9 March 2011 A methodology for dynamic functional connectivity
Author Affiliations +
Proceedings Volume 7965, Medical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging; 796503 (2011); doi: 10.1117/12.878829
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States
Abstract
Classical measures of functional connectivity assume that the stationarity of the time courses and the time-invariance of functional connectivity under investigation. These assumptions may not be valid in the real cases. Also, they are bivariate measures and may not provide the directional information flow between brain units. A new approach is proposed to tackle these problems. A statistics reasoning shows that the short-length time course is more likely to be stationary than the long-length time course. Thus, the entire time course under investigation is divided into short segments with the proper length. Magnitude squared coherence (in spectrum domain) is computed to assess functional connectivity on these segments, hence, provides a dynamic measure of functional connectivity. The averaged magnitude squared coherence over the segments gives an overall measure of functional connectivity. This approach has been applied to several neuroimaging data analysis. The results and the interpretations / predictions are in good agreement. Mutual coherence (in time domain) is computed to assess functional connectivity, hence, provides an insight on directional information flow. By using grid computing, this approach will be extended from the bivariate to the multivariate.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tianhu Lei, John Dell, Timothy P. L. Roberts, "A methodology for dynamic functional connectivity", Proc. SPIE 7965, Medical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging, 796503 (9 March 2011); doi: 10.1117/12.878829; https://doi.org/10.1117/12.878829
PROCEEDINGS
12 PAGES


SHARE
KEYWORDS
Signal to noise ratio

Brain

Magnetoencephalography

Mode locking

Neuroimaging

Information theory

Interference (communication)

RELATED CONTENT


Back to Top