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My research mainly focuses on understanding adaptive decision making and learning. Specifically, I am interested in exploring neural mechanisms adaptive processes and how computations required for flexibility in behavior are performed by neuronal elements in the brain. I use detailed computational modeling at different levels (synaptic, cellular, and network), as well as psychophysics and behavioral studies in humans, to look for feasible mechanisms that account for both behavioral and neural data. The ultimate goal of my research is to bridge the gap between cognitive and neuronal processes, and further explain behavioral laws in terms of biophysical parameters and constraints.
Psychological and Brain Sciences
Trepka E, Spitmaan MM, Bari BA, Costa V, Cohen JY, Soltani A (2021). Entropy-Based Metrics for Predicting Choice Behavior Based on Local Response to Reward. Nature Communications, 12:6567.
Spitmaan MM, Seo H, Lee D, Soltani A (2020). Multiple Timescales of Neural Dynamics and Integration of Task-relevant Signals across Cortex. Proceedings of the National Academy of Sciences, 117 (36), 22522-22531
Farashahi S, Donahue C, Hayden B, Lee D, Soltani A (2019). Flexible Combination of Reward Information across Primates. Nature Human Behaviour, 3(11), 1215-1224
Soltani A, Izquierdo A (2019). Adaptive learning under expected and unexpected uncertainty. Nature Reviews Neuroscience, 20(10), 635-644