). (–) CA1 neurons were transfected with either XIAP, BIR1,2, BIR3 or CrmA (co-transfected with GFP) in Aβ-treated slices. () LTP was induced in XIAP-transfected cells (open symbol, n = 6), but not in simultaneously recorded nontransfected cells (closed symbol, n = 6). () LTP was induced in BIR1,2-transfected cells (open symbol, n = 6), but not in nontransfected cells (closed symbol, n = 6). () LTP was inhibited in BIR3-transfected cells (n = 6) and () in CrmA-transfected cells (n = 6). Error bars represent s.e.m. * Figure 2: Caspase-3 and cleavage of Akt1 are involved in the Aβ inhibition of LTP. () LTP could be induced in acute hippocampal slices from Casp3+/+ mice (closed symbol, n = 12), but was inhibited following Aβ treatment (open symbol, n = 11). () LTP could be induced in acute hippocampal slices from Casp3−/− mice (closed symbol, n = 12), even following Aβ treatment (open symbol, n = 11). () LTP was induced in triple mutant Akt1–transfected cells, but not in neighboring nontransfected cells in the same slices receiving Aβ pretreatment (n = 6). () LTP could not be induced in wild-type Akt1–transfected cells following Aβ treatment (n = 6). Error bars represent s.e.m. * Figure 3: Aβ inhibition of LTP is reversed by blockade of GSK-3. () Active caspase-3 was enhanced by both 30-min and 2-h Aβ treatments. Bar chart shows pooled data (n = 4, four independent experiments from four rats); O.D., optical density of signal. () GSK-3 activity (reduction in phosphorylation of serine 9) was increased after 30 min and 2 h of Aβ treatment. Bar chart shows pooled data (n = 4, four independent experiments from four rats). () Pre-incubation of cultured slices with CT-99021 (1 μM) prevented Aβ inhibition of LTP (n = 6). () CT-99021 alone had no effect on LTP (n = 6). () CT-99021 prevented Aβ inhibition of LTP in acute slices (CT-99021 with Aβ, triangle, n = 6; Aβ alone, circle, n = 5). () LTP induction in two independent pathways following first tetanus (input 1) and second tetanus (input 2, 60 min after first tetanus) in control slices (n = 5). () LTP was completely inhibited in both inputs following a 2-h Aβ treatment (n = 5) before the first tetanus. () Pooled data showing that CT-99021 (applied from 30 min be! fore the second tetanus) rescued Aβ inhibition of LTP (n = 5). *P < 0.05, **P < 0.01. Error bars represent s.e.m. Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Jihoon Jo & * Daniel J Whitcomb Affiliations * Henry Wellcome Laboratories for Integrative Neuroscience and Endocrinology, School of Clinical Sciences, Faculty of Medicine and Dentistry, University of Bristol, Bristol, UK. * Jihoon Jo, * Daniel J Whitcomb, * Talitha L Kerrigan, * Gilles Bru-Mercier, * Bryony Dickinson, * Sarah Scullion & * Kwangwook Cho * Department of Neuroscience, Genentech Inc., South San Francisco, California, USA. * Kimberly Moore Olsen, * Shih-Ching Lo & * Morgan Sheng * MRC Centre for Synaptic Plasticity, University of Bristol, Bristol, UK. * Sarah Scullion, * Graham Collingridge & * Kwangwook Cho * School of Physiology and Pharmacology, University of Bristol, Bristol, UK. * Graham Collingridge Contributions The study was conceived by K.C. The experiments were designed by K.C., M.S. and G.L.C. and carried out by J.J., D.J.W., K.M.O., T.L.K., J.S.L., G.B., B.D. and S.S. The manuscript was written by G.L.C., M.S. and K.C. Competing financial interests K.M.O., S.-C.L. and M.S. are employees of Genentech. Corresponding author Correspondence to: * Kwangwook Cho Author Details * Jihoon Jo Search for this author in: * NPG journals * PubMed * Google Scholar * Daniel J Whitcomb Search for this author in: * NPG journals * PubMed * Google Scholar * Kimberly Moore Olsen Search for this author in: * NPG journals * PubMed * Google Scholar * Talitha L Kerrigan Search for this author in: * NPG journals * PubMed * Google Scholar * Shih-Ching Lo Search for this author in: * NPG journals * PubMed * Google Scholar * Gilles Bru-Mercier Search for this author in: * NPG journals * PubMed * Google Scholar * Bryony Dickinson Search for this author in: * NPG journals * PubMed * Google Scholar * Sarah Scullion Search for this author in: * NPG journals * PubMed * Google Scholar * Morgan Sheng Search for this author in: * NPG journals * PubMed * Google Scholar * Graham Collingridge Search for this author in: * NPG journals * PubMed * Google Scholar * Kwangwook Cho Contact Kwangwook Cho Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (372K) Supplementary Figures 1, 2 and Supplementary Methods Additional data - Sensory modality–specific homeostatic plasticity in the developing optic tectum
- Nat Neurosci 14(5):548-550 (2011)
Nature Neuroscience | Brief Communication Sensory modality–specific homeostatic plasticity in the developing optic tectum * Katherine E Deeg1 * Carlos D Aizenman1 * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 14,Pages:548–550Year published:(2011)DOI:doi:10.1038/nn.2772Received12 October 2010Accepted01 February 2011Published online27 March 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg We found a previously unknown form of homeostatic synaptic plasticity in multisensory neurons in the optic tectum of Xenopus laevis tadpoles. Individual tectal neurons are known to receive converging inputs from multiple sensory modalities. We observed that long-term alterations in either visual or mechanosensory activity in vivo resulted in homeostatic changes specific to each sensory modality. In contrast with typical forms of homeostatic synaptic plasticity, such as synaptic scaling, we found that this type of plasticity occurred in a pathway-specific manner that is more reminiscent of Hebbian-type plasticity. View full text Figures at a glance * Figure 1: Multisensory convergence in optic tectal neurons. () Stimulation and recording configuration. Using a whole-brain preparation from Xenopus tadpoles, stimulating (stim.) electrodes were placed in the optic chiasm and contralateral hindbrain (HB) to activate visual (V) or mechanosensory inputs to the tectum. Whole-cell recordings (rec.) were performed from optic tectal neurons. () Extracellular Ca2+ was substituted with Sr2+ to evoke aEPSCs. () aEPSCs evoked by either hindbrain or visual stimulation were not significantly different (P = 0.359). () Scatter plot of aEPSC amplitude evoked by each pathway. () Cumulative probability distribution of aEPSC amplitudes from both pathways superimposed with sEPSC amplitudes showed no differences in amplitude distributions. * Figure 2: Modality-specific changes in aEPSC amplitude after various sensory manipulations. () aEPSCs evoked by visual or hindbrain stimulation after 48 h of visual deprivation (left), enhanced mechanosensory stimulation (middle) or enhanced mechanosensory stimulation in the presence of the inhibitory blocker PTX (right). () Comparison of hindbrain and visual stimulation after various experimental conditions. Symbols next to paired data represent average values and error bars represent s.e.m. Davg, dark average; Mavg, mechanosensory average; MPavg, mechanosensory average and PTX. () Scatterplot of aEPSC amplitude evoked by each pathway after various experimental conditions. () Cumulative probability distribution of aEPSC amplitudes from both pathways superimposed with sEPSC amplitudes after various experimental conditions. *P < 0.05. * Figure 3: Summary of synaptic changes after in vivo sensory manipulations. () Averaged data comparing aEPSC amplitude evoked by visual and mechanosensory (mech) pathways under various conditions. Notice modality specific changes. () Cumulative probability plots of sEPSC amplitudes from different experimental groups: C, control; D, dark; M, mechanosensory; M+PTX, mechanosensory plus PTX. Inset shows average sEPSC amplitudes across conditions. Error bars are s.e.m., *P < 0.05. For direct comparisons, see Supplementary Figure 5. Author information * Author information * Supplementary information Affiliations * Brown University, Department of Neuroscience, Providence, Rhode Island, USA. * Katherine E Deeg & * Carlos D Aizenman Contributions K.E.D. and C.D.A. worked on the experimental design, performed the experiments and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Carlos D Aizenman Author Details * Katherine E Deeg Search for this author in: * NPG journals * PubMed * Google Scholar * Carlos D Aizenman Contact Carlos D Aizenman Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (928K) Supplementary Figures 1–5 and Supplementary Methods Additional data - The newly sighted fail to match seen with felt
- Nat Neurosci 14(5):551-553 (2011)
Nature Neuroscience | Brief Communication The newly sighted fail to match seen with felt * Richard Held1 * Yuri Ostrovsky1 * Beatrice deGelder2 * Tapan Gandhi3 * Suma Ganesh4 * Umang Mathur4 * Pawan Sinha1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature NeuroscienceVolume: 14,Pages:551–553Year published:(2011)DOI:doi:10.1038/nn.2795Received22 December 2010Accepted03 March 2011Published online10 April 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Would a blind subject, on regaining sight, be able to immediately visually recognize an object previously known only by touch? We addressed this question, first formulated by Molyneux three centuries ago, by working with treatable, congenitally blind individuals. We tested their ability to visually match an object to a haptically sensed sample after sight restoration. We found a lack of immediate transfer, but such cross-modal mappings developed rapidly. View full text Figures at a glance * Figure 1: Stimuli and testing procedure. () Four examples from the set of 20 shape pairs used in our experiments. () The match-to-sample procedure. The within-modality tactile match to tactile sample task assesses haptic capability and task understanding. The visual match to visual sample task provides a convenient way to assess whether subjects' form vision is sufficient for visually discriminating between test objects. The tactile match to visual sample task represents the critical test of intermodal transfer. T, touch; V, vision; s, sample; d, distractor. * Figure 2: Intra- and inter-modal matching results. () Within-modality and cross-modality match to sample performance of five newly sighted individuals 2 d after sight onset. Newly sighted subjects exhibited excellent performance on the touch-to-touch (T-T) and vision-to-vision (V-V) tasks, but were near chance on the transfer (T-V) task. For each of the touch-to-touch and vision-to-vision sessions, P < 0.003 (two-tailed binomial test). For each of the transfer sessions, P > 0.25. "Average", average performance across subjects. *P < 0.05. () Visual match to tactile sample performance of three subjects across two post-operative assessments. Subjects exhibited significant improvement in cross-modal transfer a short duration after the first assessment. For each of the first transfer sessions, P > 0.25 (two-tailed binomial test). For each of the follow-up sessions shown above, P < 0.015. Author information * Author information * Supplementary information Affiliations * Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. * Richard Held, * Yuri Ostrovsky & * Pawan Sinha * Tilburg University, Tilburg, The Netherlands. * Beatrice deGelder * Indian Institute of Technology, New Delhi, India. * Tapan Gandhi * Dr. Shroff's Charity Eye Hospital, New Delhi, India. * Suma Ganesh & * Umang Mathur Contributions R.H., B.d.G., P.S. and Y.O. designed the study. S.G. and U.M. performed the surgical procedures and conducted the ophthalmic assessments. R.H., Y.O., T.G., B.d.G. and P.S. conducted the match-to-sample experiments and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Richard Held or * Pawan Sinha Author Details * Richard Held Contact Richard Held Search for this author in: * NPG journals * PubMed * Google Scholar * Yuri Ostrovsky Search for this author in: * NPG journals * PubMed * Google Scholar * Beatrice deGelder Search for this author in: * NPG journals * PubMed * Google Scholar * Tapan Gandhi Search for this author in: * NPG journals * PubMed * Google Scholar * Suma Ganesh Search for this author in: * NPG journals * PubMed * Google Scholar * Umang Mathur Search for this author in: * NPG journals * PubMed * Google Scholar * Pawan Sinha Contact Pawan Sinha Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (115K) Supplementary Methods Additional data - A new subtype of progenitor cell in the mouse embryonic neocortex
- Nat Neurosci 14(5):555-561 (2011)
Nature Neuroscience | Article A new subtype of progenitor cell in the mouse embryonic neocortex * Xiaoqun Wang1, 2 * Jin-Wu Tsai1, 2 * Bridget LaMonica1, 2, 3 * Arnold R Kriegstein1, 2 * Affiliations * Contributions * Corresponding authorsJournal name:Nature NeuroscienceVolume: 14,Pages:555–561Year published:(2011)DOI:doi:10.1038/nn.2807Received09 September 2010Accepted17 March 2011Published online10 April 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg A hallmark of mammalian brain evolution is cortical expansion, which reflects an increase in the number of cortical neurons established by the progenitor cell subtypes present and the number of their neurogenic divisions. Recent studies have revealed a new class of radial glia–like (oRG) progenitor cells in the human brain, which reside in the outer subventricular zone. Expansion of the subventricular zone and appearance of oRG cells may have been essential evolutionary steps leading from lissencephalic to gyrencephalic neocortex. Here we show that oRG-like progenitor cells are present in the mouse embryonic neocortex. They arise from asymmetric divisions of radial glia and undergo self-renewing asymmetric divisions to generate neurons. Moreover, mouse oRG cells undergo mitotic somal translocation whereby centrosome movement into the basal process during interphase precedes nuclear translocation. Our finding of oRG cells in the developing rodent brain fills a gap in our un! derstanding of neocortical expansion. View full text Figures at a glance * Figure 1: oRG cells in the developing mouse neocortex. () Labeling of radial glia and oRG-like cells (white arrows) with adeno-GFP. Note the oRG-like cell (box 1) that has a long basal process (open arrowheads) but no apical process. Red arrowhead, presumed oRG daughter cell. High-magnification images are shown at right (1 and 2). IZ, intermediate zone; VZ, ventricular zone. Scale bars, 50 μm (left) and 15 μm (right). () Representative oRG-like cell (arrow); open arrowheads indicate the basal process. CP, cortical plate. Scale bar, 25 μm. () Phosphovimentin (green) labels oRG cells in mitosis. The basal process has varicosities characteristic of M phase oRG cells. The oRG-like cells stain with radial glial progenitor markers Pax6 (blue) and Sox2 (red). Arrows indicate triple-positive oRG-like cells; open arrowheads indicate basal process. Scale bars, 50 μm (left) and 10 μm (right). () Quantification of the percentage of mitotic, basal process bearing oRG-like cells identified as P-vim+Pax6+Sox2+ by immunostaining in the VZ ! (92.95 ± 5.90%) and superficial SVZ plus IZ (7.05 ± 3.70%) (total 78 cells from six mice). () P-vim+ (green) oRG cells at E16.5 stain for Sox2 (red) but are Tbr2− (blue; an intermediate progenitor marker). High-magnification images of the representative outlined cell are shown to the right. Arrows indicate oRG-like cells co-stained for P-vim (green) and Sox2 (red); open arrowheads indicate the basal process. Scale bars, 50 μm (left) and 10 μm (right). Error bars, s.e.m. * Figure 2: oRG cells undergo mitotic somal translocation. () Experimental procedure for time lapse. () oRG-like cells undergo mitotic somal translocation before mitosis (see Supplementary Movie 1). Arrows indicate oRG-like cells (white) and a non-oRG daughter (red). Asterisks indicate the characteristic swelling in the proximal basal process. Dashed line indicates the cleavage plane. Scale bar, 20 μm; time stamp, h:min. () Representative image showing method for measuring mitotic somal translocation distances. Average distance, 23.56 ± 1.56 μm (from 114 time-lapse sequences). () Dual-labeled oRG cell (box, cell 1) 1 d after electroporation in utero at E13.5. Right, high-magnification images of mitotic cell behavior from the outlined regions. IZ, intermediate zone; VZ, ventricular zone. Scale bars, 50 μm (left) and 10 μm (right). () Three-dimensional illustration of oRG cell distribution pattern in E16 brain. Yellow rings indicate the locations of mouse oRG cells. Blue, Pax6; green, P-vim; red, Sox2. (–) Quantification of the! percentage of Pax6+P-vim+Sox2+ cells located in the outer region of ventricular zone and SVZ versus total triple-positive cells located in the entire developing neocortex. *P < 0.05; **P < 0.005; ***P < 0.001; error bars, s.e.m. * Figure 3: oRG cells generate neurons. () Experimental procedure for time-lapse analysis of oRG-like cell behavior by in utero pial surface injection of GFP-expressing adenovirus. () Time-lapse images of daughter neuron migration after oRG division. The apical daughter cell becomes bipolar after ~30 h and migrates radially (see Supplementary Movie 4). White arrows indicate the oRG cell; white arrowheads, the daughter neuron. Scale bar, 15 μm; time stamp, h:min. () Asymmetric division of an oRG cell (arrows) generates a self-renewed oRG cell (arrows) and a daughter neuron (arrowheads; see Supplementary Movie 5). () The oRG daughter was Pax6+ (a neuronal stem cell marker, blue), and the non-oRG daughter was NeuN+ (a neuronal marker, red) after 12 h more in culture. DNA, white. Scale bar, 10 μm. * Figure 4: oRG cells originate from radial glia cells. () Time-lapse image of radial glia cell division. A GFP-labeled radial glia cell was monitored at 15-min intervals (white arrow) 2 d after in utero intraventricular retrovirus infection at E11.5. Asymmetric radial glia cell division generates a self-renewed radial glia cell (red arrow), which divides again (yellow arrowheads). The first radial glia daughter cell (white arrowhead) undergoes mitotic somal translocation and divides; white and red arrowheads follow the two daughter cells after oRG division (see Supplementary Movie 6). Scale bar, 10 μm. () Lineage tree of radial glia and oRG cell divisions. Radial glia cells can divide asymmetrically to self-renew and generate oRG cells. Both progenitors can divide again to self-renew and generate daughter cells including neurons (N) and intermediate progenitors (IP). * Figure 5: Distinct behavior of centrosomes in different progenitor cells. (–) Time-lapse images of centrosome dynamics in oRG cells (; see Supplementary Movie 7), radial glia cells (; see Supplementary Movie 8) and intermediate progenitor cells (; see Supplementary Movie 9). High-magnification images from the outlined regions are shown below. Arrows indicate centrosomes. Scale bars, 10 μm (top) and 2.5 μm (bottom). Author information * Abstract * Author information * Supplementary information Affiliations * Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco, San Francisco, California, USA. * Xiaoqun Wang, * Jin-Wu Tsai, * Bridget LaMonica & * Arnold R Kriegstein * Department of Neurology, University of California San Francisco, San Francisco, California, USA. * Xiaoqun Wang, * Jin-Wu Tsai, * Bridget LaMonica & * Arnold R Kriegstein * Neuroscience Graduate Program, University of California San Francisco, San Francisco, California, USA. * Bridget LaMonica Contributions X.W. conceived the project and carried out most of the experiments. J.-W.T. helped on some of the time-lapse imaging experiments and B.L. helped on the immunohistochemistry staining procedure. X.W. analyzed data, interpreted results and wrote the manuscript. A.R.K., as the principal investigator, provided conceptual and technical guidance for all aspects of the project. All authors edited the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Xiaoqun Wang or * Arnold R Kriegstein Author Details * Xiaoqun Wang Contact Xiaoqun Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Jin-Wu Tsai Search for this author in: * NPG journals * PubMed * Google Scholar * Bridget LaMonica Search for this author in: * NPG journals * PubMed * Google Scholar * Arnold R Kriegstein Contact Arnold R Kriegstein Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information Movies * Supplementary Movie 1 (21M) This movie shows an example of mitotic somal translocation and oRG cell division. An oRG cell undergoes mitotic somal translocation and divides. The upper cell inherits the basal fiber whereas the lower cell rapidly extends a prominent process towards the ventricle. Images were acquired every 10 min and the play rate is seven frames per second. * Supplementary Movie 2 (4M) This movie shows interkinetic nuclear migration (INM) of RG cells in mouse neocortex. An RG cell undergoes INM and divides at the VZ surface. Images were acquired every 10 min and the play rate is seven frames per second. * Supplementary Movie 3 (6M) This movie shows an example of two IP cell divisions in situ. Two IP cells divide in situ without nuclear translocation. Images were acquired every 10 min and the play rate is seven frames per second. * Supplementary Movie 4 (65M) This movie shows an oRG cell that divides and generates a daughter neuron. An oRG cell undergoes mitotic somal translocation and divides. The apical daughter cell acquires neuronal morphology 40 h after division, and extends a leading process toward the pia. After acquiring a short trailing process, the bipolar daughter cell migrates rapidly to the cortical plate. Images were acquired every 30 min and the play rate is seven frames per second. * Supplementary Movie 5 (2M) This movie shows an example of an asymmetric oRG cell division that yields a daughter oRG cell and a daughter neuron. Cell fate was revealed by immunostaining with anti-Pax6 (progenitor marker) and anti-NeuN (neuronal marker) after 12h further culture following time-lapse imaging. * Supplementary Movie 6 (4M) This movie shows an example of oRG cells originating from RG cells. Two days after in-utero intra-ventricular retrovirus infection at E11.5, a GFP-labelled RG cell was monitored at 15-min intervals. Asymmetric division of the RG cell generates a self-renewed RG cell, which undergoes a second division. Another daughter cell undergoes mitotic somal translocation before mitosis, a defining feature of oRG cell behaviour. Images were acquired every 15 min and the play rate is seven frames per second. * Supplementary Movie 7 (8M) This movie shows centrosome behaviour in mitotic oRG cells. The centrosome is revealed by DsRedex-Centrin1. Frames were acquired every 10 min and the play rate is seven frames per second. * Supplementary Movie 8 (811K) This movie shows centrosome behaviour in mitotic RG cells. The centrosome is revealed by DsRedex-Centrin1. Frames were acquired every 10 min and the play rate is seven frames per second. * Supplementary Movie 9 (2M) This movie shows centrosome behaviour in mitotic IP cells. The centrosome is revealed by DsRedex-Centrin1. Frames were acquired every 10 min and the play rate is seven frames per second. * Supplementary Movie 10 (1M) This movie shows interkinetic nuclear migration (INM) of a group of RG cells in mouse neocortex. The group of RG cell undergoes INM and divides at the VZ surface. Images were acquired every 10 min and the play rate is seven frames per second. * Supplementary Movie 11 (926K) This movie shows no oRG cells mitosis after purposely severing the apical processes of radial glial cells. We used a scalpel to remove the apical surface of the VZ in order to sever the apical processes of radial glial cells. This process disrupted INM and division of RG cells at the VZ surface and does not produce oRG-like cell mitosis. Images were acquired every 10 min and the play rate is seven frames per second. PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–6, Supplementary Movies 1–11 Additional data - SFRPs act as negative modulators of ADAM10 to regulate retinal neurogenesis
