Learning and Intelligent Systems: Neurophysiological, Computational, and Educational Studies of Sequence Learning and Cognitive Planning


Grossberg S.(Executive)

Project Supported by Public Organizations in Other Countries, 1997 - 2002

  • Project Type: Project Supported by Public Organizations in Other Countries
  • Begin Date: September 1997
  • End Date: August 2002

Project Abstract

This project is being funded through the Learning and Intelligent Systems (LIS) Initiative. The project aims to advance understanding of how the brain generates intelligent behavior by examining the capacity to think about sequences of events. Whether cooking an elaborate meal or merely dialing a phone number, multiple events in a specific temporal order must be kept in mind, in a form of working memory that helps in planning complex thoughts and actions. This problem will be studied in the project through an interdisciplinary approach. To directly probe brain mechanisms, neurophysiological experiments will be performed on awake behaving animals. Computer-based experiments with young children will be used to discover how children learn sequential behaviors and to test how to optimize such learning. Behavioral studies will be done on how human infants learn sequences. Cognitive and neural modeling will be used to discover brain designs and mechanisms to link the animal neurophysiological data to the human cognitive data. This interdisciplinary approach promises to produce insights that are beyond the scope of any single approach. Conducting experiments in two different animal species (monkeys and rats), in human infants, and in young children will permit identification of intelligent mechanisms that are preserved across different species. The animal studies will analyse the activity of large groups of single neurons to study how multiple neurons interact to generate intelligent behaviors. Neural modeling will probe the laws that govern these behaviors, and will make predictions that link brain to behavior. Through these analyses of how we learn and remember sequences of events, a foundation will be built for studying the neural basis of high-level cognitive operations such as planning and reasoning; for developing better educational software; and for applying models towards the solution of outstanding technological problems that require algorithms which emulate human intelligence.