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