- Nat Neurosci 14(5):562-569 (2011)
Nature Neuroscience | Article SFRPs act as negative modulators of ADAM10 to regulate retinal neurogenesis * Pilar Esteve1, 2, 3 * Africa Sandonìs1, 2, 3 * Marcos Cardozo1, 2, 3 * Jordi Malapeira4, 5, 6 * Carmen Ibañez1 * Inmaculada Crespo1, 2, 3 * Severine Marcos1, 2, 3 * Sara Gonzalez-Garcia1 * Maria Luisa Toribio1 * Joaquin Arribas4, 5, 6 * Akihiko Shimono7 * Isabel Guerrero1 * Paola Bovolenta1, 2, 3 * Affiliations * Contributions * Corresponding authorsJournal name:Nature NeuroscienceVolume: 14,Pages:562–569Year published:(2011)DOI:doi:10.1038/nn.2794Received22 December 2010Accepted02 March 2011Published online10 April 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg It is well established that retinal neurogenesis in mouse embryos requires the activation of Notch signaling, but is independent of the Wnt signaling pathway. We found that genetic inactivation of Sfrp1 and Sfrp2, two postulated Wnt antagonists, perturbs retinal neurogenesis. In retinas from Sfrp1−/−; Sfrp2−/− embryos, Notch signaling was transiently upregulated because Sfrps bind ADAM10 metalloprotease and downregulate its activity, an important step in Notch activation. The proteolysis of other ADAM10 substrates, including APP, was consistently altered in Sfrp mutants, whereas pharmacological inhibition of ADAM10 partially rescued the Sfrp1−/−; Sfrp2−/− retinal phenotype. Conversely, ectopic Sfrp1 expression in the Drosophila wing imaginal disc prevented the expression of Notch targets, and this was restored by the coexpression of Kuzbanian, the Drosophila ADAM10 homolog. Together, these data indicate that Sfrps inhibit the ADAM10 metalloprotease, which mig! ht have important implications in pathological events, including cancer and Alzheimer's disease. View full text Figures at a glance * Figure 1: Neurogenesis is impaired in the central retina of Sfrp1−/−; Sfrp2−/− embryos. (–) Frontal cryostat sections of E16.5 (–,,), E12.5 (,), E11.5 (–) and E10.5 (,) control and Sfrp1−/−; Sfrp2−/− retinas immunostained with antibodies against Tuj1 (differentiated cells), Islet1 (RGCs and amacrine cells), Pax6 (RGCs and amacrine cells), Otx2 (bipolar cells and photoreceptors), PKC (bipolar cells) and BrdU (proliferating precursors) and counterstained with DAPI (blue; – and ,). RGCs and amacrine cells are increased, whereas bipolar cells are decreased in the mutant retinas. Proliferation in the mutant retinas is increased at early stages but is reduced at E16.5 as compared to controls (compare to ). () Quantification of BrdU+, Islet1+, Otx2+ and PKC+ cells. Positive cells were counted in equivalent areas of the central retina. Error bars are s.e.m. of at least three sections from four different embryos (n = 4). cNR, central neural retina; le, lens; RPE, retina pigmented epithelium. *P < 0.05; **P < 0.01; ***P < 0.001. Scale bar, 30 μm (–,,);! 60 μm (,); 100 μm (,). * Figure 2: Notch signaling is transiently upregulated in Sfrp1−/−; Sfrp2−/− retinas. (–) Frontal cryostat sections of E12.5 (), E13.5 () and E16.5 () control and mutant embryos immunostained with antibodies against NICD () or hybridized with probes specific for Hes5 () or Dll-1 (). Note the initial expansion of NICD and Hes5 expression in the mutants (arrowheads in ). The expression of Dll-1 is instead downregulated. () Quantification of the number of NICD+ cells in the neural retina. Positive cells were counted in equivalent areas. Error bars are s.e.m. of at least three sections. Four embryos were analyzed in each case (n = 4). () Western blot analysis of the levels of Notch processing in lysates of E12.5 cortex from mutant and control embryos. The cleaved Notch fragment (NICD) is increased in the mutants as determined by band intensity quantification normalized with α-tubulin (3.5 versus 1.2 in controls), although Notch is expressed at similar levels in both tissues (1.482 versus 1.46 in controls). The data represent a typical experiment, which was rep! eated four times with similar results. Scale bar: 30 μm (); 50 μm (); 100 μm (). * Figure 3: Inhibition of ADAM10 partially rescues the retinal phenotype of Sfrp1−/−; Sfrp2−/− embryos. (–) Cryostat sections of organotypic optic cup cultures from E11.5 controls () or Sfrp1−/−; Sfrp2−/− () embryos cultured for 24 h in the presence of DMSO () or 1–5 μM of the ADAM10 inhibitor G1254023X (). Sections were immunostained with antibodies against BrdU () or Islet1 (). () Quantification of BrdU+ and Islet1+ cells. Positive cells were counted in equivalent areas of the central retina. Note that cultured retinas from Sfrp1−/−; Sfrp2−/− embryos show an increase in cell proliferation and differentiation similar to that observed in vivo. Addition of 1–2 μM G1254023X is sufficient to decrease proliferation but not differentiation to that of controls. Error bars are s.e.m. of at least three sections from five cultures (n = 5). *,#P < 0.05. **, ##P < 0.01. ***, ###P < 0.001. Asterisks indicate comparison between controls and GX-treated mutant cultures; hash marks between DMSO- and G1254023X-treated mutant cultures. Scale bar: 30 μm. α-tubulin (αtu! b) was used as a loading control. * Figure 4: Sfrps interfere with ADAM10-mediated processing of N-cadherin and L1. (,) Western blot analysis of L1 () and N-cadherin () processing in lysates of retinas from E13.5 and E16.5 mutant and control embryos. The 32-kDa L1 and 35-kDa N-cadherin fragments (CTFs) are increased in Sfrp1−/−; Sfrp2−/− mutants as determined by band intensity quantification normalized to α-tubulin (4.4 versus 2.58 in controls for L1, and 6.51 versus 3.86 in controls for N-cadherin). The data represent a typical experiment, which was repeated three times with similar results. () Increased N-cadherin processing is paralleled by loss of membrane-bound active β-catenin in the mutant retinas as compared to controls. Scale bar: 30 μm. * Figure 5: Sfrps interferes with ADAM10-mediated processing of APP. () Western blot analysis of total (APP) and soluble (sAPPα) present in lysates from the subventricular zone of the lateral ventricles from wild-type (WT) and Sfrp1−/− adult brains. The amount of sAPPα fragment is increased in mutants (normalized density values to α-tubulin: 11.1 versus 1.32 in controls). The data represent a typical experiment, which was repeated three times with similar results. () Western blot analysis of total APP and soluble sAPPα, respectively, in the cell lysate and conditioned medium of CHO cells stably transfected with Sfrp2 or Sfrp1 constructs (, left column; densitometric analysis of sAPPα in the medium normalized to Ponceau-stained vector: 10.9 ± 2.2; Sfrp2: 13.3 ± 0.7; Sfrp1: 5.2 ± 1.7) or of CHO cells incubated with purified Sfrp1 or Sfrp2 proteins (; densitometric analysis of sAPPα in the medium normalized to Ponceau-stained vector: 10.0 ± 1.6; Sfrp2: 11.8 ± 0.7; Sfrp1: 4.1 ± 2.2). In both cases Sfrp1, but not Sfrp2, decreases t! he amount of secreted APP without changing the levels of APP in the cell lysates. * Figure 6: Sfrps interacts with ADAM10. () Embryonic telencephalic and ocular tissue from wild-type and Sfrp mutants were immunoprecipitated with antibodies to Sfrp1 and analyzed by western blot with antibodies to ADAM10. Asterisks in the upper panel indicate the coimmunoprecipitation of ADAM10 in wild-type tissue. Asterisks in the middle panel indicate Sfrp1 in wild-type tissue. Asterisks in the bottom panel indicate ProADAM10 and ADAM10 bands. The data represent a typical experiment, which was repeated five times with similar results. () HEK 293T cells were transiently transfected with expression plasmids of ADAM-myc, Sfrp1-HA or a combination of both. After 48 h cell lysates were precipitated with anti-myc and analyzed by western blot with antibodies to HA. Note that ADAM10 can immunoprecipitate Sfrp1 (asterisk). The data represent a typical experiment, which was repeated five times with similar results. () CHO cells were transfected with an ADAM10 expression plasmid or with the empty vector. Cells were thereaf! ter incubated with conditioned medium containing AP-Sfrp1 or AP alone. Increased binding of AP-Sfrp1 is observed in the ADAM10-overexpressing cell line. Scale bar, 25 μm. * Figure 7: Sfrp1 interacts with Kuz in Drosophila wing imaginal discs. () Sens (blue) and extracellular wingless (ecWg) expressions (red) in a UAS-myc-Sfrp1>Hh-Gal4 wing imaginal disc. The wingless (Wg) target Sens is repressed in the posterior compartment where Sfrp1 is expressed (Myc in green) but not in the anterior compartment that serves as a control. () Cut (green) and Hh (red) expressions in Hh-Gal4>UAS-myc-Sfrp1 wing discs. Note the repression of the Notch target Cut (open arrowhead) in the area where Sfrp1 is expressed (Hh in red). () Sens (blue) and Cut (green) expression in a UAS-myc-Sfrp1/UAS-Kuz>Hh-Gal4 wing disc (Myc in red). The ectopic expression of both Sfrp1 and Kuz rescues the expression of the Notch target Cut (arrowhead) but has no effect on that of the Wg target Sens. () Adult UAS-myc-Sfrp1>Hh-Gal4 wing phenotype showing notches in the posterior wing margin, a phenotype characteristic of wingless and Notch signaling alterations. () Wild-type wing. Scale bar, 40 μm (); 200 μm (). Author information * Abstract * Author information * Supplementary information Affiliations * Centro de Biología Molecular "Severo Ochoa", Consejo Superior de Investigaciones Científicas (CSIC)–Universidad Autónoma de Madrid, Madrid, Spain. * Pilar Esteve, * Africa Sandonìs, * Marcos Cardozo, * Carmen Ibañez, * Inmaculada Crespo, * Severine Marcos, * Sara Gonzalez-Garcia, * Maria Luisa Toribio, * Isabel Guerrero & * Paola Bovolenta * Centro de Investigación Biomédica en Red de Enfermedades Raras, Madrid, Spain. * Pilar Esteve, * Africa Sandonìs, * Marcos Cardozo, * Inmaculada Crespo, * Severine Marcos & * Paola Bovolenta * Instituto Cajal, CSIC, Madrid, Spain. * Pilar Esteve, * Africa Sandonìs, * Marcos Cardozo, * Inmaculada Crespo, * Severine Marcos & * Paola Bovolenta * Vall d'Hebron Institute of Oncology, Barcelona, Spain. * Jordi Malapeira & * Joaquin Arribas * Department of Biochemistry and Molecular Biology, Universitat Autònoma de Barcelona, Bellaterra, Spain. * Jordi Malapeira & * Joaquin Arribas * Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain. * Jordi Malapeira & * Joaquin Arribas * Cancer Science Institute of Singapore, National University of Singapore, Singapore. * Akihiko Shimono Contributions P.E. and A. Sandonìs performed most of the immunohistochemical, in situ hybridization and western blot analysis. A. Shimono generated the Sfrp knockout mice. M.C. and I.C. performed immunoprecipitation and binding assays. J.M. and J.A. designed and performed APP shedding experiments in CHO cells. I.G. designed and performed (with C.I.) the assays in Drosophila. S.M. contributed Sfrp1 and Sfrp2 in situ hybridization localization. S.G.-G. and M.L.T. contributed expertise in Notch signaling and flow cytometry. P.B. and P.E. conceived and supervised the study and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Pilar Esteve or * Paola Bovolenta Author Details * Pilar Esteve Contact Pilar Esteve Search for this author in: * NPG journals * PubMed * Google Scholar * Africa Sandonìs Search for this author in: * NPG journals * PubMed * Google Scholar * Marcos Cardozo Search for this author in: * NPG journals * PubMed * Google Scholar * Jordi Malapeira Search for this author in: * NPG journals * PubMed * Google Scholar * Carmen Ibañez Search for this author in: * NPG journals * PubMed * Google Scholar * Inmaculada Crespo Search for this author in: * NPG journals * PubMed * Google Scholar * Severine Marcos Search for this author in: * NPG journals * PubMed * Google Scholar * Sara Gonzalez-Garcia Search for this author in: * NPG journals * PubMed * Google Scholar * Maria Luisa Toribio Search for this author in: * NPG journals * PubMed * Google Scholar * Joaquin Arribas Search for this author in: * NPG journals * PubMed * Google Scholar * Akihiko Shimono Search for this author in: * NPG journals * PubMed * Google Scholar * Isabel Guerrero Search for this author in: * NPG journals * PubMed * Google Scholar * Paola Bovolenta Contact Paola Bovolenta Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (3M) Supplementary Figures 1–4 Additional data - Neuromuscular synaptic patterning requires the function of skeletal muscle dihydropyridine receptors
- Nat Neurosci 14(5):570-577 (2011)
Nature Neuroscience | Article Neuromuscular synaptic patterning requires the function of skeletal muscle dihydropyridine receptors * Fujun Chen1 * Yun Liu1 * Yoshie Sugiura1 * Paul D Allen2 * Ronald G Gregg3 * Weichun Lin1 * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 14,Pages:570–577Year published:(2011)DOI:doi:10.1038/nn.2792Received31 January 2011Accepted28 February 2011Published online27 March 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Developing skeletal myofibers in vertebrates are intrinsically 'pre-patterned' for motor nerve innervation. However, the intrinsic factors that regulate muscle pre-patterning remain unknown. We found that a functional skeletal muscle dihydropyridine receptor (DHPR, the L-type Ca2+ channel in muscle) was required for muscle pre-patterning during the development of the neuromuscular junction (NMJ). Targeted deletion of the β1 subunit of DHPR (Cacnb1) in mice led to muscle pre-patterning defects, aberrant innervation and precocious maturation of the NMJ. Reintroducing Cacnb1 into Cacnb1−/− muscles reversed the pre-patterning defects and restored normal development of the NMJ. The mechanism by which DHPRs govern muscle pre-patterning is independent of their role in excitation-contraction coupling, but requires Ca2+ influx through the L-type Ca2+ channel. Our findings indicate that the skeletal muscle DHPR retrogradely regulates the patterning and formation of the NMJ. View full text Figures at a glance * Figure 1: Loss of DHPR function leads to defects in muscle pre-patterning. () Whole mounts of diaphragm muscles (E14.5) were double-labeled with α-bungarotoxin (α-bgt) for AChR and by antibody to neurofilament (NF150) and antibody to synaptotagmin 2 (Syt2) for the nerve. Increased nerve branching and expansion of innervation territories were detected in Cacnb1−/− muscle () compared with wild-type (WT) muscle (). White dashed lines () delineate the myotendinous junction between the central tendon and the medial edge of the muscle fibers. The asterisk () indicates a small branch of the intercostal nerve attached to the outer edge of the diaphragm muscle. (–,,) High-magnification views of the dorsal regions of the diaphragm muscle. In the wild-type muscle, AChR clusters were aligned along the central region of the muscle, forming a pre-patterned endplate band (arrow in ); the nerves extended fine branches and terminated in the central endplate band (,). In contrast, in the Cacnb1−/− muscle, AChR clusters were distributed broadly across the! entire surface of the muscle, including the medial and lateral edges of the muscle (arrowheads in ); the nerves in the Cacnb1−/− muscle also branched extensively and expanded their innervation territories across the entire muscle surface (,). At this stage, the majority of the AChR clusters were not directly apposed to the nerve terminal (,). (,) AChR clusters were distributed along a central endplate band in Hb9−/− muscles (), but were distributed broadly in Cacnb1−/−; Hb9−/− muscles (). The nerves were absent in both Hb9−/− and Cacnb1−/−; Hb9−/− muscles. Scale bars represents 200 μm (,), 100 μm (–,,) and 400 μm (,). * Figure 2: Loss of DHPR function leads to multiple synaptic sites and an expansion of innervation territories. (,) Distribution of AChR clusters (labeled by α-bgt) in whole mounts of diaphragm muscles (E18.5). AChR clusters were aligned in a central endplate band in wild-type muscles (arrow in ), but were scattered over a broad region in Cacnb1−/− muscles (). (,) Dissociated myofibers stained with FITC-conjugated α-bgt and rhodamine-conjugated phalloidin. Multiple endplates were frequently detected in dissociated Cacnb1−/− myofibers (); the majority of them (72%, 399 out of 554) contained two or more endplates per fiber (two patches, 42.8%; three patches, 16.4%; four patches, 8.1%; five patches, 3.8%; six patches, 0.7%; seven patches, 0.2%). In contrast, the majority of control myofibers (99.4%, 357 out of 359) contained a single endplate; less than 1% of them (0.6%, 2 out of 359) contained two endplates per fiber. () Histogram distribution of the percentage (in log scale) of dissociated myofibers containing various numbers of endplates ranging from 1 to 7. (,) The innervat! ion territories were confined in the central region in the wild type (bordered by dashed lines ), but expanded to the entire muscle in Cacnb1−/− (). (,) Distribution of AChE clusters (arrow) revealed by cholinesterase staining. AChE clusters were localized along the central region of the muscle in the wild type (), but were broadly distributed in the Cacnb1−/− muscle (). Inset in shows a high-magnification view of individual myofibers containing multiple AChE clusters (arrowheads) in Cacnb1−/− muscle. Scale bars represent 400 μm (,), 50 μm (,), 200 μm (,) and 250 μm (,). * Figure 3: DHPR function is not required for synaptogenesis, but its absence leads to increased synaptic and muscle electrical activity. (–) Confocal images of E18.5 diaphragm muscles doubly labeled by presynaptic markers (NF150 and Syt2; ,) and postsynaptic marker α-bgt (,). Every endplate in both wild-type () and Cacnb1−/− muscle () was fully innervated by the nerves (arrows in ,). Endplates in the control muscle appeared predominantly as ovoid-shaped plaques (), whereas endplates in Cacnb1−/− muscles were bigger and some were perforated (arrowheads in ). (,) Electron micrographs of the NMJ (E18.5, diaphragm muscle). In both wild type () and Cacnb1−/− (), synaptic vesicles (SV) were abundantly present at the nerve terminal (NT) and the basal lamina (white arrow in ,) was well-defined in the synaptic cleft. (,) Sample traces of mEPPs from control () and Cacnb1−/− () myofibers. The mEPP frequency was markedly increased in Cacnb1−/− muscles. (,) Spontaneous action potentials (arrowheads) in control () and Cacnb1−/− () mice; the lower trace in and illustrates an expanded view of the p! ortion of the upper trace indicated by the gray line. Arrow in indicates the displacement of the trace resulting from muscle contraction in the control. Scale bars represent 20 μm (–) and 0.5 μm (,). * Figure 4: Muscle-specific expression of Cacnb1 rescues the patterning defects in Cacnb1−/− muscle. (,) Sample traces of mEPP recorded from P0 diaphragm muscles in control () and the Cacnb1−/− mice that also carry a HSA-Cacnb1 transgene under the control of the muscle-specific HSA promoter, as shown in the schematic drawing (Cacnb1−/−; HSA-Cacnb1, referred to as the rescued mice; ). (–) Whole-mount diaphragm muscles at E14.5 (–) and E18.5 (–) from the rescued mice were double-labeled for AChRs (,) and the nerves (,). Similar to the wild-type muscles (compared with Figs. 1 and 2), AChR clusters in the rescued muscles were aligned to a central endplate band (arrow in ,) and nerve terminals were also confined to a central endplate band, as seen in the merged images (,). (–) AChE staining of whole-mount diaphragm muscle (Dia, P0) and triangularis sterni muscle (TS, P90) from control (,) and rescued mice (,). The patterns of AChE staining (black arrow) were similar between control and the rescued mice. Scale bars represent 100 μm (–), 200 μm (–) and 1,000 ! μm (–). * Figure 5: RyRs and DHPRs have different roles in muscle pre-patterning. (–) Distribution of AChR clusters (,) and nerves (,) revealed by double immunofluorescence staining of E14.5 diaphragm muscles from Ryr1−/−; Ryr3−/− (–) and littermate control mice (Ryr1+/+; Ryr3+/−, –). Merged images are shown in and . AChRs were clustered along central regions of the