Biologically Plausible Neural Circuits for Realization of Maximum Operations
Author(s)
Yu, Angela J.
Giese, Martin A.
Poggio, Tomaso A
Date Issued
September 1, 2001
Series/Report no.
AIM-2001-022
CBCL-207
Abstract
Object recognition in the visual cortex is based on a hierarchical architecture, in which specialized brain regions along the ventral pathway extract object features of increasing levels of complexity, accompanied by greater invariance in stimulus size, position, and orientation. Recent theoretical studies postulate a non-linear pooling function, such as the maximum (MAX) operation could be fundamental in achieving such invariance. In this paper, we are concerned with neurally plausible mechanisms that may be involved in realizing the MAX operation. Four canonical circuits are proposed, each based on neural mechanisms that have been previously discussed in the context of cortical processing. Through simulations and mathematical analysis, we examine the relative performance and robustness of these mechanisms. We derive experimentally verifiable predictions for each circuit and discuss their respective physiological considerations.
Subjects
AI
maximum operation
invariance
recurrent inhibition
shunting inhibition
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