Alireza Soltani

Psychological and Brain Sciences Dartmouth College, Hanover, NH, United States 
Computational Neuroscience; Cognitive Neuroscience
"Alireza Soltani"
Mean distance: 12.31 (cluster 17)
Cross-listing: BCM Tree


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Xiao-Jing Wang grad student 2002-2006 Brandeis
 (Neural mechanism underlying reward -dependent choice behavior: A cortical network model of probabilistic decision making.)
Christof Koch post-doc 2007-2009 Caltech
P Read Montague post-doc 2009-2011 Baylor
Tirin Moore research scientist 2011-2013 Stanford Univ. School of Medicine


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Shiva Farashahi grad student 2014- Dartmouth
Mehran Spitmaan grad student 2016- Dartmouth
Mohsen Rakhshan grad student 2017- Dartmouth
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Rakhshan M, Lee V, Chu E, et al. (2019) Influence of Expected Reward on Temporal Order Judgment. Journal of Cognitive Neuroscience. 1-17
Spitmaan M, Horno O, Chu E, et al. (2019) Combinations of low-level and high-level neural processes account for distinct patterns of context-dependent choice. Plos Computational Biology. 15: e1007427
Farashahi S, Donahue CH, Hayden BY, et al. (2019) Flexible combination of reward information across primates. Nature Human Behaviour
Soltani A, Izquierdo A. (2019) Adaptive learning under expected and unexpected uncertainty. Nature Reviews. Neuroscience
Spitmaan M, Chu E, Soltani A. (2019) Salience-driven value construction for adaptive choice under risk. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience
Dehaqani MA, Vahabie AH, Parsa M, et al. (2018) Selective Changes in Noise Correlations Contribute to an Enhanced Representation of Saccadic Targets in Prefrontal Neuronal Ensembles. Cerebral Cortex (New York, N.Y. : 1991)
Farashahi S, Rowe K, Aslami Z, et al. (2018) Influence of learning strategy on response time during complex value-based learning and choice. Plos One. 13: e0197263
Farashahi S, Azab H, Hayden B, et al. (2018) On the flexibility of basic risk attitudes in monkeys. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience
Farashahi S, Ting CC, Kao CH, et al. (2018) Dynamic combination of sensory and reward information under time pressure. Plos Computational Biology. 14: e1006070
Farashahi S, Rowe K, Aslami Z, et al. (2017) Feature-based learning improves adaptability without compromising precision. Nature Communications. 8: 1768
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