muscles in both Ryr1−/−; Ryr3−/− and Ryr1+/+; Ryr3+/− mice (arrows in ,), in a pattern similar to that seen in the wild-type mice (Fig. 1b). Increased innervation was detected in Ryr1−/−; Ryr3−/− () compared with the control (Ryr1+/+; Ryr3+/−, ). Nevertheless, nerve terminals in both Ryr1−/−; Ryr3−/− and Ryr1+/+; Ryr3+/− mice were confined to the central region of the muscle, as shown in the merged images (arrowheads in ,). (–) AChR distribution in E18.5 diaphragm muscles. Unlike Cacnb1−/− muscle in which AChR clusters were broadly distributed (), the majority of AChR clusters were aligned in a central endplate band in E18.5 Ryr1−/−; Ryr3! −/− muscle (arrow in ), similar to the endplate band seen in the E18.5 WT muscle (arrow in ). However, some AChR clusters were ectopically localized to the peripheral regions of the E18.5 Ryr1−/−; Ryr3−/− muscle (* in ). Scale bars represent 100 μm (–) and 400 μm (–). * Figure 6: DHPRs pattern neuromuscular synapses by regulating the expression of the AChR genes and Musk. (–) Whole-mount in situ hybridization with DIG-labeled Chrna1 probes were carried out in E14.5 diaphragm muscles (,) or E18.5 intercostal muscles (). Chrna1 transcripts were detected along the central regions in wild-type muscle (), but were broadly distributed in the Cacnb1−/− muscle (). Chrna1 transcripts were localized to the central region of the wild-type muscle (left, ), but were detected in the entire Cacnb1−/− muscle (middle, ). The normal distribution of Chrna1 transcripts was restored in the rescued mice (right, ); rib, costal rib bone. () Whole-mount in situ hybridization of intercostal muscles using DIG-labeled Musk probes. Musk transcripts were localized to the central region of the wild-type muscle (left), but were broadly distributed in the Cacnb1−/− muscle (right). () Relative expression levels of Chrna1 and MuSK assayed by quantitative real-time PCR in C2C12 myotube cultures treated with L-type Ca2+ channel antagonists (verapamil, isradipine) o! r agonist (Bay K 8644) compared with the untreated or vehicle (DMSO) treated controls. Verapamil (10 μM) significantly increased the relative expression levels of Musk (2.21 ± 0.13, n = 5 cultures, P = 0.0002) and Chrna1 (2.10 ± 0.32, n = 5 cultures, P = 0.009) compared with controls (Musk, 1.03 ± 0.12; Chrna1, 1.04 ± 0.16; n = 5 cultures). Similarly, isradipine (1 μM) also significantly increased the relative expression levels of Musk (1.84 ± 0.21, n = 3 cultures, P = 0.0003) and Chrna1 (1.68 ± 0.31, n = 3 cultures, P = 0.0189) compared with controls (Musk, 1.01 ± 0.10; Chrna1, 1.00 ± 0.02; n = 3 cultures). Bay K 8644 significantly decreased the expression of Musk (0.60 ± 0.13, n = 3 cultures, P = 0.0012) and Chrna1 (0.83 ± 0.07, n = 3 cultures, P = 0.0337) compared with controls (Musk, 1.02 ± 0.02; Chrna1, 1.04 ± 0.10; n = 6 cultures). *P < 0.05; **P < 0.01; ***P < 0.001. () Whole-mount diaphragm muscles were immunostained with antibody to MuSK and α-bgt. M! uSK protein was clustered along the central region of the wild! -type muscles (left column), but was broadly distributed in the Cacnb1−/− muscles (middle column). MuSK distribution was restored to normal in the rescued mice (right column). Data are presented as mean ± s.e.m. Scale bars represent 500 μm (–), 400 μm () and 50 μm (). Author information * Abstract * Author information * Supplementary information Affiliations * Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, Texas, USA. * Fujun Chen, * Yun Liu, * Yoshie Sugiura & * Weichun Lin * Department of Anesthesia, Perioperative and Pain Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA. * Paul D Allen * Department of Biochemistry and Molecular Biology, University of Louisville, Louisville, Kentucky, USA. * Ronald G Gregg Contributions F.C., Y.L. and Y.S. carried out the experiment and collected and analyzed the data. P.D.A. provided the RyR mutant mice. R.G.G. provided the DHPR mutant mice. W.L. supervised the project and wrote the manuscript with critical input from F.C., Y.L., Y.S., P.D.A. and R.G.G. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Weichun Lin Author Details * Fujun Chen Search for this author in: * NPG journals * PubMed * Google Scholar * Yun Liu Search for this author in: * NPG journals * PubMed * Google Scholar * Yoshie Sugiura Search for this author in: * NPG journals * PubMed * Google Scholar * Paul D Allen Search for this author in: * NPG journals * PubMed * Google Scholar * Ronald G Gregg Search for this author in: * NPG journals * PubMed * Google Scholar * Weichun Lin Contact Weichun Lin Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–4 Additional data - Deletion of a remote enhancer near ATOH7 disrupts retinal neurogenesis, causing NCRNA disease
- Nat Neurosci 14(5):578-586 (2011)
Nature Neuroscience | Article Deletion of a remote enhancer near ATOH7 disrupts retinal neurogenesis, causing NCRNA disease * Noor M Ghiasvand1, 2 * Dellaney D Rudolph3 * Mohammad Mashayekhi4 * Joseph A Brzezinski IV3, 6 * Daniel Goldman5 * Tom Glaser3 * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 14,Pages:578–586Year published:(2011)DOI:doi:10.1038/nn.2798Received04 January 2011Accepted07 March 2011Published online27 March 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Individuals with nonsyndromic congenital retinal nonattachment (NCRNA) are totally blind from birth. The disease afflicts ~1% of Kurdish people living in a group of neighboring villages in North Khorasan, Iran. We found that NCRNA is caused by a 6,523-bp deletion that spans a remote cis regulatory element 20 kb upstream from ATOH7 (Math5), a bHLH transcription factor gene that is required for retinal ganglion cell (RGC) and optic nerve development. In humans, the absence of RGCs stimulates massive neovascular growth of fetal blood vessels in the vitreous and early retinal detachment. The remote ATOH7 element appears to act as a secondary or 'shadow' transcriptional enhancer. It has minimal sequence similarity to the primary enhancer, which is close to the ATOH7 promoter, but drives transgene expression with an identical spatiotemporal pattern in the mouse retina. The human transgene also functions appropriately in zebrafish, reflecting deep evolutionary conservation. These d! ual enhancers may reinforce ATOH7 expression during early critical stages of eye development when retinal neurogenesis is initiated. View full text Figures at a glance * Figure 1: NCRNA disease. Eye photographs from NCRNA family. () 49-year old female. () 18-year old male. () 14-year old female. () 8-year old male. Retinal detachments are evident as leukocoria (white pupils) in each case. Older NCRNA subjects develop dense gray posterior corneal opacities, consistent with chronic blood staining (,, right eye in ). They typically exhibit nystagmus and strabismus (esotropia, ). The pupils are round, but do not react to light. () Closer views showing leukocoria in young patients prior to corneal opacification (5-year old male, left eye,; 3-year old male, left eye,). The detached retina and fibrovascular mass are visible behind the clear lens (arrow). () Khorasani pedigree showing autosomal recessive inheritance of the disease over nine generations, with index cases used for mutation screening (red boxes). * Figure 2: Anatomical findings in NCRNA. Orbital magnetic resonance images of an 18-year old male showing absence or severe atrophy of the optic nerves and chiasm (red arrowheads) and bilateral detached retinas with vitreous consolidation (bright signal, blue arrowheads). () Axial (repetition time (TR)/echo time (TE) = 780/15 ms, 3 mm slices) and () oblique sagittal (right eye, TR/TE = 730/15 ms, 2 mm slice) T1-weighted spin echo (SE) views, with fat suppression and gadolinium contrast. () Coronal T1-weighted SE views (TR/TE = 780/15, 5 mm slices) with no contrast or fat suppression, shown from anterior (left) to posterior (right). () Matched coronal images from a normal 15-year old female (T1-weighted SE views, TR/TE = 550/11 ms, 3 mm slices). The vitreae are clear (left, dark signal, blue arrowhead) and the optic nerves are prominent (middle, red arrowheads). The optic chiasm is visible above the suprasellar cistern and pituitary (right, red arrowhead). () Matched axial images from the normal subject (TR/TE = 750! /11 ms, 3 mm slices). (,) Enlarged coronal views of NCRNA and normal subjects (left orbits, boxed areas in and ). The red arrowhead shows the normal optic nerve. The bright T1W signal outlining the optic nerve, extraocular muscles (sr, lr, ir, mr, so, lps) and blood vessels (sov) originates from retrobulbar fat. 3v, third ventricle; cc, corpus callosum; cis, suprasellar cistern; eth, ethmoid sinus; hyp, hypothalamus; ica, internal carotid artery; io, inferior oblique; ir, inferior rectus; la, levator aponeurosis; lg, lacrimal gland; lps, levator palpebrae superioris; lr, lateral rectus; lv, lateral ventricle; max, maxillary sinus; mr, medial rectus; nph, nasopharynx; oa, ophthalmic artery; oc, optic canal; on, optic nerve; pit, pituitary gland; po, pons; ps, pituitary stalk; so, superior oblique; sov, superior orbital vein; sph, sphenoid sinus; sr, superior rectus; st, sella turcica; tem, temporal lobe; vit, vitreous; x, optic chiasm. * Figure 3: Homozygous deletion of 5′ ATOH7 genomic sequences in NCRNA. () The 1,639-kb critical region on chromosome 10q21 spans 14 positional candidate genes. The segment between PBLD to MYPN (blue bracket) is expanded below. () Genomic PCRs showing deletion of four adjacent amplicons in an NCRNA subject (rr) compared to wildtype (RR). Two additional amplicons were also missing (Supplementary Table 3). () Map of the 74-kb intergenic region surrounding ATOH7 (Chr10:69,714,052–69,640,048) modified from the University of California at Santa Cruz (UCSC) Genome browser (NCBI36/hg18, Mar 2006 assembly), showing the terminal exons of flanking genes,KRTψ (human-specific keratin-18 pseudogene), vertebrate and mammalian evolutionary conservation (cons) tracks (PhastCons), interspersed repetitive elements, PCR amplicons (red) used to compare homozygous mutant and wild-type DNA samples, and the 6.5-kb NCRNA deletion. Orthologous vertebrate sequences are indicated in the vertebrate MultiZ alignment. In the nontherian genomes, similarity between KRTψ an! d unlinked keratin loci gives a false positive signal of homologous evolution. The corresponding mouse Pbld-Mypn intergenic segment is 42.5 kb. Two SNPs associated with optic disc area in human genome-wide studies44, 45 are indicated for comparison (rs1900004, rs3858145). The deletion removes a cluster of CNEs (conserved noncoding elements) ~20 kb upstream of ATOH7. * Figure 4: Endpoints of the NCRNA deletion. () Triplex PCR genotypes showing transmission of the mutation in a small family. () Sequence chromatograms from PCR products showing the distal and proximal breakpoints in wild-type DNA, with 5-bp microhomology (double arrow) and the deletion junction in a DNA from a blind individual. * Figure 5: The NCRNA mutation deletes an ATOH7 retinal enhancer. () Map of the 30-kb upstream region (Chr10:69,690,000–69,660,000) modified from the UCSC Genome browser (NCBI36/hg18, Mar 2006 assembly) showing mammalian base-wise sequence conservation and the NCRNA deletion. The 3034-BGnCherry transgene contains 3.8 kb of human genomic DNA, which spans the three deleted CNEs and regulates expression from the minimal human β-globin promoter. The location of the Math5-GFP transgene is shown for comparison. This reporter contains the endogenous mouse ATOH7 promoter, 0.3 kb of 5′ UTR and 1.8 kb of upstream genomic DNA31, 50. () Brightfield and () fluorescence images revealed eye-specific nuCherry expression in a pigmented E13.5 transgenic (Tg) founder. * Figure 6: Activity of the remote ATOH7 retinal enhancer in 3034-BGnCherry mice. Double transgenic 3034-BGnCherry;Math5-lacZ/+ embryos were exposed to BrdU, harvested between E12 and E16, cryosectioned, and immunostained for nuCherry (red) and β-galactosidase, BrdU or PH3 (green). (,,) The nuclear 3034-BGnCherry and cytoplasmic Math5-lacZ patterns essentially overlap, with >85% cell concordance (data not shown). However, the subcellular localizations differ, with accumulation of β-galactosidase in RGC axons at the inner retinal surface and nascent optic nerve (open arrowheads). (,,–) The 3034-BGnCherry transgene is expressed in post-mitotic retinal cells, with no overlap between nuCherry and the mitotic markers BrdU (S phase) or PH3 (M phase). Closed arrowheads mark the apical (sclerad) side in –. Scale bars represent 20 μm (), 40 μm (–) and 10 μm (–). * Figure 7: Remote and primary ATOH7 enhancers have similar activity in the developing mouse retina, indicated by coexpression of nuCherry and GFP transgenes. (–) Double transgenic 3034-BGnCherry; Math5-GFP embryos immunostained for both reporters. Low (–) and confocal high (–) magnification views of E11.5–16.5 retinal sections. The onset and expression patterns of the transgenes are essentially overlapping. () Two-dimensional flow cytometric analysis of dissociated E14.5 retinal cells from 3034-BGnCherry × Math5-GFP littermate embryos carrying one, neither or both transgenes. The percentage of cells in each quadrant is indicated in the contour plots. The concordance between nuCherry and GFP fluorescence is high. Double-positive cells represent ~40% of the neural retina in 3034-BGnCherry; Math5-GFP embryos (upper right). () Dissociated cells from an E14.5 double transgenic embryo immunostained for nuCherry and GFP. Arrowheads in – mark the apical side. Scale bars represent 40 μm (–), 20 μm (-) and 10 μm (). * Figure 8: The human remote ATOH7 enhancer functions in developing zebrafish. (,) Lateral and dorsal views of live embryos showing specific retinal expression of the 3034-BGnCherry transgene in progenitor cells at 72 hours post fertilization (hpf) development. (–) Transverse sections of immunostained 3034-BGnCherry; ath5:GFP embryos showing colocalized expression of nuCherry and GFP in the retina at 48, 72 and 128 hpf, with perdurance of reporter proteins in RGCs. The cytoplasmic GFP also labels RGC axons in the optic nerves, chiasm and tracts projecting to the thalamus and tectum. g, ganglion cell layer; hb, habenula; i, inner nuclear layer; o, outer nuclear layer; on, optic nerve; rtt, retinotectal tract; tel, telencephalon; th, thalamus. Scale bars represent 50 μm. Author information * Abstract * Author information * Supplementary information Affiliations * Neuroscience Research Center and Department of Medical Genetics, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran,Iran. * Noor M Ghiasvand * Department of Biology, Grand Valley State University, Allendale,Michigan,USA. * Noor M Ghiasvand * Departments of Human Genetics and Internal Medicine, University of Michigan,Ann Arbor,Michigan, USA. * Dellaney D Rudolph, * Joseph A Brzezinski IV & * Tom Glaser * Ophthalmology Ward, Emam Ali Hospital, Bojnourd,North Khorasan,Iran. * Mohammad Mashayekhi * Molecular and Behavioral Neuroscience Institute, Department of Biochemistry, University of Michigan,Ann Arbor, Michigan,USA. * Daniel Goldman * Present address:Department of Biological Structure, University of Washington,Seattle,Washington, USA. * Joseph A Brzezinski IV Contributions N.M.G. and M.M. collected clinical data. N.M.G., D.D.R., J.A.B. and T.G. performed genomic and functional experiments. D.G. developed and bred transgenic fish. N.M.G., D.D.R., J.A.B., D.G. and T.G. analyzed data and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Tom Glaser Author Details * Noor M Ghiasvand Search for this author in: * NPG journals * PubMed * Google Scholar * Dellaney D Rudolph Search for this author in: * NPG journals * PubMed * Google Scholar * Mohammad Mashayekhi Search for this author in: * NPG journals * PubMed * Google Scholar * Joseph A Brzezinski IV Search for this author in: * NPG journals * PubMed * Google Scholar * Daniel Goldman Search for this author in: * NPG journals * PubMed * Google Scholar * Tom Glaser Contact Tom Glaser Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (913K) Supplementary Figures 1–10, Supplementary Tables 1–3 and Supplementary Note Additional data - Structural basis for the role of inhibition in facilitating adult brain plasticity
- Nat Neurosci 14(5):587-594 (2011)
Nature Neuroscience | Article Structural basis for the role of inhibition in facilitating adult brain plasticity * Jerry L Chen1, 2 * Walter C Lin1, 3 * Jae Won Cha4 * Peter T So4, 5 * Yoshiyuki Kubota6, 7, 8 * Elly Nedivi1, 2, 9 * Affiliations * Corresponding authorJournal name:Nature NeuroscienceVolume: 14,Pages:587–594Year published:(2011)DOI:doi:10.1038/nn.2799Received01 November 2010Accepted04 March 2011Published online10 April 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Although inhibition has been implicated in mediating plasticity in the adult brain, the underlying mechanism remains unclear. Here we present a structural mechanism for the role of inhibition in experience-dependent plasticity. Using chronic in vivo two-photon microscopy in the mouse neocortex, we show that experience drives structural remodeling of superficial layer 2/3 interneurons in an input- and circuit-specific manner, with up to 16% of branch tips undergoing remodeling. Visual deprivation initially induces dendritic branch retractions, and this is accompanied by a loss of inhibitory inputs onto neighboring pyramidal cells. The resulting decrease in inhibitory tone, also achievable pharmacologically using the antidepressant fluoxetine, provides a permissive environment for further structural adaptation, including addition of new synapse-bearing branch tips. Our findings suggest that therapeutic approaches that reduce inhibition, when combined with an instructive stimul! us, could facilitate restructuring of mature circuits impaired by damage or disease, improving function and perhaps enhancing cognitive abilities. View full text Figures at a glance * Figure 1: Chronic two-photon in vivo imaging of dendritic branch tip dynamics in superficial L2/3 cortical interneurons. () Experimental time course. Every cell was imaged at all indicated time points. () Maximum z projection (MZP) of chronically imaged interneuron (green arrow) superimposed over intrinsic signal map of monocular (V1M) and binocular (V1B) visual cortex. () Coronal section of primary visual cortex (V1) containing an imaged superficial L2/3 interneuron (~70 μm below the pial surface; green arrow) shown with respect to V1M and V1B as identified through WGA–Alexa 555 (WGA-555) labeling of thalamacortical projections from the ipsilateral eye (red) and DAPI staining of the granule cell layer (blue). () MZPs near the cell body (above) along with two-dimensional projections of three-dimensional skeletal reconstructions (below) of a superficial L2/3 interneuron (~85 μm below the pial surface) in V1B acquired at the specified intervals. Dendritic branch tip elongations and retractions identified between successive imaging sessions are indicated by blue and red arrows, respectively. ! () High-magnification view of one branch tip elongation (orange box in ). Blue arrow marks the approximate distal end of the branch tip at −14 d. () High-magnification view of one branch tip retraction (magenta box in ). Red arrow marks the approximate distal end of the branch tip at 0 d. Scale bars: , 250 μm; , 100 μm; , 50 μm; ,, 5 μm. * Figure 2: Monocular deprivation increases interneuron dendritic branch tip dynamics in adult binocular visual cortex. (,) Dendritic branch tip dynamics in superficial L2/3 interneurons imaged throughout a 14-d monocular deprivation for binocular visual cortex (individual cells shown in gray, mean shown in magenta; n = 16 cells from 13 mice, 524 branch tips) () and monocular visual cortex (individual cells shown in gray, mean shown in blue; n = 12 cells from 12 mice, 461 branch tips) (). () Rate of dendritic branch tip dynamics compared before and during monocular deprivation in binocular (magenta) and monocular (blue) visual cortex. () Cumulative fraction of dynamic branch tips in binocular visual cortex over imaging time course (**P < 0.01, *P < 0.05). Error bars, s.e.m. * Figure 3: Synapses are formed on newly extended branch tips. () In vivo image of a branch tip elongation. Blue arrow marks the approximate distal end of the branch tip at −14 d. () Reidentification of the same imaged dendrite in fixed tissue after immunostaining for GFP. () High-magnification view of dendritic portion reconstructed by serial section electron microscopy (white box in ). () Serial section electron microscopy reconstruction of the in vivo–imaged dendrite (in green) with region proximal to (yellow arrows in –) and very distal portion of (red arrows in –) elongated branch tip. Left, contacting axon terminals (in blue); right, synaptic contacts (in blue). (,) Electron micrographs showing a synapse on the newly elongated branch tip (e arrow in ) and on the proximal, stable dendrite (f arrow in ), respectively. Bottom panels show an enlargement of the synapse with visible synaptic cleft (red arrows) and synaptic vesicles. Scale bars: ,, 5 μm; , 2 μm; , 1 μm; ,, top, 500 nm; bottom, 100 nm. * Figure 4: Monocular deprivation induces laminar-specific dendritic arbor rearrangements. () Distribution of dynamic branch tips before and during monocular deprivation in binocular visual cortex. Plotted are cell soma positions (black circles) and branch tip positions of branch tip elongations (blue) or retractions (red). () Cumulative fraction distribution plot of branch tip elongations (blue) and retractions (red) from 0–4 d MD (left) and 4–7 d MD (right) as compared to control (dotted lines) (*P < 0.05). () Rate of dendritic branch tip elongations (blue) and retractions (red) in L1 and L2/3 of binocular visual cortex, before and during monocular deprivation (n = 16 cells from 13 mice; L1, 228 branch tips; L2/3, 325 branch tips) (**P < 0.01, *P < 0.05). Error bars, s.e.m. * Figure 5: