About me

I am a computational and cognitive neuroscientist interested in studying the mind, brain and mental diseases. I am currently a postdoctoral researcher at Princeton neuroscience institute, working with Nathaniel Daw. I completed my doctoral studies in cognitive neuroscience under supervision of Ivan Toni and Roshan Cools at Donders Institute. My background is control engineering and machine learning, in which I obtained my bachelor and master from University of Tehran.

The lastest

July 2021: new publication: Piray P, Daw ND, 2021, "Linear reinforcement learning in planning, grid fields, and cognitive control", Nature Communications, in press.

October 2020: new preprint: Piray P, Daw ND, 2020, "Unpredictability vs. volatility and the control of learning", biorxivThis work highlights the role of “unpredictability” in learning, its mutual interdependency with volatility, and their competition to “explain away” observed noise. We further show that failure of explaining away is evident following amygdala damage and anxiety disorders.

July 2020: new publication: Piray P, Daw ND, 2020, "A simple model for learning in volatile environments" published in PLoS Computational Biology.

May 2020: new preprint, Piray P, Daw ND. “Linear reinforcement learning: Flexible reuse of computation in planning, grid fields, and cognitive control”, biorxiv.

Jan 2020: My talk about "Hierarchical Bayesian inference for concurrent model fitting and comparison" at "Transcontinental Computational Psychiatry Workgroup" is available online.

Jan 2020: Code for "Volatile Kalman filter", related to this work: Piray P, Daw ND, 2019, "A simple model for learning in volatile environments", biorxiv.