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• Focus on neurovascular interactions
  - Nat Neurosci 14(11):1353 (2011)
  Nature Neuroscience | Editorial Neurovascular interactions Focus issue: November 2011 Volume 14, No 11 * * Perspectives * Reviews * * Contents * Editorial Focus on neurovascular interactions Journal name:Nature NeuroscienceVolume: 14,Page:1353Year published:(2011)DOI:doi:10.1038/nn1111-1353Published online26 October 2011 Blood vessels in the nervous system are not simply inert bystanders that only support the metabolic needs of neurons. We present a focus on neurovascular interactions that highlights our emerging knowledge of how these interactions shape neuronal function both in health and disease. Article tools * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The mammalian brain has an intricate and highly evolved network of vasculature that efficiently meets the high metabolic demand of nervous tissue. The neurovasculature in the CNS consists of a complex set of interactions between endothelial cells, pericytes, fibroblasts, neurons and glia, and is not simply a passive entity that merely provides oxygen and nutrients to the underlying neural tissue, but is instead a dynamic structure that responds to cues and sculpts brain function. For example, blood vessels interact with neural stem and progenitor cells and form a supportive niche around blood vessels that supports neurogenesis. Blood vessels and angiogenic molecules actively participate in the pathogenesis of neurological disorders, tumors and stroke. In this issue, we present a focus on neurovascular interactions, which highlights recent efforts in some of these areas and discusses how advances in understanding these intricate interactions may lead to new treatments. Brain tumor cells depend on a rich blood supply for their proliferation and interact directly with the neurovasculature. These tumor cells are finely regulated by the neurovasculature and in turn actively modify it. In their review, Anita Hjelmeland, Justin Lathia, Sith Sathornsumetee and Jeremy Rich discuss the interactions between a subset of brain tumor cells called brain tumor stem cells (BTSCs), which show an increased tumor propagation capacity, and components of the neurovasculature. BTSCs are enriched in the environment around the blood vessels (the perivascular niche) and stimulate angiogenesis through the secretion of growth factors. The authors discuss the neurovascular factors that help maintain BTSCs, as well as BTSC regulation of endothelial cells, and highlight ways in which our understanding of brain tumor biology can be translated to patient therapies. The perivascular niche is not only critical for regulating pathogenic cell proliferation in tumor formation, but is also important for regulating normal adult neurogenesis. On page 1382, Steven Goldman and Zhuoxun Chen review the molecular interactions that are critical to the endothelial regulation of stem and progenitor cells in the brain. They discuss the perivascular signals that support neuronal development and the signaling pathways that promote neurogenesis, neural stem cell expansion, differentiation, and neuronal migration and recruitment. Their review addresses the key observations that have been made in this area, as well as analogous concepts regarding vascular cell contributions to gliogenesis. Ethan Winkler, Robert Bell and Berislav Zlokovic review the rapidly evolving role of CNS pericytes in health and disease. CNS pericytes have both mesodermal and neuroectodermal origins, and these pericytes are opposed to CNS capillaries and have a critical role in regulating cerebral blood flow. The authors review the developmental origin of pericytes as well as the cross-talk and functional coupling between pericytes and endothelial cells. They discuss advances in our understanding of how pericytes control blood-brain barrier formation and integrity and how they support vascular stability and regulate angiogenesis. Abnormal pericyte function has been seen in several CNS disorders, including diabetic retinopathy and some neurodegenerative disorders, and the authors discuss the implications of recent findings for our understanding of pericytes' involvement in disease. On page 1390, Erik Storkebaum, Annelies Quaegebeur, Miikka Vikkula and Peter Carmeliet discuss molecular insights into neurological disorders that are caused by either excessive blood vessel growth or improper vessel regression. They focus on two monogenic disorders, cerebral cavernous malformation and hereditary hemorrhagic telangiectasia to illustrate the molecular mechanisms that affect the pathogenesis of these cerebrovascular malformations. They also discuss CADASIL, a syndrome caused by Notch3 mutations, as an example of how reduced vascularization provokes ischemic insults in white matter leading to dementia. Their review also highlights recent advances in understanding how vascular disorders can contribute to neurodegeneration in diseases such as Alzheimer's disease or amyotrophic lateral sclerosis (ALS). Finally, two perspectives in this focus issue address ischemic injury and advances in stroke research. Much research has focused on glutamatergic mechanisms that lead to ischemic neuronal death. On page 1369, Michael Tymianski discusses alternate molecular processes beyond excitotoxicity that may also critically regulate the deleterious consquences of ischemia. In his perspective, Tymianski focuses on a few examples of these nonglutamatergic mechanisms that contribute to a loss of ionic homeostasis or cellular energy failure following cerebral ischemia, such as those mediated by TRP channels, acid-sensing channels, pannexins and hemichannels. Costantino Iadecola and Josef Anrather review the different ways in which the brain protects itself after ischemic insults on page 1363, and argue that pharmacological interventions or other approaches that mobilize these endogenous neuroprotective programs could invigorate stroke research. They suggest that, unlike therapeutic approach! es that are based on counteracting selected pathways of the ischemic cascade, new therapies may need a more holistic approach, and also recruit coordinated neurovascular programs that support cerebral perfusion and promote tissue restoration. The research described in this focus has made substantial progress toward understanding the interface between neural and vascular systems in neuropathology and, by extension, the importance of these interactions in normal brain function. We hope that these articles will give our readers a sense of the recent research in this area and that they may also inspire further basic and clinical work on these important problems. Finally, we thank Kathleen Dave, for conceiving and commissioning this focus during her time at Nature Neuroscience. Additional data
• The brain's rose-colored glasses
  - Nat Neurosci 14(11):1355-1356 (2011)
  
• EphrinBs send mixed messages
  - Nat Neurosci 14(11):1356-1358 (2011)
  
• Same players, different game: AMPA receptor regulation in oligodendrocyte progenitors
  - Nat Neurosci 14(11):1358-1360 (2011)
  
• An axis of good and awful in odor reception
  - Nat Neurosci 14(11):1360-1362 (2011)
  
• Seeing more clearly with Scale
  - Nat Neurosci 14(11):1362 (2011)
  
• Stroke research at a crossroad: asking the brain for directions
  - Nat Neurosci 14(11):1363-1368 (2011)
  Nature Neuroscience | Perspective Neurovascular interactions Focus issue: November 2011 Volume 14, No 11 * * Perspectives * Reviews * * Contents * Editorial Stroke research at a crossroad: asking the brain for directions * Costantino Iadecola1 * Josef Anrather1 * Affiliations * Corresponding authorJournal name:Nature NeuroscienceVolume: 14,Pages:1363–1368Year published:(2011)DOI:doi:10.1038/nn.2953Published online26 October 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 Ischemic stroke remains a vexing public health problem. Although progress has been made in prevention and supportive care, efforts to protect the brain from ischemic cell death have failed. Thus, no new treatment has made it from bench to bedside since tissue plasminogen activator was introduced in 1996. The brain has a remarkable capacity for self-preservation, illustrated by the protective responses induced by ischemia, preconditioning and exercise. Here we describe the mechanisms underlying brain self-protection, with the goal of identifying features that could provide insight into stroke therapy. Unlike traditional therapeutic approaches based on counteracting selected pathways of the ischemic cascade, endogenous neuroprotection relies on coordinated neurovascular programs that support cerebral perfusion, mitigate the harmful effects of cerebral ischemia and promote tissue restoration. Learning how the brain triggers and implements these protective measures may advance o! ur quest to treat stroke. View full text Figures at a glance * Figure 1: Protective pathways activated by cerebral ischemia. Cerebral ischemia, while activating damaging processes, also triggers a coordinated response that attempts to counteract tissue damage. The reduction in blood flow produced by the arterial occlusion is opposed by an increase in blood pressure, by the production of vasoactive mediators in the ischemic brain and by the activation of eNOS, which increase perfusion pressure and reduce vascular resistance in collateral vessels supplying the ischemic territory. Hypoxia activates HIF1, leading to a transcriptional response that promotes oxygen and glucose delivery to the tissue. The energy deficit associated with ischemia is countered by suppression of protein synthesis and neuronal activity (spike arrest and channel closure), which reduce energy expenditures. Post-ischemic oxidative stress triggers an antioxidant response by means of the transcription factor Nrf2, while inhibitory neurotransmitters and glutamate transporters (GLT1, also known as excitatory amino acid transporter 2! , EAAT2) counterbalance the excitotoxicity associated with glutamate receptor activation. The deleterious effects of post-ischemic apoptosis are antagonized by expression of antiapoptotic factors (Bcl2, IAP), heat shock proteins (HSP) and activation of the protective kinase Akt. Inflammation is mitigated by production of anti-inflammatory cytokines and neurotransmitters, as well as an influx of lymphocytes with anti-inflammatory properties (Treg and Breg cells). Systemic immunosuppression limits the development of adaptive and innate immune responses that may induce tissue damage. Ischemia is also associated with expression of CREB-dependent prosurvival genes, including growth factors, and with proliferation of neural and vascular progenitor cells that participate in tissue repair. These endogenous protective pathways limit the extent of ischemic brain injury, as shown by studies in which their inhibition enhances the damage (for example, refs. 10,14). * Figure 2: Intracellular events leading to ischemic tolerance. Preconditioning triggers act through G protein–coupled receptor–dependent phospholipase C (PLC) activation, leading to hydrolysis of phosphatidylinositol-4,5-bisphosphate (PIP2) and generation of diacylglycerol (DAG) and inositol-1,4,5-trisphosphate (IP3), which acts on smooth endoplasmic reticulum (ER) Ca2+ channels to mobilize intracellular Ca2+ stores, leading to protein kinase C (PKC) activation. PIP2 is also phosphorylated by phosphatidylinositol-3-OH kinase (PI3K), resulting in phosphatidylinositol-3,4,5-trisphosphate (PIP3) generation and Akt activation. Ca2+ influx through glutamate receptors activates NOS. NO increases guanylate cyclase (GC) activity, resulting in cyclic GMP generation and protein kinase G (PKG) activation. Together these early mediators enhance the activity of mitochondrial potassium ATP (mK-ATP) channels and inhibit proapoptotic signaling and opening of the mitochondrial permeability transition pore (mPTP). At the same time, transcription fact! ors activated by these signaling cascades as well as by reduced oxygen levels, reactive oxygen species (ROS) and ATP deficit lead to the expression of prosurvival genes, such as the antiapoptotic factor Bcl2, heat shock proteins (HSP) and the antioxidant enzymes manganese superoxide dismutase (MnSOD) and heme-oxygenase-1 (HO-1). Genes are also expressed that help the tissue operate under reduced oxygen and glucose availability, such as the glucose transporter GLUT1, the proangiogenic growth factor VEGF and the hematopoietic and cytoprotective factor EPO. Damage-associated molecular pattern molecules (DAMPs) released from stressed cells activate Toll-like receptors (TLR), leading to NF-κB and type I interferon response. Epigenetic factors are also likely to contribute to the reprogramming of post-ischemic gene expression and may include the epigenetic modifiers Polycomb group proteins (PcG) and sirtuin class histone deacetyalses (SIRT). Lig, ligand; Me3, trimethylation on h! istone H3 Lys27; Ub, ubiquitination on histone H2A Lys119; Ac,! histone acetylation. ERK, extracellular signal–regulated kinase; HSF, heat shock factor; IFN-β, interferon-β; iNOS, inducible NOS; IRF3, interferon regulatory factor 3; Keap1, kelch-like ECH-associated protein 1; MEK, MAP kinase or ERK kinase; Myd88, myeloid differentiation primary response gene 88; PPARγ, peroxisome proliferator-activated receptor gamma; TNF, tumor necrosis factor; TRIF, TIR domain–containing adapter-inducing interferon-β. * Figure 3: Local and remote mechanisms of endogenous neuroprotection. In the brain, protective interactions among neurons, astrocytes, microglia and cerebral blood vessels are mediated by cell-cell contact, by the uptake of excessive glutamate, and by the release of growth factors and cytokines. These interactions are directed at preserving tissue homeostasis by maintaining cerebral blow flow, suppressing excitotoxicity, reducing energy use, dampening inflammation and apoptosis, and boosting repair mechanisms. Central signals (red arrows) through neurohumoral pathways act on peripheral organs to support the cardiovascular system, release growth factors and cytokines, and mobilize protective cells, such as Treg and Breg lymphocytes and endothelial progenitor cells (EPC). Peripheral signals (blue arrows) generated by the systemic response, in turn, may feed back on the brain and exert protective effects. IL, interleukin. Author information * Abstract * Author information * Supplementary information Affiliations * Division of Neurobiology, Department of Neurology and Neuroscience, Weill Cornell Medical College, New York, New York, USA. * Costantino Iadecola & * Josef Anrather Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Costantino Iadecola Author Details * Costantino Iadecola Contact Costantino Iadecola Search for this author in: * NPG journals * PubMed * Google Scholar * Josef Anrather Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (115K) Supplementary Table 1 Additional data
• Emerging mechanisms of disrupted cellular signaling in brain ischemia
  - Nat Neurosci 14(11):1369-1373 (2011)
  Nature Neuroscience | Perspective Neurovascular interactions Focus issue: November 2011 Volume 14, No 11 * * Perspectives * Reviews * * Contents * Editorial Emerging mechanisms of disrupted cellular signaling in brain ischemia * Michael Tymianski1, 2Journal name:Nature NeuroscienceVolume: 14,Pages:1369–1373Year published:(2011)DOI:doi:10.1038/nn.2951Published online26 October 2011 Abstract * Abstract * 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 Recent findings have provided insights into pathogenic mechanism(s) that may complement and add to the traditional glutamatergic mechanisms to which ischemic brain injury is ascribed. The discovery of mechanisms leading to ionic imbalance and signaling cascades that mediate cross-talk between redundant pathways of cell death, as well as mechanisms that operate downstream of, upstream of and in parallel with excitotoxicity, has spurred new research into therapeutics ranging from proof of concept in animals to human clinical trials. This Perspective presents an integrated consideration of new molecular pathogenic mechanisms underlying ischemic damage in the brain, and how our combined knowledge of these mechanisms and our existing knowledge of excitotoxicity may establish new targets for therapy, by allowing clearer boundaries on what might be expected of a given intervention, and may yield advances that will benefit patients. View full text Figures at a glance * Figure 1: Strategy of perturbing protein-protein interactions involving the postsynaptic scaffolding protein PSD-95. Left: NMDARs (gray) are believed to cluster in a signaling complex that couples them to postsynaptic effector proteins, including enzymes such as neuronal nitric oxide synthase (nNOS; dark red). PSD-95, a scaffolding synaptic protein containing three PDZ domains, an SH3 homology adaptor domain and a guanylate kinase (GK)-like domain, interacts with GluN2 subunits of NMDARs. Calcium (red sphere) influx through NMDARs creates microdomains of high [Ca2+]i sufficient to ultimately provoke neurotoxic signaling, including the production of nitric oxide, a component of the oxidative response to excitotoxicity. Right: a competitor (teal green) that inhibits the capacity of PSD-95 to bind NMDARs or to nNOS reduces the efficiency with which NMDAR activity translates to excitotoxic consequences such as NO production, rendering neurons more resilient to excitotoxic insults without inhibiting other, potentially beneficial aspects of NMDAR signaling. * Figure 2: Possible involvement of NMDARs, TRPM2 and TRPM7 channels in anoxic neuronal death. Ischemia causes a reduction in extracellular divalent cations (1) which activates TRPM7 channels. Ischemia also causes excitotoxicity, which activates NMDARs (2), contributing to the rise in intracellular calcium (3) and the formation of ROS and RNS (4) and H2O2 (5). These, along with increases in cytoplasmic ADPR (6), feed back onto TRPM2 and TRPM7 channels to further increase their activity (7). This self-sustaining positive feedback loop remains operative even if excitotoxicity becomes inactivated through glutamate receptor inactivation, membrane depolarization or antiexcitotoxic therapy. NOS, nitric oxide synthase. Ca2+-CaM, calcium + calmodulin. Author information * Abstract * Author information Affiliations * Toronto Western Research Institute, University Health Network, Toronto, Ontario, Canada. * Michael Tymianski * Division of Neurosurgery, University of Toronto, Toronto, Ontario, Canada. * Michael Tymianski Competing financial interests M.T. is president and chief executive officer of NoNO Inc., a biotechnology company dedicated to the translation of new therapies discovered in the author's and collaborators' academic laboratories to human clinical trials. Corresponding author Correspondence to: * Michael Tymianski Author Details * Michael Tymianski Contact Michael Tymianski Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• Twisted tango: brain tumor neurovascular interactions
  - Nat Neurosci 14(11):1375-1381 (2011)
