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Special End-of-Year Meeting: Computational Neurobiology

Special End-of-Year Meeting: Computational Neurobiology

Wednesday, June 28, 2006

The New York Academy of Sciences

Presented By

Presented by the Computational Bio & Bioinformatics Discussion Group


Organizers: Jozsef Fiser and Don Katz, Brandeis University

The Bioinformatics and Computational Biology Discussion group brings together diverse institutions and communities to share new and relevant information at the frontiers of the interrelated fields of bioinformatics and computational biology. Recent topics have included "Benchmarking and Improving the Accuracy of Comparative Modeling of Protein Structures," "Integrated Statistical Modeling of Gene Expression Data," and "Estimating SNP Haplotype Frequencies from DNA Pools."


5:00 - 7:30: Presentations

Jonathan Victor, Weill Medical College of Cornell University, "Neural Dynamics and Representation in the Visual System."

Larry Abbott, Columbia University, "The Interplay of Background and Evoked Activity."

Aaditya Rangan, New York University, "Modeling the Visual Cortex: an Attempt to Reveal Network Mechanisms."


Jonathan Victor, "Neural Dynamics and Representation in the Visual System."
I will present a selective overview of visual processing from eye to brain, emphasizing the theme of increasing dynamic complexity. I will then describe some studies in visual cortex that imply that individual neuronal firing events (spikes), rather than the average firing rate across time or a local population, are crucial to the representation of visual information.

Larry Abbott, Columbia University, "The Interplay of Background and Evoked Activity."
Spontaneous background activity in sensory areas is often similar in both magnitude and form to evoked responses. Embedding responses evoked by sensory stimuli in such strong and complex background activity seems like a confusing way to represent information about the outside world. However, modeling studies indicate that, contrary to intuition, information about sensory stimuli is better conveyed by a network displaying chaotic background activity than by a network without spontaneous activity.

Aaditya Rangan, "Modeling the Visual Cortex: An Attempt to Reveal Network Mechanisms."
There are a variety of experiments which investigate the transient and steady-state spatio-temporal behaviour of the primary visual cortex (V1). I will present a parsimoniously constructed, physiologically reasonable cortical model which, with a single set of parameters, simultaneously reproduces many of these experimentally observed phenomena. I will also appeal to this cortical model to rationalize many of these phenomena.