Public resources (code/data)

Razmi, N.,  & Nassar, M. R. Adaptive learning through temporal dynamics of state representation. (2022) Journal of Neuroscience. 


Kobayashi, K., Lee, S., Filipowicz, A. L. S., McGaughey, K. D., Kable, J. W. & Nassar, M. R. Dynamic representation of the subjective value of information. (2021) Journal of Neuroscience,

Code + Behavioral Data

Neuroimaging data

Nassar MR, Scott D, Bhandari A. Noise correlations for faster and more robust learning (2021) Journal of Neuroscience:

Code & Supplementary Material

Nassar MR, Waltz JA, Albrecht MA, Gold JM, Frank MJ. All or nothing belief updating in patients with schizophrenia reduces precision and flexibility of beliefs. (2021) Brain:

Code + Data

Nassar MR, Troiani V. The stability flexibility tradeoff and the dark side of detail (2020) Cognitive, Affective, & Behavioral Neuroscience.

Code + Data

*Jang A, *Nassar M, Dillon D, Frank M. Positive reward prediction errors during decision-making strengthen memory encoding (2019), Nature Human Behaviour:

Code + Data

Nassar M, Bruckner R, Frank MJ. Statistical context dictates the relationship between feedback-related EEG signals and learning (2019), eLife:

Code  ,  Data

Nassar M, Wilson B, Heasly B, Gold JI. An approximately Bayesian delta-rule model explains the dynamics of belief updating in a changing environment. (2010), Journal of Neuroscience:

Model Code

Lab resources

Lab wiki