Binocular deprivation specifically increases retractions of L2/3 branch tips. () Dendritic branch tip dynamics compared before and during binocular deprivation in binocular visual cortex. () Rate of branch tip elongations (blue) and retractions (red) in L1 and L2/3 of binocular visual cortex, before and during binocular deprivation (n = 7 cells from 7 mice; L1, 108 branch tips; L2/3, 155 branch tips; # denotes a time point measurement equaling 0 ± 0.00% dynamic branch tips per week) (**P < 0.02, *P < 0.05). Error bars, s.e.m. * Figure 6: Four days of monocular deprivation increases inhibitory synapse elimination onto L5 pyramidal apical dendrites. () High-magnification view of axonal bouton remodeling of superficial L2/3 interneuron. Yellow arrows indicate stable boutons and red arrow an eliminated bouton. () Fraction of total axonal boutons added or eliminated during normal vision or in response to 4 d of monocular deprivation (n = 6 cells from 6 mice, 564 axonal boutons) (**P < 0.01, *P < 0.05). () Coronal section of a GFP-labeled L2/3 pyramidal neuron in binocular visual cortex (in green) after immunohistochemical staining of inhibitory presynaptic terminals by VGAT (in red). Examples of inhibitory presynaptic contacts onto dendritic (top right) and perisomatic (bottom right) synapses are indicated with white arrows. () Quantification of putative inhibitory synapse density on L2/3 pyramidal neuron soma and on dendrites of L2/3 and L5 pyramidal neurons in binocular visual cortex after 4 d of monocular deprivation (4 d MD) (control, n = 8 mice, 49 L2/3 pyramidal neurons, 45 L5 pyramid neurons, 9,688 synapses; 4 d MD,! n = 8, 46 L2/3 pyramidal neurons, 39 L5 pyramid neurons, 8,581 synapses) (*P < 0.05). Error bars, s.e.m. Scale bars: ,, right, 2 μm; , left, 5 μm. * Figure 7: Reduction in intracortical inhibition by fluoxetine treatment promotes experience-dependent branch tip remodeling. () Experimental time course. () High-magnification view of one branch tip retraction during fluoxetine treatment. Red arrow marks the approximate distal end of the branch tip at −28 d. Scale bar, 10 μm. () Dendritic branch tip dynamics in L1 and L2/3 of binocular visual cortex of animals under normal vision before and during fluoxetine administration. Rates of L2/3 branch tip elongations and retractions in binocular visual cortex during fluoxetine treatment under normal vision or a brief (4-d) monocular deprivation (0–4 d MD) as compared to prolonged (7-d) monocular deprivation (4–7 d MD) without fluoxetine treatment (taken from Fig. 4c) (with fluoxetine: n = 8 cells from 8 mice; L1, 113 branch tips; L2/3, 115 branch tips; without fluoxetine: n = 16 cells from 13 mice; L2/3, 325 branch tips) (**P < 0.01; *P < 0.05). Error bars, s.e.m. Author information * Abstract * Author information * Supplementary information Affiliations * Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. * Jerry L Chen, * Walter C Lin & * Elly Nedivi * Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. * Jerry L Chen & * Elly Nedivi * Harvard-MIT Division of Health Science and Technology, Harvard Medical School, Cambridge, Massachusetts, USA. * Walter C Lin * Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. * Jae Won Cha & * Peter T So * Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. * Peter T So * Japan Science and Technology Agency, Core Research for Evolutional Science and Technology, Tokyo, Japan. * Yoshiyuki Kubota * Division of Cerebral Circuitry, National Institute for Physiological Sciences, Okazaki, Japan. * Yoshiyuki Kubota * Department of Physiological Science, Graduate University for Advanced Studies (SOKENDAI), Okazaki, Japan. * Yoshiyuki Kubota * Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. * Elly Nedivi Corresponding author Correspondence to: * Elly Nedivi Author Details * Jerry L Chen Search for this author in: * NPG journals * PubMed * Google Scholar * Walter C Lin Search for this author in: * NPG journals * PubMed * Google Scholar * Jae Won Cha Search for this author in: * NPG journals * PubMed * Google Scholar * Peter T So Search for this author in: * NPG journals * PubMed * Google Scholar * Yoshiyuki Kubota Search for this author in: * NPG journals * PubMed * Google Scholar * Elly Nedivi Contact Elly Nedivi Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–6 Additional data - TRPA1 is required for histamine-independent, Mas-related G protein–coupled receptor–mediated itch
- Nat Neurosci 14(5):595-602 (2011)
Nature Neuroscience | Article TRPA1 is required for histamine-independent, Mas-related G protein–coupled receptor–mediated itch * Sarah R Wilson1 * Kristin A Gerhold1 * Amber Bifolck-Fisher1 * Qin Liu2 * Kush N Patel2 * Xinzhong Dong2 * Diana M Bautista1 * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 14,Pages:595–602Year published:(2011)DOI:doi:10.1038/nn.2789Received01 November 2010Accepted28 February 2011Published online03 April 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Itch, the unpleasant sensation that evokes a desire to scratch, accompanies numerous skin and nervous system disorders. In many cases, pathological itch is insensitive to antihistamine treatment. Recent studies have identified members of the Mas-related G protein–coupled receptor (Mrgpr) family that are activated by mast cell mediators and promote histamine-independent itch. MrgprA3 and MrgprC11 act as receptors for the pruritogens chloroquine and BAM8–22, respectively. However, the signaling pathways and transduction channels activated downstream of these pruritogens are largely unknown. We found that TRPA1 is the downstream target of both MrgprA3 and MrgprC11 in cultured sensory neurons and heterologous cells. TRPA1 is required for Mrgpr-mediated signaling, as sensory neurons from TRPA1-deficient mice exhibited markedly diminished responses to chloroquine and BAM8–22. Similarly, TRPA1-deficient mice displayed little to no scratching in response to these pruritogens. ! Our findings indicate that TRPA1 is an essential component of the signaling pathways that promote histamine-independent itch. View full text Figures at a glance * Figure 1: Chloroquine and BAM activate a subset of TRPA1-positive sensory neurons. () BAM-evoked (100 μM, yellow arrowheads) and chloroquine-evoked (CQ, 1 mM, white arrows) responses in cultured DRG neurons (representative Fura-2 ratiometric images). Scale bar represents 10 μm. () Representative BAM- and chloroquine-responsive cell. Fura-2 ratio in response to BAM (100 μM), chloroquine (1 mM), mustard oil (MO, 200 μM), and capsaicin (Cap, 1 μM). () Representative chloroquine-sensitive, BAM-insensitive cell. Fura-2 ratio in response to BAM (100 μM), chloroquine (1 mM), mustard oil (200 μM) and capsaicin (1 μM). () PCR analysis of Mrgpra3, Mrgprc11 and Trpa1 expression in chloroquine- and BAM-sensitive neurons compared with expression in chloroquine-, BAM- and mustard oil–insensitive large-diameter sensory neurons. Mrgprc11 and Trpa1 were amplified in BAM-sensitive (BAM+), but not BAM-insensitive (BAM−), cells. Mrgpra3 and Trpa1 were amplified in chloroquine-sensitive (CQ+), but not chloroquine-insensitive (CQ−) cells. MrgprA3, MrgprC11 and Trp! a1 were all amplified from DRG cDNA. Note the presence of control Gapdh in all samples. None of these genes were amplified in negative controls (CON, no reverse transcription). () Representative trace showing Ca2+ response to BAM (100 μM) in the absence (1 mM EGTA) and presence (2 mM Ca2+) of extracellular calcium. () Representative response to chloroquine (1 mM) in the absence (1 mM EGTA) and presence (2 mM Ca2+) of extracellular calcium. * Figure 2: TRPV1 is not required for chloroquine- or BAM-evoked excitation of neurons. () Cultured sensory neurons isolated from wild-type and TRPV1-deficient mice were exposed to BAM (100 μM), followed by mustard oil (200 μM) and capsaicin (1 μM), and analyzed by Fura-2 ratiometric calcium imaging (representative responses). () Cultured sensory neurons isolated from wild-type and TRPV1-deficient mice were exposed to chloroquine (1 μM), followed by mustard oil (200 μM) and capsaicin (1 μM), and analyzed by Fura-2 ratiometric calcium imaging (representative responses). () The prevalence of chloroquine sensitivity was similar in wild-type (black), TRPV1-deficient (gray) and capsazepine-treated (CPZ, 20 μM, white) neurons. In contrast, the prevalence of BAM sensitivity was reduced in TRPV1-deficient (gray, P < 0.01, one-way ANOVA) and CPZ-treated neurons (white, P < 0.05, one-way ANOVA) relative to wild-type neurons (black). The prevalence of histamine (HIS) sensitivity was also reduced in TRPV1-deficient (gray, P < 0.05, one-way ANOVA) and CPZ-treated neu! rons (white, P < 0.05, one-way ANOVA; n = 3 animals per genotype, n ≥ 500 neurons per genotype) relative to wild-type neurons (black). Error bars represent s.e.m. (NS, not significant, P > 0.5; *P < 0.05, **P < 0.01, ***P < 0.001). () TRPV1 is not required for chloroquine- or BAM-evoked action potential firing. Representative current-clamp recording showing that wild-type and TRPV1-deficient neurons fired similar numbers of action potentials in response to BAM (100 μM) and chloroquine (1 mM). No responses to capsaicin (1 μM) were observed in TRPV1-deficient neurons (n = 5–13 cells per genotype). * Figure 3: TRPA1 is required for chloroquine- and BAM-evoked excitation of neurons. () Cultured sensory neurons isolated from wild-type and TRPA1-deficient mice were exposed to BAM (100 μM), followed by mustard oil (200 μM) and capsaicin (1 μM), and responses were measured by Fura-2 ratiometric calcium imaging (representative responses). () Cultured sensory neurons isolated from wild-type and TRPA1-deficient mice were exposed to chloroquine (1 μM), followed by mustard oil (200 μM) and capsaicin (1 μM), and responses were measured by Fura-2 ratiometric calcium imaging (representative responses). () The prevalence of chloroquine sensitivity was significantly reduced in TRPA1-deficient (gray, P < 0.01, one-way ANOVA) and HC-03001–treated neurons (white, 100 μM, P < 0.001, one-way ANOVA) relative to wild-type neurons (black). Similarly, the prevalence of BAM sensitivity was reduced in TRPA1-deficient (gray, P < 0.001, one-way ANOVA) and HC-030031–treated neurons (white, P < 0.001, one-way ANOVA) relative to wild type (black). In contrast, the prevale! nce of histamine sensitivity was similar in wild-type (black), TRPA1-deficient (gray, P = 0.73, one-way ANOVA) and HC-030031-treated neurons (white, P = 0.61, one-way ANOVA, n = 3 animals per genotype, n ≥ 500 neurons per genotype). NS, not significant, P > 0.5; **P < 0.01, ***P < 0.001. Error bars represent s.e.m. () TRPA1 is required for chloroquine-evoked action potential firing. Representative current-clamp recording showed that HC-03001 (100 μM) blocked chloroquine-evoked action potential firing (n ≥ 5 cells per compound). * Figure 4: MrgprA3 and MrgprC11 couple to TRPA1 in neuronal cell lines. () Chloroquine-evoked (1 mM) calcium response in NG108 cells transfected with both Trpa1 and Mrgpra3 (bottom), Mrgpra3 alone (top), or Trpa1 alone (middle). TRPA1 expression was assessed by application of mustard oil (100 μM). Scale bar represents 10 μm. () Chloroquine-evoked Fura-2 ratiometric responses (average traces) in NG108 cells transfected with Mrgpra3 (left), Mrgpra3 and Trpv1 (middle), or with Mrgpra3 and Trpa1 (right). Ionomycin (1 μM) treatment indicated that the Mrgpra3-transfected cells were healthy and loaded with Fura-2. Capsaicin (1 μM) and mustard oil (200 μM) were used to activate TRPV1 and TRPA1 channels, respectively. MrgprA3 expression was assessed by GFP fluorescence (data not shown). () BAM-evoked Fura-2 ratiometric responses (average traces) in NG108 cells transfected with Mrgprc11 (1.58 ± 0.16, left), Mrgprc11 and Trpv1 (2.1 ± 0.3, middle), or with Mrgprc11 and Trpa1 (2.8 ± 0.3, right). Values are shown as peak ± s.e.m. (Mrgprc11 alone vers! us Mrgprc11 + Trpv1, P = 0.005; Mrgprc11 alone versus Mrgprc11 + Trpa1, P = 0.0001; Mrgprc11 + Trpa1 versus Mrgprc11 + Trpv1, P = 0.004). Capsaicin (1 μM) and mustard oil (200 μM) were used to activate TRPV1 and TRPA1 channels, respectively. MrgprC11 expression was assessed by GFP fluorescence (data not shown). * Figure 5: MrgprA3 and MrgprC11 utilize distinct signaling pathways to activate TRPA1. () Chloroquine-evoked (1 mM) calcium signals (representative traces) in cultured sensory neurons following pre-treatment (5 min) with vehicle (left), the Gβγ inhibitor gallein (middle, 100 μM) or the PLC inhibitor U73122 (right, 1 μM) as measured by Fura-2 ratiometric calcium imaging. () BAM-evoked (100 μM) calcium signals (representative traces) in cultured sensory neurons following pre-treatment (5 min) with vehicle (left), gallein (middle, 100 μM) or U73122 (right, 1 μM) as measured by Fura-2 ratiometric calcium imaging. () Quantification of the percentage of chloroquine-, BAM- and HIS-sensitive neurons following treatment with vehicle (VEH, black), gallein (GAL, white) or U73122 (U7, gray). () Gallein inhibited chloroquine-evoked action potential firing. Representative current-clamp recording showed that gallein (100 μM) blocked chloroquine-evoked action potential firing. (n = 3–5 cells per compound). () Quantification of percentage of chloroquine-sensitive NG1! 08 cells expressing Mrgpra3 and Trpa1 and BAM-sensitive NG108 cells expressing Mrgprc11 and Trpa1 co-transfected with the phosducin (PH) or control vector (CN) (n = 3 transfections, with ≥1,200 cells per treatment). NS, not significant, P > 0.05; **P < 0.01, ***P < 0.001; one way ANOVA. All error bars represent s.e.m. * Figure 6: TRPA1-deficient mice are insensitive to chloroquine- and BAM-mediated itch. () Itch-evoked scratching was measured in wild-type (WT, black), TRPV1-deficient (Trpv1−/−, dark gray) and TRPA1-deficient (Trpa1−/−, light gray) mice following subcutaneous injection of chloroquine (200 mg per 50 μl, 8 mM) or BAM (60 μg per 10 μl, 3.5 mM) into the nape of the neck. The total time spent scratching was quantified for 20 min after injection. Injection of vehicle (phosphate-buffered saline, 50 μl) elicited some scratching in wild-type mice (VEH, white). () In the cheek model of itch, subcutaneous injection of a pruritogen into the cheek (chloroquine, 200 μg per 10 μl, 40 mM) elicited scratching of the cheek with the hindpaw (left). In contrast, injection of an irritant, mustard oil (1 mM), evoked wiping with one of the forelimbs (right). () Itch-evoked scratching was measured in wild-type (black), Trpv1−/− (dark gray) and Trpa1−/− (light gray) mice following chloroquine (200 μg per 10 μl, 40 mM) or BAM (60 μg per 10 μl, 3.5 mM) injecti! on in the cheek. The total time spent scratching was quantified for 20 min after injection. Injection of vehicle (phosphate-buffered saline, 10 μl) did not elicit scratching or wiping (VEH, white). NS, not significant, P > 0.05; **P < 0.01; ***P < 0.001, one-way ANOVA. All error bars represent s.e.m. (n ≥ 8 mice per genotype). Author information * Abstract * Author information * Supplementary information Affiliations * Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, California, USA. * Sarah R Wilson, * Kristin A Gerhold, * Amber Bifolck-Fisher & * Diana M Bautista * The Solomon H. Snyder Department of Neuroscience, Center for Sensory Biology and Howard Hughes Medical Institute, Johns Hopkins University, School of Medicine, Baltimore, Maryland, USA. * Qin Liu, * Kush N Patel & * Xinzhong Dong Contributions S.R.W. and K.A.G. designed and carried out the cellular imaging, electrophysiology and PCR experiments. S.R.W. and A.B.-F. designed and implemented the behavioral studies. Q.L. and K.N.P. contributed to the cellular and behavioral studies. S.R.W., K.A.G. and D.M.B. wrote the manuscript. X.D. and D.M.B. provided advice and guidance. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Diana M Bautista Author Details * Sarah R Wilson Search for this author in: * NPG journals * PubMed * Google Scholar * Kristin A Gerhold Search for this author in: * NPG journals * PubMed * Google Scholar * Amber Bifolck-Fisher Search for this author in: * NPG journals * PubMed * Google Scholar * Qin Liu Search for this author in: * NPG journals * PubMed * Google Scholar * Kush N Patel Search for this author in: * NPG journals * PubMed * Google Scholar * Xinzhong Dong Search for this author in: * NPG journals * PubMed * Google Scholar * Diana M Bautista Contact Diana M Bautista Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information Movies * Supplementary Movie 1 (3M) Itch–evoked scratching in response to chloroquine injection. A wild type mouse displays robust scratching following subcutaneous injection of chloroquine (200 ug/10 μL, 40 mM) into the cheek. Movie displays a representative 15 second period of scratching, 5 minutes post-injection. PDF files * Supplementary Text and Figures (1M) Supplementary Figure 1 Additional data - D-Serine regulates cerebellar LTD and motor coordination through the δ2 glutamate receptor
- Nat Neurosci 14(5):603-611 (2011)
Nature Neuroscience | Article D-Serine regulates cerebellar LTD and motor coordination through the δ2 glutamate receptor * Wataru Kakegawa1, 2 * Yurika Miyoshi3 * Kenji Hamase3 * Shinji Matsuda1, 2 * Keiko Matsuda1, 2 * Kazuhisa Kohda1, 2 * Kyoichi Emi1, 2 * Junko Motohashi1, 2 * Ryuichi Konno4 * Kiyoshi Zaitsu3 * Michisuke Yuzaki1, 2 * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 14,Pages:603–611Year published:(2011)DOI:doi:10.1038/nn.2791Received15 November 2010Accepted02 March 2011Published online03 April 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg D-Serine (D-Ser) is an endogenous co-agonist for NMDA receptors and regulates neurotransmission and synaptic plasticity in the forebrain. D-Ser is also found in the cerebellum during the early postnatal period. Although D-Ser binds to the δ2 glutamate receptor (GluD2, Grid2) in vitro, its physiological significance has remained unclear. Here we show that D-Ser serves as an endogenous ligand for GluD2 to regulate long-term depression (LTD) at synapses between parallel fibers and Purkinje cells in the immature cerebellum. D-Ser was released mainly from Bergmann glia after the burst stimulation of parallel fibers in immature, but not mature, cerebellum. D-Ser rapidly induced endocytosis of AMPA receptors and mutually occluded LTD in wild-type, but not Grid2-null, Purkinje cells. Moreover, mice expressing mutant GluD2 in which the binding site for D-Ser was disrupted showed impaired LTD and motor dyscoordination during development. These results indicate that glial D-Ser regula! tes synaptic plasticity and cerebellar functions by interacting with GluD2. View full text Figures at a glance * Figure 1: D-Ser causes a decrease in PF-EPSCs through GluD2. () Representative data showing PF-EPSC reduction induced by application of exogenous D-Ser (200 μM; 10 min during time 0–10 min) in a cerebellar slice from immature wild-type (WT) mouse. The insets show PF-EPSCs observed just before (1) and 30 min after (2) the application of D-Ser. () Averaged data of D-Ser–mediated PF-EPSC rundown recorded from immature wild-type Purkinje cells in the absence (–) or presence (+) of NMDA receptor blockers (100 μM D-AP5 plus 25 μM MK801) in the extracellular solution. (,) Averaged data showing effect of D-Ser on PF-EPSC reduction in immature cerebellar slices from Grid2-null (), Grid2-null TgWT (open circles in ) or Grid2-null TgR/K (filled circles in ) mice. During the recordings, NMDA receptor blockers were continuously perfused. Insets in – indicate the representative PF-EPSCs just before (black traces) and 30 min after (gray traces) the application of D-Ser in each condition. () Dose-response curve for D-Ser–mediated PF-EPSC! reduction in wild-type cerebellar slices in the presence of NMDA receptor blockers. Each PF-EPSC amplitude was normalized with that before D-Ser application (for 1 min) and the mean EPSC amplitudes 25−30 min after D-Ser application were plotted against [D-Ser]. We estimated EC50 using the sigmoidal curve fitting methods corresponding to logistical function. The number of experiments is shown in parentheses. P values were obtained using Mann-Whitney's U test. Data represent means ± s.e.m. * Figure 2: D-Ser induces AMPA receptor endocytosis by binding to GluD2. () D-Ser–mediated reduction in PF-EPSCs was blocked by AP2-specific binding peptide (pep-ΔA849-Q853; 500 μM) but not by the control peptide (pep-K844A; 500 μM) in patch pipettes. Inset traces show representative PF-EPSCs observed just before (black traces) and 30 min after (gray traces) the application of D-Ser (200 μM) for each condition. () Representative images showing the cell-surface expression of virally introduced HA-GluA2 (surface HA-GluA2; left) on wild-type Purkinje cell dendrites in the absence (–; top) and presence (+; bottom) of treatment with D-Ser (1 mM for 30 min). After the staining of cell surface HA-GluA2 with anti-HA antibodies and treatment with detergents, all HA-GluA2 was stained using anti-HA antibodies (total HA-GluA2; right). Each Purkinje cell dendrite was identified by the staining of a Purkinje cell-positive marker, calbindin (middle). (,) Continuous PF-EPSC recordings obtained by the application of CJ-stim (30 × [parallel fiber stimulat! ion plus Purkinje cell depolarization] at 1 Hz; arrow) followed by exogenous D-Ser (200 μM) () or the application of exogenous D-Ser followed by CJ-stim () in immature wild-type cerebellar slices. The second conditioning stimulation was added 30 min after the first conditioning stimulation. Insets show representative PF-EPSCs just before the first conditioning stimulation (1) and just before (2) and 30 min after (3) the second conditioning stimulation. The P value was obtained using Mann-Whitney's U test. Data represent means ± s.e.m. * Figure 3: Activity-dependent increase in extracellular [D-Ser] in immature wild-type cerebellar slices. (–) Representative 2D-HPLC spectrograms measured from extracellular