Toward an Integrated Science of Decision Making: Bridging Levels of Analysis with the Leaky Competing Accumulator Model James L. McClelland Lucie Stern Professor Chair of Department of Psychology and Director of Center for Mind, Brain, and Computation Stanford University http://waldron.stanford.edu/~jlm/ July 14-15, 2012

Abstract

In this talk I will emphasize how considerations from neuroscience, neuroeconomics, and decision science, and computational models of human cognition come together in the development of an integrative approach to understanding how decision making occurs in the human brain.  I will describe how the Leaky Competing Accumulator model serves as a bridge between detailed biological models on the one hand and optimality analyses on the other, providing a framework in which to understand a wide range of aspects of human decision making.  Within this context I will discuss the idea, central to the LCA and some other recent models, that human decision states should are best viewed, not as fixed states that arise when a decision bound is reached, nor yet as completely continuous states such as those of a linear system, but as states that capture elements of both gradedness and continuity, as well as aspects of both stability and flexibility.

Short bio

Jay McClelland received his Ph.D. in Cognitive Psychology from the University of Pennsylvania in 1975. He served on the faculty of the University of California, San Diego, before moving to Carnegie Mellon in 1984, where he became a University Professor and held the Walter Van Dyke Bingham Chair in Psychology and Cognitive Neuroscience. He was a founding Co-Director of the Center for the Neural Basis of Cognition, a joint project of Carnegie Mellon and the University of Pittsburgh. In 2006 McClelland moved to Stanford University, where he is now Lucie Stern Professor in the Social Sciences, Chair of the Department of Psychology, and founding Director of the Center for Mind, Brain and Computation.

Over his career, McClelland has contributed to both the experimental and theoretical literatures in a number of areas, most notably in the application of connectionist/parallel distributed processing models to problems in perception, cognitive development, language learning, and the neurobiology of memory. He was a co-founder with David E. Rumelhart of the Parallel Distributed Processing (PDP) research group, and together with Rumelhart he led the effort leading to the publication in 1986 of the two-volume book, Parallel Distributed Processing, in which the parallel distributed processing framework was laid out and applied to a wide range of topics in cognitive psychology and cognitive neuroscience. McClelland and Rumelhart jointly received the 1993 Howard Crosby Warren Medal from the Society of Experimental Psychologists, the 1996 Distinguished Scientific Contribution Award from the American Psychological Association, the 2001 Grawemeyer Prize in Psychology, and the 2002 IEEE Neural Networks Pioneer Award for this work. McClelland has served as Senior Editor of Cognitive Science, as President of the Cognitive Science Society, and as a member of the National Advisory Mental Health Council, and he is currently President of the Federation of Associations in Behavioral and Brain Sciences (FABBS). He is a member of the National Academy of Sciences, and he has received the APS William James Fellow Award for lifetime contributions to the basic science of psychology.

McClelland currently teaches on the PDP approach to cognition and its neural basis in the Psychology Department and in the Symbolic Systems Program at Stanford and conducts research on learning, memory, conceptual development, decision making, and semantic cognition.