Network anatomy and in vivo physiology of visual cortical neurons

In the cerebral cortex, local circuits consist of tens of thousands of neurons, each of which makes thousands of synaptic connections. Perhaps the biggest impediment to understanding these networks is that we have no wiring diagrams of their interconnections. Even if we had a partial or complete wiring diagram, however, understanding the network would also require information about each neuron's function. Here we show that the relationship between structure and function can be studied in the cortex with a combination of in vivo physiology and network anatomy. We used two-photon calcium imaging to characterize a functional property—the preferred stimulus orientation—of a group of neurons in the mouse primary visual cortex. Large-scale electron microscopy of serial thin sections was then used to trace a portion of these neurons’ local network. Consistent with a prediction from recent physiological experiments, inhibitory interneurons received convergent anatomical input from nearby excitatory neurons with a broad range of preferred orientations, although weak biases could not be rejected.

[1]  S. R. Cajal Textura del Sistema Nervioso del Hombre y de los Vertebrados, 1899–1904 , 2019 .

[2]  M. Dennis,et al.  Synaptic vesicle exocytosis captured by quick freezing and correlated with quantal transmitter release , 1979, The Journal of cell biology.

[3]  P. Sterling Microcircuitry of the cat retina. , 1983, Annual review of neuroscience.

[4]  A. Peters,et al.  The neuronal composition of area 17 of rat visual cortex. II. The nonpyramidal cells , 1985, The Journal of comparative neurology.

[5]  A. Peters,et al.  The neuronal composition of area 17 of rat visual cortex. I. The pyramidal cells , 1985, The Journal of comparative neurology.

[6]  S. Brenner,et al.  The structure of the nervous system of the nematode Caenorhabditis elegans. , 1986, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[7]  R. Dacheux,et al.  The rod pathway in the rabbit retina: a depolarizing bipolar and amacrine cell , 1986, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[8]  S. Sherman,et al.  Synaptic circuits involving an individual retinogeniculate axon in the cat , 1987, The Journal of comparative neurology.

[9]  E. White Cortical Circuits: Synaptic Organization of the Cerebral Cortex , 1989 .

[10]  I. Divac Cortical circuits: Synaptic organization of the cerebral cortex. Structure, function and theory by Edward L. White, Birkäuser, 1989. Sw. fr. 88.00 (xvi + 223 pages) ISBN 3 7643 3402 9 , 1990, Trends in Neurosciences.

[11]  K. Stratford,et al.  Synaptic transmission between individual pyramidal neurons of the rat visual cortex in vitro , 1991, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[12]  S. Palay,et al.  The Fine Structure of the Nervous System: Neurons and Their Supporting Cells , 1991 .

[13]  T. Wiesel,et al.  Targets of horizontal connections in macaque primary visual cortex , 1991, The Journal of comparative neurology.

[14]  J. C. Anderson,et al.  Map of the synapses formed with the dendrites of spiny stellate neurons of cat visual cortex , 1994, The Journal of comparative neurology.

[15]  K. Martin,et al.  Map of the synapses onto layer 4 basket cells of the primary visual cortex of the cat , 1997, The Journal of comparative neurology.

[16]  H. Markram,et al.  Physiology and anatomy of synaptic connections between thick tufted pyramidal neurones in the developing rat neocortex. , 1997, The Journal of physiology.

[17]  G. Shepherd,et al.  Three-Dimensional Structure and Composition of CA3→CA1 Axons in Rat Hippocampal Slices: Implications for Presynaptic Connectivity and Compartmentalization , 1998, The Journal of Neuroscience.

[18]  P. Somogyi,et al.  Differentially Interconnected Networks of GABAergic Interneurons in the Visual Cortex of the Cat , 1998, The Journal of Neuroscience.

[19]  Prof. Dr. Dr. Valentino Braitenberg,et al.  Cortex: Statistics and Geometry of Neuronal Connectivity , 1998, Springer Berlin Heidelberg.

[20]  K M Harris,et al.  Stability in Synapse Number and Size at 2 Hr after Long-Term Potentiation in Hippocampal Area CA1 , 1998, The Journal of Neuroscience.

[21]  L. Garey Cortex: Statistics and Geometry of Neuronal Connectivity, 2nd edn. By V. BRAITENBERG and A. SCHÜZ. (Pp. xiii+249; 90 figures; ISBN 3 540 63816 4). Berlin: Springer. 1998. , 1999 .

[22]  G. Feng,et al.  Imaging Neuronal Subsets in Transgenic Mice Expressing Multiple Spectral Variants of GFP , 2000, Neuron.

[23]  J. Fiala,et al.  Cylindrical diameters method for calibrating section thickness in serial electron microscopy , 2001, Journal of microscopy.

[24]  Yun Wang,et al.  Synaptic connections and small circuits involving excitatory and inhibitory neurons in layers 2-5 of adult rat and cat neocortex: triple intracellular recordings and biocytin labelling in vitro. , 2002, Cerebral cortex.

[25]  Bertram Ludäscher,et al.  A cell-centered database for electron tomographic data. , 2002, Journal of structural biology.

[26]  R. Shapley,et al.  Orientation Selectivity in Macaque V1: Diversity and Laminar Dependence , 2002, The Journal of Neuroscience.

