Research Biography of James McClelland
Dr. James McClelland’s theoretical and experimental contributions have been instrumental in establishing an alternative to the traditional symbolic theory of mind. In his connectionist alternative, cognition is conceptualized as the emergent result of interactions within interconnected networks of simple neuron-like units. Inspired by the massive parallelism found in brains, local inhibitory and excitatory connections between units give rise to structured thoughts, mental schemas, and memories that are distributed across units. Learning is conceptualized as changes to the efficacy with which units excite or inhibit one another. Drs. McClelland and Rumelhart formed the PDP Research group to pursue this connectionist program, and this group produced the two-volume Parallel Distributed Processing (Rumelhart, McClelland, and the PDP Research Group, 1986). These two volumes galvanized much of the cognitive science community to develop, explore and test new computational models of phenomena in learning, memory, language, and cognitive development.
Much of Dr. McClelland’s work has fused connectionist computational modeling with empirical research in cognitive psychology and neuroscience. He pioneered information processing models in which earlier processing stages do not complete their processing before beginning to send their products to subsequent stages (McClelland, 1979). This cascaded processing dynamic was put to effective use in the joint work with Rumelhart on the Interactive Activation model of word perception. This model was an early and elegant example of a working computational model that showed how it is possible for letter perception to influence word perception at the same time that word perception influences letter perception without these bidirectional influences being viciously circlar (McClelland & Rumelhart, 1981). This model captured many empirical phenomena, including the striking “word superiority effect” in which letters are better identified in the context of words than in isolation or when contained within non-words (Johnston & McClelland, 1974; Rumelhart & McClelland, 1982).
In 1986, Dr. McClelland (in collaboration with Jeffrey Elman) proposed a connectionist model of speech perception and lexical processing based on the idea that word activation and competition unfolds in time. The McClelland and Elman TRACE (1986) paper is one of the most highly cited papers in psycholinguistics with its original ideas now incorporated in contemporary models of lexical activation and well supported by the experimental evidence.
Another collaboration between Rumelhart and McClelland addressed the basis of language knowledge and the process of language acquisition. Focusing on the past tense inflection of English words, they showed how a simple PDP network could learn through a simple connection adjustment process to regularize and even over-regularize, over-riding correct performance on exceptions as knowledge of the regular inflectional pattern in the language was acquired. With Karalyn Patterson, David Plaut, Mark Seidenberg, and others, McClelland extended these ideas to single word reading, and with Mark St. John he extended them to sentence comprehension. This work prompted an intense ongoing debate on the nature of language knowledge and of the mechanisms of language acquisition.
More recently, Dr. McClelland has developed and empirically tested neurologically plausible models of memory. His model of the neurological specialization of memory function has been particularly influential. This model attributes rapid learning of potentially arbitrarily juxtaposed aspects of an event to the hippocampus, whereas the neocortex plays a complementary role in gradual learning that exploits structure implicitly present in ensembles of inputs (McClelland, McNaughton, and O’Reilly, 1995). This model accounts for striking patterns of spared and impaired memory in amnesic patients and sets a new standard for theory in cognitive science — insight and testable predictions about both behavior and brain functioning.
Building on earlier work on learned distributed semantic representations by Geoffrey Hinton and David Rumelhart, McClelland has worked with several colleagues to develop a broad theory of how the neocortex may learn and represent semantic knowledge (Rogers and McClelland, 2004; Rogers et al, 2004). This connectionist model of semantic knowledge provides a unified explanation of children’s acquisition of basic and superordinate categories, their reasoning about these categories, and also of the deterioration of this knowledge in dementia.
Dr. McClelland has also made many important service contributions to cognitive science. He has been associate or senior editor for Cognitive Science, Neural Computation, Hippocampus, Neurocomputing, and Proceedings of the National Academy of Sciences and he served as a member of the National Advisory Mental Health Council He was president of the Cognitive Science Society from 1991-1992, member of the Cognitive Science Society governing board from 1988-1994, and his currently is the president-elect of the Federation of Associations in Behavioral and Brain Sciences. He has was the founding Co-Director of the Center for the Neural Basis of Cognition at Carnegie Mellon, and is currently the founding Director of the Center for Mind, Brain, and Computation at Stanford University. In September, 2009, he will become the Chair of the Psychology Department at Stanford.
Prior to receiving the Rumelhart Prize, Dr. McClelland has earned a number of honors and awards. He is a member of the National Academy of Sciences, a fellow of the American Association for the Advancement of Science, a member of the American Philosophical Society,. He has received the APS William James Fellow Award for lifetime contributions to the basic science of psychology, the 1993 Howard Crosby Warren Medal from the Society of Exerimental Psychologists, the 1996 American Psychological Association Distinguished Scientific Contribution Award, the 2001 Barlett lectureship from the Experimental Psychological Society, The 2001 Grawemeyer Award, the 2002 IEEE Neural Networks Pioneer Award, the 2003 American Psychological Society William James Fellow award, and the 2005 University of Turin Mind-Brain Prize.
