We have broad research interests in understanding the relationship between various cognitive functions and their underlying neural substrates, using both computational and experimental approaches. The overarching theme of research in the lab is focused on value-based learning, decision making, and attention.



Alireza Soltani

 Dr. Soltani is a neuroscientist with training in computational and cognitive neuroscience and theoretical physics. He obtained a Ph.D. in Physics with a focus in Computational Neuroscience from Brandeis University working with Xiao-Jing Wang. Following his Ph.D., he has done postdoctoral research with Christof Koch at Caltech, Read Montague at Baylor, and Tirin Moore at Stanford.

Dr. Soltani's research mainly focuses on understanding influences of reward on two main cognitive functions: decision making and selective attention. Specifically, he is 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. To achieve this goal, he uses detailed computational modeling at different levels (synaptic, cellular, and network), as well as psychophysics and behavioral studies, to look for feasible mechanisms that account for both behavioral and neural data. The ultimate goal is to bridge the gap between cognitive and neuronal processes, and further explain behavioral laws in terms of biophysical parameters and constraints.

A central part of this research involves collaboration with experimentalists who work with rats, monkeys, and humans, and use a wide range of methods such as electrophysiology, MEG, fMRI, psychophysics, and behavioral economics.


Attention-Related Publications

Dehaqani MR, Vahabie AH, Parsa M, Noudoost B, Soltani A (2016). Enhanced representation of space by prefrontal neuronal ensembles and its dependence on cognitive states. bioRxiv, 065581.

Soltani A, Khorsand P, Guo CZ, Farashahi S, Liu J (2016). Neural substrates of cognitive biases during probabilistic inference. Nature Communications, 7:11393.

Khorsand P, Moore T, Soltani A (2015). Combined contribution of feedforward and feedback inputs to bottom-up attention. Frontiers in Psychology, 6(155):1-11.

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 of the USA, 110(9):3579-84.

Soltani A, Koch C (2010). Visual saliency computations: mechanisms, constraints, and the effect of feedback. Journal of Neuroscience, 30(38):12831-43.