Paper Info
Title
Significant feed-forward connectivity revealed by high frequency components of BOLD fMRI signals.
Abstract
Granger causality analysis has been suggested as a method of estimating causal modulation without specifying the direction of information flow a priori. Using BOLD-contrast functional MRI (fMRI) data, such analysis has been typically implemented in the time domain. In this study, we used magnetic resonance inverse imaging, a method of fast fMRI enabled by massively parallel detection allowing up to 10Hz sampling rate, to investigate the causal modulation at different frequencies up to 5Hz. Using a visuomotor two-choice reaction-time task, both the spectral decomposition of Granger causality and isolated effective coherence revealed that the BOLD signal at frequency up to 3Hz can still be used to estimate significant dominant directions of information flow consistent with results from the time-domain Granger causality analysis. We showed the specificity of estimated dominant directions of information flow at high frequencies by contrasting causality estimates using data collected during the visuomotor task and resting state. Our data suggest that hemodynamic responses carry physiological information related to inter-regional modulation at frequency higher than what has been commonly considered.
Year
DOI
Venue
2015
10.1016/j.neuroimage.2015.07.036
NeuroImage
Keywords
Field
DocType
Causality,Granger,Spectral decomposition,Visuomotor
Causality,Computer science,A priori and a posteriori,Granger causality,Sampling (signal processing),Resting state fMRI,Cognitive psychology,Modulation,Artificial intelligence,Time domain,Pattern recognition,Coherence (physics),Machine learning
Journal
Volume
ISSN
Citations 
121
1053-8119
5
PageRank 
References 
Authors
0.42
25
7
Name
Order
Citations
PageRank
Fa-Hsuan Lin124624.33
Ying-Hua Chu2332.99
Yi-Cheng Hsu390.79
Jo-Fu Lotus Lin491.13
Kevin Wen-Kai Tsai5494.60
Shang-Yueh Tsai691.13
Wen-Jui Kuo716320.42