Greg Ashby

Psychology University of California, Santa Barbara, Santa Barbara, CA, United States 
Category Learning, Neurcomputational Modeling, Decison Making
"Greg Ashby"
Mean distance: 14.41 (cluster 15)
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Crossley MJ, Maddox WT, Ashby FG. (2018) Increased cognitive load enables unlearning in procedural category learning. Journal of Experimental Psychology. Learning, Memory, and Cognition
Filoteo JV, Maddox WT, Ashby FG. (2017) Quantitative modeling of category learning deficits in various patient populations. Neuropsychology. 31: 862-876
Turner BO, Crossley MJ, Ashby FG. (2017) Hierarchical control of procedural and declarative category-learning systems. Neuroimage
Valentin VV, Maddox WT, Ashby FG. (2016) Dopamine dependence in aggregate feedback learning: A computational cognitive neuroscience approach. Brain and Cognition. 109: 1-18
Hélie S, Turner BO, Crossley MJ, et al. (2016) Trial-by-trial identification of categorization strategy using iterative decision-bound modeling. Behavior Research Methods
Soto FA, Bassett DS, Ashby FG. (2016) Dissociable changes in functional network topology underlie early category learning and development of automaticity. Neuroimage
Crossley MJ, Horvitz J, Balsam P, et al. (2015) Expanding the Role of Striatal Cholinergic Interneurons and the Midbrain Dopamine System in Appetitive Instrumental Conditioning. Journal of Neurophysiology. jn.00473.2015
Paul EJ, Smith JD, Valentin VV, et al. (2015) Neural networks underlying the metacognitive uncertainty response. Cortex; a Journal Devoted to the Study of the Nervous System and Behavior. 71: 306-322
Crossley MJ, Paul EJ, Roeder JL, et al. (2015) Declarative strategies persist under increased cognitive load. Psychonomic Bulletin & Review
Cantwell G, Crossley MJ, Ashby FG. (2015) Multiple stages of learning in perceptual categorization: evidence and neurocomputational theory. Psychonomic Bulletin & Review
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