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bioRxiv · 10.1101/501858

The impact of learning on perceptual decisions and its implication for speed-accuracy tradeoffs

Mendonca, A. G.·Drugowitsch, J.·Vicente, M. I.·DeWitt, E.·Pouget, A.·Mainen, Z. F.
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Abstract

In standard models of perceptual decision-making, noisy sensory evidence is considered to be the primary source of choice errors and the accumulation of evidence needed to overcome this noise gives rise to speed-accuracy tradeoffs. Here, we investigated how the history of recent choices and their outcomes interacts with these processes using a combination of theory and experiment. We found that the speed and accuracy of performance of rats on olfactory decision tasks could be best explained by a Bayesian model that combines reinforcement-based learning with accumulation of uncertain sensory evidence. This model predicted the specific pattern of trial history effects that were found in the data. The results suggest that learning is a critical factor contributing to speed-accuracy tradeoffs in decision-making and that task history effects are not simply biases but rather the signatures of an optimal learning strategy.

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Mendonca, A. G., Drugowitsch, J., Vicente, M. I., DeWitt, E., Pouget, A., Mainen, Z. F.. 2018-12-19. The impact of learning on perceptual decisions and its implication for speed-accuracy tradeoffs. https://doi.org/10.1101/501858

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