|Last updated September 27, 2012|
James L. (Jay) McClelland
Lucie Stern Professor in the Social Sciences
Director, Center for Mind, Brain and Computation
Department of Psychology
344 Jordan Hall, Bldg 420
One line of research in my lab was inspired by the striking pattern of spared and impaired memory in patients with damage to the hippocampal region, suggesting that different parts of the brain play different, specialized roles in memory. In a paper with a colleague and a former student (McClelland, McNaughton, and O'Reilly, 1995), we suggested that the hippocampus and neocortex may play complementary roles in learning and memory. The neocortex uses a very gradual learning procedure that allows it to exploit the structure in ensembles of inputs. The hippocampus is needed to complement the neocortex, providing a mechanism for rapid learning of the specific arbitrary aspects of particular items. The results of this rapid learning are gradually integrated into the neocortical system, accounting for the pattern of retrograde amnesia seen in many amnesic patients. We are now considering how the neocortex may learn and represent semantic knowledge, addressing children's acquisition of knowledge of living things and the deterioration of this knowledge in dementia. Developmental data suggest a progressive differentiation of concepts: We distinguish animals from plants before we distinguish birds from fish, or canaries from robins. In semantic dementia this trend reverses, so that the finer distinctions are lost before more general ones. These findings coexist with the fact that in some tasks, there appears to be a priority for accessing and naming concepts at an intermediate ("basic") level of specificity (e.g., bird is more accessible than animal or robin). Current work with a former student (McClelland and Rogers, 2003; Rogers and McClelland, 2004) addresses all these phenomena in a single model, where they reflect the interplay of frequency and concept similarity in determining the semantic representations of concepts and the ease with which distinct names may be assigned to them. We also apply the approach to show that many findings that have been taken as supporting the existance of innate naive domain theories can arise from the kind of learning process that takes place in connectionist networks. A BBS multiple book review of this work (Rogers and McClelland, 2008) provides an overview of this work, along with commentaries by many researchers who work in related areas, and our reply to the commentaries, which comes at the end of the multiple book review, and presents new simulation studies supporting some of our arguments for our approach. Ongoing work on this topic is described in my Rumelhart prize lecture, delivered at the Cogntive Science Society meeting in Portland, Oregon in August, 2010.
My lab is also currently involved in an extensive collaborative investigation of the dynamics of decision making, building on earlier work with Marius Usher (Usher & McClelland, 2001). We are pursuing the perspective that human decision states simultaneously exhibit both categorical and discrete characteristics. That is, there tends to be a bifurcation during decision making, leading to a state favoring one altenative or another, but this state is still graded, and sensitive to differences in the strength of support for the state, and even subject to reversal as further evidence accumulates. This work links my laboratory with the Newsome primate neurophysiology laboratory at Stanford, the labs of Jon Cohen and Phil Holmes at Princeton and the labs of Nathan Urban in Pittsburgh and Marius Usher in Tel Aviv.
I retain a strong interest in the nature, processing, and learning of language. In my view, linguistic structure and language processing exhibit far more graded structure than is recognized by some of the most prominent researchers in linguistics and language processing research. I have collaborated with the linguist Joan Bybee in voicing this view (Bybee and McClelland, 2005; McClelland and Bybee, 2007), and I am pursuing a graded constraint satisfaction approach to understanding the factors that determine the goodness of phonological word forms (McClelland and VanderWyk, 2006). One specific line of research concerns the presence of graded signs of regularity in exceptions (Lupyan and McClelland, 2003). These signs appear to reflect a balance between a pressure favoring regularity and another pressure favoring simplicity, producing reductions of what would be the fully regular form among high frequency exceptions.
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 (see citation) 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.