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Psychological Sciences Faculty

Sebastien HelieSebastien Hélie

Assistant Professor, Mathematical and Computational Cognitive Science

Mailing Address:
Department of Psychological Sciences
Purdue University
703 Third Street
West Lafayette, IN 47907-2081 USA

Campus Address:
Peirce Hall, Room 359

E-mail: shelie@purdue.edu
Telephone: (765) 496-2692
Webpage: http://ccn.psych.purdue.edu/

 

Degree: Ph.D. Universite du Quebec A Montreal, 2007

Research Interests:

Research interests include computational cognitive neuroscience, cognitive neuroscience, categorization, automaticity, rule learning, sequence learning, skill acquisition, intuition in decision-making and creative problem solving.

Recent Publications:

Hélie, S. & Sun, R. (in press). Implicit cognition in problem solving. In. S. Hélie (Ed.) The Psychology of Problem Solving: An Interdisciplinary Approach. Nova Science Publishers.

Hélie, S. (Ed.). (2013). The Psychology of Problem Solving: An Interdisciplinary Approach. Nova Science Publishers.

Sun, R., & Hélie, S. (2013). Psychologically realistic cognitive agents: Taking human cognition seriously. Journal of Experimental & Theoretical Artificial Intelligence. 25, 65-92.

Hélie, S., Paul, E.J., & Ashby, F.G. (2012). A neurocomputational account of cognitive deficits in Parkinson's disease. Neuropsychologia, 50, 2290-2302.

Ell, S. W., Hélie, S., & Hutchinson, S. (2012). Contributions of the putamen to cognitive function. In A. Costa & E. Villalba (Eds.) Horizon in Neuroscience. Volume 7 (pp. 29-52). Nova Publishers.

Hélie, S. & Ashby, F. G. (2012). Learning and transfer of category knowledge in an indirect categorization task. Psychological Research, 76, 292-303.

Hélie, S., Paul, E.J., & Ashby, F.G. (2012). Simulating the effect of dopamine imbalance on cognition: From positive affect to Parkinson’s disease. Neural Networks, 32, 74-85.

Sun, R., & Hélie, S. (2012). Reasoning with heuristics and induction: An account based on the CLARION cognitive architecture. Proceedings of the International Joint Conference on Neural Networks (pp. 1359-1366). Brisbane, AU: IEEE Press.

Ashby, F. G. & Hélie, S. (2011). A Tutorial on Computational Cognitive Neuroscience: Modeling the Neurodynamics of Cognition. Journal of Mathematical Psychology, 55, 273-289.

Hélie, S. & Cousineau, D. (2011). The cognitive neuroscience of automaticity: Behavioral and brain signatures. Cognitive Sciences, 6, 25-43.

Hélie, S., Paul, E. J., & Ashby, F. G. (2011). Simulating Parkinson’s disease patient deficits using a COVIS-based computational model. Proceedings of the International Joint Conference on Neural Networks (pp. 207-214). San Jose, CA: IEEE Press.

Hélie, S., Proulx, R., & Lefebvre, B. (2011). Bottom-up learning of explicit knowledge using a Bayesian algorithm and a new Hebbian learning rule. Neural Networks, 24, 219-232.

Hélie, S. & Sun, R. (2011). How the Core Theory of CLARION Captures Human Decision-Making. Proceedings of the International Joint Conference on Neural Networks (pp. 173-180). San Jose, CA: IEEE Press.

Hélie, S., Roeder, J. L., & Ashby, F. G. (2010). Evidence for cortical automaticity in rule-based categorization. Journal of Neuroscience, 30, 14225-14234.

Hélie, S. & Sun, R. (2010). Creative problem solving: A CLARION theory. Proceedings of the International Joint Conference on Neural Networks (pp. 1460-1466). Barcelona, ES: IEEE Press. Hélie, S. & Sun, R. (2010). Incubation, insight, and creative problem solving: A unified theory and a connectionist model. Psychological Review, 117, 994-1024.

Hélie, S., Waldschmidt, J. G., & Ashby, F. G. (2010). Automaticity in rule-based and information-integration categorization. Attention, Perception, & Psychophysics, 72, 1013-1031.

Hélie, S. & Ashby, G. F. (2009). A neurocomputational model of automaticity and maintenance of abstract rules. Proceedings of the International Joint Conference on Neural Networks (pp. 1192-1198). Atlanta, GA: IEEE Press.

Hélie, S. & Sun, R. (2009). Simulating incubation effects using the Explicit - Implicit Interaction with Bayes factor (EII-BF) model. Proceedings of the International Joint Conference on Neural Networks (pp. 1199-1205). Atlanta, GA: IEEE Press.