CCS Seminar
Friday - April 20, 2007
12:00 noon
Physics Research Building - Room 595
Professor Uri Eden- Mathematics & Statistics - Boston University

"Decoding Neural Spiking Data"

Recent technological developments in neuro-electrophysiology have led to an explosion in the amount and types of data we can collect from the brain. In order to develop our understanding of how the brain represents biological and behavioral signals, new methods for analyzing this wealth of neural data must be developed. These new methods incorporate elements of neuroscience, physics, signal processing, control theory, statistics, and computer algorithm design.

In this presentation, I will discuss a powerful framework for the statistical analysis of neural spiking data. Although it is well known that neurons receive, process and transmit signals via sequences of sudden stereotyped electrical events, many analyses of neural data ignore the highly localized nature of spikes. The theory of point processes offers a unified, principled approach to modeling and estimating the firing properties of spiking neural systems, and assessing goodness-of-fit between a neural model and observed spike train data.

These methods will be illustrated in the context of the analysis of place field activity in the rodent hippocampus. Place cells, which tend to fire preferentially when the animal is in specific locations, have been implicated in cognitive tasks such as navigation and decision making. Using simple point process models, we are able to accurately characterize the localized spiking activity of these neurons as a function of the animal?s position in its environment, and reconstruct the animal?s movements from the spiking of a hippocampal population.

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