The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Scale-Free Properties of the Functional Magnetic Resonance Imaging Signal during Rest and Task
Open accessAbstract
It has been shown recently that a significant portion of brain electrical field potentials consists of scale-free dynamics. These scale-free brain dynamics contain complex spatiotemporal structures and are modulated by task performance. Here we show that the fMRI signal recorded from the human brain is also scale free; its power-law exponent differentiates between brain networks and correlates with fMRI signal variance and brain glucose metabolism. Importantly, in parallel to brain electrical field potentials, the variance and power-law exponent of the fMRI signal decrease during task activation, suggesting that the signal contains more long-range memory during rest and conversely is more efficient at online information processing during task. Remarkably, similar changes also occurred in task-deactivated brain regions, revealing the presence of an optimal dynamic range in the fMRI signal. The scale-free properties of the fMRI signal and brain electrical field potentials bespeak their respective stationarity and nonstationarity. This suggests that neurovascular coupling mechanism is likely to contain a transformation from nonstationarity to stationarity. In summary, our results demonstrate the functional relevance of scale-free properties of the fMRI signal and impose constraints on future models of neurovascular coupling.
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A default mode of brain function
Raichle, M. E., MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., & Shulman, G. L. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.2.676 · Cited by 12,190
Functional connectivity in the motor cortex of resting human brain using echo‐planar mri
Biswal, B., Zerrin Yetkin, F., Haughton, V. M., & Hyde, J. S. (1995) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910340409 · Cited by 9,812
The human brain is intrinsically organized into dynamic, anticorrelated functional networks
Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0504136102 · Cited by 8,553
Power-Law Distributions in Empirical Data
Clauset, A., Shalizi, C. R., & Newman, M. E. J. (2009) · SIAM Review · doi:10.1137/070710111 · Cited by 8,019
Dissociable intrinsic connectivity networks for salience processing and executive control
Seeley, W. W., Menon, V., Schatzberg, A. F., Keller, J., Glover, G. H., Kenna, H., Reiss, A. L., & Greicius, M. D. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.5587-06.2007 · Cited by 7,426
Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging
Fox, M. D., & Raichle, M. E. (2007) · Nature Reviews Neuroscience · doi:10.1038/nrn2201 · Cited by 6,700
Consistent resting-state networks across healthy subjects
Damoiseaux, J. S., Rombouts, S. A. R. B., Barkhof, F., Scheltens, P., Stam, C. J., Smith, S. M., & Beckmann, C. F. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0601417103 · Cited by 4,326
Spontaneous neuronal activity distinguishes human dorsal and ventral attention systems
Fox, M. D., Corbetta, M., Snyder, A. Z., Vincent, J. L., & Raichle, M. E. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0604187103 · Cited by 2,101
Common blood flow changes across visual tasks: II. Decreases in cerebral cortex
Shulman, G. L., Fiez, J. A., Corbetta, M., Buckner, R. L., Miezin, F. M., Raichle, M. E., & Petersen, S. E. (1997) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.1997.9.5.648 · Cited by 1,890
Evidence for a Frontoparietal Control System Revealed by Intrinsic Functional Connectivity
Vincent, J. L., Kahn, I., Snyder, A. Z., Raichle, M. E., & Buckner, R. L. (2008) · Journal of Neurophysiology · doi:10.1152/jn.90355.2008 · Cited by 1,869
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Buckner, R. L., & DiNicola, L. M. (2019) · Nature Reviews Neuroscience · doi:10.1038/s41583-019-0212-7 · Cited by 1,058
Brain network dynamics are hierarchically organized in time
Vidaurre, D., Smith, S. M., & Woolrich, M. W. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1705120114 · Cited by 867
Scale-free brain activity: past, present, and future
He, B. J. (2014) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2014.04.003 · Cited by 802
Self-citationSlow cortical dynamics and the accumulation of information over long timescales
Honey, C. J., Thesen, T., Donner, T. H., Silbert, L. J., Carlson, C. E., Devinsky, O., Doyle, W. K., Rubin, N., Heeger, D. J., & Hasson, U. (2012) · Neuron · doi:10.1016/j.neuron.2012.08.011 · Cited by 532
Moment-to-moment brain signal variability: A next frontier in human brain mapping?
Garrett, D. D., Samanez-Larkin, G. R., MacDonald, S. W. S., Lindenberger, U., McIntosh, A. R., & Grady, C. L. (2013) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2013.02.015 · Cited by 585
Metadata
- Authors
- He, B. J.
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2011-09-28
- Volume
- 31
- Issue
- 39
- Pages
- 13786-13795
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- OpenAlex
- W2021053759
- Cited by
- 435
- References
- 22
- FWCI
- 8.29
- Type
- journal article
- Language
- en
- Open access
- hybrid
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