title: Topological analysis of population activity in visual cortex.
abstract: Information in the cortex is thought to be represented by the joint activity of neurons. Here we describe how fundamental questions about neural representation can be cast in terms of the topological structure of population activity. A new method, based on the concept of persistent homology, is introduced and applied to the study of population activity in primary visual cortex (V1). We found that the topological structure of activity patterns when the cortex is spontaneously active is similar to those evoked by natural image stimulation and consistent with the topology of a two sphere. We discuss how this structure could emerge from the functional organization of orientation and spatial frequency maps and their mutual relationship. Our findings extend prior results on the relationship between spontaneous and evoked activity in V1 and illustrates how computational topology can help tackle elementary questions about the representation of information in the nervous system.
authors.affiliation: Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA. gurjeet@stanford.edu
authors.forename: Gurjeet
authors.initials: G
authors.lastname: Singh
authors.forename: Facundo
authors.initials: F
authors.lastname: Memoli
authors.forename: Tigran
authors.initials: T
authors.lastname: Ishkhanov
authors.forename: Guillermo
authors.initials: G
authors.lastname: Sapiro
authors.forename: Gunnar
authors.initials: G
authors.lastname: Carlsson
authors.forename: Dario L
authors.initials: DL
authors.lastname: Ringach
mesh_terms: D000818:Animals; D055724:Electrophysiological Phenomena; D005583:Fourier Analysis; D008252:Macaca fascicularis; D008959:Models, Neurological; D009462:Neurology / Q000379:methods*; D009474:Neurons / Q000502:physiology*; D010775:Photic Stimulation / Q000379:methods; D014793:Visual Cortex / Q000166:cytology* / Q000502:physiology*