Assistant Professor of Psychological and Brain Sciences
My research focuses on understanding influences of reward on two main cognitive functions, decision making and selective attention. I am interested in understanding neural mechanisms underlying these cognitive processes and exploring how computations required for these processes are performed by neuronal elements in the brain. We use detailed computational modeling at different levels (synaptic, cellular, and network) to look for feasible mechanisms that account for both behavioral and neural data, and to make testable predictions. We also use various experimental approaches to test some of these predictions to ultimately link cognitive processes to biophysical properties and limitations of the nervous system.
Farashahi S, Donahue CH, Khorsand P, Seo H, Lee D, and Soltani A (2017). Metaplasticity as a Neural Substrate for Adaptive Learning Choice under Uncertainty. Neuron. 94(2), 401–414
Soltani A, Khorsand P, Guo CZ, Farashahi S, Liu J (2016) Neural Substrates of Cognitive Biases during Probabilistic Inference. Nature Communications, 7:11393
Gu X, Lohrenz TM, Salas R, Baldwin PR, Soltani A, Kirk U, Cinciripini P, Montague PR (2015). Belief about nicotine selectively modulates value and reward prediction signals in smokers. Proceedings of the National Academy of Sciences, 112 (8): 2539–44.
Soltani A, Noudoost B, Moore T (2013) Dissociable Dopaminergic Control of Saccadic Target Selection and its Implications for Reward Modulation. Proceedings of the National Academy of Sciences, 110 (9): 3579-84
Hunt LT, Kolling N, Soltani A, Woolrich MW, Rushworth MFS, Behrens TEJ (2012) Mechanisms Underlying Cortical Activity During Value-guided Choice. Nature Neuroscience, 15(3): 470-476
Soltani A, Wang X-J (2010) Synaptic Computation Underlying Probabilistic Inference. Nature Neuroscience, 13(1): 112-119
Soltani A, Koch C (2010) Visual Saliency Computations: Mechanisms, Constraints, and the Effect of Feedback. Journal of Neuroscience, 30(38): 12831-43
Soltani A, Wang X-J (2006) A Biophysically-based Neural Model of Matching Law Behavior: Melioration by Stochastic Synapses. Journal of Neuroscience, 26(14): 3731-3744