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Hartung J, Schroeder A, Péréz Vázquez RA, Poorthuis RB, Letzkus JJ. Layer 1 NDNF interneurons are specialized top-down master regulators of cortical circuits. Cell Rep 2024; 43:114212. [PMID: 38743567 DOI: 10.1016/j.celrep.2024.114212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 03/10/2024] [Accepted: 04/23/2024] [Indexed: 05/16/2024] Open
Abstract
Diverse types of inhibitory interneurons (INs) impart computational power and flexibility to neocortical circuits. Whereas markers for different IN types in cortical layers 2-6 (L2-L6) have been instrumental for generating a wealth of functional insights, only the recent identification of a selective marker (neuron-derived neurotrophic factor [NDNF]) has opened comparable opportunities for INs in L1 (L1INs). However, at present we know very little about the connectivity of NDNF L1INs with other IN types, their input-output conversion, and the existence of potential NDNF L1IN subtypes. Here, we report pervasive inhibition of L2/3 INs (including parvalbumin INs and vasoactive intestinal peptide INs) by NDNF L1INs. Intersectional genetics revealed similar physiology and connectivity in the NDNF L1IN subpopulation co-expressing neuropeptide Y. Finally, NDNF L1INs prominently and selectively engage in persistent firing, a physiological hallmark disconnecting their output from the current input. Collectively, our work therefore identifies NDNF L1INs as specialized master regulators of superficial neocortex according to their pervasive top-down afferents.
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Affiliation(s)
- Jan Hartung
- Institute for Physiology, Faculty of Medicine, University of Freiburg, 79108 Freiburg, Germany; BrainLinks-BrainTools, IMBIT (Institute for Machine-Brain Interfacing Technology), University of Freiburg, Georges-Köhler-Allee 201, 79110 Freiburg, Germany.
| | - Anna Schroeder
- Institute for Physiology, Faculty of Medicine, University of Freiburg, 79108 Freiburg, Germany
| | | | - Rogier B Poorthuis
- Department of Translational Neuroscience, UMC Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands
| | - Johannes J Letzkus
- Institute for Physiology, Faculty of Medicine, University of Freiburg, 79108 Freiburg, Germany; BrainLinks-BrainTools, IMBIT (Institute for Machine-Brain Interfacing Technology), University of Freiburg, Georges-Köhler-Allee 201, 79110 Freiburg, Germany; Center for Basics in NeuroModulation (NeuroModul Basics), University of Freiburg, 79106 Freiburg, Germany.
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2
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Rich PD, Thiberge SY, Scott BB, Guo C, Tervo DGR, Brody CD, Karpova AY, Daw ND, Tank DW. Magnetic voluntary head-fixation in transgenic rats enables lifespan imaging of hippocampal neurons. Nat Commun 2024; 15:4154. [PMID: 38755205 PMCID: PMC11099169 DOI: 10.1038/s41467-024-48505-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 05/01/2024] [Indexed: 05/18/2024] Open
Abstract
The precise neural mechanisms within the brain that contribute to the remarkable lifetime persistence of memory are not fully understood. Two-photon calcium imaging allows the activity of individual cells to be followed across long periods, but conventional approaches require head-fixation, which limits the type of behavior that can be studied. We present a magnetic voluntary head-fixation system that provides stable optical access to the brain during complex behavior. Compared to previous systems that used mechanical restraint, there are no moving parts and animals can engage and disengage entirely at will. This system is failsafe, easy for animals to use and reliable enough to allow long-term experiments to be routinely performed. Animals completed hundreds of trials per session of an odor discrimination task that required 2-4 s fixations. Together with a reflectance fluorescence collection scheme that increases two-photon signal and a transgenic Thy1-GCaMP6f rat line, we are able to reliably image the cellular activity in the hippocampus during behavior over long periods (median 6 months), allowing us track the same neurons over a large fraction of animals' lives (up to 19 months).
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Affiliation(s)
- P Dylan Rich
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
| | | | - Benjamin B Scott
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, USA
- Neurophotonics Center, Boston University, Boston, MA, USA
| | - Caiying Guo
- Janelia Research Campus, Ashburn, VA, USA
- Howard Hughes Medical Institute, Ashburn, VA, USA
| | - D Gowanlock R Tervo
- Janelia Research Campus, Ashburn, VA, USA
- Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Carlos D Brody
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Howard Hughes Medical Institute, Princeton University, Princeton, NJ, USA
| | - Alla Y Karpova
- Janelia Research Campus, Ashburn, VA, USA
- Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Nathaniel D Daw
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Department of Psychology, Princeton University, Princeton, NJ, USA
| | - David W Tank
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
- Bezos Center for Neural Circuit Dynamics, Princeton University, Princeton, NJ, USA.
