Complexity of low-frequency blood oxygen level-dependent fluctuations covaries with local connectivity

Very low‐frequency blood oxygen level‐dependent (BOLD) fluctuations have emerged as a valuable tool for describing brain anatomy, neuropathology, and development. Such fluctuations exhibit power law frequency dynamics, with largest amplitude at lowest frequencies. The biophysical mechanisms generati...

Full description

Saved in:
Bibliographic Details
Published inHuman brain mapping Vol. 35; no. 4; pp. 1273 - 1283
Main Authors Anderson, Jeffrey S., Zielinski, Brandon A., Nielsen, Jared A., Ferguson, Michael A.
Format Journal Article
LanguageEnglish
Published New York, NY Blackwell Publishing Ltd 01.04.2014
Wiley-Liss
John Wiley & Sons, Inc
John Wiley and Sons Inc
Subjects
Online AccessGet full text
ISSN1065-9471
1097-0193
1097-0193
DOI10.1002/hbm.22251

Cover

More Information
Summary:Very low‐frequency blood oxygen level‐dependent (BOLD) fluctuations have emerged as a valuable tool for describing brain anatomy, neuropathology, and development. Such fluctuations exhibit power law frequency dynamics, with largest amplitude at lowest frequencies. The biophysical mechanisms generating such fluctuations are poorly understood. Using publicly available data from 1,019 subjects of age 7–30, we show that BOLD fluctuations exhibit temporal complexity that is linearly related to local connectivity (regional homogeneity), consistently and significantly covarying across subjects and across gray matter regions. This relationship persisted independently of covariance with gray matter density or standard deviation of BOLD signal. During late neurodevelopment, BOLD fluctuations were unchanged with age in association cortex while becoming more random throughout the rest of the brain. These data suggest that local interconnectivity may play a key role in establishing the complexity of low‐frequency BOLD fluctuations underlying functional magnetic resonance imaging connectivity. Stable low‐frequency power dynamics may emerge through segmentation and integration of connectivity during development of distributed large‐scale brain networks. Hum Brain Mapp 35:1273–1283, 2014. © 2013 Wiley Periodicals, Inc.
Bibliography:ark:/67375/WNG-34XMFRFS-9
istex:80F0362CBD7F20D261B4CCB1D1521256DF293F59
Ben B. and Iris M. Margolis Foundation
ArticleID:HBM22251
Primary Children's Foundation Early Career Development Award
National Institute of Health - No. K08MH092697; No. T32DC008553
http://fcon_1000.projects.nitrc.org/
The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Mental Health or other funding institutions. Investigators and funding sources who contributed to the 1000 Functional Connectome Dataset and ADHD 200 Dataset are available at
.
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Mental Health or other funding institutions. Investigators and funding sources who contributed to the 1000 Functional Connectome Dataset and ADHD 200 Dataset are available at http://fcon_1000.projects.nitrc.org/.
ISSN:1065-9471
1097-0193
1097-0193
DOI:10.1002/hbm.22251