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

Abstract Details

Activity Number: 664
Type: Topic Contributed
Date/Time: Thursday, August 5, 2010 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #307660
Title: Pruning and Dimension Reduction in Conditional Granger Causality
Author(s): Haley Hedlin*+ and Brian Scott Caffo
Companies: Johns Hopkins Bloomberg School of Public Health and Johns Hopkins Bloomberg School of Public Health
Address: , , ,
Keywords: Granger causality ; connectivity ; neurophysiological signals
Abstract:

Granger causality (GC) is a statistical technique used to estimate temporal associations in multivariate time series. Many applications and extensions of GC have been proposed since its formulation by Granger in 1969. Here we consider an extension to control for potentially mediating or confounding signals, called conditional GC, in the context of electrocorticographic (ECoG) signals. A pruning approach to reduce the required number of estimations is proposed. Finally, we consider the potential of conditional GC applied to independent components as a method to explore temporal relationships between underlying source signals. Applications to simulated and real ECoG signals are presented.


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