- Department of Molecular Biology, Princeton University, Princeton, NJ, USA.
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3
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Huang S, Wu SJ, Sansone G, Ibrahim LA, Fishell G. Layer 1 neocortex: Gating and integrating multidimensional signals. Neuron 2024; 112:184-200. [PMID: 37913772 PMCID: PMC11180419 DOI: 10.1016/j.neuron.2023.09.041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 09/23/2023] [Accepted: 09/28/2023] [Indexed: 11/03/2023]
Abstract
Layer 1 (L1) of the neocortex acts as a nexus for the collection and processing of widespread information. By integrating ascending inputs with extensive top-down activity, this layer likely provides critical information regulating how the perception of sensory inputs is reconciled with expectation. This is accomplished by sorting, directing, and integrating the complex network of excitatory inputs that converge onto L1. These signals are combined with neuromodulatory afferents and gated by the wealth of inhibitory interneurons that either are embedded within L1 or send axons from other cortical layers. Together, these interactions dynamically calibrate information flow throughout the neocortex. This review will primarily focus on L1 within the primary sensory cortex and will use these insights to understand L1 in other cortical areas.
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Affiliation(s)
- Shuhan Huang
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Program in Neuroscience, Harvard University, Cambridge, MA 02138, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Sherry Jingjing Wu
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Giulia Sansone
- Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia
| | - Leena Ali Ibrahim
- Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia.
| | - Gord Fishell
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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4
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Rindner DJ, Proddutur A, Lur G. Cell-type-specific integration of feedforward and feedback synaptic inputs in the posterior parietal cortex. Neuron 2022; 110:3760-3773.e5. [PMID: 36087582 PMCID: PMC9671855 DOI: 10.1016/j.neuron.2022.08.019] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 07/19/2022] [Accepted: 08/16/2022] [Indexed: 12/15/2022]
Abstract
The integration of feedforward (sensory) and feedback (top-down) neuronal signals is a principal function of the neocortex. Yet, we have limited insight into how these information streams are combined by individual neurons. Using a two-color optogenetic strategy, we found that layer 5 pyramidal neurons in the posterior parietal cortex receive monosynaptic dual innervation, combining sensory inputs with top-down signals. Subclasses of layer 5 pyramidal neurons integrated these synapses with distinct temporal dynamics. Specifically, regular spiking cells exhibited supralinear enhancement of delayed-but not coincident-inputs, while intrinsic burst-firing neurons selectively boosted coincident synaptic events. These subthreshold integration characteristics translated to a nonlinear summation of action potential firing. Complementing electrophysiology with computational modeling, we found that distinct integration profiles arose from a cell-type-specific interaction of ionic mechanisms and feedforward inhibition. These data provide insight into the cellular properties that guide the nonlinear interaction of distinct long-range afferents in the neocortex.
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Affiliation(s)
- Daniel J Rindner
- Department of Neurobiology and Behavior, University of California, Irvine, 1215 McGaugh Hall, Irvine, CA 92697, USA
| | - Archana Proddutur
- Department of Neurobiology and Behavior, University of California, Irvine, 1215 McGaugh Hall, Irvine, CA 92697, USA
| | - Gyorgy Lur
- Department of Neurobiology and Behavior, University of California, Irvine, 1215 McGaugh Hall, Irvine, CA 92697, USA.
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5
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Udvary D, Harth P, Macke JH, Hege HC, de Kock CPJ, Sakmann B, Oberlaender M. The impact of neuron morphology on cortical network architecture. Cell Rep 2022; 39:110677. [PMID: 35417720 PMCID: PMC9035680 DOI: 10.1016/j.celrep.2022.110677] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Revised: 09/22/2021] [Accepted: 03/22/2022] [Indexed: 11/17/2022] Open
Abstract
The neurons in the cerebral cortex are not randomly interconnected. This specificity in wiring can result from synapse formation mechanisms that connect neurons, depending on their electrical activity and genetically defined identity. Here, we report that the morphological properties of the neurons provide an additional prominent source by which wiring specificity emerges in cortical networks. This morphologically determined wiring specificity reflects similarities between the neurons’ axo-dendritic projections patterns, the packing density, and the cellular diversity of the neuropil. The higher these three factors are, the more recurrent is the topology of the network. Conversely, the lower these factors are, the more feedforward is the network’s topology. These principles predict the empirically observed occurrences of clusters of synapses, cell type-specific connectivity patterns, and nonrandom network motifs. Thus, we demonstrate that wiring specificity emerges in the cerebral cortex at subcellular, cellular, and network scales from the specific morphological properties of its neuronal constituents. Neuronal network architectures reflect the morphologies of their constituents Morphology predicts nonrandom connectivity from subcellular to network scales Morphology predicts connectivity patterns consistent with those observed empirically Neuron morphology is a major source for wiring specificity in the cerebral cortex
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Affiliation(s)
- Daniel Udvary
- In Silico Brain Sciences Group, Max Planck Institute for Neurobiology of Behavior - caesar, Ludwig Erhard Allee 2, 53175 Bonn, Germany
| | - Philipp Harth
- Department of Visual and Data-Centric Computing, Zuse Institute Berlin, Takustraße 7, 14195 Berlin, Germany
| | - Jakob H Macke
- Machine Learning in Science, Tübingen University, Maria von Linden Straße 6, 72076 Tübingen, Germany
| | - Hans-Christian Hege
- Department of Visual and Data-Centric Computing, Zuse Institute Berlin, Takustraße 7, 14195 Berlin, Germany
| | - Christiaan P J de Kock
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 Amsterdam, the Netherlands
| | - Bert Sakmann
- Max Planck Institute of Neurobiology, Am Klopferspitz 18, 82152 Martinsried, Germany
| | - Marcel Oberlaender
- In Silico Brain Sciences Group, Max Planck Institute for Neurobiology of Behavior - caesar, Ludwig Erhard Allee 2, 53175 Bonn, Germany.
