Talk in Department of Humanities and Social Sciences

Title:  Regularized regression models for detecting neuronal interactions

Speaker: Prof. Satish Iyengar
Location: L3 
Date: May 24, 2013 at 11:00 a.m

Abstract:

Interactions among neurons are a key component of neural signal processing. Richneural data sets potentially containing evidence of interactions are now collected readily in the laboratory. Generalized linear models are a platform for analyzing multi-electrode recordings of neuronal spike train data. We suggest an L1-regularized logistic regression model (L1L method) to detect short-term (order of 3 ms) neuronal interactions. We describe the computational aspects of this model, the results of simulation studies that indicate improvements over traditional cross-correlation methods, and application of our method to monkey dorsal premotor cortex.