[27]  C. Stosiek,et al.  In vivo two-photon calcium imaging of neuronal networks , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[28]  A. Thomson,et al.  Interlaminar connections in the neocortex. , 2003, Cerebral cortex.

[29]  T. Harkany,et al.  Pyramidal cell communication within local networks in layer 2/3 of rat neocortex , 2003, The Journal of physiology.

[30]  D. Whitteridge,et al.  Synaptic targets of HRP-filled layer III pyramidal cells in the cat striate cortex , 2004, Experimental Brain Research.

[31]  W. Denk,et al.  Serial Block-Face Scanning Electron Microscopy to Reconstruct Three-Dimensional Tissue Nanostructure , 2004, PLoS biology.

[32]  R. Douglas,et al.  A Quantitative Map of the Circuit of Cat Primary Visual Cortex , 2004, The Journal of Neuroscience.

[33]  F. Wörgötter,et al.  Quantitative determination of orientational and directional components in the response of visual cortical cells to moving stimuli , 1987, Biological Cybernetics.

[34]  H. Markram,et al.  Interneurons of the neocortical inhibitory system , 2004, Nature Reviews Neuroscience.

[35]  Sen Song,et al.  Highly Nonrandom Features of Synaptic Connectivity in Local Cortical Circuits , 2005, PLoS biology.

[36]  Mark Ellisman,et al.  Design of a New 8k x 8k Lens Coupled Detector for Wide-field, High-resolution Transmission Electron Microscopy , 2005, Microscopy and Microanalysis.

[37]  E. Callaway,et al.  Excitatory cortical neurons form fine-scale functional networks , 2005, Nature.

[38]  Sooyoung Chung,et al.  Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex , 2005, Nature.

[39]  E. Callaway,et al.  Fine-scale specificity of cortical networks depends on inhibitory cell type and connectivity , 2005, Nature Neuroscience.

[40]  N. Kasthuri,et al.  Automating the Collection of Ultrathin Serial Sections for Large Volume TEM Reconstructions , 2006, Microscopy and Microanalysis.

[41]  J. Bourne,et al.  Uniform Serial Sectioning for Transmission Electron Microscopy , 2006, The Journal of Neuroscience.

[42]  R. Reid,et al.  Specificity and randomness in the visual cortex , 2007, Current Opinion in Neurobiology.

[43]  T. Tsumoto,et al.  GABAergic Neurons Are Less Selective to Stimulus Orientation than Excitatory Neurons in Layer II/III of Visual Cortex, as Revealed by In Vivo Functional Ca2+ Imaging in Transgenic Mice , 2007, The Journal of Neuroscience.

[44]  W. M. Keck,et al.  Highly Selective Receptive Fields in Mouse Visual Cortex , 2008, The Journal of Neuroscience.

[45]  Alex S. Ferecskó,et al.  Local Potential Connectivity in Cat Primary Visual Cortex , 2008 .

[46]  Kevin L. Briggman,et al.  3D structural imaging of the brain with photons and electrons , 2008, Current Opinion in Neurobiology.

[47]  D. Heeger,et al.  The Normalization Model of Attention , 2009, Neuron.

[48]  Benjamin F. Grewe,et al.  Optical probing of neuronal ensemble activity , 2009, Current Opinion in Neurobiology.

[49]  D. Mastronarde,et al.  A Computational Framework for Ultrastructural Mapping of Neural Circuitry , 2009, PLoS biology.

[50]  Sreekanth H. Chalasani,et al.  Imaging neural activity in worms, flies and mice with improved GCaMP calcium indicators , 2009, Nature Methods.

[51]  Li I. Zhang,et al.  Visual Receptive Field Structure of Cortical Inhibitory Neurons Revealed by Two-Photon Imaging Guided Recording , 2009, The Journal of Neuroscience.

[52]  Nathalie L Rochefort,et al.  Dendritic organization of sensory input to cortical neurons in vivo , 2010, Nature.

[53]  Nathan R. Wilson,et al.  Response Features of Parvalbumin-Expressing Interneurons Suggest Precise Roles for Subtypes of Inhibition in Visual Cortex , 2010, Neuron.

[54]  A. Cardona,et al.  An Integrated Micro- and Macroarchitectural Analysis of the Drosophila Brain by Computer-Assisted Serial Section Electron Microscopy , 2010, PLoS biology.

[55]  Li I. Zhang,et al.  Intervening Inhibition Underlies Simple-Cell Receptive Field Structure in Visual Cortex , 2009, Nature Neuroscience.

[56]  Henry J. Alitto,et al.  Function of inhibition in visual cortical processing , 2010, Current Opinion in Neurobiology.

[57]  K. Harris,et al.  Ultrastructural Analysis of Hippocampal Neuropil from the Connectomics Perspective , 2010, Neuron.

[58]  Li I. Zhang,et al.  Visual Representations by Cortical Somatostatin Inhibitory Neurons—Selective But with Weak and Delayed Responses , 2010, The Journal of Neuroscience.

[59]  R. Reid,et al.  Broadly Tuned Response Properties of Diverse Inhibitory Neuron Subtypes in Mouse Visual Cortex , 2010, Neuron.

[60]  Joseph F. Murray,et al.  Convolutional Networks Can Learn to Generate Affinity Graphs for Image Segmentation , 2010, Neural Computation.