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6
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Rikhye RV, Yildirim M, Hu M, Breton-Provencher V, Sur M. Reliable Sensory Processing in Mouse Visual Cortex through Cooperative Interactions between Somatostatin and Parvalbumin Interneurons. J Neurosci 2021; 41:8761-8778. [PMID: 34493543 PMCID: PMC8528503 DOI: 10.1523/jneurosci.3176-20.2021] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 08/16/2021] [Accepted: 08/23/2021] [Indexed: 11/21/2022] Open
Abstract
Intrinsic neuronal variability significantly limits information encoding in the primary visual cortex (V1). However, under certain conditions, neurons can respond reliably with highly precise responses to the same visual stimuli from trial to trial. This suggests that there exists intrinsic neural circuit mechanisms that dynamically modulate the intertrial variability of visual cortical neurons. Here, we sought to elucidate the role of different inhibitory interneurons (INs) in reliable coding in mouse V1. To study the interactions between somatostatin-expressing interneurons (SST-INs) and parvalbumin-expressing interneurons (PV-INs), we used a dual-color calcium imaging technique that allowed us to simultaneously monitor these two neural ensembles while awake mice, of both sexes, passively viewed natural movies. SST neurons were more active during epochs of reliable pyramidal neuron firing, whereas PV neurons were more active during epochs of unreliable firing. SST neuron activity lagged that of PV neurons, consistent with a feedback inhibitory SST→PV circuit. To dissect the role of this circuit in pyramidal neuron activity, we used temporally limited optogenetic activation and inactivation of SST and PV interneurons during periods of reliable and unreliable pyramidal cell firing. Transient firing of SST neurons increased pyramidal neuron reliability by actively suppressing PV neurons, a proposal that was supported by a rate-based model of V1 neurons. These results identify a cooperative functional role for the SST→PV circuit in modulating the reliability of pyramidal neuron activity.SIGNIFICANCE STATEMENT Cortical neurons often respond to identical sensory stimuli with large variability. However, under certain conditions, the same neurons can also respond highly reliably. The circuit mechanisms that contribute to this modulation remain unknown. Here, we used novel dual-wavelength calcium imaging and temporally selective optical perturbation to identify an inhibitory neural circuit in visual cortex that can modulate the reliability of pyramidal neurons to naturalistic visual stimuli. Our results, supported by computational models, suggest that somatostatin interneurons increase pyramidal neuron reliability by suppressing parvalbumin interneurons via the inhibitory SST→PV circuit. These findings reveal a novel role of the SST→PV circuit in modulating the fidelity of neural coding critical for visual perception.
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Affiliation(s)
- Rajeev V Rikhye
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
| | - Murat Yildirim
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
| | - Ming Hu
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
| | - Vincent Breton-Provencher
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
| | - Mriganka Sur
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
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7
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Staiger JF, Petersen CCH. Neuronal Circuits in Barrel Cortex for Whisker Sensory Perception. Physiol Rev 2020; 101:353-415. [PMID: 32816652 DOI: 10.1152/physrev.00019.2019] [Citation(s) in RCA: 49] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
The array of whiskers on the snout provides rodents with tactile sensory information relating to the size, shape and texture of objects in their immediate environment. Rodents can use their whiskers to detect stimuli, distinguish textures, locate objects and navigate. Important aspects of whisker sensation are thought to result from neuronal computations in the whisker somatosensory cortex (wS1). Each whisker is individually represented in the somatotopic map of wS1 by an anatomical unit named a 'barrel' (hence also called barrel cortex). This allows precise investigation of sensory processing in the context of a well-defined map. Here, we first review the signaling pathways from the whiskers to wS1, and then discuss current understanding of the various types of excitatory and inhibitory neurons present within wS1. Different classes of cells can be defined according to anatomical, electrophysiological and molecular features. The synaptic connectivity of neurons within local wS1 microcircuits, as well as their long-range interactions and the impact of neuromodulators, are beginning to be understood. Recent technological progress has allowed cell-type-specific connectivity to be related to cell-type-specific activity during whisker-related behaviors. An important goal for future research is to obtain a causal and mechanistic understanding of how selected aspects of tactile sensory information are processed by specific types of neurons in the synaptically connected neuronal networks of wS1 and signaled to downstream brain areas, thus contributing to sensory-guided decision-making.
