Vector-Based Integration of Local and Long-Range Information in Visual Cortex


Autoria(s): Somers, David C.; Todorov, Emanuel V.; Siapas, Athanassios G.; Sur, Mriganka
Data(s)

20/10/2004

20/10/2004

18/01/1996

Resumo

Integration of inputs by cortical neurons provides the basis for the complex information processing performed in the cerebral cortex. Here, we propose a new analytic framework for understanding integration within cortical neuronal receptive fields. Based on the synaptic organization of cortex, we argue that neuronal integration is a systems--level process better studied in terms of local cortical circuitry than at the level of single neurons, and we present a method for constructing self-contained modules which capture (nonlinear) local circuit interactions. In this framework, receptive field elements naturally have dual (rather than the traditional unitary influence since they drive both excitatory and inhibitory cortical neurons. This vector-based analysis, in contrast to scalarsapproaches, greatly simplifies integration by permitting linear summation of inputs from both "classical" and "extraclassical" receptive field regions. We illustrate this by explaining two complex visual cortical phenomena, which are incompatible with scalar notions of neuronal integration.

Formato

11 p.

2170488 bytes

1066936 bytes

application/postscript

application/pdf

Identificador

AIM-1556

CBCL-127

http://hdl.handle.net/1721.1/7190

Idioma(s)

en_US

Relação

AIM-1556

CBCL-127

Palavras-Chave #MIT #Receptive Field #Cortical Circuits #Modules #Cortical Inhibition #Computational Neuroscience.