Ensemble accumulator modeling of speed-accuracy tradeoff in visual search

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 DESCRIPTION (provided by applicant): The goal of this proposal is to carry out research training to develop new expertise in cognitive modeling that is inspired and constrained by neurophysiology. My previous work in human group decision making, and the sponsors' recent formulation of a novel modeling framework to explore neural ensemble decision making, yields an excellent opportunity for new training and interdisciplinary collaboration. Aim 1 will systematically investigate the relationship between neurons, instantiated as evidence accumulators, and the collective behavior of ensembles of neural accumulators in decision choice tasks; predicted choice behavior and dynamics of ensembles will be compared to observed saccade choice behavior and measured neural dynamics of awake behaving monkeys. Aim 2 will significantly extend this work by exploring alternative computational mechanisms for aggregation across accumulators in an ensemble, with hypotheses for alternative aggregation schemes drawn from other domains of group decision making. Training potential is high because the work will develop new computational models of decisions made by ensembles of neurons, an area of research in which I have no prior experience, but which offers exciting new directions for linking to my prior work on the Wisdom of Crowds. Forging novel connections between my new postdoctoral work and my previous PhD work will form a basis for my future research as an independent investigator. The findings have potential wide interest and applicability, as it may shed insight into how ensembles of neurons collectively make decisions in the brain.