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Affiliation(s)
- Jochen F Staiger
- University Medical Center Göttingen, Institute for Neuroanatomy, Göttingen, Germany; and Laboratory of Sensory Processing, Faculty of Life Sciences, Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Carl C H Petersen
- University Medical Center Göttingen, Institute for Neuroanatomy, Göttingen, Germany; and Laboratory of Sensory Processing, Faculty of Life Sciences, Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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8
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Voltage Imaging of Cortical Oscillations in Layer 1 with Two-Photon Microscopy. eNeuro 2020; 7:ENEURO.0274-19.2020. [PMID: 32321770 PMCID: PMC7253639 DOI: 10.1523/eneuro.0274-19.2020] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2019] [Revised: 03/25/2020] [Accepted: 03/26/2020] [Indexed: 12/16/2022] Open
Abstract
Membrane voltage oscillations in layer 1 (L1) of primary sensory cortices might be important indicators of cortical gain control, attentional focusing, and signal integration. However, electric field recordings are hampered by the low seal resistance of electrodes close to the brain surface. To study L1 membrane voltage oscillations, we synthesized a new voltage-sensitive dye, di1-ANNINE (anellated hemicyanine)-6plus, that can diffuse into tissue. We applied it with a new surgery, leaving the dura intact but allowing injection of large quantities of staining solution, and imaged cortical membrane potential oscillations with two-photon microscopy depth-resolved (25-100 μm below dura) in anesthetized and awake mice. We found delta (0.5-4 Hz), theta (4-10 Hz), low beta (10-20 Hz), and low gamma (30-40 Hz) oscillations. All oscillations were stronger in awake animals. While the power of delta, theta, and low beta oscillations increased with depth, the power of low gamma was more constant throughout L1. These findings identify L1 as an important coordination hub for the dynamic binding process of neurons mediated by oscillations.
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9
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Systematic Integration of Structural and Functional Data into Multi-scale Models of Mouse Primary Visual Cortex. Neuron 2020; 106:388-403.e18. [DOI: 10.1016/j.neuron.2020.01.040] [Citation(s) in RCA: 90] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Revised: 10/17/2019] [Accepted: 01/27/2020] [Indexed: 01/08/2023]
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10
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Fan LZ, Kheifets S, Böhm UL, Wu H, Piatkevich KD, Xie ME, Parot V, Ha Y, Evans KE, Boyden ES, Takesian AE, Cohen AE. All-Optical Electrophysiology Reveals the Role of Lateral Inhibition in Sensory Processing in Cortical Layer 1. Cell 2020; 180:521-535.e18. [PMID: 31978320 PMCID: PMC7259440 DOI: 10.1016/j.cell.2020.01.001] [Citation(s) in RCA: 95] [Impact Index Per Article: 23.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2019] [Revised: 11/06/2019] [Accepted: 01/03/2020] [Indexed: 11/22/2022]
Abstract
Cortical layer 1 (L1) interneurons have been proposed as a hub for attentional modulation of underlying cortex, but the transformations that this circuit implements are not known. We combined genetically targeted voltage imaging with optogenetic activation and silencing to study the mechanisms underlying sensory processing in mouse barrel cortex L1. Whisker stimuli evoked precisely timed single spikes in L1 interneurons, followed by strong lateral inhibition. A mild aversive stimulus activated cholinergic inputs and evoked a bimodal distribution of spiking responses in L1. A simple conductance-based model that only contained lateral inhibition within L1 recapitulated the sensory responses and the winner-takes-all cholinergic responses, and the model correctly predicted that the network would function as a spatial and temporal high-pass filter for excitatory inputs. Our results demonstrate that all-optical electrophysiology can reveal basic principles of neural circuit function in vivo and suggest an intuitive picture for how L1 transforms sensory and modulatory inputs. VIDEO ABSTRACT.
