Lapses in perceptual decisions reflect exploration
Abstract
Perceptual decision-makers often display a constant rate of errors independent of evidence strength. These 'lapses' are treated as a nuisance arising from noise tangential to the decision, e.g. inattention or motor errors. Here, we use a multisensory decision task in rats to demonstrate that these explanations cannot account for lapses' stimulus dependence. We propose a novel explanation: lapses reflect a strategic trade-off between exploiting known rewarding actions and exploring uncertain ones. We tested this model's predictions by selectively manipulating one action's reward magnitude or probability. As uniquely predicted by this model, changes were restricted to lapses associated with that action. Finally, we show that lapses are a powerful tool for assigning decision-related computations to neural structures based on disruption experiments (here, posterior striatum and secondary motor cortex). These results suggest that lapses reflect an integral component of decision-making and are informative about action values in normal and disrupted brain states.
Data availability
Data are publicly available: http://repository.cshl.edu/id/eprint/38957/
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Dataset from: Lapses in perceptual decisions reflect explorationhttps://doi.org/10.14224/1.38957.
Article and author information
Author details
Funding
Army Research Office (W911NF-16-1-0368)
- Sashank Pisupati
- Lital Chartarifsky-Lynn
- Anup Khanal
- Anne K Churchland
National Institutes of Health (R01 EY022979)
- Anne K Churchland
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: All animal procedures and experiments were in accordance with the National Institutes of Healths Guide for the Care and Use of Laboratory Animals and were approved by the Cold Spring Harbor Laboratory Animal Care and Use Committee (protocol 19-16-13-10-7).
Copyright
© 2021, Pisupati et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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