Can winner-take-all mechanism underlie pop out visual search computation?

Visual search involves active scanning of the environment to locate objects of interest against a background of irrelevant distractors. One widely accepted theory posits that pop out visual search is computed by a winner-take-all (WTA) competition between contextually modulated cells that form a saliency map. However, previous studies have shown that the ability of WTA mechanisms to accumulate information from large populations of neurons is limited, thus raising the question of whether WTA can underlie pop out visual search. To address this question, we conducted a modelling study to investigate how accurately the WTA mechanism performs a pop out task. We analyzed a single-best-cell WTA, where the decision is based on a single winning cell, alongside two types of population readouts, where the decision relies on a winning population of similarly tuned cells. Our results reveal specific limitations in WTA readouts and their capacity to explain the behavioral accuracy reported in pop-out search. Specifically, inherent neuronal heterogeneity prevents the single-best-cell WTA from effectively accumulating information. Furthermore, the accuracy of the generalized population-based WTA is constrained by widely reported noise correlations. Finally, even for an optimal readout that utilizes neural heterogeneity to overcome noise correlations, accuracy remains limited by synaptic coarse-tuning. Taken together, these findings highlight the need to revisit our current understanding of the mechanisms underlying pop-out visual search.