The evolution of large-scale modeling of monkey primary visual cortex, V1: Steps towards understanding cortical function

Research output: Contribution to journalArticle

Abstract

Over the past two decades, mathematicians and neuroscientists at New York University have developed several large-scale computational models of a layer of macaque primary visual cortex. Here we provide an overview of these models, organized by the specific questions about cortical processing that each model addressed. Each model was founded upon the available anatomical and physiological data; and not by building into the model network assumptions about theoretical mechanisms specifically designed to enable the network to produce desired response properties. Also, our aim was to use one comprehensive network, with a fixed architecture and one set of parameters, to model all experiments. The response properties of individual neurons and populations of neurons then emerge from this experimentally constrained model. This overview is dedicated to Professor David Cai, who played a leading role in several of the models described here. We are very fortunate to have had the opportunity to work with him over the past two decades.

Original languageEnglish (US)
Pages (from-to)1387-1406
Number of pages20
JournalCommunications in Mathematical Sciences
Volume17
Issue number5
DOIs
StatePublished - 2019

Keywords

  • Computational modeling
  • Orientation tuning
  • Visual neural science

ASJC Scopus subject areas

  • Mathematics(all)
  • Applied Mathematics

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