A novel rodent task combines a memory-guided choice and confidence report
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Rats demonstrate the ability to compute memory confidence
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A deep-neural-network-derived memory decision variable tracks trial difficulty
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A generative model of evolving memory distributions predicts choice and confidence
Summary
Memory enables access to past experiences to guide future behavior. Humans can determine which memories to trust (high confidence) and which to doubt (low confidence). How memory retrieval, memory confidence, and memory-guided decisions are related, however, is not understood. In particular, how confidence in memories is used in decision making is unknown. We developed a spatial memory task in which rats were incentivized to gamble their time: betting more following a correct choice yielded greater reward. Rat behavior reflected memory confidence, with higher temporal bets following correct choices. We applied machine learning to identify a memory decision variable and built a generative model of memories evolving over time that accurately predicted both choices and confidence reports. Our results reveal in rats an ability thought to exist exclusively in primates and introduce a unified model of memory dynamics, retrieval, choice, and confidence.
Graphical abstract
Keywords
memory
behavior
spatial memory
metamemory
confidence
deep neural network
machine learning
decision making
rat
Data and code availability
All original code has been deposited at GitHub: https://github.com/hrjoo/TotalRecall and is publicly available as of the date of publication. All original data have been deposited at Zenodo: https://doi.org/10.5281/zenodo.5123545 and are publicly available as of the date of publication. DOIs are listed in the Key resources table. DOIs are listed in the key resources table. Any additional information required to reanalyze the data reported in this paper will be made available upon reasonable request.