  Nature Neuroscience | Review Neurovascular interactions Focus issue: November 2011 Volume 14, No 11 * * Perspectives * Reviews * * Contents * Editorial Twisted tango: brain tumor neurovascular interactions * Anita B Hjelmeland1 * Justin D Lathia1 * Sith Sathornsumetee2 * Jeremy N Rich1, 3 * Affiliations * Corresponding authorsJournal name:Nature NeuroscienceVolume: 14,Pages:1375–1381Year published:(2011)DOI:doi:10.1038/nn.2955Published online26 October 2011 Abstract * Abstract * 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 The brain is a complicated organ with complexity derived from cellular and microenvironmental interactions. Similarly, brain tumor cells actively modify and are regulated by their microenvironment. Brain tumors are highly heterogeneous and frequently show a cellular hierarchy with self-renewing tumorigenic brain tumor stem cells (BTSCs) at the apex. Although BTSCs are distinct from neural stem cells, they share characteristics, including bidirectional interplay with supportive vasculature critical for maintenance of undifferentiated states and survival. BTSCs stimulate angiogenesis through growth factor secretion and are enriched in perivascular niches. Microenvironmental conditions, including hypoxia, drive expression of stem cell genes and proangiogenic factors, further linking cellular hierarchy regulation and instructive stromal elements. BTSCs may also directly contribute to tumor vasculature through plasticity toward an endothelial lineage. Interrogating the codependen! ce of BTSCs and the perivascular niche may directly inform clinical approaches for brain tumor therapy through targeting of highly angiogenic and tumorigenic cellular subsets. View full text Figures at a glance * Figure 1: Learning the steps: isolation and characterization of BTSCs. BTSCs from malignant tumors (glioma, medulloblastoma, ependymoma) can be enriched on the basis of cell surface expression using flow cytometry with markers including but not limited to CD133, A2B5, CD171 (L1CAM), CD15 (SSEA1), CD49f (integrin-α6), CD44 and EGFR. Upon enrichment, hierarchy should be validated by functional assays of tumor propagation. BTSCs often have cellular phenotypes associated with the promotion of angiogenesis, therapeutic resistance, immune evasion and niche interactions that are elevated in comparison to non-stem tumor cells. * Figure 2: Shall we dance? Coordinated communication between cells in the perivascular niche. Neural stem cells (NSCs) present in the perivascular niche rely on a series of signals between the extracellular matrix (ECM), blood vessels (BV), ependymal cells (E) and other niche cells (NC) to promote their maintenance. BTSCs rely on similar interactions in the perivascular niche, which also consists of ECM, non-stem tumor cells (NSTC) and tumor blood vessels (TBV). BTSC plasticity toward an endothelial lineage and incorporation of these BTSC-derived endothelial cells (BDECs) into the vasculature may also contribute to the perivascular niche. Figure modified from ref. 12. Author information * Abstract * Author information Affiliations * Department of Stem Cell Biology and Regenerative Medicine, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA. * Anita B Hjelmeland, * Justin D Lathia & * Jeremy N Rich * Department of Medicine, Faculty of Medicine at Siriraj Hospital, Mahidol University, Bangkok, Thailand. * Sith Sathornsumetee * Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University School of Medicine and University Hospitals, Cleveland, Ohio, USA. * Jeremy N Rich Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Anita B Hjelmeland or * Jeremy N Rich Author Details * Anita B Hjelmeland Contact Anita B Hjelmeland Search for this author in: * NPG journals * PubMed * Google Scholar * Justin D Lathia Search for this author in: * NPG journals * PubMed * Google Scholar * Sith Sathornsumetee Search for this author in: * NPG journals * PubMed * Google Scholar * Jeremy N Rich Contact Jeremy N Rich Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• Perivascular instruction of cell genesis and fate in the adult brain
  - Nat Neurosci 14(11):1382-1389 (2011)
  Nature Neuroscience | Review Neurovascular interactions Focus issue: November 2011 Volume 14, No 11 * * Perspectives * Reviews * * Contents * Editorial Perivascular instruction of cell genesis and fate in the adult brain * Steven A Goldman1 * Zhuoxun Chen1 * Affiliations * Corresponding authorJournal name:Nature NeuroscienceVolume: 14,Pages:1382–1389Year published:(2011)DOI:doi:10.1038/nn.2963Published online26 October 2011 Abstract * Abstract * 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 The perivascular niche for neurogenesis was first reported as the co-association of newly generated neurons and their progenitors with both dividing and mitotically quiescent endothelial cells in restricted regions of the brain in adult birds and mammals alike. This review attempts to summarize our present understanding of the interaction of blood vessels with neural stem and progenitor cells, addressing both glial and neuronal progenitor cell interactions in the perivascular niche. We review the molecular interactions that are most critical to the endothelial control of stem and progenitor cell mobilization and differentiation. The focus throughout will be on defining those perivascular ligand-receptor interactions shared among these systems, as well as those that clearly differ as a function of cell type and setting, by which specificity may be achieved in the development of targeted therapeutics. View full text Figures at a glance * Figure 1: Perivascular interactions within the subgranular zone of the adult mammalian hippocampus. This cartoon illustrates the architecture of the subgranular zone and dentate granule layer of the adult hippocampus and shows the relationships of hippocampal NSCs to transit-amplifying progeny and their neuronally restricted progeny. Only those interactions identified as being specifically between the microvascular bed and hippocampal stem and progenitor cells are noted; many mitogens and differentiation agents of nonvascular origin have otherwise been defined in the hippocampus. The subgranular zone of the dentate gyrus manifests a cellular hierarchy that is similar to that of the ventricular subependyma. Major molecular interactions, as cited in the text, include the provision of ATP to vascular NTPDase-2/CD39L1, with generation of ADP that interacts with P2YRs expressed by the stem cell pool, vascular VEGF, which interacts with both endothelial and neural precursor receptors, CD24 and its endothelial P-selectin receptors, both endothelial NOS (eNOS) and precursor-derive! d neuronal NOS (nNOS), with their derived NO and targets thereof, and endothelial BDNF and its neuronal receptors. GCL, granule cell layer; ML, molecular layer; SGZ, subgranular zone. * Figure 2: Perivascular interactions with the adult mammalian subependyma. This cartoon illustrates the architecture of the striatal ventricular wall and shows the relationships of subependymal NSCs (B cells, according to the nomenclature of Alvarez-Buylla3, 19, 75) to transit-amplifying progeny (C cells) and their neuronally restricted progeny (A cells). Major molecular interactions, as citevd in the text, include the provision of ATP to vascular NTPDase-2/CD39L1, with generation of ADP that interacts with B and C cell P2YRs, vascular VEGF and PEDF, which interact with cognate B cell receptors, B cell CD15 and C and A cell CD24 with their endothelial P-selectin receptors, endothelial SDF1/CXCL12 with its A cell receptors CXCR4 and CXCR7, endothelial BDNF with both its B and C cell p75 and A cell trkB receptors, endothelial laminin with its C and A cell a6b1 integrin receptor, and both endothelial eNOS and neural precursor-derived nNOS, and their derived NO with cellular targets thereof. * Figure 3: Angiogenesis and neurogenesis in the adult songbird brain. Testosterone-induced neuronal addition to the adult songbird vocal control center, HVC, requires the androgenic induction of VEGF, followed by VEGF-stimulated matrix metalloproteinase release and angiogenesis. The expanded vasculature acts as a source of BDNF, which supports the immigration of new neurons from the overlying ventricular zone23, 77, 78, 80. AR, androgen receptor; ER, estrogen receptor; Nucleus RA, the HVC target nucleus robustus archistriatalis. Author information * Abstract * Author information Affiliations * Department of Neurology and the Center for Translational Neuromedicine, University of Rochester Medical School, Rochester, New York, USA. * Steven A Goldman & * Zhuoxun Chen Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Steven A Goldman Author Details * Steven A Goldman Contact Steven A Goldman Search for this author in: * NPG journals * PubMed * Google Scholar * Zhuoxun Chen Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• Cerebrovascular disorders: molecular insights and therapeutic opportunities
  - Nat Neurosci 14(11):1390-1397 (2011)
  Nature Neuroscience | Review Neurovascular interactions Focus issue: November 2011 Volume 14, No 11 * * Perspectives * Reviews * * Contents * Editorial Cerebrovascular disorders: molecular insights and therapeutic opportunities * Erik Storkebaum1 * Annelies Quaegebeur2, 3 * Miikka Vikkula4, 5 * Peter Carmeliet2, 3 * Affiliations * Corresponding authorJournal name:Nature NeuroscienceVolume: 14,Pages:1390–1397Year published:(2011)DOI:doi:10.1038/nn.2947Published online26 October 2011 Abstract * Abstract * 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 Blood vessels in the nervous system have traditionally been considered neutral bystanders that only passively adapt their structure and function in response to the needs of neural cells. Emerging evidence suggests, however, that vessels and angiogenic molecules actively participate in the pathogenesis of neurological disorders. Here we will discuss molecular insights into neurological disorders resulting either from excessive vessel growth (cerebral vascular malformations) or improper vessel regression (neurodegeneration and white matter lesions). These genetic insights offer alternative therapeutic options, some of which are being evaluated in the clinic. View full text Figures at a glance * Figure 1: Cellular mechanisms of cerebrovascular malformations. () In the healthy brain, a feeder artery (red) ramifies into a branched network of capillaries that are drained by a vein (blue). () CCMs are low-flow lesions characterized by dysplastic capillaries forming cavernous sinusoids. () AVMs are fast-flow lesions wherein feeder arterioles shunt directly to veins without intervening capillaries. Candidate disease-associated molecules that are upregulated (+) or downregulated (−) are shown. EC, endothelial cell. * Figure 2: Molecular mechanisms identified in CCM. In endothelial cells, CCM proteins interact directly or indirectly with the cytosolic domains of VE-cadherin, HEG1, integrin-β1 and VEGFR2 to connect extracellular cues to intracellular signaling pathways. The cellular responses that result from activation of these signal transduction cascades are indicated. ECM, extracellular matrix; β-cat, β-catenin. For more information, see Box 1 text. * Figure 3: Model of CADASIL. Scheme illustrating the pathogenic pathway underlying the vascular alterations in CADASIL. * Figure 4: Role and therapeutic potential of VEGF in ALS. () In healthy conditions, the mRNA stabilizer HuR binds to VEGF mRNA, resulting in sufficient VEGF protein to provide neuroprotection and oxygen supply to motor neurons. () In ALS, mutant SOD1 competes with HuR for binding, reducing VEGF and compromising neuroprotection and perfusion, leading to motor neuron degeneration. () Recombinant VEGF is delivered intracerebroventricularly to provide degenerating motor neurons an increased neuroprotective survival signal and improved oxygen supply. For reasons of simplicity, the amount of oxygen supply is denoted by the degree of vessel branching. Author information * Abstract * Author information Affiliations * Molecular Neurogenetics Laboratory, Max Planck Institute for Molecular Biomedicine, Muenster, Germany. * Erik Storkebaum * The Laboratory of Angiogenesis and Neurovascular Link, Vesalius Research Center, Katholieke Universiteit (K.U.) Leuven, Leuven, Belgium. * Annelies Quaegebeur & * Peter Carmeliet * The Laboratory of Angiogenesis and Neurovascular Link, Vesalius Research Center, VIB (Flanders Institute for Biotechnology), K.U. Leuven, Leuven, Belgium. * Annelies Quaegebeur & * Peter Carmeliet * WELBIO (Walloon Excellence in Lifesciences and Biotechnology), de Duve Institute, Université catholique de Louvain, Brussels, Belgium. * Miikka Vikkula * Laboratory of Human Molecular Genetics, de Duve Institute, Université catholique de Louvain, Brussels, Belgium. * Miikka Vikkula Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Peter Carmeliet Author Details * Erik Storkebaum Search for this author in: * NPG journals * PubMed * Google Scholar * Annelies Quaegebeur Search for this author in: * NPG journals * PubMed * Google Scholar * Miikka Vikkula Search for this author in: * NPG journals * PubMed * Google Scholar * Peter Carmeliet Contact Peter Carmeliet Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• Central nervous system pericytes in health and disease
  - Nat Neurosci 14(11):1398-1405 (2011)
  Nature Neuroscience | Review Neurovascular interactions Focus issue: November 2011 Volume 14, No 11 * * Perspectives * Reviews * * Contents * Editorial Central nervous system pericytes in health and disease * Ethan A Winkler1, 2 * Robert D Bell1, 2 * Berislav V Zlokovic1 * Affiliations * Corresponding authorJournal name:Nature NeuroscienceVolume: 14,Pages:1398–1405Year published:(2011)DOI:doi:10.1038/nn.2946Published online26 October 2011 Abstract * Abstract * 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 Pericytes are uniquely positioned within the neurovascular unit to serve as vital integrators, coordinators and effectors of many neurovascular functions, including angiogenesis, blood-brain barrier (BBB) formation and maintenance, vascular stability and angioarchitecture, regulation of capillary blood flow and clearance of toxic cellular byproducts necessary for proper CNS homeostasis and neuronal function. New studies have revealed that pericyte deficiency in the CNS leads to BBB breakdown and brain hypoperfusion resulting in secondary neurodegenerative changes. Here we review recent progress in understanding the biology of CNS pericytes and their role in health and disease. View full text Figures at a glance * Figure 1: Structural and molecular pericyte connections within the neurovascular unit. Right: pericytes (green) and endothelial cells (purple) are connected to a shared basement membrane (yellow) by several types of integrin molecule. In areas lacking the basement membrane, interdigitations of pericyte and endothelial cell membranes, called peg and socket contacts, form direct connections and contain several different transmembrane junctional proteins (inset). N-cadherin is the key adherens junction protein between pericytes and endothelium. Pairs of connexin 43 (CX43) hemichannels expressed respectively in pericytes and endothelium form gap junctions that allow transfer of molecules between pericytes and endothelial cells. Adhesion plaques similar to desmosomes contain fibronectin deposits in the intercellular spaces between pericytes and endothelial cells. CX43 is also abundant at astrocyte–endothelial cell and astrocyte-neuron interfaces. Different types of tight junction proteins, tight junction adaptor proteins and adhesion junctions regulate direct end! othelial cell–endothelial cell contacts forming the anatomical blood-brain barrier. * Figure 2: Origin of pericytes in the CNS. The embryonic sources of pericytes include (1) neuroectoderm-derived neural crest cells, which give rise to pericytes of the forebrain, (2) mesoderm-derived mesenchymal stem cells, which give rise to pericytes in the midbrain, brain stem and spinal cord, and (3) expansion by proliferation from the newly established pericyte pools. Postnatal sources of pericytes include (3) expansion by proliferation from the existing pericyte pools and (4) mesoderm-derived circulating mesenchymal stem cells (bone marrow pericyte progenitor cells) and presently undetermined 'other' sources. * Figure 3: Pericyte-endothelial signaling. () Pericyte proliferation and migration. Endothelial cell (EC)-secreted PDGF-BB is retained within the extracellular matrix (ECM). PDGF-BB binds to PDGFRβ on the pericyte (PC) plasma membrane, leading to PDGFRβ dimerization, autophosphorylation and activation of several downstream signal transduction cascades (for example, Src, the Grb2 adaptor protein, phosphatidylinositol-3-OH kinase (PI3K), Ras GTPase activating protein (RasGAP), phospholipase C (PLC)-γ, SHP-2 tyrosine phosphatase), resulting in pericyte proliferation and cytoskeletal rearrangements facilitating migration. () Pericyte attachment and differentiation. In both pericytes and endothelium, TGF-β binding to TGFβR2 leads to activation of the ALK5-SMAD2/3 pathway and nuclear translocation of the Smad2/3/4 complex with unique consequences in the two cell types. In pericytes, it inhibits proliferation and leads to expression of contractile and ECM proteins. In endothelium, it also inhibits proliferation and coo! perates with Notch signaling to increase expression of N-cadherin. Specifically, when Notch1 on the endothelial cell binds to an unspecified Notch ligand on the pericyte, activation leads to nuclear translocation of the Notch intracellular domain (NICD). NICD and the Smad2/3/4 complex interact with the transcription factor RBP-Jκ, promoting the upregulation of N-cadherin. Sphingosine-1 phosphate (S1P)-mediated activation of endothelial S1P1 facilitates N-cadherin trafficking to the endothelial cell membrane by the action of the GTPases RhoA and Rac1. Elevated endothelial N-cadherin leads to increased homophilic interactions with N-cadherin on pericytes, resulting in endothelial cell–pericyte adhesion. PDGF-BB/PDGFRβ signaling may also contribute to endothelial cell-pericyte attachment. However, the mechanism by which this occurs and whether N-cadherin is involved remain to be determined. () Pericyte survival. Activated PDGFRβ leads to activation of Akt and Erk serine/t! hreonine kinases and downstream survival pathways. Some studie! s implicate Notch3 signaling in pericyte survival. () Endothelial maturation. Pericyte-derived TGF-β binds to TGFβR2 in endothelium and activates ALK5-Smad2/3/4 and ALK1-Smad1/5/8 pathways, exerting opposing effects on endothelial proliferation. Smad2/3/4 and angiopoietin-1 (Angpt1)/Tie2 signaling contribute to BBB formation. * Figure 4: Pericytes are multi-functional members of the neurovascular unit. Pericytes (1) control BBB integrity by regulating the orientation and abundance of endothelial tight and adherens junction proteins, as well as the rate of bulk flow fluid transcytosis (transendothelial transport of fluid-filled vesicles); (2) regulate the stability and architecture of newly formed cerebral microvessels; (3) contribute to secretion and regulate the levels of extracellular matrix proteins forming the basement membrane; (4) regulate capillary diameter and blood flow; and (5) provide clearance and phagocytotic functions in brain. * Figure 5: Pericyte loss can trigger primary vascular dysfunction leading to neurodegeneration. () (1) Blood-brain barrier (BBB) breakdown due to disrupted BBB tight and adherens junctions and increased bulk flow fluid transcytosis leads to brain influx of serum proteins (for example, albumin, immunoglobulin G (IgG)), causing edema, and of blood-derived vasculotoxic and neurotoxic macromolecules (for example, fibrin, thrombin, hemoglobin (Hb)-derived iron), causing neuronal injury and neurodegenerative changes. RBC, red blood cell; ROS, reactive oxygen species. (2) Reductions in capillary blood flow due to microvascular degeneration and pericapillary edema aggravate chronic hypoperfusion and hypoxia, depriving metabolically active neurons of oxygen and other essential nutrients, which leads to neuronal dysfunction. () Flow chart diagram depicting how deficient PDGFB/PDGFRβ signaling leads to pericyte loss resulting in (1) BBB breakdown and (2) hypoperfusion and hypoxia, as shown in . Both arms 1 and 2 contribute to secondary neuronal degenerative changes. Author information * Abstract * Author information Primary authors * These authors contributed equally to this work. * Ethan A Winkler & * Robert D Bell Affiliations * Center for Neurodegenerative and Vascular Brain Disorders, Department of Neurosurgery and Neurology, University of Rochester Medical Center, Rochester, New York, USA. * Ethan A Winkler, * Robert D Bell & * Berislav V Zlokovic Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Berislav V Zlokovic Author Details * Ethan A Winkler Search for this author in: * NPG journals * PubMed * Google Scholar * Robert D Bell Search for this author in: * NPG journals * PubMed * Google Scholar * Berislav V Zlokovic Contact Berislav V Zlokovic Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• Ivy/neurogliaform interneurons coordinate activity in the neurogenic niche
