FEIT Research Project Database

Understanding cortical processing: Neuronal activity and learning in recurrently connected networks

Project Leader: David Grayden
Staff: Anthony Burkitt
Primary Contact: David Grayden (grayden@unimelb.edu.au)
Keywords: computational neuroscience; neural models
Disciplines: Biomedical Engineering,Computing and Information Systems
Domains: Convergence of engineering and IT with the life sciences
Research Centre: Neuroengineering Research Laboratory

The aim of this project is to address one of the great challenges of neuroscience, namely how information is processed in the brain. In particular, we aim to understand mathematically the function and structure of recurrently connected neuronal networks. This involves an analysis of both the network activity and the network structure that results from this activity through spike-timing-dependent learning. The methods of dynamical systems theory and control theory will be used to study both the spiking activity and emergent network structure. The results will significantly advance our knowledge of intelligent information processing and will have important implications for robotics, machine learning, and adaptive control.