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Affiliation(s)
- Linlin Z Fan
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Simon Kheifets
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Urs L Böhm
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Hao Wu
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Kiryl D Piatkevich
- Media Lab and McGovern Institute for Brain Research, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
| | - Michael E Xie
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Vicente Parot
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Yooree Ha
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | | | - Edward S Boyden
- Media Lab and McGovern Institute for Brain Research, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
| | - Anne E Takesian
- Harvard Medical School, Boston, MA, USA; Massachusetts Eye and Ear Infirmary, Boston, MA, USA
| | - Adam E Cohen
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA; Department of Physics, Harvard University, Cambridge, MA, USA; Howard Hughes Medical Institute, Chevy Chase, MD, USA.
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11
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Egger R, Narayanan RT, Guest JM, Bast A, Udvary D, Messore LF, Das S, de Kock CPJ, Oberlaender M. Cortical Output Is Gated by Horizontally Projecting Neurons in the Deep Layers. Neuron 2019; 105:122-137.e8. [PMID: 31784285 PMCID: PMC6953434 DOI: 10.1016/j.neuron.2019.10.011] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Revised: 09/01/2019] [Accepted: 10/02/2019] [Indexed: 12/13/2022]
Abstract
Pyramidal tract neurons (PTs) represent the major output cell type of the mammalian neocortex. Here, we report the origins of the PTs’ ability to respond to a broad range of stimuli with onset latencies that rival or even precede those of their intracortical input neurons. We find that neurons with extensive horizontally projecting axons cluster around the deep-layer terminal fields of primary thalamocortical axons. The strategic location of these corticocortical neurons results in high convergence of thalamocortical inputs, which drive reliable sensory-evoked responses that precede those in other excitatory cell types. The resultant fast and horizontal stream of excitation provides PTs throughout the cortical area with input that acts to amplify additional inputs from thalamocortical and other intracortical populations. The fast onsets and broadly tuned characteristics of PT responses hence reflect a gating mechanism in the deep layers, which assures that sensory-evoked input can be reliably transformed into cortical output. Simulations predict in vivo responses for major output cell type of the neocortex Simulations reveal strategy how to test the origins of cortical output empirically Manipulations confirm that deep-layer corticocortical neurons gate cortical output Gating of cortical output originates from deep-layer thalamocortical input stratum
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Affiliation(s)
- Robert Egger
- Max Planck Research Group In Silico Brain Sciences, Center of Advanced European Studies and Research (caesar), Ludwig-Erhard-Allee 2, 53175 Bonn, Germany
| | - Rajeevan T Narayanan
- Max Planck Research Group In Silico Brain Sciences, Center of Advanced European Studies and Research (caesar), Ludwig-Erhard-Allee 2, 53175 Bonn, Germany
| | - Jason M Guest
- Max Planck Research Group In Silico Brain Sciences, Center of Advanced European Studies and Research (caesar), Ludwig-Erhard-Allee 2, 53175 Bonn, Germany
| | - Arco Bast
- Max Planck Research Group In Silico Brain Sciences, Center of Advanced European Studies and Research (caesar), Ludwig-Erhard-Allee 2, 53175 Bonn, Germany
| | - Daniel Udvary
- Max Planck Research Group In Silico Brain Sciences, Center of Advanced European Studies and Research (caesar), Ludwig-Erhard-Allee 2, 53175 Bonn, Germany
| | - Luis F Messore
- Max Planck Research Group In Silico Brain Sciences, Center of Advanced European Studies and Research (caesar), Ludwig-Erhard-Allee 2, 53175 Bonn, Germany
| | - Suman Das
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, VU Amsterdam, De Boelelaan 1085, 1081 Amsterdam, the Netherlands
| | - Christiaan P J de Kock
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, VU Amsterdam, De Boelelaan 1085, 1081 Amsterdam, the Netherlands
| | - Marcel Oberlaender
- Max Planck Research Group In Silico Brain Sciences, Center of Advanced European Studies and Research (caesar), Ludwig-Erhard-Allee 2, 53175 Bonn, Germany.
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12
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Yamawaki N, Li X, Lambot L, Ren LY, Radulovic J, Shepherd GMG. Long-range inhibitory intersection of a retrosplenial thalamocortical circuit by apical tuft-targeting CA1 neurons. Nat Neurosci 2019; 22:618-626. [PMID: 30858601 PMCID: PMC6435388 DOI: 10.1038/s41593-019-0355-x] [Citation(s) in RCA: 55] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2018] [Accepted: 02/04/2019] [Indexed: 02/06/2023]
Abstract
Hippocampus, granular retrosplenial cortex (RSCg), and anterior thalamic nuclei (ATN) interact to mediate diverse cognitive functions. To identify cellular mechanisms underlying hippocampo-thalamo-retrosplenial interactions, we investigated the potential circuit suggested by projections to RSCg layer 1 (L1) from GABAergic CA1 neurons and ATN. We find that CA1→RSCg projections stem from GABAergic neurons with a distinct morphology, electrophysiology, and molecular profile. Their long-range axons inhibit L5 pyramidal neurons in RSCg via potent synapses onto apical tuft dendrites in L1. These inhibitory inputs intercept L1-targeting thalamocortical excitatory inputs from ATN to coregulate RSCg activity. Subicular axons, in contrast, excite proximal dendrites in deeper layers. Short-term plasticity differs at each connection. Chemogenetically abrogating CA1→RSCg or ATN→RSCg connections oppositely affects the encoding of contextual fear memory. Our findings establish retrosplenial-projecting CA1 neurons as a distinct class of long-range dendrite-targeting GABAergic neuron and delineate an unusual cortical circuit specialized for integrating long-range inhibition and thalamocortical excitation.