  - Nat Neurosci 14(11):1407-1409 (2011)
  Nature Neuroscience | Brief Communication Ivy/neurogliaform interneurons coordinate activity in the neurogenic niche * Sean J Markwardt1 * Cristina V Dieni1 * Jacques I Wadiche1 * Linda Overstreet-Wadiche1 * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 14,Pages:1407–1409Year published:(2011)DOI:doi:10.1038/nn.2935Received11 July 2011Accepted15 August 2011Published online09 October 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Depolarization by the neurotransmitter GABA regulates adult neurogenesis. We found interneurons of the neurogliaform cell family to be a primary source of GABA for newborn neurons in mouse dentate gyrus. GABAergic depolarization occurred in concert with reduced synaptic inhibition of mature neurons, suggesting that the local circuitry coordinates the activation of new and pre-existing cells. View full text Figures at a glance * Figure 1: Ivy/NGs innervate NGCs. () Location of interneurons (diamonds) that innervated NGCs in acute brain slices. All procedures were approved by the University of Alabama at Birmingham Institutional Animal Care and Use Committee. GC, granule cell. () Typical slow uPSCs in a NGC. Top, current injection protocol. The average postsynaptic response (green) is overlaid on individual uPSCs. Inset, location of pre- (black) and postsynaptic (green) cells. () uIPSCs in mature cells were either fast (top) or slow (bottom). Normalized currents from a NGC (green) and mature cells (black) are shown overlaid in the lower inset. () Rise times were fit with two Gaussian distributions with mean values of 0.78 (70%) and 1.7 ms in mature cells and 1.7 (57%) and 3.5 ms in NGCs. Decay τ values were well fit with two Gaussian distributions with mean values of 14 (70%) and 32 ms in mature cells and a single distribution with a mean value of 48 ms in NGCs. The PPR of uIPSCs in mature cells was more variable than in NGCs (300-m! s interval). Error bars indicate s.e.m. () Interneuron action potentials and corresponding PSCs in a NGC (top left) and interneuron firing pattern (bottom left). A reconstruction of this presynaptic interneuron near the granule cell layer (dashed lines) is shown on the right, with soma and dendrites in red (length, 820 μm) and partial axon in black (length, 8,424 μm). The inset shows dense varicosities in a 50-μm length of axon. Post hoc immunolabeling of reelin in the same interneuron is shown below. Scale bar represents 10 μm. * Figure 2: Activity patterns in 4-AP support Ivy/NG innervation. () Two distinct interneuron firing patterns in 4-AP (100 μM). Left, example of a burst interneuron that fired spikes and spikelets at 0.04 Hz. Inset, burst shown on an expanded timescale. Right, example of a pause interneuron that was inhibited at 0.04 Hz. Somatic hyperpolarization altered the tonic firing rate of all interneurons, but did not change the low-frequency burst or pause patterns. Some pause interneurons did not fire spontaneously at resting potential (as in ). () Example of an interneuron with a delayed firing pattern that showed bursting in 4-AP (cell shown in ). The dense axonal arbor (length, 13,664 μm) and expression of NPY-GFP (inset) is consistent with Ivy/NGs5, 7, 8. () Example of a non–late-spiking interneuron that was inhibited at 0.04 Hz. The high-frequency firing, fast action potential kinetics and morphology suggest that it is a basket cell (dendrite length, 2,493 μm; partial axon length, 3,320 μm). () Both bursts (upper pair) and pauses (lower! pair) were correlated with giant PSCs in NGCs. Right, cross-correlation analysis revealed a positive correlation with interneuron bursts (4 of 11 pairs, C0 = 0.57 ± 0.05; see Supplementary Methods) and a negative correlation with pauses (7 of 11 pairs, C0 = −0.65 ± 0.05). * Figure 3: Disinhibition of mature cells by Ivy/NGs predicts coordinated activity. () The GAT1 inhibitor NO711 (2 μM) increased the amplitude (114 ± 4% of control, P = 0.02) and decay phase (half width = 161 ± 16% of control, P = 0.05; area = 200 ± 22% of control, P = 0.01) of slow IPSCs in pause interneurons, supporting innervation by Ivy/NGs9, 10. Inset, pause pattern of firing during subsequent 4-AP application. The axon of the pause cell shown in and revealed that it targeted the perisomatic region of mature cells. () Spontaneous interneuron firing induced by somatic depolarization was inhibited by the slow IPSP (from 1.0 ± 0.4 Hz to 0.1 ± 0.1 Hz, P = 0.05, n = 5). Arrow indicates the time of synaptic stimulation. Six traces are overlaid. () Left, sIPSCs in mature granule cells (GC) were reduced after molecular layer stimulation (arrow). Eight traces are overlaid. Bottom and right, NO711 significantly prolonged the suppression of sIPSC (half-width increased from 136 ± 20 ms to 222 ± 35 ms, n = 6, P < 0.02). Error bars indicate s.e.m. Author information * Author information * Supplementary information Affiliations * Department of Neurobiology, McKnight Brain Institute, University of Alabama at Birmingham, Birmingham, Alabama, USA. * Sean J Markwardt, * Cristina V Dieni, * Jacques I Wadiche & * Linda Overstreet-Wadiche Contributions All of the authors contributed to each aspect of this work. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Linda Overstreet-Wadiche Author Details * Sean J Markwardt Search for this author in: * NPG journals * PubMed * Google Scholar * Cristina V Dieni Search for this author in: * NPG journals * PubMed * Google Scholar * Jacques I Wadiche Search for this author in: * NPG journals * PubMed * Google Scholar * Linda Overstreet-Wadiche Contact Linda Overstreet-Wadiche Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (7M) Supplementary Figures 1–8, Supplementary Table 1 and Supplementary Methods Additional data
• PDZ binding of TARPγ-8 controls synaptic transmission but not synaptic plasticity
  - Nat Neurosci 14(11):1410-1412 (2011)
  Nature Neuroscience | Brief Communication PDZ binding of TARPγ-8 controls synaptic transmission but not synaptic plasticity * Akio Sumioka1, 2, 6 * Travis E Brown3, 4, 6 * Akihiko S Kato5 * David S Bredt5 * Julie A Kauer3, 4 * Susumu Tomita1, 2 * Affiliations * Contributions * Corresponding authorsJournal name:Nature NeuroscienceVolume: 14,Pages:1410–1412Year published:(2011)DOI:doi:10.1038/nn.2952Received21 June 2011Accepted17 August 2011Published online16 October 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The reduction in synaptic transmission and plasticity in mice lacking the hippocampus-enriched AMPA receptor (AMPAR) auxiliary subunit TARPγ-8 could be a result of a reduction in AMPAR expression or of the direct action of γ-8. We generated TARPγ-8Δ4 knock-in mice lacking the C-terminal PDZ ligand. We found that synaptic transmission and AMPARs were reduced in the mutant mice, but extrasynaptic AMPAR expression and long-term potentiation (LTP) were unaltered. Our findings suggest that there are distinct TARP-dependent mechanisms for synaptic transmission and LTP. View full text Figures at a glance * Figure 1: TARPγ-8 PDZ binding is necessary for synaptic localization of AMPARs. () Diagram of the synaptic AMPAR-TARP–PSD-95 complex. The PDZ ligand (–TTPV) is deleted. () The γ-8 antibody recognized γ-8 in both γ-8+/+ and γ-8Δ4/Δ4 mice, whereas the antibody to TTPV recognized γ-8 only in γ-8+/+ mice. Brain lysates were immunoprecipitated with normal rabbit IgG (control) or antibody to γ-8, followed by western blotting. All full and uncropped blots are shown in Supplementary Figure 7. () PSD-95 was not associated with γ-8Δ4 in vivo. PSD-95 was co-immunoprecipitated with γ-8 in γ-8+/+, but not in γ-8Δ4/Δ4, mice. () Protein levels of γ-8, GluA1 and GluA2/3 were somewhat decreased in hippocampi in a γ-8Δ4 dosage-dependent manner (n = 4). () Protein levels of γ-8, GluA1 and GluA2/3 in the PSD fraction from hippocampus were reduced in γ-8Δ4/Δ4 mice, but not in the Triton X-100–solublized synaptosome fraction (Syn/Tx). In contrast, expression of γ-8, GluA1 and GluA2/3 in the Syn/Tx fraction were significantly reduced in γ-8−/�! �� mice, but not in γ-8Δ4/Δ4 mice. () Protein levels were normalized to those from γ-8+/+ mice (n = 4). Synaptophysin (Sph) was used as a non-PSD protein. All data are given as mean ± s.e.m. *P < 0.05. * Figure 2: The γ-8 PDZ ligand modulates AMPAR-mediated basal transmission, but not LTP. () The ratio of AMPAR-to-NMDAR EPSCs was reduced by ~30% in CA1 pyramidal cells from γ-8Δ4/Δ4 slices (n = 11) compared with those from γ-8+/+ slices (n = 5). Representative examples of averaged EPSCs are shown (AMPAR current = light trace; NMDAR current = dark trace). Calibration: 100 ms, 20 pA (+/+) and 16 pA (Δ4/Δ4). () Ratio of stimulus intensity (input) to the excitatory postsynaptic potential (EPSP) slope (output). Input-output was significantly reduced in slices from γ-8Δ4/Δ4 (n = 6) compared with those from γ-8+/+ mice (n = 10). *P < 0.05, paired t test. () Whole-cell AMPA-evoked (100 nM) currents were reduced by ~38% in γ-8Δ4/Δ4 (n = 8) compared with γ-8+/+ mice (n = 7). Inset, AMPA-evoked current from representative cells are shown. Calibration: 1 min, 50 pA. () Extracellular recordings of field EPSPs (fEPSPs) before and after tetanic stimulation of Schaffer collaterals (arrow). LTP was elicited to a similar degree in γ-8+/+ (open squares, n = 6), γ-! 8+/Δ4 (light gray squares, n = 9) and γ-8Δ4/Δ4 slices (dark gray squares, n = 10), but was attenuated in γ-8−/− slices (black triangles, n = 4). Inset, averaged fEPSPs before (dark trace) and during LTP (light trace). Calibration: 10 ms, 0.5 mV (+/+), 0.38 mV (+/Δ4), 0.45 mV (Δ4/Δ4) and 0.5 mV (−/−). () Whole-cell recordings from CA1 pyramidal cells before and after a pairing protocol (arrow). LTP was induced in slices from γ-8+/+ (n = 5), γ-8+/Δ4 (n = 4) and γ-8Δ4/Δ4 mice (n = 6). Inset, representative examples of averaged EPSCs recorded before and during LTP. Calibration: 20 ms, 200 pA (+/+), 200 pA (+/Δ4) and 160 pA (Δ4/Δ4). All data are given as mean ± s.e.m. *P < 0.05. Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Akio Sumioka & * Travis E Brown Affiliations * Program in Cellular Neuroscience, Neurodegeneration and Repair, Yale University School of Medicine, New Haven, Connecticut, USA. * Akio Sumioka & * Susumu Tomita * Department of Cellular and Molecular Physiology, Yale University School of Medicine, New Haven, Connecticut, USA. * Akio Sumioka & * Susumu Tomita * Depatment of Molecular Pharmacology, Physiology and Biotechnology, Brown University, Providence, Rhode Island, USA. * Travis E Brown & * Julie A Kauer * Department of Neuroscience, Brown University, Providence, Rhode Island, USA. * Travis E Brown & * Julie A Kauer * Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana, USA. * Akihiko S Kato & * David S Bredt Contributions S.T. and J.A.K. conceived the project and wrote the manuscript. A.S., T.E.B., A.S.K. D.S.B. and S.T. performed all of the experiments and analyzed the results. All of the authors contributed to the final version of the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Susumu Tomita or * Julie A Kauer Author Details * Akio Sumioka Search for this author in: * NPG journals * PubMed * Google Scholar * Travis E Brown Search for this author in: * NPG journals * PubMed * Google Scholar * Akihiko S Kato Search for this author in: * NPG journals * PubMed * Google Scholar * David S Bredt Search for this author in: * NPG journals * PubMed * Google Scholar * Julie A Kauer Contact Julie A Kauer Search for this author in: * NPG journals * PubMed * Google Scholar * Susumu Tomita Contact Susumu Tomita Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (13M) Supplementary Figures 1–7 and Supplementary Methods Additional data
• Hemisphere-specific optogenetic stimulation reveals left-right asymmetry of hippocampal plasticity
  - Nat Neurosci 14(11):1413-1415 (2011)
  Nature Neuroscience | Brief Communication Hemisphere-specific optogenetic stimulation reveals left-right asymmetry of hippocampal plasticity * Michael M Kohl1, 2 * Olivia A Shipton1, 2 * Robert M Deacon3 * J Nicholas P Rawlins3 * Karl Deisseroth4 * Ole Paulsen1, 2 * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 14,Pages:1413–1415Year published:(2011)DOI:doi:10.1038/nn.2915Received08 April 2011Accepted21 July 2011Published online25 September 2011Corrected online13 October 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Postsynaptic spines at CA3-CA1 synapses differ in glutamate receptor composition according to the hemispheric origin of CA3 afferents. To study the functional consequences of this asymmetry, we used optogenetic tools to selectively stimulate axons of CA3 pyramidal cells originating in either left or right mouse hippocampus. We found that left CA3 input produced more long-term potentiation at CA1 synapses than right CA3 input as a result of differential expression of GluN2B subunit–containing NMDA receptors. View full text Figures at a glance * Figure 1: Optogenetics enables selective stimulation of CA3 afferents ex vivo. () Adeno-associated virus containing a DIO Channelrhodopsin2 (ChR2)-eYFP construct was stereotactically injected into either the left or right dorsal CA3 region of Camk2a::cre mice. EF-1α, elongation factor-1α; ITR, inverted terminal repeat; WPRE, woodchuck hepatitis post-transcriptional regulatory element. () ChR2-eYFP expression was limited to the injection site (identified by co-injection of red latex beads) in the CA3 region and ipsilateral and contralateral projections. () Only pyramidal neurons (arrowheads) in the ipsilateral CA3 region expressed ChR2-eYFP. s.l., stratum lucidum; s.r., stratum radiatum; s.o., stratum oriens. () Electrical and optical stimulation in the stratum radiatum produced EPSPs in CA1 pyramidal cells by evoking action potentials that were blocked by 1 μM tetrodotoxin (TTX). () Both electrical (E) and optical (O) stimulation displayed paired-pulse facilitation. The lack of cross-facilitation confirmed that the two inputs were independent. Error! bars represent s.e.m. * Figure 2: Hemispheric asymmetry of t-LTP at the CA3-CA1 pyramidal cell synapse. Indiscriminate electrical stimulation (triangles) in the stratum radiatum produced robust t-LTP in CA1 pyramidal neurons. (–) Selective optical stimulation (circles) of CA3 Schaffer collaterals (ipsilateral projections) and commissural fibers (contralateral projections) originating in the left hemisphere also both induced t-LTP. (–) In contrast, optical stimulation of CA3 projections originating in the right hemisphere led to significantly less t-LTP than electrical stimulation. Insets show representative EPSPs at the indicated time points (1, 2). Error bars represent s.e.m. **P < 0.01, Student's t test. * Figure 3: Asymmetric expression of GluN2B-containing NMDARs underlies hemispheric differences in t-LTP. () Hemisphere-selective optical stimulation (gray traces, gray bars) and hemisphere-indiscriminate electrical stimulation (black traces, black bars) of afferents from CA3 were used to evoke postsynaptic currents in CA1 pyramidal cells contralateral to the injection side. There was no difference in the overall NMDA/AMPA ratios between left and right for either electrical or optical stimulation (dark gray box indicates the time window for estimation of the NMDAR current). () Selective block of GluN2B subunit–containing NMDARs with 0.5 μM Ro 25-6981 affected the NMDAR current evoked by left CA3 input more than that evoked by right CA3 input. Open bars indicate NMDAR current estimate in control, filled bars indicate remaining NMDAR current in the presence of 0.5 μM Ro 25-6981. Traces show representative optically evoked postsynaptic currents at +60 mV in the presence of 0.5 μM Ro 25-6981 for left- and right-injected animals. () 0.5 μM Ro 25-6981 completely blocked t-LTP in! CA1 cells receiving left CA3 (optical stimulation, circles) or mixed CA3 inputs (electrical stimulation, triangles). Insets show representative EPSPs at the indicated time points (1, 2). Error bars represent s.e.m. *P < 0.05, Student's t test. Change history * Change history * Author information * Supplementary informationCorrected online 13 October 2011In the version of this article initially published online, the schematics, traces and graphs in Figs. 2d and 2e were interchanged. The error has been corrected for the print, PDF and HTML versions of this article. Author information * Change history * Author information * Supplementary information Affiliations * Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK. * Michael M Kohl, * Olivia A Shipton & * Ole Paulsen * Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK. * Michael M Kohl, * Olivia A Shipton & * Ole Paulsen * Department of Experimental Psychology, University of Oxford, Oxford, UK. * Robert M Deacon & * J Nicholas P Rawlins * Department of Bioengineering, Stanford University, Stanford, California, USA. * Karl Deisseroth Contributions M.M.K. conducted the experiments and analyzed the data. O.A.S. contributed recordings. M.M.K. and R.M.D. injected the animals. J.N.P.R. provided advice on the project. K.D. designed and cloned the AAV DIO ChR2-YFP vector. M.M.K. and O.P. designed the experiments. M.M.K., O.A.S. and O.P. wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Ole Paulsen Author Details * Michael M Kohl Search for this author in: * NPG journals * PubMed * Google Scholar * Olivia A Shipton Search for this author in: * NPG journals * PubMed * Google Scholar * Robert M Deacon Search for this author in: * NPG journals * PubMed * Google Scholar * J Nicholas P Rawlins Search for this author in: * NPG journals * PubMed * Google Scholar * Karl Deisseroth Search for this author in: * NPG journals * PubMed * Google Scholar * Ole Paulsen Contact Ole Paulsen Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Change history * Author information * Supplementary information PDF files * Supplementary Text and Figures (561K) Supplementary Figures 1 and 2, Supplementary Table 1, and Supplementary Methods Additional data
• Amygdala lesions selectively impair familiarity in recognition memory
  - Nat Neurosci 14(11):1416-1417 (2011)
