Rats and Humans Can Optimally Accumulate Evidence for Decision-Making

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Science  05 Apr 2013:
Vol. 340, Issue 6128, pp. 95-98
DOI: 10.1126/science.1233912

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How to Make Decisions

Recently, a number of methods to probe internal properties of nonlinear neural systems have been developed. In these methods, highly variable stimuli are used to explore the input space of the system. Neural responses are then studied using models that take advantage of the known trial-by-trial stimulus information. Brunton et al. (p. 95) adapted this combined approach to decision-making. Both in rats and humans, the diffusion constant of the drift-diffusion model of decision-making was zero, implying that the noise is all in the processing of sensory input and not in the evidence accumulator. In addition, rats gradually accumulated evidence for decision-making, with strong effects of sensory adaptation on gradual accumulation of evidence.


The gradual and noisy accumulation of evidence is a fundamental component of decision-making, with noise playing a key role as the source of variability and errors. However, the origins of this noise have never been determined. We developed decision-making tasks in which sensory evidence is delivered in randomly timed pulses, and analyzed the resulting data with models that use the richly detailed information of each trial’s pulse timing to distinguish between different decision-making mechanisms. This analysis allowed measurement of the magnitude of noise in the accumulator’s memory, separately from noise associated with incoming sensory evidence. In our tasks, the accumulator’s memory was noiseless, for both rats and humans. In contrast, the addition of new sensory evidence was the primary source of variability. We suggest our task and modeling approach as a powerful method for revealing internal properties of decision-making processes.

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