of Categorization, Novelty-Detection and the Neural Representation of SimilarityABSTRACT
Neurocomputational models provide fundamental insights towards understanding the human brain circuits for learning new associations and organizing our world into appropriate categories. In this talk Iwill review the information-processing functions of four interacting brain systems for learning and categorization:
(1) the basal ganglia which incrementally adjusts choice behaviors using environmental feedback about the consequences of our actions,
(2) the hippocampus which supports learning in other brain regions through the creation of new stimulus representations (and, hence, new similarity relationships) that reflect important statistical regularities in the environment,
(3) the medial septum which works in a feedback-loop with the hippocampus, using novelty-detection to alter the rate at which stimulus representations are updated through experience,
(4) the frontal lobes which provide for selective attention and executive control of learning and memory. The computational models to be described have been evaluated through a variety of empirical methodoligies including human functional brain imaging, studies of patients with localized brain damage due to injury or early-stage neurodegenerative diseases, behavioral genetic studies of naturally-occuring individual variability, as well as comparative lesion and genetic studies with rodents. Our applications of these models to engineering and computer science including automated anomaly detection systems for mechanical fault diagnosis on US Navy helicopters and submarines as well more recent contributions to the DoD's DARPA program for Biologically Inspired Cognitive Architectures(BICA).
Mark Gluck Professor of Neuroscience, Center for Molecular & Behavioral NeuroscienceRutgers University - Newark Co-Director, Memory Disorders Project at Rutgers-Newark Publisher, Memory Loss and the Brain. He works at the interface between neuroscience, psychology, and computer science studying the neural bases of learning and memory. His research spans numerous methodologies including neurocomputational modeling, clinical studies of brain-damaged patients, functional and structural brain imaging, behavioral genetics, and comparative studies of rodent and human learning. He is the co-author of Gateway to Memory: An Introduction to Neural Network Models of the Hippocampus and Memory (MIT Press, 2001) as well as a new undergraduate textbook Learning and Memory: From Brain to Behavior (Worth Publishers, 2008). He has edited several other books including Neuroscience and Connectionist Theory (1990), Model Systems and the Neurobiology of Associative Learning: A Festschrift for Richard F. Thompson (2001), and Memory and Mind: A Festschrift for Gordan H. Bower (2007), as well as over 80 scientific journal articles and book chapters. His awards include the Distinguished Scientific Award for Early Career Contributions from the American Psychological Society and the Young Investigator Award for Cognitive and Neural Sciences from the Office of Naval Research. In 1996, he was awarded a NSF Presidential Early Career Award for Scientists and Engineers by President Bill Clinton. For more information, see http://www.gluck.edu/.
