A Unified Brain Architecture for Perception and Cognition With Applications to Information Processing Technology
Abstract
This project develops neural and computational models of the brain mechanisms that underlie human perception and cognition. It does this by mathematically characterizing and quantitatively simulating key brain mechanisms underlying higher-order human information processing as carried out within the laminar structure of the cerebral cortex. A model Laminar Computing paradigm promises to generate powerful information processing tools for dealing with large-scale problems. Perceptual projects model how the laminar circuits of visual cortex are designed to group distributed visual information into emergent object representations, to pay attention selectively to important information, and to learn their own optimal operating parameters in different visual environments; Cognitive processing projects model how the laminar circuits of inferotemporal and prefrontal cortex can rapidly classify, decide between, and predict noisy and potentially conflicting information in rapidly changing environments. The resulting models can be applied to technological problems in which the ability to autonomously visualize, learn, predict, and control information in rapidly changing environments is required. Testbed problems, including geospatial mapping and medical database analysis, have been developed in the context of the AFOSR-sponsored CNS Technology Laboratory.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 22, 2004
- Accession Number
- ADA428485
Entities
People
- Gail A. Carpenter
- Stephen Grossberg
Organizations
- Boston University