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Found 11 results
Author Title [ Type] Year Filters: Author is Valentin, Vivian V [Clear All Filters]
Neural networks underlying the metacognitive uncertainty response.
Cortex. 71, 306-22.
(2015). Multiple systems of perceptual category learning: Theory and cognitive tests.
Handbook of categorization in cognitive science. 547–572.
(2005). Modulation of dopamine for adaptive learning: A neurocomputational model.
Computational Brain & Behavior. 1–19.
(2020). FROST: a distributed neurocomputational model of working memory maintenance.
Journal of Cognitive Neuroscience. 17(11), 1728-1743.
(2005). Dopamine dependence in aggregate feedback learning: A computational cognitive neuroscience approach.
Brain & Cognition. 109, 1-18.
(2016). Differential effects of dopamine-directed treatments on cognition.
Neuropsychiatric Disease and Treatment. 11, 1859-1875.
(2015). A computational model of the temporal dynamics of plasticity in procedural learning: Sensitivity to feedback timing.
Frontiers in Psychology. 5, 643.
(2014). Computational cognitive neuroscience: Building and testing biologically plausible computational models of neuroscience, neuroimaging, and behavioral data.
Statistical and process models for cognitive neuroscience and aging. 15–58.
(2007). Multiple systems of perceptual category learning: Theory and cognitive tests.
In H. Cohen and C. Lefebvre (Eds.), Handbook of Categorization in Cognitive Science (Second Edition). 157–188.
(2017). The effects of positive affect and arousal on working memory and executive attention.
In S. Moore & M. Oaksford (Eds.), Emotional Cognition: From Brain to Behaviour. 245–288.
(2002). The categorization experiment: Experimental design and data analysis.
In E. J. Wagenmakers & J. T. Wixted (Eds.), Stevens handbook of experimental psychology and cognitive neuroscience, Fourth Edition, Volume Five: Methodology. New York: Wiley. 307-.
(2018).