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Affiliation(s)
- Naoki Yamawaki
- Department of Physiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
| | - Xiaojian Li
- Department of Physiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Laurie Lambot
- Department of Physiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Lynn Y Ren
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Jelena Radulovic
- Department of Physiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Gordon M G Shepherd
- Department of Physiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
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Layer 3 Dynamically Coordinates Columnar Activity According to Spatial Context. J Neurosci 2019; 39:281-294. [PMID: 30459226 DOI: 10.1523/jneurosci.1568-18.2018] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2018] [Revised: 10/16/2018] [Accepted: 10/16/2018] [Indexed: 01/03/2023] Open
Abstract
To reduce statistical redundancy of natural inputs and increase the sparseness of coding, neurons in primary visual cortex (V1) show tuning for stimulus size and surround suppression. This integration of spatial information is a fundamental, context-dependent neural operation involving extensive neural circuits that span across all cortical layers of a V1 column, and reflects both feedforward and feedback processing. However, how spatial integration is dynamically coordinated across cortical layers remains poorly understood. We recorded single- and multiunit activity and local field potentials across V1 layers of awake mice (both sexes) while they viewed stimuli of varying size and used dynamic Bayesian model comparisons to identify when laminar activity and interlaminar functional interactions showed surround suppression, the hallmark of spatial integration. We found that surround suppression is strongest in layer 3 (L3) and L4 activity, where suppression is established within ∼10 ms after response onset, and receptive fields dynamically sharpen while suppression strength increases. Importantly, we also found that specific directed functional connections were strongest for intermediate stimulus sizes and suppressed for larger ones, particularly for connections from L3 targeting L5 and L1. Together, the results shed light on the different functional roles of cortical layers in spatial integration and on how L3 dynamically coordinates activity across a cortical column depending on spatial context.SIGNIFICANCE STATEMENT Neurons in primary visual cortex (V1) show tuning for stimulus size, where responses to stimuli exceeding the receptive field can be suppressed (surround suppression). We demonstrate that functional connectivity between V1 layers can also have a surround-suppressed profile. A particularly prominent role seems to have layer 3, the functional connections to layers 5 and 1 of which are strongest for stimuli of optimal size and decreased for large stimuli. Our results therefore point toward a key role of layer 3 in coordinating activity across the cortical column according to spatial context.
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Learning-Related Plasticity in Dendrite-Targeting Layer 1 Interneurons. Neuron 2018; 100:684-699.e6. [PMID: 30269988 PMCID: PMC6226614 DOI: 10.1016/j.neuron.2018.09.001] [Citation(s) in RCA: 117] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2018] [Revised: 08/09/2018] [Accepted: 08/31/2018] [Indexed: 11/23/2022]
Abstract
A wealth of data has elucidated the mechanisms by which sensory inputs are encoded in the neocortex, but how these processes are regulated by the behavioral relevance of sensory information is less understood. Here, we focus on neocortical layer 1 (L1), a key location for processing of such top-down information. Using Neuron-Derived Neurotrophic Factor (NDNF) as a selective marker of L1 interneurons (INs) and in vivo 2-photon calcium imaging, electrophysiology, viral tracing, optogenetics, and associative memory, we find that L1 NDNF-INs mediate a prolonged form of inhibition in distal pyramidal neuron dendrites that correlates with the strength of the memory trace. Conversely, inhibition from Martinotti cells remains unchanged after conditioning but in turn tightly controls sensory responses in NDNF-INs. These results define a genetically addressable form of dendritic inhibition that is highly experience dependent and indicate that in addition to disinhibition, salient stimuli are encoded at elevated levels of distal dendritic inhibition. Video Abstract
NDNF is a selective marker for neocortical layer 1 interneurons NDNF interneurons mediate prolonged inhibition of distal pyramidal neuron dendrites Inhibition from Martinotti cells tightly controls NDNF interneuron responses Dendritic inhibition by NDNF interneurons is highly experience dependent
