Codes & Datasets

If you download the following datasets or packages and plan to use them in your publications, please make sure to cite the corresponding papers. Also, please respect the licenses and special requests attached to each dataset or package.

The following packages are free software. You can redistribute them and/or modify them under the terms of the GNU General Public License, or alternative licenses specified in the package.

Salience-driven value construction for adaptive choice under risk by Spitmaan, Chu and Soltani (2019)

The package contains all the data you need to run the analysis plus some code in order to read the data [github].

Citation:

  • Spitmaan, M., Chu, E., & Soltani, A. (2019). Salience-driven value construction for adaptive choice under risk. Journal of Neuroscience, 39(26), 5195-5209.
Dynamic combination of sensory and reward information under time pressure by Farashahi et al (2018)

The package contains all the data you need to run the analysis plus some code in order to read the data [download].

Citation:

  • Farashahi, S., Ting, C. C., Kao, C. H., Wu, S. W., & Soltani, A. (2018). Dynamic combination of sensory and reward information under time pressure. PLoS computational biology, 14(3), e1006070.
Feature-based learning improves adaptability without compromising precision by Farashahi et al (2017)

The package contains all the experimental data plus some codes in order to read the data and perform some basic data analyses [Dataset download; Code download (github)].

Citation:

  • Farashahi, S., Rowe, K., Aslami, Z., Lee, D., & Soltani, A. (2017). Feature-based learning improves adaptability without compromising precision. Nature communications, 8(1), 1768.
  • Farashahi, S., Rowe, K., Aslami, Z., Gobbini, M. I., & Soltani, A. (2018). Influence of learning strategy on response time during complex value-based learning and choice. PloS one, 13(5), e0197263.