solutions superfusing the cerebellar slices without parallel fiber stimulation (no stim; ,), with parallel fiber stimulation in the absence (PF burst; ,) or presence of NaFAC (NaFAC + PF burst; ) or NASP (NASP + PF burst; ) treatment, and with kainate treatment (100 μM for 5 min; ,). The spectrograms in – and – are from immature and mature wild-type cerebellar slices, respectively. Filled and open circles represent signal peaks for D- and L-Ser, respectively. () Averaged data showing extracellular [D-Ser] after each stimulation in immature (top; n = 17 slices from 12 mice each) and mature (bottom; n = 14 slices from 7 mice each) slices. [D-Ser] was calculated from the fluorescence intensity of the signal peak for D-Ser. nd, not determined. *P < 0.05 (ANOVA with Dunnett's test). Data represent means ± s.e.m. * Figure 4: Endogenous D-Ser is released mainly from Bergmann glia and regulates LTD in the developing cerebellum. () Diagram showing the CJ-stim protocol (30 × [10 cycles of parallel fiber stimuli at 50 Hz plus Purkinje cell depolarization from −60 mV to +20 mV] at 1 Hz; top) and the CJ-stim–derived Ca2+ spike responses (bottom). All responses are overlaid as gray traces and the representative one is shown as a black trace. (,) Averaged data showing cerebellar LTD from immature () or mature () wild-type cerebellar slices in the absence (–) or presence (+) of DAAO (0.125 U ml−1, preincubation for at least 60 min and perfusion during recordings). (,) Averaged data for cerebellar LTD from immature () or mature () wild-type cerebellar slices in the absence (control) or presence of NaFAC (3 mM, preincubation for at least 90 min) or NASP (100 μM, perfusion during recordings) treatment. () Immunohistochemical images showing the adenoviral (AV) expression of GFP (green) and a glial marker, 3-phosphoglycerate dehydrogenase (3-PGDH; red), in a cerebellar slice from an immature (P13) wil! d-type mouse. () Averaged data for cerebellar LTD from immature wild-type Purkinje cells whose neighboring Bergmann glia were infected with AV-GFP or AV-GFP-TeNT. CJ-stim was applied at 0 min (arrow). Insets (–,) show PF-EPSC traces just before (black) and 30 min after (gray) CJ-stim in each condition. P values were obtained using Mann-Whitney's U test in ,, and ANOVA in ,. Data represent means ± s.e.m. * Figure 5: Cerebellar LTD is enhanced by D-Ser binding to GluD2 in the developing cerebellum. (,) Results of cerebellar LTD in the absence (control) or presence of treatment with NMDA receptor blockers (100 μM D-AP5 plus 25 μM MK801, perfusion during recording) or NMDA receptor blockers plus DAAO (0.125 U ml−1, preincubation for at least 60 min and perfusion during recordings) in immature () and mature () wild-type cerebellar slices. () Averaged data of LTD recordings from mature Purkinje cells in Dao+/+ and Dao−/− cerebellar slices treated with or without DAAO (0.125 U ml−1, preincubation for at least 60 min and perfusion during recordings). (,) Averaged data showing cerebellar LTD in immature () and mature () Purkinje cells from Grid2-null TgWT or Grid2-null TgR/K cerebellar slices. NMDA receptor blockers were constantly added to the extracellular solution during the recordings in –. CJ-stim was applied at 0 min (arrow). Insets show representative PF-EPSCs just before (black traces) and 30 min after (gray traces) CJ-stim for each condition. P values wer! e obtained using Mann-Whitney's U test. Data represent means ± s.e.m. * Figure 6: Disruption of D-Ser binding to GluD2 impaired motor coordination and learning in developing mice. (,,,,) Continuous measurements of the rotor-rod test performed over 5 d (Day 1 to 5) in immature (,) or mature (,,) Grid2-null TgWT and Grid2-null TgR/K mice. Daily sessions consisted of six trials and the retention time on the rotating rod was measured (maximum score, 120 s in ,, and 300 s in ,). The rotating speeds were set at 5 r.p.m. in ,, 20 r.p.m. in and 4−40 r.p.m. in ,. P values were obtained using two-way repeated measure ANOVA. (,,,,) Averaged data of ,,, and , respectively. The results were averaged every day (6 trials) for each condition. ***P < 0.001, **P < 0.01, *P < 0.05 (ANOVA with Bonferroni's correction for multiple comparisons). Data represent means ± s.e.m. * Figure 7: D-Ser conveys signals for LTD through the cytoplasmic C-terminal tails of GluD2 independent of its channel function but dependent on PKC activities in immature Purkinje cells. () Immunohistochemical images showing Sindbis viral expression of GFP (green) and GluD2 (red) in a cerebellar slice from an immature (P13) Grid2-null mouse. () Rescue of impaired cerebellar LTD in Grid2-null Purkinje cells by the viral expression of GFP plus GluD2WT (GluD2WT) or GluD2V/R (GluD2V/R), but not GFP alone (vector). (,) LTD in the developing cerebellum requires the C-terminal tails of GluD2. Averaged data of cerebellar LTD () and PF-EPSC changes induced by exogenous D-Ser (200 μM during 0−10 min, ) in immature Grid2-null TgΔCT7 mice. (,) LTD in the developing cerebellum requires PKC activities in Purkinje cells. Averaged data of cerebellar LTD () and PF-EPSC changes induced by exogenous D-Ser (200 μM during 0−10 min, ) in immature wild-type Purkinje cells loaded with a PKC inhibitory peptide (PKC[19–36]; 500 μM) or a control peptide (PKC[19–36]-R27E; 500 μM) in the patch pipette. In experiments shown in – and NMDA receptor blockers were constantly a! dded to the extracellular solution. CJ-stim was applied at 0 min (arrows). Insets show representative PF-EPSCs observed just before (black traces) and 30 min after (gray traces) CJ-stim (,,) or D-Ser application (,). P values were obtained using ANOVA in and Mann-Whitney's U test in ,. Author information * Abstract * Author information * Supplementary information Affiliations * Department of Physiology, School of Medicine, Keio University, Shinjuku-ku, Tokyo, Japan. * Wataru Kakegawa, * Shinji Matsuda, * Keiko Matsuda, * Kazuhisa Kohda, * Kyoichi Emi, * Junko Motohashi & * Michisuke Yuzaki * Core Research for Evolutional Science and Technology, Japan Science and Technology Corporation, Kawaguchi, Saitama, Japan. * Wataru Kakegawa, * Shinji Matsuda, * Keiko Matsuda, * Kazuhisa Kohda, * Kyoichi Emi, * Junko Motohashi & * Michisuke Yuzaki * Graduate School of Pharmaceutical Science, Kyushu University, Higashi-ku, Fukuoka, Japan. * Yurika Miyoshi, * Kenji Hamase & * Kiyoshi Zaitsu * Center for Medical Science, International University of Health and Welfare Graduate School, Ohtawara, Tochigi, Japan. * Ryuichi Konno Contributions W.K. designed the experiments, performed the electrophysiological, immunohistochemical and behavioral studies, analyzed the data, and wrote the manuscript. Y.M., K.H. and K.Z. performed 2D-HPLC analysis. S.M. and K.M. performed cell surface staining. K.K. prepared the recombinant viruses and performed the biochemical analysis. K.E. supported behavioral experiments. J.M. performed biochemical assays and maintained mouse lines. R.K. provided the Dao−/− mouse. M.Y. supervised the project, designed the experiments and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Michisuke Yuzaki Author Details * Wataru Kakegawa Search for this author in: * NPG journals * PubMed * Google Scholar * Yurika Miyoshi Search for this author in: * NPG journals * PubMed * Google Scholar * Kenji Hamase Search for this author in: * NPG journals * PubMed * Google Scholar * Shinji Matsuda Search for this author in: * NPG journals * PubMed * Google Scholar * Keiko Matsuda Search for this author in: * NPG journals * PubMed * Google Scholar * Kazuhisa Kohda Search for this author in: * NPG journals * PubMed * Google Scholar * Kyoichi Emi Search for this author in: * NPG journals * PubMed * Google Scholar * Junko Motohashi Search for this author in: * NPG journals * PubMed * Google Scholar * Ryuichi Konno Search for this author in: * NPG journals * PubMed * Google Scholar * Kiyoshi Zaitsu Search for this author in: * NPG journals * PubMed * Google Scholar * Michisuke Yuzaki Contact Michisuke Yuzaki Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (1M) Supplementary Figures 1–17 Additional data - A Drosophila model for alcohol reward
- Nat Neurosci 14(5):612-619 (2011)
Nature Neuroscience | Article A Drosophila model for alcohol reward * Karla R Kaun1 * Reza Azanchi1 * Zaw Maung1 * Jay Hirsh2 * Ulrike Heberlein1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature NeuroscienceVolume: 14,Pages:612–619Year published:(2011)DOI:doi:10.1038/nn.2805Received12 January 2011Accepted09 March 2011Published online17 April 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The rewarding properties of drugs contribute to the development of abuse and addiction. We developed a new assay for investigating the motivational properties of ethanol in the genetically tractable model Drosophila melanogaster. Flies learned to associate cues with ethanol intoxication and, although transiently aversive, the experience led to a long-lasting attraction for the ethanol-paired cue, implying that intoxication is rewarding. Temporally blocking transmission in dopaminergic neurons revealed that flies require activation of these neurons to express, but not develop, conditioned preference for ethanol-associated cues. Moreover, flies acquired, consolidated and retrieved these rewarding memories using distinct sets of neurons in the mushroom body. Finally, mutations in scabrous, encoding a fibrinogen-related peptide that regulates Notch signaling, disrupted the formation of memories for ethanol reward. Our results thus establish that Drosophila can be useful for unde! rstanding the molecular, genetic and neural mechanisms underling the rewarding properties of ethanol. View full text Figures at a glance * Figure 1: Ethanol is both aversive and rewarding to flies. () Flies were trained by three spaced training sessions of a 10-min exposure to one odor followed by a 10-min exposure to the second odor paired with 53% ethanol vapor. During the test, flies were given the choice of the two odors and a preference index was calculated by subtracting the number of flies entering the vial with the odor not previously associated with ethanol (odor−) from the vial with the odor previously associated with ethanol (odor+) and dividing this number by the total number of flies. CPI was calculated by averaging the preference indexes of the two reciprocal groups. () Flies showed conditioned aversion when tested 30 min after training (n = 8, P = 0.006) and conditioned preference 24 h after training (n = 8, P = 0.02) compared with an unpaired control (Wilcoxon two sample). *P < 0.05. () Conditioned preference lasted for up to 7 d if flies were left undisturbed (Wilcoxon one way, n = 8, P = 0.007 on day 7). () Compared with flies that received either o! dor or ethanol alone, flies conditioned with ethanol or sucrose (Dunnett's, n = 11 flies per group, P = 0.05 and P = 0.006, respectively) walked over a 2-cm, 100-V electric grid to attain the conditioned odor, whereas only flies conditioned with ethanol walked over a 120-V electric grid to attain the conditioned odor (P = 0.0004). Exposures to either odor alone or ethanol alone (P = 0.99 and P = 0.87, respectively) did not affect the likelihood of walking over an electric grid. CS, conditioned stimulus. All values are reported as mean ± s.e.m. * Figure 2: Pharmacological properties of ethanol induce preference. () Flies absorbed significant amounts of ethanol during conditioning (Student's t post hoc test, n = 11 flies per group, P = 0.04, P = 0.02 and P = 0.004 for trials 1, 2 and 3, respectively) and recovered within 30 min (P = 0.54). *P < 0.05. () Ethanol absorbed during training induced a significant increase in locomotor activity characteristic of acute intoxication (repeated-measures ANOVA, n = 11 flies per group, P = 0.002). () An odor presented before ethanol resulted in significant conditioned aversion (Wilcoxon one way, n = 8 flies per group, P = 0.007), but not conditioned preference (P = 1.00), suggesting that an odor can predict onset of the aversive effects of ethanol. () An odor presented directly after ethanol resulted in significant conditioned aversion and significant conditioned preference (Wilcoxon one way, n = 8, P = 0.007 for both behaviors), suggesting that ethanol intoxication is required for conditioned preference to form. All data are shown as mean ± s.e! .m. * Figure 3: Dopamine is required for conditioned preference. (,) Blocking synaptic transmission in dopaminergic neurons during both training and testing did not affect conditioned aversion tested 30 min after training (Kruskal-Wallis, n = 8 flies per group, P = 0.84, ), but blocked the formation of preference in both TH- and Ddc-expressing neurons tested 24 h later (Wilcoxon one way, n = 8, P = 0.0003 and P = 0.007, respectively, ). *P < 0.05. () Conditioned aversion was not affected by decreasing serotonin levels in the brain using αMTP or dopamine levels using 3IY (Kruskal-Wallis, n = 8 flies per group, P = 0.07). () Conditioned preference was not affected by αMTP (Student's t post hoc, n = 8 flies per group, P = 0.21), but was blocked by decreasing dopamine levels in the brain using 3IY (P = 0.0002). All data are shown as mean ± s.e.m. * Figure 4: Dopamine is required for expression of ethanol reward. (,) Transiently blocking neurotransmission of TH-expressing cells during acquisition () or consolidation () did not affect conditioned preference (Kruskal-Wallis, n = 8 flies per group, P = 0.06 and P = 0.27, respectively). () Activity of TH-expressing cells was required for the retrieval or expression of conditioned preference (Kruskal-Wallis, n = 8 flies per group, P = 0.0005). *P < 0.05. All data are shown as mean ± s.e.m. * Figure 5: The mushroom body is required for aversion and preference. () Schematic of the subsets of mushroom body neurons: yellow, γ neurons; blue, αβ neurons; red, α′β′ neurons. () We transiently inactivated neurotransmission in selected sets of mushroom body neurons using the GAL4 drivers OK107, 201Y, MB247, 5-66a and 4-59. Blocking synaptic transmission of specific mushroom body neurons using the GAL4 drivers OK107 (Student's t post hoc, n = 8 per group, P < 0.0001), 201Y (P = 0.003), MB247 (P < 0.0001) and 5-66a (P = 0.01) during training and testing disrupted conditioned aversion tested 30 min after training. Colored circles represent mushroom body neurons in which GAL4 drivers are expressed as defined above. *P < 0.05. () Inactivation of mushroom body using OK107 (P < 0.0001), 201Y (P = 0.003), MB247 (P < 0.0001) and 5-66a (P = 0.01) during both training and test disrupted conditioned preference 24 h after training. All data are shown as mean ± s.e.m. * Figure 6: Sequential use of mushroom body neurons. () Inactivation using drivers OK107 (Student's t post hoc, n = 8 flies per group P < 0.0001), 201Y (P < 0.0001) and MB247 (P = 0.006), but not 5-66a, during training disrupted acquisition, implicating the γ neurons in acquisition of conditioned preference. *P < 0.05. () Inactivation using drivers OK107 (P = 0.004) and 4-59 (P = 0.02) disrupted stabilization, implicating the α′β′ neurons in consolidation of conditioned preference. () Inactivation using drivers OK107 (P < 0.0001), 201Y (P = 0.003), MB247 (P < 0.0001) and 5-66a (P < 0.0001) disrupted retrieval, implicating the αβ neurons in retrieval or expression of conditioned preference. All data are shown as mean ± s.e.m. * Figure 7: sca affects memories for ethanol reward. () A screen for conditioned ethanol preference of 160 P{GawB}-containing strains with known expression in the mushroom body identified three mutations in which conditioned aversion persisted 24 h after training (magenta), 54 mutations in which conditioned preference was not expressed (orange) and three mutations in which conditioned preference was enhanced (green). Strains that showed CPI that was not significantly different from control are shown in gray. Values represent mean (n = 8 per strain). () In the sca5-120 mutant, the P{GawB} element was inserted 125 bp 5′ of exon 1 of sca. () Quantitative PCR revealed that the sca5-120 mutation decreased sca mRNA expression to 55% that of wild-type controls (mean ± s.e.m., n = 6 independent samples). () sca5-120 did not affect conditioned aversion for ethanol 30 min after training. () sca5-120 affected conditioned preference for ethanol 24 h after training. () Complementation analysis of conditioned preference 30 min after trai! ning with two independent sca alleles confirmed that sca did not affect conditioned aversion. () sca5-120 failed to complement the sca1 and scaBP2 alleles for 24-h conditioned preference. CPI values represent mean ± s.e.m. () The sca5-120-GAL4 expression pattern suggests that sca is expressed in the mushroom body αβ and γ neurons, the antennal lobe (AL), eye and a number of cell bodies near the ventrolateral protocerebrum and subesophageal ganglia (SEG) (see also Supplementary Fig. 7). Scale bar represents 50 μm. Author information * Abstract * Author information * Supplementary information Affiliations * Department of Anatomy, University of California, San Francisco, California, USA. * Karla R Kaun, * Reza Azanchi, * Zaw Maung & * Ulrike Heberlein * Department of Biology, University of Virginia, Charlottesville, Virginia, USA. * Jay Hirsh Contributions K.R.K. conceived, conducted and interpreted the experiments, performed data analysis, and co-wrote the paper. R.A. assisted with the behavior experiments. Z.M. conducted control experiments. J.H. performed high-performance liquid chromatography experiments. U.H. conceived and interpreted experiments and co-wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Ulrike Heberlein or * Karla R Kaun Author Details * Karla R Kaun Contact Karla R Kaun Search for this author in: * NPG journals * PubMed * Google Scholar * Reza Azanchi Search for this author in: * NPG journals * PubMed * Google Scholar * Zaw Maung Search for this author in: * NPG journals * PubMed * Google Scholar * Jay Hirsh Search for this author in: * NPG journals * PubMed * Google Scholar * Ulrike Heberlein Contact Ulrike Heberlein Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (3M) Supplementary Figures 1–7 and Supplementary Tables 1–5 Additional data - Activation of dopamine neurons is critical for aversive conditioning and prevention of generalized anxiety
- Nat Neurosci 14(5):620-626 (2011)
Nature Neuroscience | Article Activation of dopamine neurons is critical for aversive conditioning and prevention of generalized anxiety * Larry S Zweifel1, 2, 3, 8 * Jonathan P Fadok3, 4, 8 * Emmanuela Argilli5 * Michael G Garelick4 * Graham L Jones1, 2 * Tavis M K Dickerson3 * James M Allen6 * Sheri J Y Mizumori7 * Antonello Bonci5 * Richard D Palmiter3 * Affiliations * Contributions * Corresponding authorsJournal name:Nature NeuroscienceVolume: 14,Pages:620–626Year published:(2011)DOI:doi:10.1038/nn.2808Received18 January 2011Accepted18 March 2011Published online17 April 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Generalized anxiety is thought to result, in part, from impairments in contingency awareness during conditioning to cues that predict aversive or fearful outcomes. Dopamine neurons of the ventral midbrain exhibit heterogeneous responses to aversive stimuli that are thought to provide a critical modulatory signal to facilitate orientation to environmental changes and assignment of motivational value to unexpected events. Here we describe a mouse model in which activation of dopamine neurons in response to an aversive stimulus is attenuated by conditional genetic inactivation of functional NMDA receptors on dopamine neurons. We discovered that altering the magnitude of excitatory responses by dopamine neurons in response to an aversive stimulus was associated with impaired conditioning to a cue that predicts an aversive outcome. Impaired conditioning by these mice was associated with the development of a persistent, generalized anxiety-like phenotype. These data are consistent! with a role for dopamine in facilitating contingency awareness that is critical for the prevention of generalized anxiety. View full text Figures at a glance * Figure 1: NMDARs control amplitude of activation of dopamine neurons in response to tail pinch. (,) Assessment of NMDAR-dependent activation of dopamine neurons during tail pinch. Peri-event time histograms of representative dopamine neurons illustrating inhibitory () and excitatory () responses to tail pinch (n = 5 control mice and n = 6 knockout mice). Inserts, average waveform for representative neurons is shown on the left and pie charts showing the proportion of quinpirole-sensitive neurons inhibited or activated by tail pinch (black shade) for control and knockout mice are shown on the right. (,) Average Z score corrected inhibitory () and excitatory () responses to tail pinch (dashed lines represent s.e.m., s.e.m.). Excitatory responses are significantly reduced in knockout mice compared to controls (Bonferroni post-tests, ***P < 0.001). * Figure 2: Cue-dependent fear conditioning is impaired in knockout mice. () Startle amplitude was enhanced 10 min after cue–foot shock pairings to a greater extent in knockout (n = 8) than control (n = 9) mice in both the presence and absence of the cue (Bonferroni post-tests, P < 0.05 and P < 0.01 post-conditioning compared with pre-conditioning in the presence or absence of the cue, *P < 0.05 knockout compared with control no cue and cue tests, #P < 0.05 and ##P < 0.01 test compared to baseline). () Amplitude of startle response in conditioned knockout mice at 105 dB was lower than the startle response of unconditioned knockout mice at 120 dB. Startle amplitude to foot shock during conditioning trials was not different between groups. Error bars represent s.e.m. * Figure 3: Sensitization of ASR following fear conditioning in knockout mice is context independent. () ASR before (dashed line) and 10 min after foot shock conditioning (solid line) in a distinct environmental context (control, n = 13; knockout, n = 11; Bonferroni post-tests, *P < 0.05, knockout post-shock versus knockout pre-shock and control pre- and post-shock). () ASR (control, n = 14; knockout, n = 14) before (dashed line) and 1 d post-shock (solid line) was elevated in knockout mice following shock (Bonferroni post-tests, ***P < 0.001 and *P < 0.05, knockout post-shock versus knockout pre-shock and control pre- and post-shock). () Same groups of mice as in 1 week following conditioning in novel context. We observed persistent elevation of the ASR in knockout mice following foot shock (Bonferroni post-tests, knockout post-shock versus knockout pre-shock and control pre- and post-shock). () ASR following repeated exposure to ASR chamber without conditioning (control, n = 8; knockout, n = 7) is not different between groups. () Average ASR at 105 dB across all groups of ! mice pre- and post-conditioning (NS, no shock; repeated exposure group; Bonferroni post-tests, knockout post-shock versus knockout pre-shock and knockout post-shock versus control pre- and post-shock). Error bars represent s.e.m. * Figure 4: Anxiety-related behavior is enhanced in knockout mice following foot shock conditioning. () Frequency of open-arm entries in an elevated-plus maze following foot shock was significantly reduced in knockout (n = 14) compared with control mice (n = 13) or mice repeatedly exposed (RE) to the elevated-plus maze (Bonferroni post-tests, **P < 0.01, knockout post-shock versus all other groups). () Representative activity traces from control (left) and knockout mice (right) in elevated-plus maze test following foot shock (C, closed arm; O, open arm). () Frequency of center crossings in an open-field apparatus by knockout mice (n = 14) following foot shock conditioning was reduced compared to control mice (n = 13) or mice repeatedly exposed to the open field (knockout, n = 13; control, n = 10; Bonferroni post-tests, *P < 0.05, knockout post-shock versus all other groups). () Representative activity traces from control (left) and knockout mice (right) in open field following foot shock conditioning. () Distance traveled in the open arm of the elevated-plus maze was signif! icantly reduced in knockout mice following foot shock compared with other groups (Bonferroni post-tests, *P < 0.05, knockout post-shock versus all other groups). () Distance traveled in closed arm of elevated-plus maze was not significantly reduced in knockout mice that received foot shock. *P < 0.05. Error bars represent s.e.m. * Figure 5: Sensory motor gating, peripheral stress response and monoamine levels are not altered following foot shock conditioning. () Increasing pre-pulse intensities led to greater PPI of ASRs, but was not altered in knockout mice following foot shock. () Cort was increased immediately (t = 0) after exposure to the startle chamber with shock (S) or without shock (NS) and was elevated 1 h following shock, but not 1 d or 1 week later. () Whole-brain monoamine as measured by high-performance liquid chromatography were not different in knockout or control mice that had received shock. DA, dopamine; NE, norepinephrine; 5-HT, serotonin. () Monoamine metabolites were unaltered by foot shock conditioning. 