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Deitcher Y, Eyal G, Kanari L, Verhoog MB, Atenekeng Kahou GA, Mansvelder HD, de Kock CPJ, Segev I. Comprehensive Morpho-Electrotonic Analysis Shows 2 Distinct Classes of L2 and L3 Pyramidal Neurons in Human Temporal Cortex. Cereb Cortex 2018; 27:5398-5414. [PMID: 28968789 PMCID: PMC5939232 DOI: 10.1093/cercor/bhx226] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2017] [Indexed: 12/31/2022] Open
Abstract
There have been few quantitative characterizations of the morphological, biophysical, and cable properties of neurons in the human neocortex. We employed feature-based statistical methods on a rare data set of 60 3D reconstructed pyramidal neurons from L2 and L3 in the human temporal cortex (HL2/L3 PCs) removed after brain surgery. Of these cells, 25 neurons were also characterized physiologically. Thirty-two morphological features were analyzed (e.g., dendritic surface area, 36 333 ± 18 157 μm2; number of basal trees, 5.55 ± 1.47; dendritic diameter, 0.76 ± 0.28 μm). Eighteen features showed a significant gradual increase with depth from the pia (e.g., dendritic length and soma radius). The other features showed weak or no correlation with depth (e.g., dendritic diameter). The basal dendritic terminals in HL2/L3 PCs are particularly elongated, enabling multiple nonlinear processing units in these dendrites. Unlike the morphological features, the active biophysical features (e.g., spike shapes and rates) and passive/cable features (e.g., somatic input resistance, 47.68 ± 15.26 MΩ, membrane time constant, 12.03 ± 1.79 ms, average dendritic cable length, 0.99 ± 0.24) were depth-independent. A novel descriptor for apical dendritic topology yielded 2 distinct classes, termed hereby as “slim-tufted” and “profuse-tufted” HL2/L3 PCs; the latter class tends to fire at higher rates. Thus, our morpho-electrotonic analysis shows 2 distinct classes of HL2/L3 PCs.
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Affiliation(s)
- Yair Deitcher
- Department of Neurobiology, The Hebrew University of Jerusalem, Jerusalem 91904, Israel.,Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem 91904, Israel
| | - Guy Eyal
- Department of Neurobiology, The Hebrew University of Jerusalem, Jerusalem 91904, Israel
| | - Lida Kanari
- Blue Brain Project, Ecole Polytechnique Fédérale de Lausanne, Campus Biotech, Chemin de Mines, 9, Geneva 1202, Switzerland
| | - Matthijs B Verhoog
- Department of Integrative Neurophysiology, Centre for Neurogenomics and Cognitive Research, VU University Amsterdam, Amsterdam NL-1081 HV, The Netherlands
| | - Guy Antoine Atenekeng Kahou
- Blue Brain Project, Ecole Polytechnique Fédérale de Lausanne, Campus Biotech, Chemin de Mines, 9, Geneva 1202, Switzerland
| | - Huibert D Mansvelder
- Department of Integrative Neurophysiology, Centre for Neurogenomics and Cognitive Research, VU University Amsterdam, Amsterdam NL-1081 HV, The Netherlands
| | - Christiaan P J de Kock
- Department of Integrative Neurophysiology, Centre for Neurogenomics and Cognitive Research, VU University Amsterdam, Amsterdam NL-1081 HV, The Netherlands
| | - Idan Segev
- Department of Neurobiology, The Hebrew University of Jerusalem, Jerusalem 91904, Israel.,Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem 91904, Israel
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Linking neuronal structure to function in rodent hippocampus: a methodological prospective. Cell Tissue Res 2017; 373:605-618. [PMID: 29181629 DOI: 10.1007/s00441-017-2732-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2017] [Accepted: 10/27/2017] [Indexed: 10/18/2022]
Abstract
Since the discovery of place cells, hippocampus-dependent spatial navigation has proven to be an ideal model system for resolving the relationship between neural coding and behavior. Electrical recordings from the hippocampal formation in freely moving animals have revealed a rich repertoire of spatial firing patterns and have enormously advanced our understanding of the neural principles of spatial representation. However, limited progress has been achieved in resolving the underlying cellular mechanisms. This is partially attributable to the inability of standard recording techniques to link neuronal structure to function directly. In this review, we summarize recent efforts aimed at filling this gap. We also highlight the development of methodologies that allow functional measurements from identified neuronal elements in behaving rodents. Recent progress in the dentate gyrus serves as a showcase to reveal the potential of such methodologies and the necessity of resolving structure-function relationships in order to access the cellular mechanisms of hippocampal circuit computations.
