Psychology and neurobiology of simple decisions

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Abstract

Patterns of neural firing linked to eye movement decisions show that behavioral decisions are predicted by the differential firing rates of cells coding selected and nonselected stimulus alternatives. These results can be interpreted using models developed in mathematical psychology to model behavioral decisions. Current models assume that decisions are made by accumulating noisy stimulus information until sufficient information for a response is obtained. Here, the models, and the techniques used to test them against response-time distribution and accuracy data, are described. Such models provide a quantitative link between the time-course of behavioral decisions and the growth of stimulus information in neural firing data.

Section snippets

Neural correlates of simple two-choice decisions

Neural activity linked to eye movement decisions has been recorded in several visual tasks (Figure 1) from oculomotor areas including the middle temporal area (MT), the lateral interparietal area (LIP) in extrastriate cortex [8], the frontal eye field (FEF) 9, 10, 11, and the superior colliculus (SC) 12, 13, 14. These structures are part of the circuit that controls saccadic eye movements to behaviorally salient targets [3]. For example, in the oddball discrimination task, monkeys are trained

From neurons to sequential-sampling models

The picture that emerges from these findings is strikingly consistent with statistical decision models that have been developed during the past 40 years in mathematical psychology. Two broad classes of model have been developed that apply to different kinds of decisions. One class, of sequential-sampling models, applies to speeded decisions in perceptual and memory tasks 1, 21. These decisions are typically made within a second or so. A second class, based on economic concepts of expected

Testing behavioral models

Behavioral research in psychology has identified several key patterns of data that must be explained by any plausible model for two-choice tasks. First, there are systematic relationships between RT and accuracy; explanation of these relationships requires a model capable of producing errors 48, 49. Second, a model must account for the ordering of mean RTs for correct responses and errors across experimental conditions – that is, across the values of manipulated variables and across levels of

Linking neurobiology and psychology

A model that seeks to link neurobiology and behavior needs to relate three levels of analysis: the spike trains of individual neurons, the statistical properties of the neural ensemble, and behavioral data. A successful model would simultaneously account for data on all three levels. Whether decisions are based on single cells, small groups of cells or populations of cells is an open question. Some authors have reported that individual neurons predict responses that match the accuracy of

Concluding remarks

The picture that emerges from recent single-cell studies of decision making in neuroscience is strikingly consistent with the picture that emerges from behavioral studies of decision making in psychology. In both, decisions are made by mechanisms that accumulate noisy information to a response criterion. Such mechanisms have been inferred from the results of behavioral experiments, but recent single-cell studies have begun to provide complementary evidence. Future theoretical progress in this

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