Affordable Access

Publisher Website

Biologically realistic excitatory and inhibitory cell properties emerge from a sparse coding network

Authors
Journal
BMC Neuroscience
1471-2202
Publisher
Springer (Biomed Central Ltd.)
Publication Date
Volume
13
Identifiers
DOI: 10.1186/1471-2202-13-s1-p55
Keywords
  • Poster Presentation

Abstract

Biologically realistic excitatory and inhibitory cell properties emerge from a sparse coding network POSTER PRESENTATION Open Access Biologically realistic excitatory and inhibitory cell properties emerge from a sparse coding network Mengchen Zhu1*, Christopher J Rozell2 From Twenty First Annual Computational Neuroscience Meeting: CNS*2012 Decatur, GA, USA. 21-26 July 2012 Neurons in the primary visual cortex exhibit a baffling array of tuning properties, often unaccountable by the classical linear feedforward model. Specifically, excita- tory neurons display a number of nonlinear effects col- lectively known as non-classical receptive field (nCRF) effects [1], and inhibitory neurons have diverse orienta- tion tuning properties [2]. Furthermore, excitatory cells outnumber inhibitory cells by a ratio of 9:1 [3], yet the excitatory and inhibitory drives are balanced. Efficient coding models of early vision have been shown to be able to explain key features of linear filter- ing properties [4] and some single cell nonlinear effects [5]. However, population statistics of nonlinear proper- ties have not been studied in these models. In addition, inhibitory cells were not typically modeled. Here we demonstrate that many of the aforemen- tioned excitatory cell and inhibitory cell properties emerge naturally from a network that implements sparse coding. To be specific, several nCRF effects including surround suppression, contrast invariant orientation tuning, and cross orientation suppression emerge in the excitatory cell population as a result of sparse coding strategy; the excitatory to inhibitory cell ratio could be understood largely as a result of the overcompletness of representation; moreover, a subpopulation of inhibitory interneurons exhibit orientation tuning due to sparse recurrent connections with the principal cells; another subpopulation displays untuned properties due to low rank connectivity patterns. We also demonstrate that the network exhibits balanced excitation a

There are no comments yet on this publication. Be the first to share your thoughts.