5-HIAA, 5-hydroxyindoleacetic acid; DOPAC, dihydroxyphenylacetic acid; HVA, homovanillic acid. Error bars represent s.e.m. * Figure 6: Conditional restoration of NMDAR signaling to ventral midbrain dopamine neurons prevents generalized anxiety-like behavior. () Low magnification of ventral midbrain (top). HA-NR1 (green) was predominantly localized to the tyrosine hydroxylase (TH)-positive region of the VTA and not the SNc. Scale bar represents 500 μm. High-magnification (bottom) images reveled that HA-NR1 colocalized with tyrosine hydroxylase–positive neurons. Scale bar represents 25 μm. () Evoked AMPAR- and NMDAR-mediated EPSCs from control, knockout and virally rescued knockout mice. (–) Expression of HA-NR1 in knockout mice prevented generalized anxiety-like behavior: ASR (), frequency of open arm entries in the elevated-plus maze (), and frequency of center crossing in the open field () before and after foot shock conditioning in novel context (control, n = 11; virally rescued knockout, n = 11). Error bars represent s.e.m. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Larry S Zweifel & * Jonathan P Fadok Affiliations * Department of Pharmacology, University of Washington, Seattle, Washington, USA. * Larry S Zweifel & * Graham L Jones * Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, Washington, USA. * Larry S Zweifel & * Graham L Jones * Department of Biochemistry and Howard Hughes Medical Institute, University of Washington, Seattle, Washington, USA. * Larry S Zweifel, * Jonathan P Fadok, * Tavis M K Dickerson & * Richard D Palmiter * Graduate Program in Neurobiology and Behavior, University of Washington, Seattle, Washington, USA. * Jonathan P Fadok & * Michael G Garelick * Ernest Gallo Clinic and Research Center and Department of Neurology, University of California, San Francisco, San Francisco, California, USA. * Emmanuela Argilli & * Antonello Bonci * Department of Neurology, University of Washington, Seattle, Washington, USA. * James M Allen * Department of Psychology, University of Washington, Seattle, Washington, USA. * Sheri J Y Mizumori Contributions L.S.Z. and J.P.F. designed the experiments. L.S.Z. performed in vivo recordings with assistance from G.L.J. and S.J.Y.M. L.S.Z. and J.P.F. performed behavioral experiments with assistance from M.G.G. and T.M.K.D. E.A. performed slice physiology with support from A.B. R.D.P. constructed the AAV1-fs-HA-NR1 viral vector. J.M.A. purified AAV1-fs-HA-NR1. The manuscript was written by L.S.Z. with assistance from J.P.F. and R.D.P. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Larry S Zweifel or * Richard D Palmiter Author Details * Larry S Zweifel Contact Larry S Zweifel Search for this author in: * NPG journals * PubMed * Google Scholar * Jonathan P Fadok Search for this author in: * NPG journals * PubMed * Google Scholar * Emmanuela Argilli Search for this author in: * NPG journals * PubMed * Google Scholar * Michael G Garelick Search for this author in: * NPG journals * PubMed * Google Scholar * Graham L Jones Search for this author in: * NPG journals * PubMed * Google Scholar * Tavis M K Dickerson Search for this author in: * NPG journals * PubMed * Google Scholar * James M Allen Search for this author in: * NPG journals * PubMed * Google Scholar * Sheri J Y Mizumori Search for this author in: * NPG journals * PubMed * Google Scholar * Antonello Bonci Search for this author in: * NPG journals * PubMed * Google Scholar * Richard D Palmiter Contact Richard D Palmiter Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–4 Additional data - Glutamatergic pre-ictal discharges emerge at the transition to seizure in human epilepsy
- Nat Neurosci 14(5):627-634 (2011)
Nature Neuroscience | Article Glutamatergic pre-ictal discharges emerge at the transition to seizure in human epilepsy * Gilles Huberfeld1, 2, 3 * Liset Menendez de la Prida1, 4 * Johan Pallud1, 5 * Ivan Cohen1 * Michel Le Van Quyen6 * Claude Adam2 * Stéphane Clemenceau1, 2, 7 * Michel Baulac1, 2 * Richard Miles1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature NeuroscienceVolume: 14,Pages:627–634Year published:(2011)DOI:doi:10.1038/nn.2790Received28 December 2010Accepted02 March 2011Published online03 April 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The mechanisms involved in the transition to an epileptic seizure remain unclear. To examine them, we used tissue slices from human subjects with mesial temporal lobe epilepsies. Ictal-like discharges were induced in the subiculum by increasing excitability along with alkalinization or low Mg2+. During the transition, distinct pre-ictal discharges emerged concurrently with interictal events. Intracranial recordings from the mesial temporal cortex of subjects with epilepsy revealed that similar discharges before seizures were restricted to seizure onset sites. In vitro, pre-ictal events spread faster and had larger amplitudes than interictal discharges and had a distinct initiation site. These events depended on glutamatergic mechanisms and were preceded by pyramidal cell firing, whereas interneuron firing preceded interictal events that depended on both glutamatergic and depolarizing GABAergic transmission. Once established, recurrence of these pre-ictal discharges triggered! seizures. Thus, the subiculum supports seizure generation, and the transition to seizure involves an emergent glutamatergic population activity. View full text Figures at a glance * Figure 1: Ictal discharges generated in the human subiculum. Convulsants produced patterned ictal discharges restricted to the subiculum. () Multiple extracellular recordings of an ictal event in a slice containing the hippocampus, subiculum and entorhinal cortex. Electrode locations: 1, dentate gyrus; 2, CA2; 3, CA1; 4–5–6, subiculum; 7, presubiculum; 8, entorhinal cortex. () Ictal event structure. An ictal discharge recorded in a 65 mM HCO3− and 8 mM K+ solution. Top, pre-ictal discharges (larger events, filled circles) recurred before a fast low-voltage activity (gray line) at seizure onset followed by rythmic bursts (black line). Seizure onset is indicated by the dotted arrow. Middle, time frequency representation of the local field potential (LFP). Bottom, multi-unit activity (MUA) revealed recurring PIDs of short duration followed by the rapid unpatterned action potential discharges at seizure onset and then by oscillatory bursts. * Figure 2: IIDs, PIDs and ictal discharges in intracranial recordings. () Stereo EEG recording (electrode HipAg1) showing activity of the subiculum and head of the hippocampus at seizure onset. The seizure was preceded by recurring IIDs (blue circles) and PIDs (pink circles). It began (arrow) with fast low-voltage activity and continued with oscillatory rhythmic bursts. () Recordings from multiple electrode contacts on a referential montage. Traces from contacts with no epileptic activity are shown in green, those with isolated IIDs in blue, and those recording both IIDs and PIDs in pink. Left, IID sample (blue circle). Middle, PID sample (pink circle). Right, seizure onset (thick arrow). The thin arrow indicates an expanded trace from the HipAg1 contact in . Seizure onset is highlighted in yellow. Electrodes are identified according to the recorded area (amyg, amygdala; Hip, hippocampus; TB, temporo-basal; T2, second temporal gyrus; OrFr, orbito-frontal), location (A, anterior; M, median; P, posterior; AP, antero-posterior) and hemisphere (g, ! left; d, right). The first contact is at the tip of the electrode and the last as it emerges from the cranium. () Amplitude distribution for all field potentials preceding a single ictal event by 30 min showing the distinct amplitudes of IIDs (25–125 μV) and PIDs (150–500 μV). () Three-dimensional reconstruction of electrode contacts from post-implantation magnetic resonance imaging showing sites where PIDs (pink), IIDs (blue) or no epileptic events (green) were recorded. An arrow highlighted in yellow indicates the site of seizure onset. The name of each electrode is shown at the site of emergence from the skull. * Figure 3: PIDs emerge during the transition to ictal-like activity in vitro. () Extracellular recordings of the transition to seizure-like activity induced by increased external HCO3− (85 mM) and K+ (8 mM). E1 and E2 are recordings from two subicular electrodes. MUA frequency (upper trace) and the extracellular signal from E2 (lower trace) are shown. () Amplitude measurements for all field potentials recorded by electrode E2 during the transition show the emergence of larger PIDs, whereas the amplitude of inter-ictal events did not change. () Dual extracellular recordings showing IIDs (open circles, left) before convulsant application and coexpression of PIDs (filled circles, right) with IIDs during the transition. () Amplitude distribution for all field potentials during the 35-min transition period showed IIDs of amplitude 10–50 μV and PIDs of amplitude 125–175 μV. () Mean and s.d. of the amplitude (black), duration (red) and propagation speed (blue) of IIDs and PIDs at steady state. Amplitudes and propagation speed, but not durations, were! significantly different (line with asterisk). () Propagation of IIDs and PIDs. Triple extracellular recording (E1, E2, E3; E1–E2 distance, 1 mm; E2–E3 distance, 0.7 mm; E1–E3 distance, 1.4 mm) during the transition to ictal-like events. Field potential (FP) amplitude is plotted from signals from each electrode and the propagation speed of fields during the transition (between E1 and E3) is shown above. Top traces show initial IIDs (left), emerging PIDs (middle) and fully developed PIDs (right). Gray lines link FP peaks. * Figure 4: PIDs depend on glutamatergic signaling. () Intracellular recording from a subicular pyramidal cell (I) with a local extracellular recording (E). This cell received hyperpolarizing synaptic inputs during IIDs (open circle) both before and after convulsants were added. In contrast, it was depolarized during PIDs (filled circle) in the presence of convulsants. Intracellular action potentials were cut. () IIDs and PIDs coexisted during the transition to ictal discharges induced by 0.25 mM Mg2+ and 8 mM K+ (left trace). Bicuculline (bic) blocked IIDs, but not PIDs (middle left). The NMDA receptor blocker D,L-AP5 (100 μM) did not change PIDs (middle right), but the AMPA receptor antagonist NBQX (10 μM) suppressed them (right). () Distinct reversal potentials for synaptic events associated with IIDs and PIDs. The amplitude of postsynaptic potentials associated with IIDs (open circles) and PIDs (filled circles) is plotted against membrane potential during the transition. The data shown are from three different cells (bl! ack, blue and red). Inset, postsynaptic potentials associated with IIDs and PIDs at different membrane potentials. Intracellular (upper) and extracellular (lower). The mean reversal potential of IIDs was −59.1 ± 3.8 mV and the estimated reversal potential of PIDs was −15.1 ± 5.9 mV. () PIDs were induced by increasing excitability with high K+. Field potentials revealed that PIDs (filled circle) and IIDs (open circle) coexisted in 10 mM K+. * Figure 5: NMDA receptor signaling is involved in seizure generation and in the emergence of PIDs, but not their maintenance. All extracellular recordings were made from the same site in the subiculum. () Left, spontaneous IIDs (open circles). D,L-AP5 did not affect IIDs (middle), but the convulsant solution (10 mM K+ / 0.25 mM Mg2+) did not induce PIDs or ictal-like events (right trace) when D,L-AP5 was present. () Left, after D,L-AP5 washout, the convulsant solution induced PIDs (filled circles) during the transition period (middle left) to ictal discharges (gray line, middle right). Application of D,L-AP5 after PIDs had emerged did not change them, but suppressed the initiation of ictal-like events (right). * Figure 6: IIDs and PIDs are generated by distinct networks. (,) Firing of putative pyramidal cells () and interneurons () recorded juxtacellularly during IIDs (blue) and PIDs (red). Cell type was determined from action potential duration (upper traces) measured from the positive to the negative peak (pyramidal cells > 0.7 ms, interneurons < 0.7 ms). Spike timing for pyramidal cells and interneurons (shown as dots in the box), spike probability (histograms) and spike frequency (lower traces) are shown with respect to IID and PID field potentials (upper trace). The dotted line with an arrow tail indicates the onset of field potentials and the dotted line with an arrow head indicates its peak. Most pyramidal cells were inhibited during IIDs and fired during PIDs (left), whereas a subset of pyramidal cells (7 of 39) fired both during IIDs and before PIDs onset (right) (). All interneurons fired before IID onset and after PID initiation (left), but some interneurons (2 of 6) fired before both IID and PID onset (). * Figure 7: Dynamics of population activity during the transition to ictal events. () Dual extracellular recordings made during the interictal period (white line), the pre-ictal period (black line) and the onset of an ictal-like event (green line). Interictal events (open circle) and pre-ictal events (filled circle) during the transition are shown below on an expanded timescale. Time frequency analysis of the extracellular signal is shown below. () Cross-correlation index versus time lag for IIDs (empty circles) and PIDs (filled circles). () Three-dimensional plot of the cross-correlation index, time lag between sites, and the amplitude of the field potential for IIDs, PIDs and initial ictal discharges. () Histograms of the amplitude, time lag and cross-correlation index for each type of event. Error bars indicate s.d. Lines with an asterisk indicate a significant difference (P < 0.05). * Figure 8: Repeated PIDs trigger seizure-like events. () Dual extracellular recordings of an ictal event preceded by PIDs. The lower black trace was recorded at the site of onset of PIDs and ictal events. The upper gray record was made from a follower region. Right, expanded traces from the period indicated with the asterisk. () Electrical stimulation (2 Hz, 2 s, black sign) near the site of PID initiation elicited PIDs (expanded at right), which induced a seizure-like event. () Identical electrical stimulation (gray sign) in a region of PID propagation did not trigger seizure-like events. () High-intensity bipolar electrical stimulation (large gray sign) in the region of PID propagation generated PIDs at their initiation site. A seizure-like event followed. The double-headed arrow indicates the delay between stimulation and back-propagated PID onset. () Probability of triggering an ictal-like event by moderate intensity stimuli at the PID focus (black), at a follower site (white) or by strong stimuli at the follower site gener! ating back-propagated PIDs (gray). *P < 10−6, **P < 10−12. Author information * Abstract * Author information * Supplementary information Affiliations * Cortex and Epilepsy, Centre de Recherche de l'Institut du Cerveau et de la Moelle Epinière, INSERM UMRS975, Centre National de la Recherche Scientifique (CNRS) UMR7225, Université Pierre et Marie Curie (UPMC), Paris, France. * Gilles Huberfeld, * Liset Menendez de la Prida, * Johan Pallud, * Ivan Cohen, * Stéphane Clemenceau, * Michel Baulac & * Richard Miles * Unité d'Epileptologie, Centre Hospitalo-Universitaire Pitié-Salpêtrière, Assistance Publique - Hôpitaux de Paris (AP-HP), Paris, France. * Gilles Huberfeld, * Claude Adam, * Stéphane Clemenceau & * Michel Baulac * Département de Neurophysiologie, UPMC, Centre Hospitalo-Universitaire Pitié-Salpêtrière, Paris, France. * Gilles Huberfeld * Laboratorio de Circuitos Neuronales, Instituto Cajal, Consejo Superior de Investigaciones Científicas, Madrid, Spain. * Liset Menendez de la Prida * Service de Neurochirurgie, Centre Hospitalier Ste Anne, Université Paris Descartes, France. * Johan Pallud * Network Dynamics and Cellular Excitability, Centre de Recherche de l'Institut du Cerveau et de la Moelle Epinière, INSERM UMRS975, CNRS UMR7225, UPMC, Paris, France. * Michel Le Van Quyen * Service de Neurochirurgie, Centre Hospitalo-Universitaire Pitié-Salpêtrière, AP-HP, Paris, France. * Stéphane Clemenceau Contributions G.H., L.M.d.l.P. and R.M. designed the study. G.H., L.M.d.l.P. and R.M. performed the in vitro experiments. G.H., S.C., J.P., C.A. and M.B. performed the in vivo work and analysis. G.H., L.M.d.l.P., J.P., I.C., M.L.V.Q. and R.M. contributed to data analysis. G.H. and R.M. wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Richard Miles or * Gilles Huberfeld Author Details * Gilles Huberfeld Contact Gilles Huberfeld Search for this author in: * NPG journals * PubMed * Google Scholar * Liset Menendez de la Prida Search for this author in: * NPG journals * PubMed * Google Scholar * Johan Pallud Search for this author in: * NPG journals * PubMed * Google Scholar * Ivan Cohen Search for this author in: * NPG journals * PubMed * Google Scholar * Michel Le Van Quyen Search for this author in: * NPG journals * PubMed * Google Scholar * Claude Adam Search for this author in: * NPG journals * PubMed * Google Scholar * Stéphane Clemenceau Search for this author in: * NPG journals * PubMed * Google Scholar * Michel Baulac Search for this author in: * NPG journals * PubMed * Google Scholar * Richard Miles Contact Richard Miles Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (5M) Supplementary Figures 1–3 and Supplementary Table 1 Additional data - Single-neuron dynamics in human focal epilepsy
- Nat Neurosci 14(5):635-641 (2011)
