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Journal Article

Synchronous inhibition as a mechanism for unbiased selective gain control

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons83805

Bethge,  M
Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Bethge, M. (2001). Synchronous inhibition as a mechanism for unbiased selective gain control. Neurocomputing, 38-40, 483-488. doi:10.1016/S0925-2312(01)00373-3.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-E272-6
Abstract
While there are many experiments providing evidence for synchronized neuronal activity, there is little agreement about its functional role. Since many proposals rely on the assumption that neuronal activity can be modulated by top-down or feedback signals in a multiplicative way, it is a critical question how the dynamics of neurons may account for a selective control of their gain. In this paper we present a novel gain control mechanism based on the interplay of synaptic depression and synchronous inhibition. From simulations of a two-layered model of populations of integrate-and-fire neurons connected by stochastic depressing synapses, we conclude that synchronous inhibition can act as a selective gain control signal, which may be relevant, in particular when sensory processing reflects an ongoing process of hypotheses testing.