2022 (3)
Note: °co-first authors; *corresponding author(s).
Woo JH, Aguirre CG, Bari BA, Tsutsui KI, Grabenhorst F, Cohen JY, Schultz W, Izquierdo A, Soltani A* (2022).
Mechanisms of Adjustments to Different Types of Uncertainty in the Reward Environment across Mice and Monkeys. [bioRxiv]
Rakhshan M, Schafer RJ, Moore T, Soltani A* (2022).
Contribution of Frontal Eye Field to Adaptive Choice.
under review [available on SSRN].
Soltani A*, Koechlin E* (2022).
Computational models of adaptive behavior and prefrontal cortex.
Neuropsychopharmacology, 47, 58-71.
2021 (5)
Farashahi S*, Soltani A* (2021).
Computational Mechanisms of Distributed Value Representations and Mixed Learning Strategies.
Nature Communications, 12: 7191
Trepka E°, Spitmaan MM°, Bari BA, Costa VD, Cohen JY, Soltani A* (2021).
Entropy-based metrics for predicting choice behavior based on local response to reward.
Nature Communications, 12: 6567
Soltani A, Murray JD, Seo H, Lee D (2021).
Timescales of cognition in the brain.
Current Opinion in Behavioral Sciences, 41, 30-37.
Harris C°, Aguirre CG°, Kolli S, Das K, Izquierdo A*, Soltani A (2021).
Unique Features of Stimulus-based Probabilistic Reversal Learning.
Behavioral Neuroscience, 135 (4), 550
Soltani A*, Rakhshan M, Schafer RJ, Burrows BE, Moore T (2021).
Separable Influences of Reward on Sensory Processing and Choice.
Journal of Cognitive Neuroscience, 33 (2), 248-262.
2020 (4)
Soltani A (2020).
Learning from Others, but with What Confidence?
Trends in Cognitive Sciences, 24(12), 963-964 [PDF].
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,
Farashahi S°, Xu J°, Wu S-W, Soltani A* (2020).
Learning Arbitrary Stimulus-Reward Associations for Naturalistic Stimuli Involves Transition from Learning about Features to Learning about Objects.
Cognition, 205 (104425) [PDF] [Data]
Rakhshan M°, Lee V°, Chu E°, Harris L, Laiks L, Khorsand P, Soltani A* (2020).
Influence of Expected Reward on Temporal Order Judgment.
Journal of Cognitive Neuroscience, 32(4), 674-690.
2019 (5)
Stolyarova A°, Rakhshan M°, Hart EE , O’Dell TJ, Peters MAK, Lau H, Soltani A*, Izquierdo A* (2019).Contributions of Anterior Cingulate Cortex and Basolateral Amygdala in Decision Confidence and Learning under Uncertainty.
Nature Communications, 10:4704
Featured in Nature Communications Editors’ Highlights
Spitmaan MM°, Horno O°, Chu E, Soltani A* (2019).
Combinations of low-level and high-level neural processes account for distinct patterns
of context-dependent choice. PLOS Computational Biology, 15(10): e1007427
Farashahi S, Donahue C, Hayden B, Lee D, Soltani A* (2019).
Flexible Combination of Reward Information across Primates.
Nature Human Behaviour, 3: 1215–1224 (online copy) [PDF].
Highlighted in PNAS Journal Club
Spotlight in Trends in Cognitive Sciences by Etienne Koechlin
Spitmaan MM°, Chu E°, Soltani A* (2019).
Salience-Driven Value Construction for Adaptive Choice under Risk.
Journal of Neuroscience, 39(26):5195-5209
Soltani A*, Izquierdo A* (2019) [PDF].
Adaptive Learning under Expected and Unexpected Uncertainty.
Nature Reviews Neuroscience, 20(10): 635–644
2018 (4)
Dehaqani MR, Vahabie AH, Parsa M, Noudoost B*, Soltani A* (2018) [PDF].
Selective Changes in Noise Correlations Contributes to an Enhanced Representation of Saccadic Targets in Prefrontal Neuronal Ensembles.
Cerebral Cortex, 28(8),3046–63
Farashahi S, Rowe K, Aslami Z, Gobbini MI, Soltani A* (2018) [PDF].
Influence of Learning Strategy on Response Time during Complex Value-based Learning and Choice.
PLOS ONE, 13(5): e197263
Farashahi S, Azab H, Hayden B, Soltani A* (2018) [PDF].
On the Flexibility of Basic Risk Attitudes in Monkeys.
Journal of Neuroscience, 38(18):4383-98
Farashahi S, Ting C-C, Kao C-H, Wu S-W*, Soltani A* (2018) [PDF].
