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ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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Distinct value computations support rapid sequential decisions

Authors: Mah, Andrew; Schiereck, Shannon; Bossio, Veronica; Constantinople, Christine;

Distinct value computations support rapid sequential decisions

Abstract

This behavioral and modeling data was used and described in the following paper:Mah, A., Schiereck, S.S., Bossio, V., Constantinople, C.M. (2023). Distinct value computations support rapid sequential decisions. Nature Communications.The dataset comprises 1) Behavioral data for the value-based decision making task in rats, and 2) computational models fit to the rat behavioral data. All files are Matlab data (.mat) files. The code to analyze this data and generate all figures in Mah et al., 2023 is available at {https://github.com/constantinoplelab/published/tree/main/rat_behavior. Data was analyzed using Matlab 2023a with the following additional toolboxes:Curve FitterOptimizationSignal Analyzer Funding: This work was supported by a K99/R00 Pathway to Independence Award (R00MH111926), an Alfred P. Sloan Fellowship, a Klingenstein-Simons Fellowship in Neuroscience, an NIH Director's New Innovator Award (DP2MH126376), an NSF CAREER Award, R01MH125571, and a McKnight Scholars Award to C.M.C. A.M. was supported by 5T90DA043219 and F31MH130121. A.M. and S.S.S. were supported by 5T32MH019524.

Related Organizations
Keywords

neuroscience, reinforcement learning, hidden state inference, decision making

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average