  Nature Neuroscience | Brief Communication Amygdala lesions selectively impair familiarity in recognition memory * Anja Farovik1 * Ryan James Place1 * Danielle Renée Miller1 * Howard Eichenbaum1 * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 14,Pages:1416–1417Year published:(2011)DOI:doi:10.1038/nn.2919Received29 April 2011Accepted28 July 2011Published online25 September 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg A major controversy in the study of memory concerns whether there are distinct medial temporal lobe (MTL) substrates of recollection and familiarity. Studies using receiver operating characteristics analyses of recognition memory indicate that the hippocampus is essential for recollection, but not for familiarity. We found the converse pattern in the amygdala, wherein damage impaired familiarity while sparing recollection. Combined with previous findings, these results dissociate recollection and familiarity by selective MTL damage. View full text Figures at a glance * Figure 1: Recognition memory task. Each day, the rats studied ten stimuli consisting of scented sand in cups with buried rewards, and then recognition was tested on the studied (old) odors plus another ten new odors. Response bias was manipulated by varying the height of the cup and the amount of reward received for correctly digging in new test cups or correctly withholding the response to old test stimuli and receiving reward elsewhere. Hits consist of correct identifications of old odors and false alarms are incorrect identifications of new odors as old. * Figure 2: ROC function in recognition performance. () Pre-operative (pre-op) ROC for control rats (C, R = 0.31, d′ = 0.93) and rats that were later given amygdala lesions (A, R = 0.17, d′ = 1.26). () Post-operative (post-op) ROC functions in control rats (R = 0.17, d′ = 1.11) and amygdala-lesioned rats (R = 0.38, d′ = 0.43). Flattened ROC curve in amygdala-lesioned rats indicates loss of familiarity. Response criteria: 5 = conservative and 1 = liberal. Insets, parameter estimates (+s.e.m.) of recollection (R) and familiarity (F) for control rats and lesioned rats. () Reconstruction of amygdala lesions at −3.0 mm (68% damage, left) and −2.00 mm (44% damage, right) posterior to bregma. Gray indicates the area of the average lesion size; dashed line indicates the largest lesion. Author information * Author information * Supplementary information Affiliations * Center for Memory and Brain, Boston University, Boston, Massachusetts, USA. * Anja Farovik, * Ryan James Place, * Danielle Renée Miller & * Howard Eichenbaum Contributions H.E. and A.F. designed the study and wrote the manuscript. A.F. carried out the surgery and analyzed the data. R.J.P., D.R.M. and A.F. performed the experiment, and R.J.P. and A.F. performed the histological analysis. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Howard Eichenbaum Author Details * Anja Farovik Search for this author in: * NPG journals * PubMed * Google Scholar * Ryan James Place Search for this author in: * NPG journals * PubMed * Google Scholar * Danielle Renée Miller Search for this author in: * NPG journals * PubMed * Google Scholar * Howard Eichenbaum Contact Howard Eichenbaum Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (86K) Supplementary Results, Supplementary Methods and Supplementary Figure 1 Additional data
• Sleep and waking modulate spine turnover in the adolescent mouse cortex
  - Nat Neurosci 14(11):1418-1420 (2011)
  Nature Neuroscience | Brief Communication Sleep and waking modulate spine turnover in the adolescent mouse cortex * Stephanie Maret1, 3 * Ugo Faraguna1, 3 * Aaron B Nelson1, 2 * Chiara Cirelli1 * Giulio Tononi1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature NeuroscienceVolume: 14,Pages:1418–1420Year published:(2011)DOI:doi:10.1038/nn.2934Received01 June 2011Accepted08 August 2011Published online09 October 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Cortical development involves synaptic formation and elimination. Although synaptogenesis predominates in the early stages and pruning in the later stages, the two processes are thought to happen concurrently. In adults, synaptic strength is modulated by behavioral state, and we asked whether synaptic remodeling may be affected by sleep and waking states. Using two-photon microscopy in adolescent mice, we found that waking results in a net increase in cortical spines, whereas sleep is associated with net spine loss. View full text Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Stephanie Maret & * Ugo Faraguna Affiliations * Department of Psychiatry, University of Wisconsin, Madison, Wisconsin, USA. * Stephanie Maret, * Ugo Faraguna, * Aaron B Nelson, * Chiara Cirelli & * Giulio Tononi * Neuroscience Training Program, University of Wisconsin, Madison, Wisconsin, USA. * Aaron B Nelson Contributions C.C. and G.T. designed the experiments, analyzed the data and wrote the paper. S.M. and U.F. performed the experiments, analyzed the data and contributed to the manuscript. A.B.N. gathered EEG pilot data. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Chiara Cirelli or * Giulio Tononi Author Details * Stephanie Maret Search for this author in: * NPG journals * PubMed * Google Scholar * Ugo Faraguna Search for this author in: * NPG journals * PubMed * Google Scholar * Aaron B Nelson Search for this author in: * NPG journals * PubMed * Google Scholar * Chiara Cirelli Contact Chiara Cirelli Search for this author in: * NPG journals * PubMed * Google Scholar * Giulio Tononi Contact Giulio Tononi Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (1M) Supplementary Figures 1–3 and Supplementary Discussion and Supplementary Results Additional data
• A dual shaping mechanism for postsynaptic ephrin-B3 as a receptor that sculpts dendrites and synapses
  - Nat Neurosci 14(11):1421-1429 (2011)
  Nature Neuroscience | Article A dual shaping mechanism for postsynaptic ephrin-B3 as a receptor that sculpts dendrites and synapses * Nan-Jie Xu1 * Suya Sun2 * Jay R Gibson3 * Mark Henkemeyer1 * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 14,Pages:1421–1429Year published:(2011)DOI:doi:10.1038/nn.2931Received13 April 2011Accepted17 August 2011Published online02 October 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 As the neural network becomes wired, postsynaptic signaling molecules are thought to control the growth of dendrites and synapses. However, how these molecules are coordinated to sculpt postsynaptic structures is less well understood. We find that ephrin-B3, a transmembrane ligand for Eph receptors, functions postsynaptically as a receptor to transduce reverse signals into developing dendrites of mouse hippocampal neurons. Both tyrosine phosphorylation–dependent GRB4 SH2/SH3 adaptor-mediated signals and PSD-95–discs large–zona occludens-1 (PDZ) domain–dependent signals are required for inhibition of dendrite branching, whereas only PDZ interactions are necessary for spine formation and excitatory synaptic function. PICK1 and syntenin, two PDZ domain proteins, participate with ephrin-B3 in these postsynaptic activities. PICK1 has a specific role in spine and synapse formation, and syntenin promotes both dendrite pruning and synapse formation to build postsynaptic stru! ctures that are essential for neural circuits. The study thus dissects ephrin-B reverse signaling into three distinct intracellular pathways and protein–protein interactions that mediate the maturation of postsynaptic neurons. View full text Figures at a glance * Figure 1: eB3 is required for dendrite pruning and spine formation in hippocampal CA1 neurons. () Developmental expression of eB3 in the CA1 pyramidal cell layer visualized by X-gal staining of coronal sections for the eB3–β-gal fusion protein (blue) in Efnb3lacZ mice from postnatal week 1 (PW1) to PW6. Structure of the hippocampus is visualized by eosin counterstaining (red). Arrowheads indicate the localization of eB3 protein in the CA1 dendritic field. There is also strong expression of eB3 in granule cells of the dentate gyrus (DG) where the eB3–β-gal fusion localizes to mossy fiber axons and dendrites. Scale bars represent 300 μm (top) and 150 μm (bottom). () Efnb3−/− and Efnb3−/−; Efnb2lacZ/6FΔV mutants at P12 showed excessive dendrites and reduced spine density in CA1 pyramidal neurons. Top left, dashed white circle indicates the crossed primary dendrites. Green, Thy1-GFP-M fluorescence; blue, NeuroTrace to stain CA1 pyramidal cell layer; white arrowheads, individual spines. Scale bars represent 20 μm (top) and 10 μm (bottom). (–) Quantific! ation of primary dendrites (), spine density (), percentage distribution of spine length () and spine head diameter () in wild-type, Efnb3−/− and Efnb3−/−; Efnb2lacZ/6FΔV neurons at P12 and P20 (n = 12 in each group). Error bars represent mean ± s.e.m. *P < 0.05, **P < 0.01, ***P < 0.001. * Figure 2: eB3 is required and sufficient for excitatory synaptic function in hippocampal CA1 neurons. (,) Efnb3−/− mutant showed reduced mEPSC frequency in CA1 pyramidal neurons at P12 and P20. Scale bar represents 20 pA (vertical) × 1 s (horizontal). Error bars, mean ± s.e.m. **P < 0.01, ***P < 0.001. () Generation of conditional loxP-flanked knock-in Efnb3neo mutant. Exons (coding and non-coding segments shown by dark gray and light gray boxes) and introns (lines) are flanked by a diphtheria toxin (DT-A) and thymidine kinase (TK) expression cassette for negative selection. EcoRI (E) and NsiI (N) indicate restriction sites. The primary targeted allele, Efnb3neo homozygous was crossed with CAGG-CreERT2M driver and a tdTomato reporter to identify cells exposed to active Cre. eB3 expression in the initial Efnb3neo/neo mutant was restored on tamoxifen administration, which was used to induce Cre-mediated excision of the loxP-flanked PGK-neo cassette. () Schedule of tamoxifen treatment and hippocampus dissection during postnatal development. () Cre-mediated recombination i! n CA1 area was detected in P12 hippocampal sections by tdTomato fluorescence (arrowheads) in cre+; tdTomato+; Efnb3neo/neo mice but not in cre−; tdTomato+; Efnb3neo/neo mice following tamoxifen administration at P5. Scale bars represent 100 μm (left) and 20 μm (right). () mEPSC recordings were performed in tdTomato-positive (indicated by glass electrodes) and tdTomato-negative neurons in hippocampal CA1 area of cre+; tdTomato+; Efnb3neo/neo mice after tamoxifen treatment. Scale bars represent 10 μm (left) and 20 pA (vertical) × 1 s (horizontal) (right). * Figure 3: eB3 tyrosine phosphorylation and PDZ binding are differentially required for dendrite morphogenesis and synaptic function. () Point mutations in Efnb3 that change tyrosines (Y) to phenylalanines (F) to eliminate tyrosine phosphorylation and SH2 binding (3F and 5F), the C-terminal valine (V) required for PDZ binding (ΔV) or both SH2 and PDZ binding (3FΔV). () Thy1-GFP-M fluorescence (green) was used to visualize the morphology of CA1 neurons at P12. White arrowheads indicate individual spines. Scale bars represent 20 μm (left) and 10 μm (right). (–) Quantification of primary dendrites (), spine density (), and percentage distribution of spine length () and spine head diameter () in wild-type, Efnb33F/3F, Efnb35F/5F, Efnb3ΔV/ΔV and Efnb33FΔV/3FΔV mutants at P12 (n = 25 for each group). Error bars, mean ± s.e.m. *P < 0.05, **P < 0.01, ***P < 0.001. * Figure 4: PDZ binding of eB3 are required for synaptic function. () mEPSCs were recorded in CA1 pyramidal neurons from wild types, Efnb33F/3F, Efnb35F/5F, Efnb3ΔV/ΔV and Efnb33FΔV/3FΔV mutants at P12. Scale bars represent 20 pA (vertical) × 1 s (horizontal). (,) Quantification of mEPSC frequency () and amplitude () for CA1 pyramidal neurons from the different Efnb3 mutants (n = 15). Error bars represent mean ± s.e.m. *P < 0.05, ***P < 0.001. * Figure 5: PICK1 and syntenin mediate eB3 reverse signaling through PDZ binding to control spine and synapse formation and synaptic function. () Spine and synapse formation were indicated with a transfected f-EGFP reporter and presynaptic marker synapsin in 12-d cultured hippocampal neurons from wild-type, Efnb3−/− and Efnb3ΔV/ΔV mice. Arrowhead, synapse on spine; arrow, synapse on shaft. Scale bar represents 10 μm. () The density of spines and synapses on spines (arrowhead in ) and on shafts (arrow in ) were quantified. n = 10. () mEPSCs were recorded in 12–14-d cultured neurons from Efnb3 mutants and wild-type (left), and in Efnb3−/− hippocampal neurons that were infected with lentivirus packaged eB3-PICK1 or eB3-syntenin (Syn) expression vectors. Quantification of mEPSC frequency (top) and amplitude (bottom) is shown. n = 15–20. Error bars, mean ± s.e.m. () Expression of Flag-tagged wild-type eB3-PICK1 or Syn chimeric fusion proteins (left panels) in transfected Efnb3−/− neurons rescues spine and synapse formation, as visualized with f-EGFP and synapsin in chimeric protein-expressing neurons! labeled with anti-Flag antibodies (upper panels). Expression of the eB3-PICK1-ΔPDZ or eB3-Syn-ΔPDZ1+2 fusion proteins deleted for the respective PDZ domains (right panels) had little if any effect on spine and synapse formation in Efnb3−/− neurons. Arrowhead, synapse on spine; arrow, synapse on shaft. Scale bar represents 10 μm. () Examples of mEPSC recorded in Efnb3−/− neurons expressing eB3-PICK1 or Syn fusion proteins and their PDZ-deleted mutant forms. Scale bars represent 40 pA (vertical) × 2 s (horizontal). *P < 0.05, **P < 0.01, ***P < 0.001. * Figure 6: GRB4, PICK1 and syntenin mediated distinct reverse signaling to prune primary dendrites in cultured hippocampal neurons. () Expression of eB3-GRB4-SH3 or eB3-syntenin (eB3-Syn) chimeric fusion proteins in transfected Efnb3−/− hippocampal neurons reduces primary dendrites as visualized with f-EGFP. Expression of eB3-PICK1 or its mutant eB3-PICK1-ΔPDZ or mutants of eB3-GRB4 or eB3-Syn fusion proteins had little, if any, effect on the number of primary dendrites in Efnb3−/− neurons. Scale bar represents 10 μm. () Cultured hippocampal neurons at P12 from Efnb3−/− mice show more primary dendritic branches than wild-type littermates, as visualized with f-EGFP. Scale bar represents 10 μm. () Analysis of the number of primary dendrites in neurons expressing different chimeric fusion proteins. Error bars, mean ± s.e.m. n = 10–12. *P < 0.05, **P < 0.01. * Figure 7: Association of eB3-PICK1 or eB3-Syn with downstream signaling molecules. () Following EphB2-Fc treatment for 16 h in cultured hippocampal neurons to cluster the eB3 proteins to spots on the plasma membrane, wild-type Flag-eB3-PICK1 co-localized with PICK1, whereas wild-type Flag-eB3-Syn co-localized with syndecan-2 (SDC2) (arrowheads). The PDZ domain-deleted proteins showed highly diminished or no ability to form protein–protein interactions with PICK1 or SDC2. Scale bar represents 5 μm. () In transfected Cos-1 cells, HA-PICK1 or HA-SDC2 was co-immunoprecipitated with wild-type Flag-eB3-PICK1 or Flag-eB3-Syn, respectively, but little if any was precipitated with the eB3-PICK1-ΔPDZ or eB3-Syn-ΔPDZ1+2 PDZ deleted counterparts. IB, immunoblot; IP, immunoprecipitation. The blots presented were cropped, and the full-length blots are presented in Supplementary Figure 15. Author information * Abstract * Author information * Supplementary information Affiliations * Department of Developmental Biology and Kent Waldrep Center for Basic Research on Nerve Growth and Regeneration, University of Texas Southwestern Medical Center, Dallas, Texas, USA. * Nan-Jie Xu & * Mark Henkemeyer * Department of Physiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA. * Suya Sun * Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, Texas, USA. * Jay R Gibson Contributions N.-J.X. generated Ephb3neo, Ephb33F, Ephb35F, Efnb3ΔV and Efnb33FΔV knock-in mice. N.-J.X. and S.S. performed the experiments. J.R.G. supervised the electrophysiological recording in brain slides. N.-J.X. and M.H. designed experiments and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Mark Henkemeyer Author Details * Nan-Jie Xu Search for this author in: * NPG journals * PubMed * Google Scholar * Suya Sun Search for this author in: * NPG journals * PubMed * Google Scholar * Jay R Gibson Search for this author in: * NPG journals * PubMed * Google Scholar * Mark Henkemeyer Contact Mark Henkemeyer 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 1–16 Additional data
• Bidirectional plasticity of calcium-permeable AMPA receptors in oligodendrocyte lineage cells
  - Nat Neurosci 14(11):1430-1438 (2011)
  Nature Neuroscience | Article Bidirectional plasticity of calcium-permeable AMPA receptors in oligodendrocyte lineage cells * Marzieh Zonouzi1 * Massimiliano Renzi1 * Mark Farrant1 * Stuart G Cull-Candy1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature NeuroscienceVolume: 14,Pages:1430–1438Year published:(2011)DOI:doi:10.1038/nn.2942Received30 June 2011Accepted11 August 2011Published online09 October 2011Corrected online20 October 2011 Abstract * Abstract * Change history * 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 Oligodendrocyte precursor cells (OPCs), a major glial cell type that gives rise to myelinating oligodendrocytes in the CNS, express calcium-permeable AMPA receptors (CP-AMPARs). Although CP-AMPARs are important for OPC proliferation and neuron-glia signaling, they render OPCs susceptible to ischemic damage in early development. We identified factors controlling the dynamic regulation of AMPAR subtypes in OPCs from rat optic nerve and mouse cerebellar cortex. We found that activation of group 1 mGluRs drove an increase in the proportion of CP-AMPARs, reflected by an increase in single-channel conductance and inward rectification. This plasticity required the elevation of intracellular calcium and used PI3K, PICK-1 and the JNK pathway. In white matter, neurons and astrocytes release both ATP and glutamate. Unexpectedly, activation of purinergic receptors in OPCs decreased CP-AMPAR expression, suggesting a capacity for homeostatic regulation. Finally, we found that stargazin-re! lated transmembrane AMPAR regulatory proteins, which are critical for AMPAR surface expression in neurons, regulate CP-AMPAR plasticity in OPCs. View full text Figures at a glance * Figure 1: DHPG increases rectification of AMPARs in CG4 OPCs. () Representative whole-cell current responses to voltage ramps (0, −100, +60 and 0 mV) from a control CG4 OPC (top) and one treated with 100 μM DHPG (bottom). () I-V relationship (−100 to +60 mV) for the control cell shown in . The rectification index (+60/−60 mV) was 0.54. () Data are presented as in for the DHPG-treated cell shown in . Rectification was greater (rectification index = 0.38). () Averaged normalized whole-cell I-V relationships from untreated (n = 10) and DHPG-treated (n = 8) CG4 cells. Filled areas indicate s.e.m. () Pooled data showing the effect of DHPG treatment on rectification index and block of DHPG effect by the mGluR antagonists ACDPP (10 μM) and MCPG (1 mM). Error bars denote s.e.m. **P < 0.01. () Pooled data showing the effect of DHPG on current density (−100 mV) and block by ACDPP and MCPG. ***P < 0.001. () Representative western blots showing the effect of DHPG on cell surface expression of GluA2, GluA3 and GluA4. () Pooled data from t! hree experiments of the type shown in . Error bars denote s.e.m. *P < 0.05. * Figure 2: DHPG increases single-channel conductance of AMPARs in CG4 OPCs. () Representative averaged current response to 10 mM glutamate (100 ms, −60 mV) recorded from an outside-out patch taken from an untreated CG4 OPC (average of 80 responses). The weighted time constant of desensitization (τdes; see Online Methods) was 5.6 ms. Inset, current-variance plot for the same patch (fitted with equation (1), see Online Methods). Circles indicate mean values and error bars represent s.e.m. Dashed line indicates background variance. For this cell, the weighted mean single-channel conductance was 34.1 pS and the peak open probability was 0.79. () Data presented as in for a representative DHPG-treated cell (average of 110 responses). () Global averaged current-variance traces for control (n = 14) and DHPG-treated cells (n = 12). Circles indicate mean values and error bars represent s.e.m. Filled areas indicate 95% confidence intervals for the fits. (–) Pooled data showing the effect of DHPG treatment on single-channel conductance, Po,peak and τdes. ! Bars indicate mean values and error bars represent s.e.m. Note that the DHPG-induced increase in conductance was blocked by the mGluR antagonists ACDPP and MCPG (10 μM and 1 mM) and by pre-treatment with BAPTA-AM (20 μM). **P < 0.01. * Figure 3: mGluR-induced AMPAR plasticity is developmentally regulated in native OPCs. () Global averaged normalized whole-cell I-V plots for OPCs (6 DIV, n = 14 and 10). Traces indicate means and shaded areas denote s.e.m. Note the increase in rectification following DHPG treatment. Inset, immature OPC labeled with antibody to O4 (permeabilized). Scale bar represents 25 μm. () Data presented as in for a pre-myelinating OPC (Pre-m. OPC) developed from OPCs starved of growth factors. I-V plots were generated from five cells each in and . Note the linear I-V relationship in the control condition and the lack of change following DHPG treatment. () Pooled data showing the effect of DHPG treatment on rectification index in immature OPCs and the lack of effect in pre-myelinating OPCs. Bars indicate mean values and error bars represent s.e.m.