Nature Neuroscience | Article Single-neuron dynamics in human focal epilepsy * Wilson Truccolo1, 2, 3, 4, 16 * Jacob A Donoghue1, 16 * Leigh R Hochberg1, 3, 4, 5 * Emad N Eskandar6, 7 * Joseph R Madsen8, 9 * William S Anderson9 * Emery N Brown10, 11, 12 * Eric Halgren13, 14, 15 * Sydney S Cash1 * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 14,Pages:635–641Year published:(2011)DOI:doi:10.1038/nn.2782Received23 December 2010Accepted15 February 2011Published online27 March 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Epileptic seizures are traditionally characterized as the ultimate expression of monolithic, hypersynchronous neuronal activity arising from unbalanced runaway excitation. Here we report the first examination of spike train patterns in large ensembles of single neurons during seizures in persons with epilepsy. Contrary to the traditional view, neuronal spiking activity during seizure initiation and spread was highly heterogeneous, not hypersynchronous, suggesting complex interactions among different neuronal groups even at the spatial scale of small cortical patches. In contrast to earlier stages, seizure termination is a nearly homogenous phenomenon followed by an almost complete cessation of spiking across recorded neuronal ensembles. Notably, even neurons outside the region of seizure onset showed significant changes in activity minutes before the seizure. These findings suggest a revision of current thinking about seizure mechanisms and point to the possibility of seizur! e prevention based on spiking activity in neocortical neurons. View full text Figures at a glance * Figure 1: Heterogeneous neuronal spiking patterns during seizure. () Locations of the microelectrode array in participant A (red square), and subdural ECoG electrodes OccS2 and GR50 in occipital and middle temporal cortices, respectively. () ECoG traces recorded at the locations shown in during seizure 1. The ECoG-based onset area was identified to be under the occipital electrode OccS2. Seizure onset is at time 0. The local field potential (LFP) recorded from a single channel in the microelectrode array and the corresponding spectrogram (in dB) are shown below. () Neuronal spike raster plot including all recorded neurons (n = 149). Each hash mark represents the occurrence of an action potential. Neurons were ranked (vertical axis) in increasing order according of their mean spiking rate during the seizure. (This ranking number is unrelated to physical location.) Toward the end of the seizure, activity across the population became more homogeneous until spiking was abruptly interrupted at seizure termination. With the exception of a few ne! urons, spiking in the recorded population remained suppressed for about 20 s. () The mean population rate, the percentage of active neurons and the Fano factor (FF) of the spike counts across different neurons at a given time (determined in 1-s time bins). These were roughly stationary during the several minutes preceding the seizure onset. An increase in the Fano factor, reflecting the heterogeneity in neuronal spiking, is observed around seizure onset and precedes an increase in the mean population rate. * Figure 2: Transient suppression of neuronal spiking during the seizure and at seizure termination. () Spike waveforms from neuron 44-1 (participant A, seizure 1; neuron ranked no. 131 in Fig. 1c). Spiking stopped for ~ 20 s during the initial seizure phase. The lack of major changes in spike waveform and preceding low spiking rate suggest that suppression was not due to sorting artifacts or depolarization block. () Four examples of units with similar behavior, recorded from different sites. All five units were classified as putative principal cells. () The high-pass filtered potentials recorded at electrode 44. Larger spikes correspond to unit 44-1, shown in . Dashed vertical lines show seizure onset and termination, respectively. White lines mark ±3 s.d. of the background noise, estimated from the 'silent' period after seizure termination. Another unit with smaller extracellularly recorded action potentials intensifies spiking during the 0.5–1.1 min interval. After seizure termination, both single-unit and multiunit activity were suppressed and the recorded potentials! correspond primarily to background noise. Although there is some gradual decrease in spike amplitudes, this decrease is much smaller than what would be expected from depolarization block. See Supplementary Figure 2 for channels 32, 41, 42 and 47. () Projection of thresholded waveforms onto a feature space shows clearly separable units. Blue dots represent thresholded spikes from unit 44-1; PC1 and NE denote the first principal component and a nonlinear energy feature, respectively. Green dots correspond to a smaller unit. Black dots correspond to thresholded noise and unsorted multiunit spikes. * Figure 3: Reproducibility of neuronal spiking modulation patterns across consecutive seizures. (,) An example from participant A with 131 neurons. Following conventions used in Figure 1c, neurons are ranked according to their mean rates measured during the seizure. Seizure 3 () follows the same ranking as seizure 2 (); that is, the single units in any given row of seizures 2 and 3 are the same. Most neurons coarsely preserved the types of spiking rate modulation across the two seizures. For example, the lowest-ranked neurons decreased or stopped spiking; and many of the top-ranked neurons presented similar transient increases in spiking rate modulation. As in seizure 1 (Fig. 1), an almost complete suppression of spiking in the neuronal population occurred abruptly at seizure termination. () The corresponding low-pass filtered local field potentials (LFPs) and spectrograms (from the same microelectrode array channel shown in Fig. 1; power in dB). () The Fano factor for the spike counts (1-s time bins) in the population of recorded neurons showed similar increase during! both seizures, reflecting the increased heterogeneity in neuronal spiking across the population. * Figure 4: Preictal and ictal modulations in spiking rates. () The neuronal spiking sample path N (neuron 90-1; A2: participant A, seizure 2). The corresponding spike train is shown at the bottom and the inset shows the mean ± 2 s.d. of all recorded spike waveforms. Seizure onset corresponds to time 0. For comparison purposes, the initial value of the sample path is set to 0. The yellow band corresponds to the range of the 3-min-long sample paths observed during a 30-min interictal period preceding the preictal period. Interictal sample paths in this distribution were obtained from an overlapping 3-min-long moving time window, stepped 1 s at a time. Blue curves and surrounding yellow band correspond to the average interictal sample path and the 95% confidence interval, respectively. A sample path was judged to have deviated from the interictal sample paths when it fell outside the range of the collection of interictal sample paths at any given time. () Neuron 90-1 transiently stopped spiking for tens of seconds just after the seizur! e onset. As expected, the sample path during the seizure did deviate from the observed interictal paths. The neuron's spiking rate gradually recovered and eventually settled at the typical mean rate. () Four examples of preictal and ictal sample path deviations, one for each participant. Note that although the preictal and ictal sample paths are plotted along the same axis, they refer to a 3-min period before and after, respectively, the seizure onset. * Figure 5: Preictal and ictal sample path deviations with respect to an interictal period. Each bar indicates the percentage of preictal and ictal sample path deviations in the recorded neuronal population, for each participant and seizure. Sample paths and sample path deviations were defined as in Figure 4. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Wilson Truccolo & * Jacob A Donoghue Affiliations * Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA. * Wilson Truccolo, * Jacob A Donoghue, * Leigh R Hochberg & * Sydney S Cash * Department of Neuroscience, Brown University, Providence, Rhode Island, USA. * Wilson Truccolo * Institute for Brain Science, Brown University, Providence, Rhode Island, USA. * Wilson Truccolo & * Leigh R Hochberg * Rehabilitation Research and Development Service, Department of Veterans Affairs, Providence, Rhode Island, USA. * Wilson Truccolo & * Leigh R Hochberg * School of Engineering, Brown University, Providence, Rhode Island, USA. * Leigh R Hochberg * Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA. * Emad N Eskandar * Nayef Al-Rodhan Laboratories for Cellular Neurosurgery and Neurosurgical Technology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA. * Emad N Eskandar * Department of Neurosurgery, Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA. * Joseph R Madsen * Department of Neurosurgery, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA. * Joseph R Madsen & * William S Anderson * Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA. * Emery N Brown * Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. * Emery N Brown * Harvard-Massachusetts Institute of Technology, Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. * Emery N Brown * Department of Radiology, University of California, San Diego, San Diego, California, USA. * Eric Halgren * Department of Neurosciences, University of California, San Diego, San Diego, California, USA. * Eric Halgren * Department of Psychiatry, University of California, San Diego, San Diego, California, USA. * Eric Halgren Contributions W.T., S.S.C. and J.A.D. wrote the paper. W.T. and J.A.D. conducted the data analysis. Data collection and preprocessing were done by J.A.D., W.T. and S.S.C. S.S.C., L.R.H., W.T. and E.H. conceived and planned the research. E.N.B. provided guidance on methods of data analysis and interpretation. E.N.E., W.S.A. and J.R.M. performed the surgeries and microelectrode array implantations. All authors participated in editing the manuscript. Competing financial interests L.R.H. reports receiving research support from Massachusetts General Hospital and Spaulding Rehabilitation Hospital, which in turn received clinical trial support from Cyberkinetics (CKI). CKI ceased operation in 2009. Corresponding author Correspondence to: * Wilson Truccolo Author Details * Wilson Truccolo Contact Wilson Truccolo Search for this author in: * NPG journals * PubMed * Google Scholar * Jacob A Donoghue Search for this author in: * NPG journals * PubMed * Google Scholar * Leigh R Hochberg Search for this author in: * NPG journals * PubMed * Google Scholar * Emad N Eskandar Search for this author in: * NPG journals * PubMed * Google Scholar * Joseph R Madsen Search for this author in: * NPG journals * PubMed * Google Scholar * William S Anderson Search for this author in: * NPG journals * PubMed * Google Scholar * Emery N Brown Search for this author in: * NPG journals * PubMed * Google Scholar * Eric Halgren Search for this author in: * NPG journals * PubMed * Google Scholar * Sydney S Cash Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information Movies * Supplementary Movie 1 (9M) Spiking activity on the microelectrode array (subject A, seizure 1). The movie shows the spiking rate of one single unit per electrode in the microelectrode array as a function of time. The largest unit recorded in each electrode was selected. Seizure onset, based on ECoG inspection, is at time zero. Electrodes at the darkest blue locations did not record activity that could be sorted into single units. Spiking rates are shown in spikes per second and were estimated based on 100-ms time bins. The ECoG at four locations is shown below. Location of electrodes OccS2 and GR50 are shown in Fig. 1, main text. The other two are nearby electrodes. PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–11 and Supplementary Table 1 Additional data - Perceptual learning as improved probabilistic inference in early sensory areas
- Nat Neurosci 14(5):642-648 (2011)
Nature Neuroscience | Article Perceptual learning as improved probabilistic inference in early sensory areas * Vikranth R Bejjanki1, 4 * Jeffrey M Beck1, 2, 4 * Zhong-Lin Lu3 * Alexandre Pouget1 * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 14,Pages:642–648Year published:(2011)DOI:doi:10.1038/nn.2796Received13 December 2010Accepted04 March 2011Published online03 April 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Extensive training on simple tasks such as fine orientation discrimination results in large improvements in performance, a form of learning known as perceptual learning. Previous models have argued that perceptual learning is due to either sharpening and amplification of tuning curves in early visual areas or to improved probabilistic inference in later visual areas (at the decision stage). However, early theories are inconsistent with the conclusions of psychophysical experiments manipulating external noise, whereas late theories cannot explain the changes in neural responses that have been reported in cortical areas V1 and V4. Here we show that we can capture both the neurophysiological and behavioral aspects of perceptual learning by altering only the feedforward connectivity in a recurrent network of spiking neurons so as to improve probabilistic inference in early visual areas. The resulting network shows modest changes in tuning curves, in line with neurophysiological ! reports, along with a marked reduction in the amplitude of pairwise noise correlations. View full text Figures at a glance * Figure 1: Neural and behavioral correlates of perceptual learning. () An illustration of the two types of changes observed in the tuning curves of trained orientation-selective neurons. Each panel shows an illustration of a tuning curve before (blue) and after (red) learning. The x axis represents orientation (in degrees) and the y axis represents firing rate (in Hz). () The characteristic shape of a threshold-versus-contrast, or TVC curve, plotted on a log-log scale, showing the two main regimes. The x axis represents the external noise added to the stimulus (example stimuli are shown in the top panel). The y axis represents the signal contrast needed to elicit the specific level of performance. () Observed changes in TVC curves as a result of perceptual learning, at two levels of performance27. Signal contrasts needed to elicit a specific level of performance, estimated at each of eight levels of external noise, are shown averaged over pairs of days. Smooth TVC curves are fits of the Perceptual Template Model (PTM)27. The axes are the sam! e as in . () Standard model of perceptual learning. The image is preprocessed by a set of filters corrupted by noise. The noisy output of these filters is then fed into a single decision unit trained to optimize discrimination between two orientations. * Figure 2: Network architecture. () A schematic of the neural architecture used to simulate orientation discrimination. () Contrast invariance of the tuning curve of cortical neurons in the network shown in Figure 3, after one session of training, when presented with stimuli of nine different signal contrasts. The x axis represents orientation (in degrees) and the y axis represents firing rate (in Hz). The width of the tuning is roughly invariant to changes in contrast: only the amplitude of the tuning curve changes with a change in contrast. Similar results were obtained for the network before learning and after both sessions of training. * Figure 3: Modeling perceptual learning using a realistic neural model of orientation discrimination. () Replicating the uniform shifts in TVC curves (Fig. 1b,c) using the neural model of orientation discrimination. Feedforward connections between the LGN and V1 were adjusted in a manner that moved them toward a matched filter for the stimulus. After training, we reran ten new simulations with ±10% independent noise added to the final (training session 2) feedforward thalamo-cortical weights. Pink dashed line, average TVC curve across the ten runs; error bars, 1 s.d. () Tuning curves of cortical neurons from the network, demonstrating modest amplification and sharpening as a result of learning. () Moving the thalamo-cortical feedforward weights toward a matched filter. The rightmost panel shows the two-dimensional spatial profile of a stimulus. The leftmost panel shows the two-dimensional spatial profile of the feedforward weights before learning, the second panel from left shows the spatial profile of the feedforward weights after one training session and the panel second ! from the right shows the spatial profile of the feedforward weights after two training sessions. Together these figures show the spatial profile of the thalamo-cortical feedforward connections moving toward the spatial profile of the stimulus, a manipulation that led to the changes in TVC curves shown in . * Figure 4: Perceptual learning and tuning curves: the role of amplification and sharpening. (–) Taking noise correlations into account demonstrates that amplification and sharpening are neither necessary nor sufficient for learning. (,,) Amplification is not sufficient for learning. Parameters in this network were changed in a manner that led to amplification of the orientation tuning curves (). At the level of TVC curves, the same change led to no improvement in performance—the TVC curve did not shift ()—thereby showing that amplification is not sufficient for learning. Single-cell recordings in such a network would incorrectly conclude that performance improved during training, as illustrated by the drop of the TVC curve when computed with Ishuffled (). (,,) Amplification is not necessary for learning. Performance can improve in a network () in which the gain of the tuning curve decreases during learning (). (,,) Sharpening is not sufficient for learning. This network shows no change in performance () despite substantial sharpening of the tuning curves (). ! (,,) Sharpening is not necessary for learning. Performance can improve () even in the absence of any sharpening (). All TVC curves were obtained for the 89% correct performance criterion. * Figure 5: The effect of perceptual learning on noise correlations. The dashed curve shows the correlation coefficients as a function of the difference in preferred orientation before learning. The correlation coefficients were computed using a similar procedure to that used in ref. 38, in response to a stimulus with 8% signal contrast. As has been reported in vivo20, 37, 38, correlations are between 0.4 and −0.1, and their magnitude decreases as a function of orientation difference. The solid curve shows the correlations after learning took place. The main effect of perceptual learning is to reduce the magnitude of the correlations while preserving the overall pattern of correlations. * Figure 6: TVC curves computed from responses in which noise correlations have been removed through shuffling. Curves for the network shown in Figure 3, with correlations removed using Ishuffled (see main text). The TVC curves still shift downward by a uniform amount, as was the case in Figure 3a. However, the magnitude of shift is significantly reduced and the TVC curves no longer show the characteristic linear increase in signal contrast as external noise increases, at high levels of external noise. These curves were computed for 79.3% accuracy. * Figure 7: The effect of subsampling. (,) TVC curves obtained from subsets of neurons in the networks shown in Figure 3 () and Figure 4b,f,j (). The plots in each panel were obtained by simulating the full network, but computing the TVC curve based on the response of a randomly picked sample of neurons. Number of neurons in each subset is indicated on each panel and varies from 256 to 32. () TVC curves obtained by subsampling the network shown in Figure 3. The results are qualitatively the same, even when we sample as few as 32 neurons. () TVC curves obtained by subsampling the network shown in Figure 4b,f,j. With 256 neurons, the results are similar to the results obtained with the full network (Fig. 4f), whereas with only 32 neurons, the result starts mimicking the results obtained with Ishuffled (Fig. 4j). The upward shift of the TVC curve with learning, observed with 32 cells, is therefore an artifact of subsampling and does not reflect the behavior of the whole neuronal population. All TVC curves were obtai! ned for the 79% correct performance criterion. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Vikranth R Bejjanki & * Jeffrey M Beck Affiliations * Department of Brain and Cognitive Sciences, University of Rochester, Rochester, New York, USA. * Vikranth R Bejjanki, * Jeffrey M Beck & * Alexandre Pouget * Gatsby Computational Neuroscience Unit, London, UK. * Jeffrey M Beck * Department of Psychology, University of Southern California, Los Angeles, California, USA. * Zhong-Lin Lu Contributions V.R.B. conceived the project, built the network model, ran all the simulations and analyses and wrote the paper. J.M.B. developed the analytic derivations, helped with building the network model and wrote the paper. Z.-L.L. worked on the link between the neural model and TVC curves and helped with parameter tuning. A.P. conceived the project, supervised the simulations and analyses and wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Alexandre Pouget Author Details * Vikranth R Bejjanki Search for this author in: * NPG journals * PubMed * Google Scholar * Jeffrey M Beck Search for this author in: * NPG journals * PubMed * Google Scholar * Zhong-Lin Lu Search for this author in: * NPG journals * PubMed * Google Scholar * Alexandre Pouget Contact Alexandre Pouget Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (324K) Supplementary Figures 1 and 2, Supplementary Tables 1 and 2, Supplementary Note Additional data - Large-scale remapping of visual cortex is absent in adult humans with macular degeneration
- Nat Neurosci 14(5):649-655 (2011)