Dynamic Combination of Sensory and Reward Information under Time Pressure.
PLOS Computational Biology, 14(3): e1006070
2017 (5)
Farashahi S°, Rowe K°, Aslami Z, Lee D, Soltani A* (2017) [PDF].
Feature-based Learning Improves Adaptability without Compromising Precision.
Nature Communications, 8:1768.
Media Coverage: [EurekaAlert][MedicalXpress][Science Newsline]
Khorsand P*, Soltani A* (2017) [PDF].
Optimal Structure of Metaplasticity for Adaptive Learning.
PLOS Computational Biology, 13(6): e1005630
Chauhan V, Visconti di Oleggio Castello M, Soltani A, Gobbini MI (2017) [PDF].
Social Saliency of the Cue Slows Attention Shifts.
Frontiers in Psychology, 8(738): 1-11
Farashahi S, Donahue CH, Khorsand P, Seo H, Lee D, Soltani A* (2017) [PDF].
Metaplasticity as a Neural Substrate for Adaptive Learning Choice under Uncertainty.
Neuron, 94(2), 401–414.
Media Coverage: [EurekaAlert][MedicalXpress][Medical News Today][Medindia][Psych Central][Science Newsline]
Recommended by Faculty of 1000
Soltani A, Chaisangmongkon W, Wang X-J (2017) [PDF].
Neural Circuit Mechanisms of Value-Based Decision-Making and Reinforcement Learning.
in Decision Neuroscience. Dreher JC and Tremblay L (Eds.). Academic Press.
2016 (2)
Soltani A*, Khorsand P, Guo CZ, Farashahi S, Liu J (2016) [PDF].
Neural Substrates of Cognitive Biases during Probabilistic Inference.
Nature Communications, 7:11393
Media coverage: [EurekaAlert][MedicalXpress][DailyMail][ScienceDaily][NatureMiddleEast][NatureAsia][LabEquip]
Gu X, Lohrenz TM, Salas R, Baldwin PR, Soltani A, Kirk U, Cinciripini P, Montague PR (2016) [PDF].
Belief about Nicotine Modulates Subjective Craving and Insula Activity in Deprived Smokers.
Frontiers in Psychiatry, 7(126): 1-11
2015 (2)
Khorsand P, Moore T, Soltani A* (2015) [PDF].
Combined Contribution of Feedforward and Feedback Inputs to Bottom-up Attention.
Frontiers in Psychology, 6(155): 1-11
Gu X, Lohrenz TM, Salas R, Baldwin PR, Soltani A, Kirk U, Cinciripini P, Montague PR (2015) [PDF].
Belief about Nicotine Selectively Modulates Value and Reward Prediction Signals in Smokers.
Proceedings of the National Academy of Sciences, 112 (8), 2539-44
2013 (1)
Soltani A*, Noudoost B, Moore T (2013) [PDF].
Dissociable Dopaminergic Control of Saccadic Target Selection and its Implications for Reward Modulation.
Proceedings of the National Academy of Sciences, 110 (9): 3579-84
before 2013 (7)
Soltani A°*, De Martino B°, Camerer C (2012) [PDF][SI].
A Range-normalization Model of Context-dependent Choice: A New Model and Evidence.
PLoS Computational Biology, 8(7): e1002607
Hunt LT, Kolling N, Soltani A, Woolrich MW, Rushworth MFS, Behrens TEJ (2012) [PDF][SI].
Mechanisms Underlying Cortical Activity During Value-guided Choice.
Nature Neuroscience, 15(3): 470-476
see Nature Neuroscience News and Views on this paper [PDF]
Soltani A*, Koch C (2010) [PDF] [SI].
Visual Saliency Computations: Mechanisms, Constraints, and the Effect of Feedback.
Journal of Neuroscience, 30(38): 12831-43
Soltani A*, Wang X-J* (2010) [PDF] [SI].
Synaptic Computation Underlying Probabilistic Inference.
Nature Neuroscience, 13(1): 112-119
Soltani A*, Wang X-J* (2008) [PDF].
From Biophysics to Cognition: Reward-dependent Adaptive Choice Behavior.
Current Opinion in Neurobiology, 18(2): 209-216
Soltani A, Lee D, Wang X-J (2006) [PDF].
Neural Mechanism for Stochastic Behavior During a Competitive Game.
Neural Networks, 19(8): 1075-1090
Soltani A, Wang X-J (2006) [PDF] [SI].
A Biophysically-based Neural Model of Matching Law Behavior: Melioration by Stochastic Synapses.
Journal of Neuroscience, 26(14): 3731-3744