Granger Causality: Basic Theory and Application to Neuroscience

Biology – Quantitative Biology – Quantitative Methods

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

Multi-electrode neurophysiological recordings produce massive quantities of data. Multivariate time series analysis provides the basic framework for analyzing the patterns of neural interactions in these data. It has long been recognized that 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 shown that Granger causality is a key technique to furnish this capability. The main goal of this article is to provide an expository introduction to the concept of Granger causality. Mathematical frameworks for both bivariate Granger causality and conditional Granger causality are developed in detail with particular emphasis on their spectral representations. The technique is demonstrated in numerical examples where the exact answers of causal influences are known. It is then applied to analyze multichannel local field potentials recorded from monkeys performing a visuomotor task. Our results are shown to be physiologically interpretable and yield new insights into the dynamical organization of large-scale oscillatory cortical networks.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Granger Causality: Basic Theory and Application to Neuroscience does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Granger Causality: Basic Theory and Application to Neuroscience, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Granger Causality: Basic Theory and Application to Neuroscience will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-110002

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.