Variance and autocorrelation of the spontaneous slow brain activity.
Slow (<0.1 Hz) oscillatory activity in the human brain, as measured by functional magnetic imaging, has been used to identify neural networks and their dysfunction in specific brain diseases. Its intrinsic properties may also be useful to investigate brain functions. We investigated the two functional maps: variance and first order autocorrelation coefficient (r(1)). These two maps had distinct spatial distributions and the values were significantly different among the subdivisions of the precuneus and posterior cingulate cortex that were identified in functional connectivity (FC) studies. The results reinforce the functional segregation of these subdivisions and indicate that the intrinsic properties of the slow brain activity have physiological relevance. Further, we propose a sample size (degree of freedom) correction when assessing the statistical significance of FC strength with r(1) values, which enables a better understanding of the network changes related to various brain diseases.
Department of System Neurophysiology, Graduate School of Wakayama Medical University, Wakayama, Japan. kaneoke@wakayama-med.ac.jp
Yoshiki
Y
Kaneoke
Tomohiro
T
Donishi
Jun
J
Iwatani
Satoshi
S
Ukai
Kazuhiro
K
Shinosaki
Masaki
M
Terada
D000328:Adult; D001921:Brain / Q000166:cytology / Q000378:metabolism / Q000502:physiology*; D005260:Female; D059907:Functional Neuroimaging; D006801:Humans; D007700:Kinetics; D008279:Magnetic Resonance Imaging; D008297:Male; D009474:Neurons / Q000166:cytology; D010100:Oxygen / Q000097:blood; D010363:Pattern Recognition, Automated; D010507:Periodicity
D010100:Oxygen