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17
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Systematic population spike delays across cortical layers within and between primary sensory areas. Sci Rep 2017; 7:15267. [PMID: 29127394 PMCID: PMC5681572 DOI: 10.1038/s41598-017-15611-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2017] [Accepted: 10/30/2017] [Indexed: 12/12/2022] Open
Abstract
The coordinated propagation of activity across cortical layers enables simultaneous local computation and inter-areal interactions. A pattern of upward propagation from deeper to more superficial layers, which has been repeatedly demonstrated in spontaneous activity, would allow these functions to occur in parallel. But it remains unclear whether upward propagation also occurs for stimulus evoked activity, and how it relates to activity in other cortical areas. Here we used a new method to analyze relative delays between spikes obtained from simultaneous laminar recordings in primary sensory cortex (S1) of both hemispheres. The results identified systematic spike delays across cortical layers that showed a general upward propagation of activity in evoked and spontaneous activity. Systematic spike delays were also observed between hemispheres. After spikes in one S1 the delays in the other S1 were shortest at infragranular layers and increased in the upward direction. Model comparisons furthermore showed that upward propagation was better explained as a step-wise progression over cortical layers than as a traveling wave. The results are in line with the notion that upward propagation functionally integrates activity into local processing at superficial layers, while efficiently allowing for simultaneous inter-areal interactions.
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3D reconstruction and standardization of the rat facial nucleus for precise mapping of vibrissal motor networks. Neuroscience 2017; 368:171-186. [PMID: 28958919 PMCID: PMC5798596 DOI: 10.1016/j.neuroscience.2017.09.031] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2017] [Revised: 08/21/2017] [Accepted: 09/17/2017] [Indexed: 12/16/2022]
Abstract
The rodent facial nucleus (FN) comprises motoneurons (MNs) that control the facial musculature. In the lateral part of the FN, populations of vibrissal motoneurons (vMNs) innervate two groups of muscles that generate movements of the whiskers. Vibrissal MNs thus represent the terminal point of the neuronal networks that generate rhythmic whisking during exploratory behaviors and that modify whisker movements based on sensory-motor feedback during tactile-based perception. Here, we combined retrograde tracer injections into whisker-specific muscles, with large-scale immunohistochemistry and digital reconstructions to generate an average model of the rat FN. The model incorporates measurements of the FN geometry, its cellular organization and a whisker row-specific map formed by vMNs. Furthermore, the model provides a digital 3D reference frame that allows registering structural data - obtained across scales and animals - into a common coordinate system with a precision of ∼60 µm. We illustrate the registration method by injecting replication competent rabies virus into the muscle of a single whisker. Retrograde transport of the virus to vMNs enabled reconstruction of their dendrites. Subsequent trans-synaptic transport enabled mapping the presynaptic neurons of the reconstructed vMNs. Registration of these data to the FN reference frame provides a first account of the morphological and synaptic input variability within a population of vMNs that innervate the same muscle.
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DeFelipe J, Douglas RJ, Hill SL, Lein ES, Martin KAC, Rockland KS, Segev I, Shepherd GM, Tamás G. Comments and General Discussion on "The Anatomical Problem Posed by Brain Complexity and Size: A Potential Solution". Front Neuroanat 2016; 10:60. [PMID: 27375436 PMCID: PMC4901047 DOI: 10.3389/fnana.2016.00060] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2016] [Accepted: 05/18/2016] [Indexed: 02/06/2023] Open
Affiliation(s)
- Javier DeFelipe
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de MadridMadrid, Spain; Instituto Cajal, Consejo Superior de Investigaciones CientíficasMadrid, Spain; Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED)Madrid, Spain
| | - Rodney J Douglas
- Institute of Neuroinformatics, Swiss Federal Institute of Technology in Zurich (ETH) and University of Zurich (UZH) Zurich, Switzerland
| | - Sean L Hill
- Blue Brain Project, Campus Biotech Geneva, Switzerland
| | - Ed S Lein
- Human Cell Types Department, Allen Institute for Brain Science Seattle, WA, USA
| | - Kevan A C Martin
- Institute of Neuroinformatics, Swiss Federal Institute of Technology in Zurich (ETH) and University of Zurich (UZH) Zurich, Switzerland
| | - Kathleen S Rockland
- Department of Anatomy and Neurobiology, Boston University School of MedicineBoston, MA, USA; Cold Spring Harbor Laboratory, Cold Spring HarborNY, USA
| | - Idan Segev
- Departments of Neurobiology, The Hebrew University of JerusalemJerusalem, Israel; The Interdisciplinary Center for Neural Computation, The Hebrew University of JerusalemJerusalem, Israel; Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of JerusalemJerusalem, Israel
| | - Gordon M Shepherd
- Department of Neurobiology, Yale School of Medicine New Haven, CT, USA
| | - Gábor Tamás
- MTA-SZTE Research Group for Cortical Microcircuits of the Hungarian Academy of Sciences, Department of Physiology, Anatomy and Neuroscience, University of Szeged Szeged, Hungary
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