*P < 0.05. * Figure 4: ATP reduces AMPAR rectification in native OPCs. () Global averages of normalized I-V plots obtained from untreated OPCs (n = 10) and OPCs treated with ATP (1 mM, n = 7). Filled areas indicate s.e.m. ATP treatment decreased AMPAR rectification. () Pooled data showing the effect of ATP on rectification index. The effect of ATP was blocked by the P2 receptor antagonist PPADS (100 μM) or the calcium chelator BAPTA-AM (20 μM), but not by cyclohexamide (C-hex, 25 μM). *P < 0.05, **P < 0.01. () Representative averaged response from an outside-out patch from an untreated OPC to fast application of 10 mM glutamate (100 ms, −60 mV, mean of 88 traces). Inset, current-variance plot for this cell. () Data presented as in for an OPC treated with ATP (mean of 40 traces). () Pooled normalized data showing the effect of ATP treatment on weighted mean single-channel conductance (Cond.), Po,peak and τdes. In –, bars and symbols indicate mean values and error bars represent s.e.m. ***P < 0.001. * Figure 5: TARPs are expressed in OPCs. () RT-PCR analysis of TARP expression in the rat optic nerve. mRNA for γ-2, γ-3, γ-4, γ-5 and the TARP-related protein γ-6 was detected. (–) Representative confocal images showing labeling of NG2-positive cells (), O4-positive cells () and pre-myelinating OPCs () with antibodies to pan-TARP (red), NG2 (green) and O4 (green). Note the punctate TARP labeling (indicated by arrowheads) along the processes of the pre-myelinating OPC (inset, from white rectangle in ). () Representative confocal images of oligodendrocytes identified with antibody to O1 (green). The cells exhibited reduced TARP immunoreactivity compared with that seen in pre-myelinating OPCs. Labeling similar to that shown in – was seen in 8–20 cells of each type across 12 separate cultures. Scale bars represent 25 μm (10 μm, inset). () Confocal images of a representative sagittal section of cerebellar cortex from a P7 rat showing labeling of the granule cell layer (gcl) with antibodies to NG2 (red) and! pan-TARP (green) and nuclear staining with DAPI (blue). Scale bar represents 25 μm. Arrowheads indicate presumptive NG2-positive OPC. * Figure 6: TARPs control mGluR-induced AMPAR plasticity. () Global averages of normalized I-V plots obtained from OPCs transfected either with full-length γ-2 (n = 6) or γ-2ΔC308 (n = 7). Filled areas indicate s.e.m. () DHPG did not alter AMPAR rectification in OPCs transfected with γ-2ΔC308 (n = 5). () Pooled data showing rectification index values. **P < 0.01. () Averaged glutamate-evoked response (10 mM, 100 ms, −60 mV) recorded in a patch excised from an OPC transfected with GFP alone (mean of 60 responses). Inset, current-variance plot for this patch. () Data presented as in for an OPC transfected with γ-2ΔC308 (mean of 68 responses). () Pooled normalized data showing the effect of γ-2ΔC308 expression on the weighted mean single-channel conductance (Cond.), Po,peak and τdes**P < 0.01. In –, bars and symbols indicate mean values and error bars represent s.e.m. * Figure 7: mGluR activation increases synaptic CP-AMPARs in cerebellar NG2-positive OPCs. () Representative confocal images of a sagittal cerebellar slice from an NG2-DsRed mouse (P11) labeled with antibody to calbindin (CB; green) to identify Purkinje cells and stained with DAPI (blue). NG2-positive OPCs (red) are readily identified in the Purkinje cell layer (arrowhead). Middle, the molecular layer (ml), Purkinje cell layer (Pcl), granule cell layer (gcl) and white matter (wm) are indicated. Scale bar represents 25 μm. () Representative records from an OPC showing a voltage-gated Na+ current that was blocked by tetrodotoxin (TTX, 1 μM). All cells identified as OPCs exhibited such voltage-gated Na+ currents; bar graph shows Na+ current density. Circles represent values from each cell, bar indicates mean and error bar denotes s.e.m. () Paired-pulse depression of evoked climbing fiber–NG2-positive OPC EPSCs. Inset, representative averaged responses from one cell (−80 mV, pulse separation of 500 ms). (,) Averaged climbing fiber–evoked EPSCs recorded at +60,! 0 and −80 mV in a control cell () and in a cell following 10-min application of 100 μM DHPG (). Corresponding I-V relationships are fitted with third-order polynomials (see Supplementary Fig. 2). The treated cell showed greater inward rectification than the control cell. RI, rectification index. () Averaged normalized I-V relationships from ten control and five DHPG-treated cells. Error bars denote s.e.m. and are hidden by symbols. () Pooled data showing decreased rectification index values (increased inward rectification) in the DHPG-treated cells. Bars indicate mean values and error bars denote s.e.m.**P < 0.01. Change history * Abstract * Change history * Author information * Supplementary informationCorrected online 20 October 2011In the HTML version of this article initially published online, the name of one of the corresponding authors was incorrect. The error has been corrected for the HTML version of this article. Author information * Abstract * Change history * Author information * Supplementary information Affiliations * Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK. * Marzieh Zonouzi, * Massimiliano Renzi, * Mark Farrant & * Stuart G Cull-Candy Contributions M.Z. performed electrophysiology and molecular experiments on cultured cells. M.R. and M.Z. performed slice recordings. M.F. and M.Z. analyzed the data. All of the authors contributed to the design and interpretation of experiments. S.G.C.-C. and M.F. supervised the project. M.Z., M.F. and S.G.C.-C. wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Stuart G Cull-Candy or * Mark Farrant Author Details * Marzieh Zonouzi Search for this author in: * NPG journals * PubMed * Google Scholar * Massimiliano Renzi Search for this author in: * NPG journals * PubMed * Google Scholar * Mark Farrant Contact Mark Farrant Search for this author in: * NPG journals * PubMed * Google Scholar * Stuart G Cull-Candy Contact Stuart G Cull-Candy Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Change history * Author information * Supplementary information PDF files * Supplementary Text and Figures (590K) Supplementary Figures 1 and 2 Additional data
• In utero exposure to cocaine delays postnatal synaptic maturation of glutamatergic transmission in the VTA
  - Nat Neurosci 14(11):1439-1446 (2011)
  Nature Neuroscience | Article In utero exposure to cocaine delays postnatal synaptic maturation of glutamatergic transmission in the VTA * Camilla Bellone1 * Manuel Mameli1, 3 * Christian Lüscher1, 2 * Affiliations * Contributions * Corresponding authorsJournal name:Nature NeuroscienceVolume: 14,Pages:1439–1446Year published:(2011)DOI:doi:10.1038/nn.2930Received21 June 2011Accepted09 August 2011Published online02 October 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 Maternal exposure to cocaine may perturb fetal development and affect synaptic maturation in the offspring. However, the molecular mechanism underlying such changes remains elusive. We focused on the postnatal maturation of glutamatergic transmission onto ventral tegmental area dopamine neurons in the mouse. We found that, during the first postnatal week, transmission was dominated by calcium-permeable AMPA receptors and GluN2B-containing NMDA receptors. Subsequently, mGluR1 receptors drove synaptic insertion of calcium-impermeable AMPA receptors and GluN2A-containing NMDAR. When pregnant mice were exposed to cocaine, this glutamate receptor switch was delayed in offspring as a result of a direct effect of cocaine on the fetal dopamine transporter and impaired mGluR1 function. Finally, positive modulation of mGluR1 in vivo was sufficient to rescue maturation. These data identify the molecular target through which in utero cocaine delays postnatal synaptic maturation, reveal ! the underlying expression mechanism of this impairment and propose a potential rescue strategy. View full text Figures at a glance * Figure 1: Developmental expression of glutamate receptors in DA neurons. () Plot of rectification index (RI) as function of postnatal day. Above, averaged example traces of AMPAR-EPSCs recorded at −60, 0 and +30 mV. Scale bars represent 50 pA and 10 ms. Dark green, P2–6; light green, P14–26. () Bar graph for group data of rectification index (P2–6, 1.55 ± 0.09, n = 26; P14–26, 1.0 ± 0.1, n = 8; t32 = 3, P = 0.0047). () Amplitude versus time plot and average example traces of AMPAR-EPSCs in slices at P2–6 and P14–26 in the presence of 2 μM PhTx-433 (inhibition: P2–6, 38.0 ± 7.8%, n = 5; P14–26, 8.0 ± 5.3%, n = 6; t9 = 2.7, P = 0.024). Scale bars represent 50 pA and 10 ms. () Scaled example traces and decay time for NMDAR-EPSCs (τw: P2–6, 151 ± 14 ms, n = 15; P14–26, 88 ± 8 ms, n = 14; t27 = 3.9, P = 0.0005). Scale bar represents 50 ms. () Sample traces and effects of Zn2+ (300 nM) on NMDAR-EPSCs recorded at +40 mV (Zn2+ inhibition: P2–6, 33.3 ± 4.9%, n = 7; P14–26, 50.0 ± 2.9%, n = 5; t10 = 2.6, P = 0.028). Scal! e bars represent 100 pA and 50 ms. () Amplitude versus time plot and sample traces on NMDAR-EPSCs recorded at +40 mV in slices at P2–6 and P14–26 in the presence of 3 μM ifenprodil (P2–6, 48.1 ± 1.5%, n = 11; P14–26, 86.3 ± 1.1%, n = 11; t20 = 20, P < 0.0001). Scale bars represent 100 pA and 50 ms. Error bars represent s.e.m. *P < 0.05, **P < 0.01, ***P < 0.001. * Figure 2: AMPA receptors in DA neurons mediate calcium influx during postnatal development. () Left, image of a DA neuron at P4. White box represents the line-scan position. Scale bar represents 20 μm. Right, green (Oregon Green BAPTA-1, 100 μM) and red (Alexa FluoRed 594) fluorescence collected in line-scan mode during electrical stimulation at synaptic hotspots (S) (black arrowhead). Scale bars represent 1 μm. () Similar experiments at P16. Data are presented as in . () Synaptic Ca2+ transients shown as ΔG/R fluorescence from the same cell as in during baseline (i), in the presence of DL-AP5 (ii) and in the presence of PhTx-433 (iii). Scale bars represent 1% for ΔG/R and 1 s. () Synaptic Ca2+ transients shown as ΔG/R fluorescence from the same cell as in during baseline (i), in presence of PhTx-433 (ii) and in presence of DL-AP5 (iii). Scale bars represent 1% for ΔG/R and 1 s. () Bar graph indicating group data for ΔG/R fluorescence in the same conditions as and for P2–6 and P14–26 mice (P2–6: 2.8 ± 0.7 baseline, 2.6 ± 0.6 in AP5 and 0.27 ± 0.01 ! in PhTx; F2,12 = 6.5, P = 0.012, n = 5; P14–26: 3.7 ± 1.2 baseline, 3.71 ± 1.4 in PhTx and 0.16 ± 0.02 in AP5; F2,12 = 5.98, P = 0.019, n = 5). **P < 0.02. () Sample traces, timeline and bar graph of synaptically evoked AMPAR-mediated Ca2+ transients recorded in presence of AP5 (i) and after application of VGCC blockers (ii) (mibefradil and nimodipine) (5.1 ± 0.5 versus 4.5 ± 0.04; t3 = 3.49, P = 0.025, n = 5). Error bars represent s.e.m. * Figure 3: Glutamate receptors maturation in mGluR1−/− mice. () Sample traces of AMPAR-EPSCs (recorded at −60, 0 and +30 mV) and group data for rectification index as a function of postnatal day in wild-type (WT) and mGluR1−/− littermate (P2–6: wild type, 1.55 ± 0.1, n = 5; mGluR1−/−, 1.9 ± 0.6, n = 6, P > 0.05; P14–26: wild type, 0.92 ± 0.07, n = 7; mGluR1−/−, 1.89 ± 0.20, n = 12; t17 = 3.02, P = 0.008). Scale bars represent 25 pA and 10 ms. () Sample traces and effect of PhTx-433 (2 μM) on evoked AMPAR-EPSCs in wild-type and mGluR1−/− littermate (wild type, inhibition = 15.3 ± 4.4%, n = 4; mGluR1−/−, 39.4 ± 2.6%, n = 5; t7 = 4.9, P = 0.02). Scale bars represent 25 pA and 10 ms. () Scaled sample traces and time course of decay time for NMDAR-EPSCs in wild-type and mGluR1−/− littermate at P2–6 and P14–26 (P2–6: wild type, τw = 150 ± 6, n = 4; mGluR1−/−, 138 ± 15, n = 5, P > 0.05; P14–26: wild type, τw = 81 ± 7, n = 6; mGluR1−/− 145 ± 31, n = 6; t10 = 2, P < 0.034). Scale bars ! represent 50 pA and 50 ms. () Sample traces and ifenprodil inhibition of NMDAR-EPSCs in mGluR1−/− and wild-type littermates (% of inhibition: mGluR1−/−, 35.4 ± 3.5%; wild type, 13.6 ± 3.9%; t10 = 4.1, P = 0.02, n = 5). Scale bars represent 50 pA and 50 ms. Error bars represent s.e.m. *P < 0.05, **P < 0.01. * Figure 4: mGluR1s control synaptic maturation of AMPA and NMDA receptors. () Effect of 5-min application of DHPG on the amplitude versus time plot and sample traces of AMPAR-EPSCs in slices from P2–6 mice recorded at −60 mV in the presence (open circles) or absence (filled circles) of U73122 (5 μM) applied for at least 20 min before recording (filled circles, 61.5 ± 7.0% of baseline, n = 6; open circles, 91.1 ± 2.4% of baseline, n = 5; t10 = 9, P < 0.0001). Scale bars represent 25 pA and 10 ms. () Sample traces and PhTx-433 inhibition of AMPAR-EPSCs before and after DHPG application (before DHPG, 29.0 ± 4.8%, n = 8; after DHPG, 1.0 ± 4.3%, n = 5; t11 = 4.33, P = 0.0012). Scale bars represent 25 pA and 10 ms. () Effect of DHPG on the amplitude versus time plot and sample traces of NMDAR-EPSCs in slices from P2–6 mice recorded at +40 mV in the presence (open circles) or absence (filled circles) of U73122 (5 μM) applied for at least 20 min (filled circles: 160 ± 20% of baseline, n = 8; open circles: 112.6 ± 3.2% of baseline, n = 5; t10 ! = 9, P < 0.0001). Scale bars represent 50 pA and 50 ms. () Sample traces and ifenprodil inhibition of NMDAR-EPSCs before and after DHPG application at P2–6 (before, 42.5 ± 4.7%, n = 10; after, 13.1 ± 9.1%, n = 6; t14 = 3.17, P = 0.007). Scale bars represent 50 pA and 50 ms. Error bars represent s.e.m. *P < 0.05, **P < 0.01. * Figure 5: In utero cocaine exposure impairs synaptic maturation. () Top, sample traces of AMPAR-EPSCs (−60, 0 and +30 mV) after cocaine and saline injections in utero. Scale bars represent 25 pA and 10 ms. Bottom, rectification index for different age groups after in utero cocaine or saline injections (P2–6: cocaine, 1.87 ± 0.15, n = 12; saline, 1.78 ± 0.23, n = 5; P > 0.05; P14–26: cocaine, 1.71 ± 0.10, n = 17; saline, 1.16 ± 0.20, n = 6; t21 = 2.5, P = 0.02; P30–35: cocaine, 2.1 ± 0.17, n = 7; saline, 1.1 ± 0.2; t10 = 4.5, P = 0.0012, n = 5; P60: cocaine, 1.50 ± 0.13, n = 7; saline, 1.1 ± 0.03, n = 5; t10 = 2.6, P = 0.02; P90: cocaine, 0.96 ± 0.13, n = 6; saline, 1.03 ± 0.14, n = 5; P > 0.05). () Sample traces of AMPAR-EPSCs and bar graph for PhTx-433 inhibition (32.3 ± 3.7% versus 4.9 ± 6.7%, t8 = 3.6, P = 0.007, n = 5). Scale bars represent 50 pA and 10 ms. () Sample traces of NMDAR-EPSCs and bar graph for ifenprodil inhibition (saline, 18 ± 5.5, n = 7; cocaine, 47 ± 10%, n = 8; t13 = 2.4, P = 0.03). Scale bars r! epresent 50 pA and 50 ms. () Sample traces and decay time for NMDAR-EPSCs (τw: cocaine, 127 ± 13, n = 11; saline, 91 ± 6, n = 9; t18 = 2.2, P = 0.04). Scale bars represent 50 pA and 50 ms. Error bars represent s.e.m. *P < 0.05, **P < 0.01. * Figure 6: Cocaine-evoked plasticity and postnatal maturation of AMPARs in DAT-KI mice. () Injection protocol. Heterozygous DAT-KI (Het) male and females were mated and pregnant females injected in utero with cocaine once a day (E11–18). Heterozygous and homozygous DAT-KI (KI) offspring were taken for physiology at P14–26. () Sample traces of AMPAR-EPSCs (−60, 0 and +30 mV) and bar graph of rectification index recorded at P14–26 in heterozygous and homozygous DAT-KI mice born from heterozygous mothers that received cocaine during pregnancy (heterozygous, 1.67 ± 0.17, n = 6; homozygous, 1.19 ± 0.09, n = 9; t13 = 2.7, P = 0.019). Scale bars represent 25 pA and 10 ms. () Sample traces and effect of PhTx-433 (2 μM) on evoked AMPAR-EPSCs in heterozygous and DAT-KI offspring (inhibition: heterozygous, 31.5 ± 6.1%, n = 5; homozygous, 5.2 ± 8.2%, n = 7; t10 = 2.2, P = 0.04). Scale bars represent 25 pA and 10 ms. () Sample traces and effects of ifenprodil (3 μM) on NMDAR-EPSCs recorded at +40 mV (inhibition: heterozygous, 52.6 ± 2.1%; homozygous, 23.5 ± ! 11%; t8 = 2.6, P = 0.03, n = 5). Scale bars represent 100 pA and 50 ms. () Scaled sample traces and decay time for NMDAR-EPSCs (τw: heterozygous, 148 ± 20.3, n = 9; homozygous, 79.3 ± 11.7, n = 7; t14 = 2.7, P = 0.009). Scale bars represent 50 pA and 50 ms. Error bars represent s.e.m. *P < 0.05, **P < 0.01. * Figure 7: Dopamine modulation of mGluR1. () Amplitude versus time plots and sample traces of DHPG effect at −60 mV in utero cocaine and saline-treated animals (cocaine, 52.8 ± 6.6% of baseline, n = 6; saline, 93.6 ± 6.0% of baseline, n = 7; t11 = 4.6, P = 0.0008). Scale bars represent 25 pA and 10 ms. () Amplitude versus time plots and sample traces of DHPG effect on AMPAR-EPSCs recorded at −60 mV in utero cocaine and saline offspring (cocaine, 101.9 ± 6.0% of baseline, n = 8; saline, 66.4 ± 8.5% of baseline, n = 7; t13 = 3.4, P = 0.004). Scale bars represent 25 pA and 10 ms. () Left, representative traces obtained in DA neurons from wild-type mice showing holding current response to DHPG alone (i), in presence of quinpirole bath-applied for 15 min (ii) or in presence of Trp channel blocker SKF96365 bath-applied for >10 min (iii). Right, change in holding current in the presence of DHPG, DHPG + quinpirole or DHPG + SKF96365 (DHPG, 245 ± 31 pA; DHPG + quinpirole, 76.4 ± 12 pA, t8 = 4.97, P = 0.001, n = 5; ! DHPG + SKF96365, 31.3 ± 20 pA, t9 = 5.9, P = 0.0002, n = 6). The time to peak in the presence of DHPG or DHPG + quinpirole is also plotted (DHPG, 2 ± 0.4; DHPG + quinpirole, 3.6 ± 0.4; t7 = 2.7, P = 0.03, n = 5). Scale bars represent 50 pA and 3 min. Error bars represent s.e.m. **P < 0.01, ***P < 0.001. * Figure 8: mGluR1 rescues of cocaine-induced impairment of synaptic maturation. () Injection protocol. Pregnant females were injected once each day with cocaine or saline between E11–18. Offspring were then injected with a single dose of the positive modulator for mGluR1, Ro 67-7476, and killed 1, 5 or 10 d later. () Sample traces of AMPAR-EPSCs and graph of rectification index recorded 1, 5 and 10 d after a single injection of Ro 67-7476 (4 mg per kg of body weight) in P14–26 mice (cocaine group: 1 d saline, 1.63 ± 0.12, n = 6; 1 d Ro 67-7476, 1 ± 0.05, n = 8; 5 d Ro 67-7476, 1.1 ± 0.09, n = 5; 10 d Ro 67-7476, 1.25 ± 0.08, n = 8; F3,23 = 9.3 P = 0.0003, n = 6–8; comparison between in utero cocaine conditions with Dunnett's multiple comparison test, P < 0.05). Scale bars represent 50 pA and 5 ms. () Sample traces and ifenprodil inhibition of NMDAR-EPSCs after a single injection of saline or Ro 67-7476 24 h before death (ifenprodil inhibition: saline, 47.5 ± 6.8%; Ro 67-7476, 24.8 ± 7%; t8 = 2.3, P = 0.04, n = 5). Scale bars represent 50 pA ! and 50 ms. () Scaled sample traces and decay time for NMDAR-EPSCs (τw: saline, 122 ± 8, n = 6; Ro 67-7476, 91 ± 11, n = 9; t13 = 2, P = 0.03). Scale bars represent 50 pA and 50 ms. Error bars represent s.e.m. *P < 0.05, **P < 0.01, ***P < 0.001. Author information * Abstract * Author information * Supplementary information Affiliations * Department of Basic Neurosciences, Medical Faculty, University of Geneva, Geneva, Switzerland. * Camilla Bellone, * Manuel Mameli & * Christian Lüscher * Clinic of Neurology, Department of Clinical Neurosciences, Geneva University Hospital, Geneva, Switzerland. * Christian Lüscher * Present address: Institut du Fer à Moulin, Paris, France. * Manuel Mameli Contributions C.B. carried out the in vitro electrophysiology experiments with the help of M.M., who performed the imaging experiments. C.L. designed the study and wrote the manuscript with the help of the other authors. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Camilla Bellone or * Christian Lüscher Author Details * Camilla Bellone Contact Camilla Bellone Search for this author in: * NPG journals * PubMed * Google Scholar * Manuel Mameli Search for this author in: * NPG journals * PubMed * Google Scholar * Christian Lüscher Contact Christian Lüscher 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 Additional data
