Banbury Center Workshop Series Main Page

Neurocomputational Strategies: From Synapses to Behavior (1998)
Functional Organization of the Thalamus and Cortex and their Interactions (1999)
Toward Animal Models of Attention and Consciousness (2000)
Persistent Neural Activity (2000)
Can a Machine Be Conscious? (2001)
Communication in Brain Systems (2004)
Neurobiology of Decision-Making (2005)
Computational Approaches to Cortical Functions (2006)
New Frontiers in Studies of Nonconscious Processing (2007)
Theoretical and Experimental Approaches to Auditory and Visual Attention (2008)

Banbury 2006 — Abstracts

Controlling neural network dynamics

Kanaka Rajan & Larry F. Abbott

kr2208@columbia.edu

We explore mechanisms by which a set of constant inputs to a neural network can generate predictable and repeatable patterns of activity with complex dynamics. Model networks of firing-rate or spiking neurons can exhibit dynamic activity ranging from fixed point behavior to oscillations or chaos. These patterns of activity can play useful cognitive and functional roles (Amit, 1989). Taking advantage of this richness, however, requires control of network dynamics so that a desired form of activity can be called up when it is needed. We explore mechanisms by which such control can be exerted.