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Seminar by Aatira Nedungadi

Title:                   Granger causality for point processes
Speaker:           Aatira Nedungadi

Time and date: Wednesday, April 13 2011, 3:30 p.m.
Venue:               Room 211, Mechanical Engineering Building

Abstract:
Simultaneous recordings of spike trains from multiple single neurons are  becoming commonplace. A question of interest is the evaluation of  information flow between neurons through the analysis of whether one spike train exerts causal influence on another. For continuous-valued  time series data, Granger causality has proven an effective method for this purpose. However, the basis for Granger causality estimation is autoregressive data modeling, which is not directly applicable to spike trains. Here we propose a new nonparametric approach to estimate Granger causality directly from the Fourier transforms of point processes data. We validate the method on synthetic spike trains generated by model networks of neurons with known connectivity patterns and then apply it to neurons simultaneously recorded from the thalamus and the primary somatosensory cortex of a squirrel monkey undergoing tactile stimulation.

Speaker Bio:
Aatira Nedungadi holds a PhD in Mathematics from IISc. She worked as a Postdoctoral Researcher at CCMB, Hyderabad. Her research interests are in Time Series Analysis and Statistical Modeling.

 

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