• PI3Kγ is required for NMDA receptor–dependent long-term depression and behavioral flexibility
  - Nat Neurosci 14(11):1447-1454 (2011)
  Nature Neuroscience | Article PI3Kγ is required for NMDA receptor–dependent long-term depression and behavioral flexibility * Jae-Ick Kim1, 10 * Hye-Ryeon Lee1, 10 * Su-eon Sim1, 2 * Jinhee Baek1 * Nam-Kyung Yu1 * Jun-Hyeok Choi1 * Hyoung-Gon Ko1 * Yong-Seok Lee1 * Soo-Won Park1 * Chuljung Kwak1 * Sung-Ji Ahn3 * So Yoen Choi4 * Hyun Kim4 * Kyoung-Han Kim5 * Peter H Backx5 * Clarrisa A Bradley2 * Eunjoon Kim6 * Deok-Jin Jang7 * Kyungmin Lee8 * Sang Jeong Kim2, 3 * Min Zhuo2, 5 * Graham L Collingridge2, 9 * Bong-Kiun Kaang1, 2 * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 14,Pages:1447–1454Year published:(2011)DOI:doi:10.1038/nn.2937Received07 July 2011Accepted22 August 2011Published online23 October 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 Phosphatidylinositol 3-kinase (PI3K) has been implicated in synaptic plasticity and other neural functions in the brain. However, the role of individual PI3K isoforms in the brain is unclear. We investigated the role of PI3Kγ in hippocampal-dependent synaptic plasticity and cognitive functions. We found that PI3Kγ has a crucial and specific role in NMDA receptor (NMDAR)-mediated synaptic plasticity at mouse Schaffer collateral–commissural synapses. Both genetic deletion and pharmacological inhibition of PI3Kγ disrupted NMDAR long-term depression (LTD) while leaving other forms of synaptic plasticity intact. Accompanying this physiological deficit, the impairment of NMDAR LTD by PI3Kγ blockade was specifically correlated with deficits in behavioral flexibility. These findings suggest that a specific PI3K isoform, PI3Kγ, is critical for NMDAR LTD and some forms of cognitive function. Thus, individual isoforms of PI3Ks may have distinct roles in different types of synapt! ic plasticity and may therefore influence various kinds of behavior. View full text Figures at a glance * Figure 1: Synaptic and intrinsic properties of CA1 neurons in wild-type and Pik3cg−/− mice. () Input-output relationship in wild-type (WT) and Pik3cg−/− mice (six slices from six mice for wild type; six slices from four mice for Pik3cg−/−). Scale bars represent 150 pA and 20 ms. () Paired-pulse ratio at SC-CA1 synapses (six slices from five mice for wild type; six slices from five mice for Pik3cg−/−). Scale bars represent 100 pA and 20 ms. () Top, recording traces of AMPAR/NMDAR ratio in wild-type and Pik3cg−/− mice (wild type, 143 ± 29%, seven slices from six mice; Pik3cg−/−, 156 ± 18%, seven slices from five mice). Bottom, recording traces of mEPSCs from CA1 neurons in wild-type and Pik3cg−/− mice (wild type: frequency, 1.2 ± 0.3 (Hz); amplitude, 12.2 ± 1.1 (pA); six slices from three mice; Pik3cg−/−: frequency, 0.9 ± 0.2 (Hz); amplitude, 11.6 ± 1.2 (pA); six slices from three mice). Scale bars represent 100 pA and 40 ms for AMPAR/NMDAR ratio, 10 pA and 1.5 s for mEPSCs. () Action potential responses to fixed current injections i! n hippocampal CA1 pyramidal neurons in wild-type and Pik3cg−/− mice (seven slices from six mice for wild type; seven slices from five mice for Pik3cg−/−). Scale bars represent 40 mV and 200 ms. Error bars represent mean ± s.e.m. * Figure 2: NMDAR LTD is absent in Pik3cg−/− mice. () NMDAR LTD at SC-CA1 synapses in wild-type and Pik3cg−/− mice (wild type, 83 ± 2%, 13 slices from eight mice; Pik3cg−/−, 96 ± 5%, 11 slices from nine mice; P < 0.05). () NMDAR LTD from whole-cell recording in wild-type and Pik3cg−/− mice (wild type, 76 ± 4%, six slices from four mice; Pik3cg−/−, 109 ± 7%, five slices from four mice; P < 0.01). () mGluR LTD in wild-type and Pik3cg−/− mice (wild type, 75 ± 4%, eight slices from six mice; Pik3cg−/−, 79 ± 4%, eight slices from five mice). () Depotentiation in wild-type and Pik3cg−/− mice (wild type, 111 ± 3%, five slices from three mice; Pik3cg−/−, 105 ± 2%, three slices from two mice). () LTP in wild-type and Pik3cg−/− mice (wild type, 133 ± 4%, six slices from two mice; Pik3cg−/−, 130 ± 2%, seven slices from two mice). Scale bars depict 1 mV and 30 ms for slice field recording, 100 pA and 40 ms for whole-cell recording. Statistical analysis between two groups was performed by! comparing the average amplitude of responses over a 5-min period (75–80 min for field recording, 50–55 min for whole-cell recording). Statistical significance was determined using two-tailed unpaired Student's t test. * Figure 3: NMDAR LTD is blocked by pharmacological inhibition of PI3Kγ. () The effect of AS-605240 on NMDAR LTD (vehicle, 89 ± 5%, eight slices from six mice; AS-605240, 104 ± 2%, ten slices from five mice; P < 0.05). () NMDAR LTD with AS-605240 at single neuronal level (vehicle, 70 ± 8%, eight slices from seven mice; AS-605240, 101 ± 3%, seven slices from six mice; P < 0.01). () mGluR LTD with AS-605240 (vehicle, 79 ± 5%, six slices from four mice; AS-605240, 87 ± 2%, four slices from three mice). () Depotentiation with AS-605240 (vehicle, 107 ± 3%, six slices from three mice; AS-605240, 108 ± 5%, five slices from three mice). () The effect of AS-605240 on LTP (vehicle, 145 ± 9%, nine slices from five mice; AS-605240, 129 ± 6%, seven slices from six mice). () Application of AS-605240 during induction phase of LTD (vehicle, 71 ± 13%, seven slices from seven mice; AS-605240, 107 ± 6%, six slices from six mice; P < 0.05). () Treatment of AS-605240 after LFS (vehicle, 73 ± 7%, six slices from five mice; AS-605240, 73 ± 9%, five slices! from four mice). () Postsynaptic infusion of AS-605240 during NMDAR LTD (vehicle, 71 ± 9%, seven slices from seven mice; AS-605240, 105 ± 9%, seven slices from six mice; P < 0.05). Scale bars depict 1 mV and 30 ms for slice field recording, and 100 pA and 40 ms for whole-cell recording. * Figure 4: Specificity of PI3Kγ in the induction of NMDAR LTD. () Effects of LY294002 on NMDAR LTD (70 ± 7%, 12 slices from ten mice). () Effects of the class IA PI3Kα inhibitor on NMDAR LTD (61 ± 5%, nine slices from eight mice). () Control experiments with vehicle treatment (64 ± 4%, 12 slices from ten mice). () Summary graph and statistical analysis among different inhibitors groups (F2,30 = 0.65, P > 0.5, one-way ANOVA). () Two-pathway LTD experiment at SC-CA1 synapses with AS-605240 (control pathway, 97 ± 5%; conditioned pathway, 105 ± 10%; four slices from four mice). () Two-pathway LTD experiment at SC-CA1 synapses with class IA PI3Kα inhibitor (control pathway, 84 ± 6%; conditioned pathway, 69 ± 5%; six slices from five mice). Scale bars represent 100 pA and 40 ms. Error bars represent mean ± s.e.m. * Figure 5: Recovery of NMDAR LTD impairment in Pik3cg−/− mice. () The effect of wild-type mouse p110γ administration through a recording pipette into CA1 pyramidal neurons on the impairment of NMDAR LTD in Pik3cg−/− mice (wild type, 71 ± 3%, five slices from four mice; Pik3cg−/−, 102 ± 2%, four slices from three mice; Pik3cg−/− with wild-type p110γ, 76 ± 5%, seven slices from four mice; Pik3cg−/− with heat-inactivated (HI) p110γ, 105 ± 5%, four slices from two mice). () Summary graph and statistical analysis among the groups (F3,16 = 12.65, P < 0.001, one-way ANOVA with Tukey's multiple comparison test; wild type versus Pik3cg−/−, P < 0.01; wild type versus Pik3cg−/− with heat-inactivated p110γ, P < 0.01; Pik3cg−/− versus Pik3cg−/− with wild-type p110γ, P < 0.01; Pik3cg−/− with wild-type p110γ versus Pik3cg−/− with HI p110γ, P < 0.05). *P < 0.05, **P < 0.01. Error bars represent mean ± s.e.m. * Figure 6: Signaling mechanisms involved in PI3Kγ-mediated NMDAR LTD. () A representative sample of western blottings of GSK-3β phosphorylation on Ser9 and Akt phosphorylation on Thr308 by NMDAR activation in wild-type and Pik3cg−/− mice. () Quantifications of GSK-3β and Akt phosphorylation by NMDAR activation (phosphorylated divided by total) in wild-type and Pik3cg−/− mice (GSK-3β, n = 3 per group, the effect of NMDA, F1,8 = 54.26, P < 0.001, two-way ANOVA; Akt, n = 3 per group, the effect of NMDA, F1,8 = 5.29, P > 0.05, two-way ANOVA). () A representative sample of western blots of p38 MAPK phosphorylation without NMDA (0 min) and with NMDA (100 μM) treatment for 2 min, 5 min and 10 min in hippocampal slices of wild-type and Pik3cg−/− mice. () Quantification of p38 MAPK activation (phospho-p38 divided by total p38; n = 6 per group, the effect of genotype, F1,40 = 7.07, P < 0.05, two-way ANOVA). * Figure 7: Behavioral flexibility is reduced in Pik3cg−/− mice. () Average escape time traveled to the platform (mean ± s.e.m.) in the Morris water maze (n = 11 for Pik3cg−/−, n = 14 for wild type, the effect of genotype, F1,23 = 1.89, P > 0.2, repeated-measures two-way ANOVA). () Averages ± s.e.m. for the percentage of time spent in the initial training quadrant (TQ; 57 ± 10% for Pik3cg−/−, 49 ± 9% for wild type, P > 0.05), the opposite quadrant (OQ) and two adjacent quadrants (AQ) during probe trials given on day 6 of the experiment. () Averages ± s.e.m. for the percentage for time spent in the new training quadrant (TQ; 39 ± 16% for Pik3cg−/−, 39 ± 8% for wild type, P > 0.9), the previous training quadrant (PQ; 24 ± 4% for Pik3cg−/−, 15 ± 2% for wild type, P < 0.05) and the two adjacent quadrants (AQ) during probe trials given on day 9 of the experiment. () Average number of correct choices (mean ± s.e.m.) from wild-type and Pik3cg−/− mice in delayed nonmatch to place T-maze task (n = 8 for Pik3cg−/−,! n = 7 for wild type, the effect of genotype, F1,13 = 6.55, P < 0.05, repeated-measures two-way ANOVA). Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Jae-Ick Kim & * Hye-Ryeon Lee Affiliations * National Creative Research Initiative Center for Memory, Department of Biological Sciences, College of Natural Sciences, Seoul National University, Seoul, Korea. * Jae-Ick Kim, * Hye-Ryeon Lee, * Su-eon Sim, * Jinhee Baek, * Nam-Kyung Yu, * Jun-Hyeok Choi, * Hyoung-Gon Ko, * Yong-Seok Lee, * Soo-Won Park, * Chuljung Kwak & * Bong-Kiun Kaang * Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, Korea. * Su-eon Sim, * Clarrisa A Bradley, * Sang Jeong Kim, * Min Zhuo, * Graham L Collingridge & * Bong-Kiun Kaang * Department of Physiology, Seoul National University College of Medicine, Seoul, Korea. * Sung-Ji Ahn & * Sang Jeong Kim * Department of Anatomy, College of Medicine, Korea University, Seoul, Korea. * So Yoen Choi & * Hyun Kim * Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada. * Kyoung-Han Kim, * Peter H Backx & * Min Zhuo * National Creative Research Initiative Center for Synaptogenesis, Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, Korea. * Eunjoon Kim * Department of Applied Biology, College of Ecology and Environment, Kyungpook National University, Sangju-si, Kyeongbuk, Korea. * Deok-Jin Jang * Department of Anatomy, School of Medicine, Kyungpook National University, Daegu, Korea. * Kyungmin Lee * MRC Center for Synaptic Plasticity, School of Physiology and Pharmacology, Bristol, UK. * Graham L Collingridge Contributions J.-I.K. and H.-R.L. designed, performed and analyzed most of the electrophysiology and behavioral experiments, and wrote the manuscript. S.S., J.B., N.-K.Y., J.-H.C., H.-G.K., Y.-S.L., S.-W.P., C.K., S.-J.A., S.Y.C., H.K., K.-H.K., D.-J.J., K.L. and S.J.K. conducted the biochemical, electrophysiological and behavioral studies. Y.-S.L., P.H.B., C.A.B., D.-J.J., K.L., E.K., M.Z. and G.L.C. aided in the interpretation of data and contributed to editing the manuscript. B.-K.K. supervised the project, designed the experiments and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Bong-Kiun Kaang Author Details * Jae-Ick Kim Search for this author in: * NPG journals * PubMed * Google Scholar * Hye-Ryeon Lee Search for this author in: * NPG journals * PubMed * Google Scholar * Su-eon Sim Search for this author in: * NPG journals * PubMed * Google Scholar * Jinhee Baek Search for this author in: * NPG journals * PubMed * Google Scholar * Nam-Kyung Yu Search for this author in: * NPG journals * PubMed * Google Scholar * Jun-Hyeok Choi Search for this author in: * NPG journals * PubMed * Google Scholar * Hyoung-Gon Ko Search for this author in: * NPG journals * PubMed * Google Scholar * Yong-Seok Lee Search for this author in: * NPG journals * PubMed * Google Scholar * Soo-Won Park Search for this author in: * NPG journals * PubMed * Google Scholar * Chuljung Kwak Search for this author in: * NPG journals * PubMed * Google Scholar * Sung-Ji Ahn Search for this author in: * NPG journals * PubMed * Google Scholar * So Yoen Choi Search for this author in: * NPG journals * PubMed * Google Scholar * Hyun Kim Search for this author in: * NPG journals * PubMed * Google Scholar * Kyoung-Han Kim Search for this author in: * NPG journals * PubMed * Google Scholar * Peter H Backx Search for this author in: * NPG journals * PubMed * Google Scholar * Clarrisa A Bradley Search for this author in: * NPG journals * PubMed * Google Scholar * Eunjoon Kim Search for this author in: * NPG journals * PubMed * Google Scholar * Deok-Jin Jang Search for this author in: * NPG journals * PubMed * Google Scholar * Kyungmin Lee Search for this author in: * NPG journals * PubMed * Google Scholar * Sang Jeong Kim Search for this author in: * NPG journals * PubMed * Google Scholar * Min Zhuo Search for this author in: * NPG journals * PubMed * Google Scholar * Graham L Collingridge Search for this author in: * NPG journals * PubMed * Google Scholar * Bong-Kiun Kaang Contact Bong-Kiun Kaang Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (9M) Supplementary Figures 1–7 Additional data
• Neural activity at the human olfactory epithelium reflects olfactory perception
  - Nat Neurosci 14(11):1455-1461 (2011)
  Nature Neuroscience | Article Neural activity at the human olfactory epithelium reflects olfactory perception * Hadas Lapid1, 2 * Sagit Shushan1, 3 * Anton Plotkin1 * Hillary Voet4 * Yehudah Roth3 * Thomas Hummel5 * Elad Schneidman1 * Noam Sobel1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature NeuroscienceVolume: 14,Pages:1455–1461Year published:(2011)DOI:doi:10.1038/nn.2926Received10 March 2011Accepted04 August 2011Published online25 September 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 Organization of receptive surfaces reflects primary axes of perception. In vision, retinal coordinates reflect spatial coordinates. In audition, cochlear coordinates reflect tonal coordinates. However, the rules underlying the organization of the olfactory receptive surface are unknown. To test the hypothesis that organization of the olfactory epithelium reflects olfactory perception, we inserted an electrode into the human olfactory epithelium to directly measure odorant-induced evoked responses. We found that pairwise differences in odorant pleasantness predicted pairwise differences in response magnitude; that is, a location that responded maximally to a pleasant odorant was likely to respond strongly to other pleasant odorants, and a location that responded maximally to an unpleasant odorant was likely to respond strongly to other unpleasant odorants. Moreover, the extent of an individual's perceptual span predicted their span in evoked response. This suggests that, simi! larly to receptor surfaces for vision and audition, organization of the olfactory receptor surface reflects key axes of perception. View full text Figures at a glance * Figure 1: Experimental scheme. () Experimental setup. Subject was positioned in the non-invasive stereotactic device. The EOG electrode (fixed with holding bar in front of the nose) and heated olfactometer tube were inserted into the left nostril. EOG reference electrodes were placed on the nasal bone and left earlobe. Eye motion was recorded from above the left supraorbital area. () Sagittal section of the human nasal cavity, including the inferior, middle and superior turbinates. The approximate boundaries of the olfactory epithelium are marked in purple and the boundaries from which EOG recordings were obtained are overlaid in dark blue. () Endoscopic view of an EOG recording in a right nostril. On the right is the septum, and the shiny body is the middle turbinate, onto which the EOG electrode was nestled. () Three sets of six odorants spanning the first and second principal physicochemical axes. Black dots are 2,993 modeled odorants. Green triangles indicate the first set (n = 12), blue squares indic! ate the second set (n = 16) and red circles indicate the third set (n = 13). The odorants are plotted against a dataset of 2,993 odorants. For odorant specifications, see Table 1. () ORN collision count. Based on the birthday problem in probability theory, we calculated the expected number of different receptor subtypes expressed in increasing sample populations of ORNs given a random uniform distribution. At ~2,000 neurons, we reached the maximal number of different receptor subtypes with a probability of 95%. () Average EOGs from 16 subjects (thin lines), as well as grand average (thick lines) for the odorants vanillin (Van, black) and ammonium sulfide (AmS, red). Inlay is AUC and error bars represent within-subject sum of squares between conditions. * Figure 2: Different localizer odorants revealed different epithelial response profiles. (–) Experiment 1. () Each subject's normalized AUC. Odorants are color-coded and numbered according to set 1 of Table 1. () Grand averaged EOG responses (n = 16, stimulus duration = 500 ms). Black square-wave reflects odorant onset/offset. () Number of times each of the six odorants elicited the maximal EOG AUC. (–) Experiment 2. () Subject-normalized AUC with odorant 3 as localizer. () Subject-normalized AUC with odorant 1 as localizer. () Subject normalized AUC with odorant 5 as localizer. () Averaged EOGs obtained in three recording sessions (–) from different locations in a single subject. Black square-wave reflects odorant onset/offset. Error bars are s.e.m., au are arbitrary units. * Figure 3: A common localizer odorant revealed common epithelial response profiles. () Experiment 3, each subject's normalized AUC. Odorants are color coded, and numbered according to set 2 of Table 1. () Grand averaged EOG responses (n = 12, stimulus duration = 500 ms). Black square-wave reflects odorant onset/offset. () Number of times each of the six odorants elicited the maximal EOG AUC. In 10 of 12 subjects, the maximal response was for the odorant used to localize the recording site. Error bars are s.e.m., au are arbitrary units. * Figure 4: An external common localizer odorant revealed a bimodal epithelial response profile. Experiment 4: EOG recordings conducted after searching for responsive locations with L-carvone. () Each subject's normalized AUC. Odorants are color coded, and numbered according to set 3 of Table 1. () Grand averaged EOG responses (n = 13, stimulus duration = 500 ms). Black square-wave reflects odorant onset/offset. () Number of times each of the six odorants elicited the maximal EOG AUC. Error bars are s.e.m., au are arbitrary units. * Figure 5: EOGs were unrelated to odorant sorption. () Relation between the optimized sorption metric (see Online Methods) and the actual mucosal retention times reported in the bullfrog15. Each point is a pairwise odorant comparison. () Relation between this same optimized sorption metric and EOG distances measured here. Each point is the mean odorant pairwise distance per odorant pair per subject; that is, points = n × 5. No relation is evident. Note, however, that the model is bound by the limited physicochemical span of the bullfrog experiment odorant selection, as evident in the restricted x-axis span in . au are arbitrary units. * Figure 6: EOGs were tuned to olfactory perception. In , and , each point is the mean odorant pairwise distance per odorant pair per subject; that is, points = n × 5. In , each point is a subject. () Correlation between pleasantness distances and EOG distances (n = 32). () Correlation between chemical Euclidean distance and EOG distance (n = 32). () Correlation between pleasantness span and EOG span (n = 41). () Correlation between EOG distance and pleasantness distance for the subjects with largest EOG span (n = 16). au are arbitrary units. Author information * Abstract * Author information * Supplementary information Affiliations * Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel. * Hadas Lapid, * Sagit Shushan, * Anton Plotkin, * Elad Schneidman & * Noam Sobel * Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel. * Hadas Lapid * Department of Otolaryngology-Head and Neck Surgery, Edith Wolfson Medical Center, Tel-Aviv University Sackler School of Medicine, Holon, Israel. * Sagit Shushan & * Yehudah Roth * Robert H. Smith Faculty of Agriculture, Food and Environment, Hebrew University of Jerusalem, Rehovot, Israel. * Hillary Voet * Smell and Taste Clinic, University of Dresden Medical School, Dresden, Germany. * Thomas Hummel Contributions H.L. and N.S. conceived the study. H.L., S.S., A.P., T.H., Y.R. and N.S. designed the experiments. H.L., S.S. and A.P. performed the experiments. H.L., E.S., H.V. and N.S. analyzed the data. H.L., T.H., E.S. and N.S. wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Hadas Lapid or * Noam Sobel Author Details * Hadas Lapid Contact Hadas Lapid Search for this author in: * NPG journals * PubMed * Google Scholar * Sagit Shushan Search for this author in: * NPG journals * PubMed * Google Scholar * Anton Plotkin Search for this author in: * NPG journals * PubMed * Google Scholar * Hillary Voet Search for this author in: * NPG journals * PubMed * Google Scholar * Yehudah Roth Search for this author in: * NPG journals * PubMed * Google Scholar * Thomas Hummel Search for this author in: * NPG journals * PubMed * Google Scholar * Elad Schneidman Search for this author in: * NPG journals * PubMed * Google Scholar * Noam Sobel Contact Noam Sobel Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (209K) Supplementary Figures 1 and 2, and Supplementary Tables 1–3 Additional data