Nature Neuroscience | Article Large-scale remapping of visual cortex is absent in adult humans with macular degeneration * Heidi A Baseler1 * André Gouws1, 6 * Koen V Haak2, 6 * Christopher Racey1 * Michael D Crossland3, 4 * Adnan Tufail3, 4 * Gary S Rubin3 * Frans W Cornelissen2 * Antony B Morland1, 5 * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 14,Pages:649–655Year published:(2011)DOI:doi:10.1038/nn.2793Received22 September 2010Accepted28 February 2011Published online27 March 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The occipital lobe contains retinotopic representations of the visual field. The representation of the central retina in early visual areas (V1–3) is found at the occipital pole. When the central retina is lesioned in both eyes by macular degeneration, this region of visual cortex at the occipital pole is accordingly deprived of input. However, even when such lesions occur in adulthood, some visually driven activity in and around the occipital pole can be observed. It has been suggested that this activity is a result of remapping of this area so that it now responds to inputs from intact, peripheral retina. We evaluated whether or not remapping of visual cortex underlies this activity. Our functional magnetic resonance imaging results provide no evidence of remapping, questioning the contemporary view that early visual areas of the adult human brain have the capacity to reorganize extensively. View full text Figures at a glance * Figure 1: Cortical responses to visual stimulation. BOLD responses for four individuals (from left to right): a young control subject (YC4, age 30), a young patient (J3, age 49), an elderly control subject (EC5, age 66) and an elderly patient (A6, age 70). Visual field results from microperimetry for each subject are inset to the right of each brain image and indicate absolute (black) and partial (gray) scotoma. Dotted concentric circles represent 5, 10 and 15 deg eccentricity. BOLD response coherence is encoded in color and superimposed on smoothed, left occipital lobes. Single cycle time series averages are shown for the two occipital ROIs representing central (occipital pole, OP) and more peripheral retina (calcarine sulcus, CS). Fast Fourier transforms were performed on each full time series and amplitude spectra are also shown for each ROI; stimulus frequency (seven cycles per scan) is indicated by the red dot. z scores indicate the number of s.d. the FFT amplitude at the stimulus frequency differs from the distribution ! of all of the other frequency amplitudes. * Figure 2: Mean coherences for each ROI, averaged across individuals for each group. CR, control region in nonvisual cortex. Error bars indicate standard error. ***P < 0.001, **P < 0.01. () Elderly patients (AMD) versus elderly controls. () Young patients (JMD) versus young controls. * Figure 3: Simulating retinal lesions in a control subject. In both panels, the left occipital lobe of a control subject is shown with BOLD signal coherence superimposed on the surface. Below each panel time series (averaged to a single stimulus cycle) and amplitude spectra of the time series are given for circular regions of cortex at the occipital pole and calcarine sulcus. () Response to expanding checkerboard ring stimulus spanning full field. () Response to same stimulus as in , but with central ±7.5 deg masked with a uniform, mean luminance gray disc. Data are presented as in Figure 1. * Figure 4: Occipital lobe responses compared across groups and ROIs. Mean coherences averaged across sessions and across individuals from three groups: young patient data from experiment 1, young control data from experiment 1 and lesion control group data from experiment 2 using new baseline measure at the occipital pole in response to stimulus with central ±7.5 deg masked with uniform gray. **P < 0.01, *P < 0.05. Error bars indicate s.e.m. * Figure 5: Receptive field characteristics. (,) Population receptive field (pRF) characteristics in the lesion projection zone () and the calcarine sulcus (). Mean pRF locations and sizes and the sampling probability (percent voxels exceeding 15% variance explained) are shown. Light gray bars show data for individuals with macular degeneration and age-matched controls. Data are given for combined age groups, as none of the outcome measures showed group contrasts (patient group versus control group) that were specific to age (location, F = 0.27, P = 0.603; size, F = 3.36, P = 0.074; sampling probability, F = 0.27, P = 0.603). In two patients, we were unable to derive population receptive field estimates in the lesion projection zone. Dark gray bars show data for controls that were presented the unmasked (100%) stimulus or the stimulus simulating a central scotoma (50% masked). *P < 0.05, ***P < 0.001. Error bars refer to s.e.m. * Figure 6: Individual eccentricity maps. (,) FMRI response maps of visual eccentricity superimposed on individual left, partially inflated, occipital lobes for control subjects () and six affected individuals (). False color is used to indicate the position on the retina (see semi-circular key) to which the cortex is responsive. In , filled black regions of the semicircular key indicate the absolute retinal lesion (scotoma), whereas outlined region exhibits significant, but not absolute, loss of vision. Patient group cortical maps are presented in ascending order (from left to right starting on the top row) of mean lesion diameter (MLD). The cortical representations closely corresponded to the spared retina. Indeed, even retinal locations with reduced sensitivity elicited activity. In all cases, however, the cortical activity did not spread to encompass the occipital pole. Note that this is a different subset of participants than those shown in Figure 1. * Figure 7: The cortical area representing intact visual field. (,) Schematic of the method by which the area of primary visual cortex representing a subject's intact visual field (measured by microperimetry) is predicted on the basis of normal retinotopic mapping. First, the primary visual cortex boundary was determined in each control participant by identifying the representations of the upper (purple) and lower (green) vertical meridians in calcarine cortex, as indicated by the dotted line on the surface reconstruction of the occipital lobe for one control participant (). Second, we determined whether a voxel (as indicated by the small square in and ) has a polar angle phase, θ, that is among the values of polar angle in the intact visual field, ΘΘ (see inset false color map showing the location of the scotoma (shaded) and intact (unshaded) regions). If this is the case, as it is in the illustrated example, we then determined whether the eccentricity represented by the voxel, r, is among the eccentricities in the intact field, R, a! t the polar angle θ. If the voxel's polar coordinate (r,θ) is among the set of coordinates (R,ΘΘ) of intact visual field locations, the voxel is retained. The predicted cortical area representing the patient's intact visual field, AP, is then computed from all the retained voxels. For each patient, multiple values of AP (one for each of the age-matched control retinotopic maps) were obtained and then averaged to compute the mean predicted area of activated V1, ĀP. In each patient, the area of active primary visual cortex, AM, was also measured. () The ratio of AM to ĀP for the participant groups. No significant differences between groups or between group values and unity were found (P > 0.05). Nonsignificant differences from unity present in the AMD and simulated lesion groups are likely the results of the minority of ectopically responding voxels found in Figure 5, which could not be predicted from normal retinotopic maps. Error bars indicate s.e.m. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * André Gouws & * Koen V Haak Affiliations * York Neuroimaging Centre, Department of Psychology, University of York, York, UK. * Heidi A Baseler, * André Gouws, * Christopher Racey & * Antony B Morland * Laboratory for Experimental Ophthalmology and BCN Neuroimaging Centre, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands. * Koen V Haak & * Frans W Cornelissen * Institute of Ophthalmology, University College London, London, UK. * Michael D Crossland, * Adnan Tufail & * Gary S Rubin * Moorfields Eye Hospital NHS Foundation Trust, London, UK. * Michael D Crossland & * Adnan Tufail * Hull-York Medical School, York, UK. * Antony B Morland Contributions H.A.B. and A.G. acquired and analyzed the neuroimaging data and prepared the manuscript. K.V.H. designed and implemented an analysis to determine the population receptive field characteristics and prepared the manuscript. C.R. acquired neuroimaging data. M.D.C. recruited patients, acquired and analyzed clinical data. A.T. recruited and assessed patients. G.S.R. jointly designed the study, recruited patients and acquired and analyzed clinical data. F.W.C. designed an analysis to determine the population receptive field characteristics and prepared the manuscript. A.B.M. jointly designed the study, acquired and analyzed the neuroimaging data and prepared the manuscript. All authors contributed to drafts of the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Antony B Morland Author Details * Heidi A Baseler Search for this author in: * NPG journals * PubMed * Google Scholar * André Gouws Search for this author in: * NPG journals * PubMed * Google Scholar * Koen V Haak Search for this author in: * NPG journals * PubMed * Google Scholar * Christopher Racey Search for this author in: * NPG journals * PubMed * Google Scholar * Michael D Crossland Search for this author in: * NPG journals * PubMed * Google Scholar * Adnan Tufail Search for this author in: * NPG journals * PubMed * Google Scholar * Gary S Rubin Search for this author in: * NPG journals * PubMed * Google Scholar * Frans W Cornelissen Search for this author in: * NPG journals * PubMed * Google Scholar * Antony B Morland Contact Antony B Morland Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (156K) Supplementary Figure 1 and Supplementary Results Additional data - Causal role of the prefrontal cortex in top-down modulation of visual processing and working memory
- Nat Neurosci 14(5):656-661 (2011)
Nature Neuroscience | Article Causal role of the prefrontal cortex in top-down modulation of visual processing and working memory * Theodore P Zanto1 * Michael T Rubens1 * Arul Thangavel1 * Adam Gazzaley1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature NeuroscienceVolume: 14,Pages:656–661Year published:(2011)DOI:doi:10.1038/nn.2773Received13 January 2011Accepted01 February 2011Published online27 March 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Selective attention filters information to limit what is encoded and maintained in working memory. Although the prefrontal cortex (PFC) is central to both selective attention and working memory, the underlying neural processes that link these cognitive abilities remain elusive. Using functional magnetic resonance imaging to guide repetitive transcranial magnetic stimulation with electroencephalographic recordings in humans, we perturbed PFC function at the inferior frontal junction in participants before they performed a selective-attention, delayed-recognition task. This resulted in diminished top-down modulation of activity in posterior cortex during early encoding stages, which predicted a subsequent decrement in working memory accuracy. Participants with stronger fronto-posterior functional connectivity displayed greater disruptive effects. Our data further suggests that broad alpha-band (7–14 Hz) phase coherence subserved this long-distance top-down modulation. These ! results suggest that top-down modulation mediated by the prefrontal cortex is a causal link between early attentional processes and subsequent memory performance. View full text Figures at a glance * Figure 1: Experimental procedure. White arrows indicate motion and were not present during the experiment. A black bar below a cue stimulus (also not present during the experiment) indicates that it is an item to be remembered. The pictures approximate stimuli appearance (see Online Methods). * Figure 2: Functional connectivity analysis revealed a fronto-parietal region associated with both motion and color top-down modulation, the right IFJ. However, distinct subregions in the IFJ distinguish motion (blue area) from color (yellow area) networks. * Figure 3: Behavioral results. (,) Working memory accuracy for the remember color () and remember motion () conditions. Accuracy declined as a result of rTMS only for color working memory during the first half of the experimental block. Error bars represent s.e.m. *P < 0.05. * Figure 4: Attentional modulation of the P1 during color processing and motion processing. () P1 modulation substantially declined during the first half of the experimental block following actual rTMS compared with sham. () Attentional modulation was observed during the second half of each block following both sham and actual rTMS. Bar graphs indicate the magnitude of attentional modulation (attend – ignore). rTMS altered the magnitude of P1 attentional modulation only during the first half of the actual rTMS block. *P < 0.05. (,) Attentional modulation of the P1 during motion processing was observed during both the first and the second half of each experimental block. rTMS did not change the magnitude of attentional modulation to motion stimuli. Error bars represent s.e.m. * Figure 5: Neuro-behavioral correlations. (,) Regression between the rTMS-related change in P1 modulation and either working memory accuracy () or V4/IFJ functional connectivity () when attending to color. Δ = sham – actual rTMS. * Figure 6: Alpha-band phase coherence between right-frontal and central-posterior regions immediately preceding the onset of color stimuli. Time-frequency maps depict the modulation (attend – ignore) of the phase locking values (PLVs) following sham (top) and actual rTMS (bottom). Black boxes highlight the time-frequency ROI. Author information * Abstract * Author information * Supplementary information Affiliations * Departments of Neurology, Physiology and Psychiatry, University of California, San Francisco, San Francisco, California, USA. * Theodore P Zanto, * Michael T Rubens, * Arul Thangavel & * Adam Gazzaley Contributions T.P.Z., A.T. and A.G. conceptualized and designed the task. T.P.Z. and M.T.R. performed the experiment. T.P.Z. analyzed the data. T.P.Z. and A.G. wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Theodore P Zanto or * Adam Gazzaley Author Details * Theodore P Zanto Contact Theodore P Zanto Search for this author in: * NPG journals * PubMed * Google Scholar * Michael T Rubens Search for this author in: * NPG journals * PubMed * Google Scholar * Arul Thangavel Search for this author in: * NPG journals * PubMed * Google Scholar * Adam Gazzaley Contact Adam Gazzaley Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (804K) Supplementary Figures 1–3, Supplementary Tables 1 and 2, Supplementary Results and Supplementary Discussion Additional data - Reversible large-scale modification of cortical networks during neuroprosthetic control
- Nat Neurosci 14(5):662-667 (2011)
Nature Neuroscience | Article Reversible large-scale modification of cortical networks during neuroprosthetic control * Karunesh Ganguly1, 2, 3, 4 * Dragan F Dimitrov5 * Jonathan D Wallis2, 6 * Jose M Carmena2, 3, 7, 8 * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 14,Pages:662–667Year published:(2011)DOI:doi:10.1038/nn.2797Received12 January 2011Accepted04 March 2011Published online17 April 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Brain-machine interfaces (BMIs) provide a framework for studying cortical dynamics and the neural correlates of learning. Neuroprosthetic control has been associated with tuning changes in specific neurons directly projecting to the BMI (hereafter referred to as direct neurons). However, little is known about the larger network dynamics. By monitoring ensembles of neurons that were either causally linked to BMI control or indirectly involved, we found that proficient neuroprosthetic control is associated with large-scale modifications to the cortical network in macaque monkeys. Specifically, there were changes in the preferred direction of both direct and indirect neurons. Notably, with learning, there was a relative decrease in the net modulation of indirect neural activity in comparison with direct activity. These widespread differential changes in the direct and indirect population activity were markedly stable from one day to the next and readily coexisted with the long-! standing cortical network for upper limb control. Thus, the process of learning BMI control is associated with differential modification of neural populations based on their specific relation to movement control. View full text Figures at a glance * Figure 1: Modification of neural firing properties during brain control. () For each daily session, subjects were required to serially perform a delayed center-out task in manual control (MC1), brain control and then manual control again (MC2). In the brain control task shown, visual guides (that is, lines shown in red) enforced straight trajectories. Trials were started by the animal physically moving to the center target. After a hold period, brain control (absence of any movements) was initiated. () Changes in the preferred direction of a direct neuron (P < 0.05). Solid lines are the cosine fit (R2 is the percent of variance accounted for by the fit). Circles and bars (s.e.m.) indicate the directional modulation of the firing rate. Right, waveform, crosscorrelograms (0.1% of spikes in a window < 1.5 ms) and the mean trajectories during manual control and brain control. Statistics were performed with bootstrap analysis. () Changes in the preferred direction of indirect neurons (P < 0.05). The directional modulation relationships are arranged si! milar to . Insets, waveforms of the respective indirect neurons. * Figure 2: Differential modulation of neuronal populations during brain control. () Distribution of shifts in preferred directions (ΔPD) between manual control and brain control. Each bar shows the number of neurons (counts) with a corresponding ΔPD. The labels above indicate the mean ΔPD for each population. Superimposed in gray is the bootstrap distribution. () Distribution of changes in the BC:MC MDratio for the three neural populations. Data are presented as in . () Ratio of relative modulation depths. To compare multiple experiments and experimental conditions, we normalized each session to the mean modulation depth ratio for direct neurons. Early and late represent brain control sessions from days 1 and 2 and day 3 and after training, respectively. MC2:MC1 is the ratio of modulation depths of the manual control sessions before and after brain control. Error bars indicate s.e.m. *P < 0.05. * Figure 3: Stability of neural properties. () Average directional modulation relationship during MC1 (black) and MC2 (gray) for three neurons. The neuron in the lower panel experienced a significant change (bootstrap analysis, P < 0.05). Error bars show s.e.m. () Actual (solid bars) and bootstrap (orange, mean ± s.d.) distributions of changes in preferred direction during MC1 and MC2. All three neural populations were combined, as they behaved similarly. () Distributions of modulation depth changes. Data are presented as in . * Figure 4: Stability of state-dependent changes in neural properties during a session. () Traces show the preferred direction and modulation depth for a moving window of trials (window of 16 trials) for a direct unit. Each segment is color coded and labeled (MC1, BC, MC2). () Average of multiple direct units from both animals. To illustrate the time course at the population level, the respective mean MC1 value was subtracted from each individual trace and the absolute value was used for the average. n = number of units included in the average. Each plot shows the mean (thick line) ± 2 s.e.m. (thin line). (,) Individual example () and average () responses of indirect units. Data are presented as in and . * Figure 5: Stability of neural properties across consecutive days of brain control. () Average directional modulation relationship for a direct and near unit during manual control and brain control on 2 consecutive days. Partial lines above each tuning curve represent the respective preferred direction for each daily brain control (PDBC) and manual control (PDMC) session. The shaded region is the respective variance of the bootstrap distributions of PDBC and PDMC. Waveforms and interspike interval distributions from a direct (red) and near (blue) unit on consecutive days are also shown. () Directional modulation of a far unit on 2 consecutive days. PDBC could not be estimated because of a lack of modulation. () Population distribution of preferred direction changes for indirect and direct neurons (PDBC3–PDBC4). For indirect units, the actual (gray bars) and bootstrap (black line) distributions are shown. The dark red line is the bootstrap distribution for direct units. Dotted vertical line represents a ΔPD of 0. Author information * Abstract * Author information * Supplementary information Affiliations * Department of Neurology and Rehabilitation, San Francisco VA Medical Center, San Francisco, California, USA. * Karunesh Ganguly * Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, California, USA. * Karunesh Ganguly, * Jonathan D Wallis & * Jose M Carmena * Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, California, USA. * Karunesh Ganguly & * Jose M Carmena * Department of Neurology, University of California, San Francisco, San Francisco, California, USA. * Karunesh Ganguly * Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA. * Dragan F Dimitrov * Department of Psychology, University of California, Berkeley, Berkeley, California, USA. * Jonathan D Wallis * Program in Cognitive Science, University of California, Berkeley, Berkeley, California, USA. * Jose M Carmena * Joint Graduate Group in Bioengineering, University of California, San Francisco & University of California, Berkeley, Berkeley, California, USA. * Jose M Carmena Contributions K.G. and J.M.C. designed the experiments. K.G. and J.M.C. performed behavioral training. K.G. performed the experiments and analyzed the data. K.G. and J.M.C. wrote the paper. D.F.D., J.D.W., J.M.C. and K.G. performed surgical procedures. K.G., J.D.W. and J.M.C. revised the paper. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Jose M Carmena Author Details * Karunesh Ganguly Search for this author in: * NPG journals * PubMed * Google Scholar * Dragan F Dimitrov Search for this author in: * NPG journals * PubMed * Google Scholar * Jonathan D Wallis Search for this author in: * NPG journals * PubMed * Google Scholar * Jose M Carmena Contact Jose M Carmena Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (864K) Supplementary Figures 1–9 Additional data
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