- Johnston, J. C., & McClelland, J. L. (1974). Perception of letters in words: Seek not and ye shall find. Science, 184, 1192 – 1194.
- McClelland, J. L. (1979). On the time relations of mental processes: An examination of systems of processes in cascade. Psychological Review, 86, 287 – 330.
- McClelland, J. L., & Rumelhart, D. E. (1981). An interactive activation model of context effects in letter perception, Part I: An account of basic findings. Psychological Review, 88, 375 – 407.
- Rumelhart, D. E., & McClelland, J. L. (1982). An interactive activation model of context effects in letter perception, Part II: The contextual enhancement effect and some tests and extensions of the model. Psychological Review, 89, 60 – 94.
- McClelland, J. L. & Elman, J. E. (1986). The TRACE model of speech perception. Cognitive Psychology, 18, 1-86.
- Rumelhart, D. E., & McClelland (1986). On learning the past tenses of English verbs. In McClelland, J. L., Rumelhart, D. E., and the PDP research group (Eds.) Parallel distributed processing: Explorations in the microstructure of cognition. Volume II. Cambridge, MA: MIT Press. Chapter 18, pp. 216-271.
- Rumelhart, D. E., McClelland, J. L., and the PDP research group. (1986). Parallel distributed processing: Explorations in the microstructure of cognition. Volume I. Cambridge, MA: MIT Press.
- McClelland, J. L., Rumelhart, D. E., and the PDP research group. (1986). Parallel distributed processing: Explorations in the microstructure of cognition. Volume II. Cambridge, MA: MIT Press.
- Seidenberg, M. S., & McClelland, J. L. (1989). A distributed developmental model of word recognition and naming. Psychological Review, 96(4), 523 – 568.
- Cohen, J. D., Dunbar, K., & McClelland, J. L. (1990). On the control of automatic processes: A parallel distributed processing model of the stroop effect. Psychological Review, 97, 332 – 361.
- St. John, M. F., & McClelland, J. L. (1990). Learning and applying contextual constraints in sentence comprehension. Artificial Intelligence, 46, 217-257.
- McClelland, J. L., McNaughton, B. L., & O’Reilly, R. C. (1995). Why there are complementary learning systems in hippocampus and neocortex: Insights from the successes and failures of connectionist models of learning and memory. Psychological Review, 102, 419 – 457.
- Plaut, D.C., McClelland, J. L., Seidenberg, M. S., & Patterson, K. (1996). Understanding normal and impaired word reading: Computational principles in quasi-regular domains. Psychological Review, 103, 56 – 115.
- Munakata, Y., McClelland, J. L., Johnson, M. H., & Siegler, R. S. (1997). Rethinking infant knowledge: Toward an adaptive process account of successes and failures in object permanence tasks. Psychological Review, 104, 686 – 713.
- McClelland, J. L., & Chappell, M. (1998). Familiarity breeds differentiation: A subjective-likelihood approach to the effects of experience in recognition memory. Psychological Review, 105, 4, 724 – 760.
- Movellan, J. R., & McClelland, J. L. (2001). The Morton-Massaro law of information integration: Implications for models of perception. Psychological Review, 108, 113 – 148.
- Usher, M., & McClelland, J. L. (2001). The time course of perceptual choice: The leaky competing accumulator model. Psychological Review, 108, 550 – 592.
- Rogers, T. T., Lambon Ralph, M. A., Garrard, P., Bozeat, S., McClelland, J. L., Hodges, J. R., and Patterson, K. (2004). The structure and deterioration of semantic memory: A neuropsychological and computational investigation. Psychological Review, 111, 205 – 235.
- Rogers, T. T., & McClelland, J. L. (2004). Semantic Cognition: A Parallel Distributed Processing Approach. Cambridge, MA: MIT Press.
- Usher, M., & McCelland, J. L. (2004). Loss aversion and inhibition in dynamical models of multi-alternative choice. Psychological Review, 111, 757 – 769.
- Vallabha, G. K., McClelland, J. L., Pons, F., Werker, J. and Amano, S. (2007). Unsupervised learning of vowel categories from infant-directed speech. Proceedings of the National Academy of Sciences, 104, 13273 – 13278.
- Spencer, J. P., Thomas, M. S. C. & McClelland, J. L. (Eds.) (2009). Toward a Unified Theory of Development: Connectionism and Dynamic Systems Theory Re-Considered. New York: Oxford University Press.