• Subthalamic nucleus stimulation reverses mediofrontal influence over decision threshold
  - Nat Neurosci 14(11):1462-1467 (2011)
  Nature Neuroscience | Article Subthalamic nucleus stimulation reverses mediofrontal influence over decision threshold * James F Cavanagh1 * Thomas V Wiecki1 * Michael X Cohen2, 3 * Christina M Figueroa1 * Johan Samanta4, 5 * Scott J Sherman4 * Michael J Frank1, 6, 7 * Affiliations * Contributions * Corresponding authorsJournal name:Nature NeuroscienceVolume: 14,Pages:1462–1467Year published:(2011)DOI:doi:10.1038/nn.2925Received07 June 2011Accepted02 August 2011Published online25 September 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 takes effort and time to tame one's impulses. Although medial prefrontal cortex (mPFC) is broadly implicated in effortful control over behavior, the subthalamic nucleus (STN) is specifically thought to contribute by acting as a brake on cortico-striatal function during decision conflict, buying time until the right decision can be made. Using the drift diffusion model of decision making, we found that trial-to-trial increases in mPFC activity (EEG theta power, 4–8 Hz) were related to an increased threshold for evidence accumulation (decision threshold) as a function of conflict. Deep brain stimulation of the STN in individuals with Parkinson's disease reversed this relationship, resulting in impulsive choice. In addition, intracranial recordings of the STN area revealed increased activity (2.5–5 Hz) during these same high-conflict decisions. Activity in these slow frequency bands may reflect a neural substrate for cortico–basal ganglia communication regulating decis! ion processes. View full text Figures at a glance * Figure 1: Theoretical model, task and performance. () Proposed model of mPFC-STN gating of decision threshold. Action plans are gated in a cortico-striatal loop (dashed line). In the presence of mPFC-detected conflict, the STN inhibits behavioral output by raising the threshold required for the striatum to gate action plans. This results in conflict-varying response times (solid lines). DBS to the STN interrupts this process, resulting in a disruption of the ability of mPFC to regulate control. RT, response time. () Task dynamics. During training, participants learned to choose one item in each pair (termed A/B and C/D) that was reinforced more often (A/B, 100%/0%; C/D, 75%/25%). In this example, the butterfly might be A and the piano might be B. During testing, participants had to choose the better stimulus, leading to high-conflict choices for win-win (A/C) and lose-lose (B/D) as well as low-conflict choices (A/D, C/B). For example, if the cake was C in training, this would reflect a high-conflict win-win cue. () Study I p! erformance data (mean ± s.e.m.). () Study I conflict adaptation split by accuracy (mean ± s.e.m.). Suboptimal trials were relatively speeded compared with correct trials ON (but not OFF) DBS (**P < 0.01). * Figure 2: DBS ON/OFF study: scalp EEG (FCz electrode) from the test phase split by high and low conflict. () Stimulus presentation and response commission were characterized by notable beta power suppression and theta power enhancement compared with baseline in both ON and OFF conditions, which were combined here. () Topoplots of the high-low conflict difference in standardized regression (β) weights for cue-locked theta power and response time (±0.1 std β). The FCz site is indicated on the control topoplot. () Standardized regression (β) weights (mean ± s.e.m.) for cue-locked theta power and response time, demonstrating that DBS reversed a natural coupling of theta band power with response time slowing on high-conflict trials. * Figure 3: DBS ON/OFF study: Bayesian posterior densities of decision thresholds estimated from the drift diffusion model (ordinates) and how they varied as a function of mPFC theta (abcissa). Peaks of the distributions reflect the most likely value of the parameter. Significance was assessed by at least 95% of the distribution being to the left or right of zero. () Simple effects of theta. OFF DBS, increased theta was associated with increased decision threshold for high-conflict trials, but not low-conflict trials. ON DBS, increased theta was associated with a decreased decision threshold on high-conflict trials, but not low-conflict trials. () Theta × conflict interaction. Increases in theta resulting from high > low conflict were associated with increases in threshold OFF DBS and in healthy controls. The opposite pattern was seen ON DBS. () These threshold effects are reflected by changes in response time distributions. These plots show the best fit response time distributions for optimal and suboptimal choices as a function of low and high mPFC theta/threshold in affected individuals in OFF DBS sessions. Higher theta power is associated with a reduction in t! he density of fast suboptimal choices and greater dispersion of optimal response time distributions, fitting with an account of increased threshold. * Figure 4: Intracranial EEG from the STN for dorsal, middle and ventral leads. Both beta suppression and theta enhancement were observed in the STN. The rightmost columns show the condition-wide differences revealed by permutation testing. High-conflict trials were characterized by a diminishment of low-frequency power across leads, greater post-cue activity in the dorsal lead and greater post-response activity across leads. The bottom row shows intracranial EEG data filtered from 2.5–4.5 Hz. Author information * Abstract * Author information * Supplementary information Affiliations * Department of Cognitive, Linguistic and Psychological Sciences, Brown University, Providence, Rhode Island, USA. * James F Cavanagh, * Thomas V Wiecki, * Christina M Figueroa & * Michael J Frank * Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands. * Michael X Cohen * Department of Physiology, University of Arizona, Tucson, Arizona, USA. * Michael X Cohen * Department of Neurology, University of Arizona, Tucson, Arizona, USA. * Johan Samanta & * Scott J Sherman * Banner Good Samaritan Medical Center, Phoenix, Arizona, USA. * Johan Samanta * Department of Psychiatry, Brown University, Providence, Rhode Island, USA. * Michael J Frank * Brown Institute for Brain Science, Providence, Rhode Island, USA. * Michael J Frank Contributions M.J.F., J.F.C. and M.X C. designed the experiments. J.F.C., C.M.F., J.S. and S.J.S. recruited and ran participants. J.F.C. and M.X C. processed the EEG data. T.V.W. and M.J.F. designed the computational models. J.F.C. and M.J.F. wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * James F Cavanagh or * Michael J Frank Author Details * James F Cavanagh Contact James F Cavanagh Search for this author in: * NPG journals * PubMed * Google Scholar * Thomas V Wiecki Search for this author in: * NPG journals * PubMed * Google Scholar * Michael X Cohen Search for this author in: * NPG journals * PubMed * Google Scholar * Christina M Figueroa Search for this author in: * NPG journals * PubMed * Google Scholar * Johan Samanta Search for this author in: * NPG journals * PubMed * Google Scholar * Scott J Sherman Search for this author in: * NPG journals * PubMed * Google Scholar * Michael J Frank Contact Michael J Frank Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (598K) Supplementary Figures 1–7, Supplementary Tables 1–5, Supplementary Results and Supplementary Discussion Additional data
• Dorsolateral and ventromedial prefrontal cortex orchestrate normative choice
  - Nat Neurosci 14(11):1468-1474 (2011)
  Nature Neuroscience | Article Dorsolateral and ventromedial prefrontal cortex orchestrate normative choice * Thomas Baumgartner1, 2, 4 * Daria Knoch2, 4 * Philine Hotz1 * Christoph Eisenegger1, 3 * Ernst Fehr1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature NeuroscienceVolume: 14,Pages:1468–1474Year published:(2011)DOI:doi:10.1038/nn.2933Received11 July 2011Accepted08 August 2011Published online02 October 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 Humans are noted for their capacity to over-ride self-interest in favor of normatively valued goals. We examined the neural circuitry that is causally involved in normative, fairness-related decisions by generating a temporarily diminished capacity for costly normative behavior, a 'deviant' case, through non-invasive brain stimulation (repetitive transcranial magnetic stimulation) and compared normal subjects' functional magnetic resonance imaging signals with those of the deviant subjects. When fairness and economic self-interest were in conflict, normal subjects (who make costly normative decisions at a much higher frequency) displayed significantly higher activity in, and connectivity between, the right dorsolateral prefrontal cortex (DLPFC) and the posterior ventromedial prefrontal cortex (pVMPFC). In contrast, when there was no conflict between fairness and economic self-interest, both types of subjects displayed identical neural patterns and behaved identically. These ! findings suggest that a parsimonious prefrontal network, the activation of right DLPFC and pVMPFC, and the connectivity between them, facilitates subjects' willingness to incur the cost of normative decisions. View full text Figures at a glance * Figure 1: Rejection rates. Rejection rates (means ± s.e.m.) across treatment groups, broken down for unfair (offer 4 and 6) and fair offers (offer 8 and 10). Subjects whose right DLPFC was stimulated with rTMS exhibited a much lower average rejection rate (29.2%) for the two unfair offers of 4 and 6 than those subjects whose left DLPFC was stimulated (57.3%) (independent t test for offers of 4 and 6, t30 = 2.56, P = 0.016, two-tailed). * Figure 2: Differential group activation in the right DLPFC: left TMS (unfair > fair) > right TMS (unfair > fair). () Disrupting the right DLPFC with rTMS led to a differential group activation pattern in the disrupted right DLPFC (x = 45, y = 24, z = 21, P < 0.005, uncorrected42, cluster extent threshold = 15 voxels; activity in the DLPFC survived small volume family-wise error (FWE) corrections at P < 0.05 in a 20-mm sphere defined by the peak reported in ref. 8; see Online Methods), which was qualified by increased activation in the left TMS group compared with the right TMS group during unfair offers. No such differential group activation was observed in the left DLPFC even at a strongly lowered threshold of P < 0.20 (uncorrected). () Bar plots represent differences (mean ± s.e.m.) in contrast estimates (unfair offers > fair offers) of homologs spherical regions of interest (ROIs) (5 mm) in the bilateral DLPFC around the peak coordinate of activation depicted in (for the left side, the x coordinate was mirrored), broken down for the treatment groups (left TMS/right TMS). Bar plots i! ndicate that a differential activation across right and left TMS group was only observed in the right DLPFC. * Figure 3: Differential group activation in pVMPFC: left TMS (unfair > fair) > right TMS (unfair > fair). () Disrupting the right DLPFC with rTMS changed neural activity not only in the disrupted brain area (depicted in Fig. 2), but also in another task-related remote brain region located in the pVMPFC (x = −3, y = 39, z = −9, thresholded at P < 0.005, uncorrected42, cluster extent threshold = 15 voxels; activity in the pVMPFC survived small volume FWE corrections at P < 0.05 in a 20-mm sphere defined based on peaks in refs. 25,26,27,29,30; see Online Methods). () Bar plots represent differences (mean ± s.e.m.) in contrast estimates (unfair offers > fair offers) of a functional ROI based on the depicted activation, broken down for the two treatment groups (left TMS/right TMS). Bar plots indicate that only the left TMS group reacted to unfairness with increased activity (at P < 0.005) in the pVMPFC. * Figure 4: Treatment group differences in connectivity between right DLPFC and pVMPFC. () Overlay of the pVMPFC cluster that showed a larger change in connectivity after unfair offers (compared with fair offers) with the right DLPFC in the left compared with the right TMS group (yellow, at P < 0.005, cluster extent = 18 voxels42) and the pVMPFC cluster that showed differential activation in the contrast unfair > fair offers in the left compared with the right TMS group (red). Overlapping voxels are displayed in orange. () Bar plots based on the functional ROI (red) from indicate that the differential context-dependent change in connectivity between the left and right TMS group was qualified by a differential change in connectivity during unfair offers (unfair connectivity), but not during fair offers (fair connectivity). The left TMS group therefore only showed an increased connectivity between the right DLPFC and pVMPFC at P < 0.01 during unfair offers, whereas the connectivity between these two brain regions did not change (relative to baseline connectivity)! after fair offers. Moreover, after right TMS, the connectivity between right DLPFC and pVMPFC never deviated from the baseline (indicated by the two black bars); that is, these brain regions no longer communicated more after unfair offers. Bar plots depict mean ± s.e.m. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Thomas Baumgartner & * Daria Knoch Affiliations * Department of Economics, Laboratory for Social and Neural Systems Research, University of Zurich, Zurich, Switzerland. * Thomas Baumgartner, * Philine Hotz, * Christoph Eisenegger & * Ernst Fehr * Department of Psychology, Laboratory for Social and Affective Neuroscience, University of Basel, Basel, Switzerland. * Thomas Baumgartner & * Daria Knoch * Behavioral and Clinical Neuroscience Institute, Department of Experimental Psychology, University of Cambridge, Cambridge, UK. * Christoph Eisenegger Contributions T.B., D.K. and E.F. designed the study. T.B., D.K. and C.E. performed all of the experiments. T.B. and P.H. analyzed the data. T.B., D.K. and E.F. wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Thomas Baumgartner or * Daria Knoch or * Ernst Fehr Author Details * Thomas Baumgartner Contact Thomas Baumgartner Search for this author in: * NPG journals * PubMed * Google Scholar * Daria Knoch Contact Daria Knoch Search for this author in: * NPG journals * PubMed * Google Scholar * Philine Hotz Search for this author in: * NPG journals * PubMed * Google Scholar * Christoph Eisenegger Search for this author in: * NPG journals * PubMed * Google Scholar * Ernst Fehr Contact Ernst Fehr 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 1–7, Supplementary Tables 1–3, Supplementary Analysis 1 and 2, and Supplementary Discussion Additional data
• How unrealistic optimism is maintained in the face of reality
  - Nat Neurosci 14(11):1475-1479 (2011)
