Dopamine transients encode reward prediction errors independent of learning rates

This behavioral and modeling data was used and described in the following paper: Mah, A., Golden C.E.M., Constantinople, C.M. (2023). Dopamine transients encode reward prediction errors independent of learning rates. Cell Reports. 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. Photometry data used in Figure 4 is used in other studies currently under review and will be made publically avaiable once all other studies are published. 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.