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