  Nature Neuroscience | Article How unrealistic optimism is maintained in the face of reality * Tali Sharot1, 4 * Christoph W Korn2, 3, 4 * Raymond J Dolan1 * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 14,Pages:1475–1479Year published:(2011)DOI:doi:10.1038/nn.2949Received20 June 2011Accepted07 September 2011Published online09 October 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 Unrealistic optimism is a pervasive human trait that influences domains ranging from personal relationships to politics and finance. How people maintain unrealistic optimism, despite frequently encountering information that challenges those biased beliefs, is unknown. We examined this question and found a marked asymmetry in belief updating. Participants updated their beliefs more in response to information that was better than expected than to information that was worse. This selectivity was mediated by a relative failure to code for errors that should reduce optimism. Distinct regions of the prefrontal cortex tracked estimation errors when those called for positive update, both in individuals who scored high and low on trait optimism. However, highly optimistic individuals exhibited reduced tracking of estimation errors that called for negative update in right inferior prefrontal gyrus. These findings indicate that optimism is tied to a selective update failure and diminis! hed neural coding of undesirable information regarding the future. View full text Figures at a glance * Figure 1: Task design. () On each trial, participants were presented with a short description of 1 of 80 adverse life events and asked to estimate how likely this event was to occur to them. They were then presented with the average probability of that event occurring to a person similar to themselves, living in the same socio-cultural environment. For each event, an estimation error term was calculated as the difference between the participant's estimation and the information provided. The second session was the same as the first session. For each event, an update term was calculated as the difference between the participant's first and second estimations. (,) Examples of trials for which the participant's estimate was higher () or lower () than the average probability. Here, for illustration purposes, the blue and red frames denote the participant's response (either an overestimation or underestimation, respectively). The blue and red text denote information that calls for an adjustment in an op! timistic (desirable, ) or pessimistic (undesirable, ) direction, respectively. * Figure 2: Behaviorally observed bias. () After receiving (desirable) information that presented an opportunity to adopt a more optimistic outlook, participants updated their estimations to a greater extent than after receiving (undesirable) information that called for a more pessimistic estimate. This asymmetric updates was observed in 15 out of 19 participants. For group means, see Supplementary Figure 1a. () Betas indicating the association between updates and estimation errors on an individual basis revealed that estimation errors predicted updates to a greater extent when participants received desirable information than when they received undesirable information. This asymmetry was observed in all 19 participants. For group means, see Supplementary Figure 1d. * Figure 3: Brain activity tracking estimation errors. (,) Regions in which BOLD signal tracked participants' estimation errors on a trial by trial basis in response to desirable information regarding future likelihoods included the left IFG () and bilateral MFC/SFG () (P < 0.05, cluster level corrected). () BOLD signal tracking participants' estimation errors in response to undesirable information was found in the right IFG/precentral gyrus (P < 0.05, cluster level corrected). () Parameter estimates of the parametric regressors in both the left IFG and bilateral MFC/SFG did not differ between individuals with high or low scores on trait optimism. In contrast, in the right IFG, a stronger correlation between BOLD activity and undesirable errors was found for individuals with low scores on trait optimism relative to those with high scores. Error bars represent s.e.m. *P < 0.05, two-tailed independent sample t test. * Figure 4: Optimism and brain activity tracking undesirable estimation errors. () Across individuals, the extent of the update bias (difference in update in response to desirable errors minus undesirable errors) correlated with how strong the peak voxel in the right IFG ROI correlated with undesirable errors (r12 = 0.45). Participants showing the greatest optimistic bias in updating showed the weakest tracking of undesirable estimation errors. () Participants who updated their estimates more in response to undesirable information showed a greater reduction in activity in the right IFG ROI the second time desirable information was presented relative to the first time the information was presented (r = −0.47). Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Tali Sharot & * Christoph W Korn Affiliations * Wellcome Trust Centre for Neuroimaging, University College London, London, UK. * Tali Sharot & * Raymond J Dolan * Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany. * Christoph W Korn * School of Mind and Brain, Humboldt Universität zu Berlin, Berlin, Germany. * Christoph W Korn Contributions T.S. conceived the study. T.S. and C.W.K. designed the study, developed stimuli, and gathered and analyzed behavioral and fMRI data. T.S., C.W.K. and R.J.D. interpreted the data and wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Tali Sharot Author Details * Tali Sharot Contact Tali Sharot Search for this author in: * NPG journals * PubMed * Google Scholar * Christoph W Korn Search for this author in: * NPG journals * PubMed * Google Scholar * Raymond J Dolan Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (401K) Supplementary Results, Supplementary Table 1, Supplementary Figure 1, List of Stimuli, and Behavioral Studies 1 and 2 Additional data
• Scale: a chemical approach for fluorescence imaging and reconstruction of transparent mouse brain
  - Nat Neurosci 14(11):1481-1488 (2011)
  Nature Neuroscience | Technical Report Scale: a chemical approach for fluorescence imaging and reconstruction of transparent mouse brain * Hiroshi Hama1 * Hiroshi Kurokawa1, 2 * Hiroyuki Kawano1, 3 * Ryoko Ando1 * Tomomi Shimogori1 * Hisayori Noda1, 4 * Kiyoko Fukami2 * Asako Sakaue-Sawano1, 3 * Atsushi Miyawaki1, 3 * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 14,Pages:1481–1488Year published:(2011)DOI:doi:10.1038/nn.2928Received21 March 2011Accepted12 August 2011Published online30 August 2011Corrected online13 October 2011 Abstract * Abstract * Change history * 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 Optical methods for viewing neuronal populations and projections in the intact mammalian brain are needed, but light scattering prevents imaging deep into brain structures. We imaged fixed brain tissue using Scale, an aqueous reagent that renders biological samples optically transparent but completely preserves fluorescent signals in the clarified structures. In Scale-treated mouse brain, neurons labeled with genetically encoded fluorescent proteins were visualized at an unprecedented depth in millimeter-scale networks and at subcellular resolution. The improved depth and scale of imaging permitted comprehensive three-dimensional reconstructions of cortical, callosal and hippocampal projections whose extent was limited only by the working distance of the objective lenses. In the intact neurogenic niche of the dentate gyrus, Scale allowed the quantitation of distances of neural stem cells to blood vessels. Our findings suggest that the Scale method will be useful for light mi! croscopy–based connectomics of cellular networks in brain and other tissues. View full text Figures at a glance * Figure 1: Tissue clearing performance of ScaleA2. () Transmission curves of ScaleA2 (blue), 60% sucrose/PBS (green), FocusClear (yellow) and MountClear (magenta). () Transmission curves of fixed brain slices (1.5 mm thick) in ScaleA2 (blue), 60% sucrose/PBS (green), Focus/MountClear (magenta, a slice treated with FocusClear was placed in MountClear) and PBS (violet) after treatment with the respective solutions. () A whole fixed and cleared brain of a mouse (P15) after treatment with ScaleA2 for 2 weeks. () A photo was taken with a black and white pattern as background. () The green light from a 1-mW, 532-nm laser beam pointer traversed the cleared brain. () A photo of two embryos (E13.5) taken with a black and white pattern as background. Left, embryo placed in PBS after fixation with 4% PFA. Right, embryo incubated in ScaleA2 solution for 2 weeks after fixation with 4% PFA. (–) Characterization of the expansion of macroscopic structures in fixed brain slices of a YFP-H mouse during ScaleA2 treatment. A coronal slice (1 ! mm thick) containing the hippocampus was prepared from a 9-week-old mouse. The slice was split into two halves and the right half was incubated in ScaleA2 solution for 5 d while the left half was incubated in PBS. Before (0 d, –) and 1 d (–), 2 d (–) or 5 d (–) after these incubations, the pair of slices on a coverslip with a patterned background were imaged using a fluorescence stereomicroscope for transmission (, , , , , , and ) and YFP fluorescence (, , , , , , and ). The slice became transparent and expanded after a 1–2-d incubation in ScaleA2 solution (, , , , and ). The extent of the linear expansion was calculated as 1.28. Ag, amygdala; Cp, cerebral peduncle (basal part); Cx, cortex; Dmn, dorsomedial nucleus; Hf, hippocampal formation; Pmc, posteromedial cortical amygdala nucleus. The outlines of the slices and their internal structures at 0 d and 5 d were drawn with blue and orange, respectively. The outlines of the PBS-treated slice at 0 d and 5 d overlap! ped substantially (). Reduced drawings of the outlines of the ! ScaleA2-treated slice at 5 d also overlapped with the outlines at 0 d extensively (). In addition, the outlines of the ScaleA2-treated half (green) at 0 d were inverted and overlaid to the outlines of the PBS-treated half (magenta) at 0 d. As the brain slice had been split slightly asymmetrically, the edges of each half were not precisely even, but proper alignment was achieved (). A similar overlay was done between the size-normalized outlines at 5 d (). In and , the difference between green and red traces indicates the inherent baseline left/right asymmetry of the slice. Notably, the degree and distribution of the asymmetry are almost identical between and . All scale bars represent 5 mm. * Figure 2: Comparison of ScaleA2 with BABB. () Sensitivity of EGFP fluorescence to ScaleA2 solution and a conventional chemical clearing reagent (BABB). Cultured HeLa cells expressing EGFP were fixed with 4% PFA and were time-lapse imaged while being exposed to ScaleA2 solution () or BABB following dehydration with ethanol and hexane (). Replacement of Hanks' Balanced Salt Solution with ScaleA2 resulted in a change in focus and a slight decrease in fluorescence intensity. () Fluorescence images comparing the preservation of YFP signals between aqueous (left) and chemical (right) clearing agents. The brain of a YFP-H mouse (7 weeks old) was split into two halves. The left half was treated with ScaleA2 for 3 d. The right half was treated with BABB after dehydration. Then slices (1 mm thick) were prepared and imaged for fluorescence with a stereomicroscope. The original shape of the fixed brain is drawn with broken lines. Scale bar represents 5 mm. * Figure 3: Three-dimensional reconstructions of YFP-expressing neurons in ScaleA2-treated brain samples of YFP-H mice. The actual imaging depth is shown in parentheses. Unsectioned brains (–) and an excised hippocampus () were imaged. (–) TPEFM imaging using a 25× objective (XLPLN25XWMP, numerical aperture (NA) = 1.05, working distance = 2.0 mm). The experimental setup for TPEFM imaging using the commercially available objective is shown in . A three-dimensional reconstruction of YFP-expressing neurons in 16 (8 × 2) quadratic prisms located in the cerebral cortex and hippocampus is shown in . A high-magnification xy image at a depth of 0.9 mm (a yellow box in ) is shown in . (–) Three-dimensional reconstruction of YFP-expressing neurons in a quadratic prism located in the cerebral cortex. The same brain region was imaged using a 20× objective (W-PlanApochromat, NA = 1.0, working distance = 2.0 mm) and taking both two-photon (920-nm excitation, –) and one-photon (514-nm excitation, –) approaches. For each volume rendering, three xy images at different z positions (– and –) ar! e presented. (–) TPEFM imaging using a custom-designed objective with a working distance of 4.0 mm. The experimental setup for TPEFM imaging using the objective lens is shown in and . Three-dimensional reconstructions of YFP-expressing neurons in a quadratic prism located in the cerebral cortex and hippocampus () and in 24 (4 × 6) quadratic prisms located in the excised hippocampus () are shown. DG, dentate gyrus; GCL, granule cell layer; ML, molecular layer. All scale bars represent 50 μm. * Figure 4: Visualization of labeled callosal connections in the intact mouse brain. A population of layer II/III pyramidal neurons was labeled by in utero electroporation of plasmids encoding EYFP into the dorsal ventricular zone on the right side (R) of the mouse forebrain at E15.5, and their axonal projections into the left side (L) were visualized at P10 using a macro-zoom confocal microscope after fixation and a 7-d treatment with ScaleA2. CC, corpus callosum; CPu, caudate putamen; Cx, cortex; HC, hippocampus; LV, lateral ventricle; ML, midline; TM, thalamus. () We acquired 18 confocal images (52-μm steps) using a 1× objective lens at scanner zoom 3×, and z stacked them. () We acquired 17 confocal images (43-μm steps) using a 2× objective lens at scanner zoom 2×, and z stacked them. () We acquired 34 confocal images (10.8 μm steps) using a 2× objective lens at scanner zoom 4×, and z stacked them. All scale bars represent 500 μm. * Figure 5: Quantitation of the distances between proliferating neural stem cell (PNSC) nuclei and blood vessels in the subgranular zone (SGZ) of adult mice. (–) Visualization of GFP-labeled neural stem cells (NSCs) and Texas Red–labeled blood vessels in the adult mouse hippocampus. A schematic diagram showing the approach of TPEFM imaging (red arrow) to a cleared excised hippocampus is presented in . The imaged area is shown by six quadratic prisms. A high-magnification volume rendering of NSCs (green) and blood vessels (red) in the SGZ is shown in . Volume renderings generated from a large region in the hippocampus are shown in . Five perspective views were created from different angles (D, dorsal; V, ventral; C, caudal; R, rostral; F, front). GCL, granule cell layer; ML, molecular layer. (–) Hippocampi were excised from the fixed brains of #504 mice (7 weeks old) and cleared with ScaleA2 for 2 d. An excised hippocampus for TPEFM imaging is shown in . The quadratic prism that was approached from the surface (red arrow) is shown. The objective was placed so that the z axis came into contact with the apex of the hilus. A se! ries of perspective images of PNSC nuclei (green) and blood vessels (red) when tunneling into the hippocampus are shown in . Backward perspective images were created at different depths. After passing through the SGZ, no PNSC nuclei were seen ahead. These images are animated in Supplementary Video 4. RINZO automatically calculated the distance (white lines) from each PNSC nucleus (green) to the nearest blood vessel (red) surface (). Histograms show the distribution of distances to blood vessels for all SGZ cell nuclei (violet), and for PNSC nuclei (green). Cell numbers () or their frequencies () were plotted. The real distance is shown in parentheses. Scale bars represent 500 μm () and 20 μm (). * Figure 6: Three-dimensional reconstructions of Fucci transgenic mouse embryos treated with ScaleU2. (–) Green and red signals are derived from the Fucci-S/G2/M marker and Fucci-G1/G0 marker, respectively. Transgenic mouse #596/#504 embryos (E11.5 and E13.5) were fixed with 4% PFA/PBS and then incubated in ScaleU2 for 6 months. The right halves of their bodies (heads) were imaged using macro-zoom LSCM (AZ-C1) equipped with a 2× objective lens (AZ-PlanFluor, NA = 0.2, working distance = 45 mm). The z step size was 5 μm. We used 488-nm and 561-nm laser diodes. Shown are maximum intensity projection (MIP) images at E11.5 () and E13.5 (). A confocal image of the region indicated by a white box in the MIP image () is shown in . (–) Immunohistochemical localization of Nestin (–) or PSA-NCAM (–) on sections of the posterior end of the diencephalon of an E13.5 #504 transgenic embryo producing mAG-hGem(1/110). The immunostaining and mAG-hGem(1/110) signals are shown in white and green, respectively. High-magnification images of the regions indicated by yellow boxes in and ! are shown in and , respectively. IC, inferior colliculus; V, ventricle. Scale bars represent 1 mm (–) and 100 μm (–). * Figure 7: Immunohistochemistry on sections restored from ScaleA2. (–) A brain sample from the thy1-YFP mouse line H (7 weeks old) was used. Sections of the dentate gyrus were prepared from a fixed sample (–) and a sample restored from ScaleA2 (–). Samples were stained with a mouse monoclonal antibody to PSA-NCAM. The YFP fluorescence and immunoreactivity for PSA-NCAM (with a secondary antibody conjugated to Alexa Fluor 546) were visualized. (–) A brain sample from wild-type mouse (7 weeks old) was used. Sections of the CA3 region were prepared from a fixed sample (–) and a sample restored from ScaleA2 (–). Samples were stained with a rabbit polyclonal antibody to GluR1 and a mouse monoclonal antibody to synaptophysin. These primary antibodies were visualized with secondary antibodies conjugated to Alexa Fluor 488 and 546, respectively (Molecular Probes). Scale bars represent 20 μm. Change history * Abstract * Change history * Author information * Supplementary informationCorrected online 13 October 2011In the HTML version of this article initially published online, Greek μ characters were misformatted as the letter m and a prime sign was omitted. The errors have been corrected in the HTML version of this article. Author information * Abstract * Change history * Author information * Supplementary information Affiliations * Brain Science Institute, RIKEN, Wako-city, Saitama, Japan. * Hiroshi Hama, * Hiroshi Kurokawa, * Hiroyuki Kawano, * Ryoko Ando, * Tomomi Shimogori, * Hisayori Noda, * Asako Sakaue-Sawano & * Atsushi Miyawaki * School of Life Science, Tokyo University of Pharmacy and Life Science, Hachioji, Tokyo, Japan. * Hiroshi Kurokawa & * Kiyoko Fukami * Life Function and Dynamics, Exploratory Research for Advanced Technology, Japan Science and Technology Agency, Wako-city, Saitama, Japan. * Hiroyuki Kawano, * Asako Sakaue-Sawano & * Atsushi Miyawaki * Tokyo Institute of Technology, Meguro-ku, Tokyo, Japan. * Hisayori Noda Contributions H.H. and A.M. conceived and designed the study. H.H. performed all the experiments and analyzed the data. H. Kurokawa devised the algorithms and analyzed the data. H. Kawano constructed the TPEFM system. R.A. performed in vitro experiments using fluorescent proteins. T.S. designed and performed the experiments that imaged callosal connections. H.N. refined the algorithms. K.F. contributed to data analysis. A.S.-S. performed the experiments using Fucci transgenic mouse embryos. A.M. supervised the project and wrote the manuscript with the help of H.H. Competing financial interests H. Hama, H. Kurokawa, H. Kawano, R. Ando and A. Miyawaki hold the patent for the Scale technique. Corresponding author Correspondence to: * Atsushi Miyawaki Author Details * Hiroshi Hama Search for this author in: * NPG journals * PubMed * Google Scholar * Hiroshi Kurokawa Search for this author in: * NPG journals * PubMed * Google Scholar * Hiroyuki Kawano Search for this author in: * NPG journals * PubMed * Google Scholar * Ryoko Ando Search for this author in: * NPG journals * PubMed * Google Scholar * Tomomi Shimogori Search for this author in: * NPG journals * PubMed * Google Scholar * Hisayori Noda Search for this author in: * NPG journals * PubMed * Google Scholar * Kiyoko Fukami Search for this author in: * NPG journals * PubMed * Google Scholar * Asako Sakaue-Sawano Search for this author in: * NPG journals * PubMed * Google Scholar * Atsushi Miyawaki Contact Atsushi Miyawaki Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Change history * Author information * Supplementary information PDF files * Supplementary Text and Figures (3M) Supplementary Figures 1–9 and Table 1 Movies * Supplementary Video 1 (5.3M) Visualizing the 3D architecture of neuronal networks comprised of YFP-expressing neurons in a long quadratic prism (2 mm). A series of X − Y images through the 3D reconstruction data (500 × 500 × 2,000 μm volume) from the cerebral surface to the hippocampus of the YFP-H mouse (13 weeks old). TPEFM with a non-descanned detector and a 20× objective (NA 1.0, WD 2.0 mm) was used. * Supplementary Video 2 (11.7M) Visualizing the 3D architecure of neuronal networks comprised of YFP-expressing neurons in a very long quadratic prism (4 mm). A series of X−Y images through the 3D reconstruction data (500 × 500 × 4,000 μm volume) from the cerebral surface to the dentate gyrus of the YFP-H mouse (13 weeks old). TPEFM with a non-descanned detector and a custom designed 25× objective lens (NA 1.0, WD 4.0 mm) was used. * Supplementary Video 3 (2.3M) YFP-labeled pyramidal neurons in layers II and III in the right hemisphere and their callosal axons travelling into the left hemisphere. A series of X−Y images through the 3D reconstruction data (10 × 10 × 0.75 mm volume) from anterior to posterior of a brain (10 days old) containing the corpus callosum. A population of layer II/III pyramidal neurons on the right side is highlighted with EYFP fluorescence. A macro zoom confocal microscopy system was used. * Supplementary Video 4 (2.9M) Nuclei of proliferating neural stem cells exclusively localized in the subgranular zone in association with a network of blood vessels. Animation (zooming in) of 3D image data (500 × 500 × 1,400 μm volume) in the hippocampal dentate gyrus of a #504 adult (7 weeks old) mouse extensively labeled with Texas Red-labeled lectin. Red, blood vessels; Green, nuclei of proliferating neural stem cells (PNSC) emitting mAG-hGem(1/110) fluorescence. TPEFM with two non-descanned detectors was used. Additional data