Visual processing in the cortex can be characterized by a predominantly hierarchical architecture, in which specialized brain regions along the processing pathways extract visual features of increasing complexity, accompanied by greater invariance in stimulus properties such as size and position. Various studies have postulated that a nonlinear pooling function such as the maximum (MAX) operation could be fundamental in achieving such selectivity and invariance. In this article, we are concerned with neurally plausible mechanisms that may be involved in realizing the MAX operation. Different canonical models are proposed, each based on neural mechanisms that have been previously discussed in the context of cortical processing. Through simulations and mathematical analysis, we compare the performance and robustness of these mechanisms. We derive experimentally verifiable predictions for each model and discuss the relevant physiological considerations.

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