Cosyne 2007 Workshops

February 27, 2007

The Canyons, Utah

Workshop Title

What role does spike synchrony or correlation play in sensory processing?


Jason Samonds (Carnegie Mellon University):
Matt Smith (Carnegie Mellon University):


More laboratories are now routinely recording from larger numbers of neurons trying to answer questions about cortical circuitry and population coding. We have long known there is weak, but significant correlation or synchrony between pairs of neurons at every level of sensory processing. The correlation occurs at various temporal scales (milliseconds to 100's of msec) and for neuron pairs with distances approaching several millimeters. The objective of this workshop is to discuss what we have learned about these correlations and how they might effect sensory processing. Specifically, how can we interpret or extract how these results influence sensory processing at the network level.

This workshop will be of interest to neurophysiologists recording from multiple electrodes simultaneously, computational neuroscientists working on network models, and information theorists interested in population coding. The interaction among these specialists should lead to a synergistic relation to improve experiment design and data interpretation and modify current models with the most recent empirical data.


8:30-8:35 Opening Remarks
8:35-9:05 AB Bonds (Vanderbilt University) Now that you have that multicell data you always wanted, what do you do with it?
9:15-9:45 Don Johnson (Rice University) Correlations in Populations: Information-Theoretic Limits
9:55-10:10 Break
10:10-10:40 Matt Smith (Carnegie Mellon University) Stimulus and distance dependence of neuronal correlation in macaque primary visual cortex
10:50-11:20 Simon Schultz (Imperial College London) Synchrony and sensory coding in the cortex and cerebellum
4:00-4:30 Elad Schneidman (Weizmann Institute of Science) Weak pairwise correlations imply strongly correlated networks states in neural population codes
4:40-5:10 Ifije Ohiorhenuan (Cornell University) Maximum entropy modeling of multi-neuron firing patterns in V1
5:20-5:35 Break
5:35-6:05 Peter Latham (Gatsby Computational Neuroscience Unit) Unsupervised learning, correlations, and error correcting codes: how are they related, and what can neural data tell us about them?
6:15-6:45 Jason Samonds (Carnegie Mellon University) Evidence of cooperative and competitive mechanisms for stereo computation in macaque V1
6:45-7:00 Discussion and Concluding Remarks

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