title: Local networks in visual cortex and their influence on neuronal responses and dynamics.
abstract: Networks of neurons in the cerebral cortex generate complex outputs that are not simply predicted by their inputs. These emergent responses underlie the function of the cortex. Understanding how cortical networks carry out such transformations requires a description of the responses of individual neurons and of their networks at multiple levels of analysis. We focus on orientation selectivity in primary visual cortex as a model system to understand cortical network computations. Recent experiments in our laboratory and others provide significant insight into how cortical networks generate and maintain orientation selectivity. We first review evidence for the diversity of orientation tuning characteristics in visual cortex. We then describe experiments that combine optical imaging of orientation maps with intracellular and extracellular recordings from individual neurons at known locations in the orientation map. The data indicate that excitatory and inhibitory synaptic inputs are summed across the cortex in a manner that is consistent with simple rules of integration of local inputs. These rules arise from known anatomical projection patterns in visual cortex. We propose that the generation and plasticity of orientation tuning is strongly influenced by local cortical networks-the diversity of these properties arises in part from the diversity of neighbourhood features that derive from the orientation map.
authors.affiliation: Department of Brain and Cognitive Sciences, Picower Center for Learning and Memory, MIT, E25-235, Cambridge, MA 02139, USA.
authors.forename: James
authors.initials: J
authors.lastname: Schummers
authors.forename: Jorge
authors.initials: J
authors.lastname: Mariño
authors.forename: Mriganka
authors.initials: M
authors.lastname: Sur
mesh_terms: D000818:Animals; D001931:Brain Mapping; D002540:Cerebral Cortex / Q000502:physiology; D003198:Computer Simulation; D005074:Evoked Potentials, Visual / Q000502:physiology*; D006801:Humans; D008564:Membrane Potentials; D008954:Models, Biological; D009415:Nerve Net / Q000502:physiology*; D016571:Neural Networks, Computer; D009475:Neurons, Afferent / Q000502:physiology*; D009949:Orientation / Q000502:physiology; D013997:Time Factors; D014793:Visual Cortex / Q000502:physiology*