Thomas V. Wiecki

Brown University, Providence, RI 
Computational Cognitive Neuroscience, Response Inhibition, Hierarchical Bayesian Modeling
"Thomas Wiecki"
Cross-listing: Neurotree

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Lawlor VM, Webb CA, Wiecki TV, et al. (2019) Dissecting the impact of depression on decision-making. Psychological Medicine. 1-10
Lawlor V, Webb C, Wiecki T, et al. (2019) T139. Dissecting the Impact of Depression on Decision-Making During a Probabilistic Reward Task Biological Psychiatry. 85: S183
Dutilh G, Annis J, Brown SD, et al. (2018) The Quality of Response Time Data Inference: A Blinded, Collaborative Assessment of the Validity of Cognitive Models. Psychonomic Bulletin & Review
Boehm U, Annis J, Frank MJ, et al. (2018) Estimating across-trial variability parameters of the Diffusion Decision Model: Expert advice and recommendations Journal of Mathematical Psychology. 87: 46-75
Wiecki TV, Antoniades CA, Stevenson A, et al. (2016) A Computational Cognitive Biomarker for Early-Stage Huntington's Disease. Plos One. 11: e0148409
Dillon DG, Wiecki T, Pechtel P, et al. (2015) A computational analysis of flanker interference in depression. Psychological Medicine. 45: 2333-44
Frank MJ, Gagne C, Nyhus E, et al. (2015) fMRI and EEG predictors of dynamic decision parameters during human reinforcement learning. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 35: 485-94
Wiecki TV, Poland J, Frank MJ. (2015) Model-Based Cognitive Neuroscience Approaches to Computational Psychiatry: Clustering and Classification Clinical Psychological Science. 3: 378-399
Cavanagh JF, Wiecki TV, Kochar A, et al. (2014) Eye tracking and pupillometry are indicators of dissociable latent decision processes. Journal of Experimental Psychology. General. 143: 1476-88
Wiecki TV, Sofer I, Frank MJ. (2013) HDDM: Hierarchical Bayesian estimation of the Drift-Diffusion Model in Python. Frontiers in Neuroinformatics. 7: 14
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