Consistent resting-state networks across healthy subjects

Proceedings of the National Academy of Sciences of the United States of America - Tập 103 Số 37 - Trang 13848-13853 - 2006
Jessica S. Damoiseaux1, Serge A.R.B. Rombouts2,3, Frederik Barkhof4, Philip Scheltens5,6, Cornelis J. Stam7,6, Stephen M. Smith8, Christian F. Beckmann8
1Department of Neurology, VU University Medical Center, de Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
2Leiden Institute for Brain and Cognition, Department of Radiology, Leiden University Medical Center, and Department of Psychology, Leiden University, Postzone C2-S, P.O. Box 9600, 2300 RC Leiden, The Netherlands; and
3Physics and Medical Technology,
4Radiology and Nuclear Medicine
5Departments of Neurology
6Vrije Universiteit;
7Clinical Neurophysiology, VU University Medical Center, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands;
8Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DU, United Kingdom,

Tóm tắt

Functional MRI (fMRI) can be applied to study the functional connectivity of the human brain. It has been suggested that fluctuations in the blood oxygenation level-dependent (BOLD) signal during rest reflect the neuronal baseline activity of the brain, representing the state of the human brain in the absence of goal-directed neuronal action and external input, and that these slow fluctuations correspond to functionally relevant resting-state networks. Several studies on resting fMRI have been conducted, reporting an apparent similarity between the identified patterns. The spatial consistency of these resting patterns, however, has not yet been evaluated and quantified. In this study, we apply a data analysis approach called tensor probabilistic independent component analysis to resting-state fMRI data to find coherencies that are consistent across subjects and sessions. We characterize and quantify the consistency of these effects by using a bootstrapping approach, and we estimate the BOLD amplitude modulation as well as the voxel-wise cross-subject variation. The analysis found 10 patterns with potential functional relevance, consisting of regions known to be involved in motor function, visual processing, executive functioning, auditory processing, memory, and the so-called default-mode network, each with BOLD signal changes up to 3%. In general, areas with a high mean percentage BOLD signal are consistent and show the least variation around the mean. These findings show that the baseline activity of the brain is consistent across subjects exhibiting significant temporal dynamics, with percentage BOLD signal change comparable with the signal changes found in task-related experiments.

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Proceedings of the National Academy of Sciences of the United States of America

Tập 103 Số 37

13848-13853

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