Journal
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
Volume 25, Issue 6, Pages 539-546Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNSRE.2016.2593655
Keywords
Brain networks; dynamic Granger causality; effective connectivity; mental chronometry
Categories
Funding
- National Institutes of Health, United States [5R01EB000461]
- Auburn University MRI Research Center
Ask authors/readers for more resources
Decoding the sequential flow of events in the human brain non-invasively is critical for gaining a mechanistic understanding of brain function. In this study, we propose a method based on dynamic Granger causality analysis to measure timing differences in brain responses from fMRI. We experimentally validate this method by detecting sub-100 ms timing differences in fMRI responses obtained from bilateral visual cortex using fast sampling, ultra-high field and an event-related visual hemifield paradigm with known timing difference between the hemifields. Classical Granger causality was previously shown to be able to detect sub-100 ms timing differences in the visual cortex. Since classical Granger causality does not differentiate between spontaneous and stimulus-evoked responses, dynamic Granger causality has been proposed as an alternative, thereby necessitating its experimental validation. In addition to detecting timing differences as low as 28 ms using dynamic Granger causality, the significance of the inference from our method increased with increasing delay both in simulations and experimental data. Therefore, it provides amethodology for understanding mental chronometry from fMRI in a data-driven way.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available