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Neurocomputing 32}33 (2000) 623}628 Gain modulation of recurrent networks
 

Summary: Neurocomputing 32}33 (2000) 623}628
Gain modulation of recurrent networks
Jian Zhang*, L.F. Abbott
Volen Center for Complex Systems Department of Biology, Brandeis University, Waltham,
MA 02454-9110, USA
Accepted 13 January 2000
Abstract
Gain modulation is an important mechanism by which attentional and other inputs modify
the amplitude of neuronal responses without changing their selectivity. Gain modulation has
been studied previously in feedforward circuits but not in recurrent neural networks. We show
how gain modulation modi"es the response of a recurrent network to feedforward inputs. Even
modest gain modulation of the recurrent network can cause downstream neurons to switch
from a state in which they are unresponsive to a stimulus to a state where they respond
selectively. Funneling the recurrent connections of a network through gain modulated neurons
allows the selectivity within the network to be modi"ed by modulatory inputs. 2000
Elsevier Science B.V. All rights reserved.
Keywords: Recurrent model; Switching; Gain modulation; Attention
1. Introduction
Neuronal responses can change over short time scales due to attentional e!ects and
processes related to motor response selection and activation. Goldberg et al. [7] have

  

Source: Abbott, Laurence - Center for Neurobiology and Behavior & Department of Physiology and Cellular Biophysics, Columbia University

 

Collections: Biology and Medicine