This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 360
Type: Contributed
Date/Time: Tuesday, August 3, 2010 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #308947
Title: An Inhibitory-Excitatory Approach for the Analysis of the Neural Spike Train
Author(s): Reza Ramezan*+ and Paul Marriott and Shojaeddin Chenouri
Companies: University of Waterloo and University of Waterloo and University of Waterloo
Address: Dept. of Statistics and ACTSCI - U of Waterloo, Waterloo, ON, N2L3G1, Canada
Keywords: density estimation ; intensity function estimation ; multi-resolution analysis ; spike train data ; multiple-neuron modeling

A sequence of neural spikes from a single neuron is called a spike train. It is unknown precisely how the brain decodes the information. However, assuming that the intensity function of such a spike train encodes all information is one of the well known hypotheses. Following a multiscale framework, we introduce a biologically justifiable model for estimating the intensity function of the spike train data which has two important properties. It models the burstings, resting periods, and the theta-rhythm of the brain without over-fitting the data. Furthermore, it allows for the complete range of correlations; i.e., [-1,1] in the bivariate analysis of the spike trains which is not possible using the conventional ways of modeling the intensity function based upon such data.

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