Abstract
Decision-making behavior is often characterized by substantial variability, but its source remains unclear. We developed a visual accumulation of evidence task designed to quantify sources of noise and to be performed during voluntary head restraint, enabling cellular resolution imaging in future studies. Rats accumulated discrete numbers of flashes presented to the left and right visual hemifields and indicated the side that had the greater number of flashes. Using a signal-detection theory-based model, we found that the standard deviation in their internal estimate of flash number scaled linearly with the number of flashes. This indicates a major source of noise that, surprisingly, is not consistent with the widely used 'drift-diffusion modeling' (DDM) approach but is instead closely related to proposed models of numerical cognition and counting. We speculate that this form of noise could be important in accumulation of evidence tasks generally.
Highlights
Subjects performing perceptual decision-making tasks display a large amount of trial-to-trial behavioral variability
In our rat visual accumulation of evidence task (Figure 1A and B), subjects initiate a trial by inserting their nose into the center port of a three-port operant conditioning chamber
In this study we developed a visual accumulation of evidence task to study the sources of noise that contribute to behavioral variability
Summary
Subjects performing perceptual decision-making tasks display a large amount of trial-to-trial behavioral variability. Determining the sources of this variability could provide insight into the neural mechanisms of decision-making and produce more accurate predictions of behavior. It has been proposed that behavioral variability is caused in part by noise accruing during the process of evidence accumulation. This noise may have a variety of origins depending on the behavioral task. It can be inherent in the natural world, produced by the signal detection limits of sensory organs themselves (Barlow and Levick, 1969), or it may reflect the variability of neural responses in the brain at different stages of processing. Previous studies have attempted to trace the sources of noise using a combination of behavioral and neurophysiological approaches
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