Abstract: Multielectrode neurophysiological recording and functional brain imaging produce massive quantities of data. Multivariate time series analysis provides the basic framework for analyzing the patterns of neural interactions in these data. Neural interactions are directional. Being able to assess the directionality of neuronal interactions is thus a highly desired capability for understanding the cooperative nature of neural computation. Research over the last few years has identified Granger causality as a promising technique to furnish this capability. In this talk, I will introduce the concept of Granger causality and present results from applications of this technique to electrophysiological and functional imaging data.

Bio: Prof. Ding received his BS degree in astrophysics from Peking University in 1982 and his PhD degree in physics from the University of Maryland in 1990. He is currently the J Crayton Pruitt Family Professor of Biomedical Engineering at the University of Florida. Prof. Ding’s research focuses on multivariate signal processing, multimodal neuroimaging, cognitive neuroscience, and cognitive impairments in neurological and psychiatric disorders. He is known for developing causal functional connectivity measures and applying these measures to multimodal neural data including multiple single unit spike trains, local field potentials, EEG, and fMRI. Prof. Ding has authored more than 140 refereed journal papers and these papers have received 10,000 Google Scholar citations (H-index=55).

~BME Faculty Host: Zhongming Liu~

***Coffee and juice will be provided at West Lafayette***

(via teleconference to SL165 at IUPUI)