Neurally constrained modeling of perceptual decision making.

Abstract

Stochastic accumulator models account for response time in perceptual decision-making tasks by assuming that perceptual evidence accumulates to a threshold. The present investigation mapped the firing rate of frontal eye field (FEF) visual neurons onto perceptual evidence and the firing rate of FEF movement neurons onto evidence accumulation to test alternative models of how evidence is combined in the accumulation process. The models were evaluated on their ability to predict both response time distributions and movement neuron activity observed in monkeys performing a visual search task. Models that assume gating of perceptual evidence to the accumulating units provide the best account of both behavioral and neural data. These results identify discrete stages of processing with anatomically distinct neural populations and rule out several alternative architectures. The results also illustrate the use of neurophysiological data as a model selection tool and establish a novel framework to bridge computational and neural levels of explanation. Keywordsperceptual decision making; stochastic accumulator models; mental chronometry; frontal eye field Mathematical psychology has converged on a general framework to explain the time course of perceptual decisions. Models that assume perceptual information accumulates to a response threshold provide excellent accounts of decision-making behavior (Bogacz, Brown, Moehlis, Holmes, & Cohen, 2006;Nosofsky & Palmeri, 1997;Palmeri, 1997;Ratcliff & Rouder, 1998;Smith & Van Zandt, 2000;Usher & McClelland, 2001). These accumulator models entail at least two distinct processes: (a) A stimulus must be encoded with respect to the current task to represent perceptual evidence, and (b) some mechanism must accumulate that evidence to reach a decision. Models that assume very different decisionmaking architectures can account for many of the same behavioral phenomena (S. Brown & Heathcote, 2005;S. D. Brown & Heathcote, 2008;. Recently, the observation that the pattern of activity of certain neurons resembles an accumulation to threshold sparked a synthesis of mathematical psychology and neurophysiology (Beck et al., 2008;Boucher, Palmeri, Logan, & Schall, 2007;Bundesen, Habekost, & Kyllingsbaek, 2005;Carpenter, Reddi, & Anderson, 2009;Ditterich, 2006b;Mazurek, Roitman, Ditterich, & Shadlen, 2003;Niwa & Ditterich, 2008;Ratcliff, Cherian, & Segraves, 2003;Ratcliff, Hasegawa, Hasegawa, Smith, & Segraves, 2007;Schall, 2004;Wang, 2002;Wong, Huk, Shadlen, & Wang, 2007;Wong & Wang, 2006). This synthesis is powerful because neurophysiology can constrain key assumptions about the representation of perceptual evidence, the mechanisms that accumulate evidence to threshold, and how the two interact.Correspondence concerning this article should be addressed to Thomas J. Palmeri, Department of Psychology, Vanderbilt University, PMB 407817, 2301 Vanderbilt Place, Nashville, TN 37240-7817. thomas.j.palmeri@vanderbilt.edu. NIH Public Access Author ManuscriptPsychol Rev. Author manuscript; availa...

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