The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Linking inter-individual differences in neural activation and behavior to intrinsic brain dynamics
Open accessAbstract
The brain’s energy economy excessively favors intrinsic, spontaneous neural activity over extrinsic, evoked activity, presumably to maintain its internal organization. Emerging hypotheses capable of explaining such an investment posit that the brain’s intrinsic functional architecture encodes a blueprint for its repertoire of responses to the external world. Yet, there is little evidence directly linking intrinsic and extrinsic activity in the brain. Here we relate differences among individuals in the magnitude of task-evoked activity during performance of an Eriksen flanker task, to spontaneous oscillatory phenomena observed during rest. Specifically, we focused on the amplitude of low-frequency oscillations (LFO, 0.01–0.1Hz) present in the BOLD signal. LFO amplitude measures obtained during rest successfully predicted the magnitude of task-evoked activity in a variety of regions that were all activated during performance of the flanker task. In these regions, higher LFO amplitude at rest predicted higher task-evoked activity. LFO amplitude measures obtained during rest were also found to have robust predictive value for behavior. In midline cingulate regions, LFO amplitudes not only predicted the speed and consistency of performance, but also the magnitude of the behavioral congruency effect embedded in the flanker task. These results support the emerging hypothesis that the brain’s repertoire of responses to the external world are represented and updated in the brain’s intrinsic functional architecture.
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Jenkinson, M., Bannister, P., Brady, M., & Smith, S. (2002) · NeuroImage · doi:10.1006/nimg.2002.1132 · Cited by 11,888
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
Self-citationCorrespondence of the brain's functional architecture during activation and rest
Smith, S. M., Fox, P. T., Miller, K. L., Glahn, D. C., Fox, P. M., Mackay, C. E., Filippini, N., Watkins, K. E., Toro, R., Laird, A. R., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0905267106 · Cited by 5,150
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
Mapping the structural core of human cerebral cortex
Hagmann, P., Cammoun, L., Gigandet, X., Meuli, R., Honey, C. J., Wedeen, V. J., & Sporns, O. (2008) · PLoS Biology · doi:10.1371/journal.pbio.0060159 · Cited by 4,173
MacDonald, A. W., Cohen, J. D., Stenger, V. A., & Carter, C. S. (2000) · Science · doi:10.1126/science.288.5472.1835 · Cited by 3,666
Conflict monitoring and anterior cingulate cortex: an update
Botvinick, M. M., Cohen, J. D., & Carter, C. S. (2004) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2004.10.003 · Cited by 3,623
Investigations into resting-state connectivity using independent component analysis
Beckmann, C. F., DeLuca, M., Devlin, J. T., & Smith, S. M. (2005) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2005.1634 · Cited by 3,398
A method for making group inferences from functional MRI data using independent component analysis
Calhoun, V. D., Adali, T., Pearlson, G. D., & Pekar, J. J. (2001) · Human Brain Mapping · doi:10.1002/hbm.1048 · Cited by 2,994
Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI
Yu-Feng, Z., Yong, H., Chao-Zhe, Z., Qing-Jiu, C., Man-Qiu, S., Meng, L., Li-Xia, T., Tian-Zi, J., & Yu-Feng, W. (2007) · Brain and Development · doi:10.1016/j.braindev.2006.07.002 · Cited by 2,660
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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
Exploring the network dynamics underlying brain activity during rest
Cabral, J., Kringelbach, M. L., & Deco, G. (2014) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2013.12.005 · Cited by 351
Cox, C. L., Uddin, L. Q., Di Martino, A., Castellanos, F. X., Milham, M. P., & Kelly, C. (2012) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsr051 · Cited by 333
Self-citationA Sliding Time-Window ICA Reveals Spatial Variability of the Default Mode Network in Time
Kiviniemi, V., Vire, T., Remes, J., Elseoud, A. A., Starck, T., Tervonen, O., & Nikkinen, J. (2011) · Brain Connectivity · doi:10.1089/brain.2011.0036 · Cited by 253
Metadata
- Authors
- Mennes, M., Zuo, X.-N., Kelly, C., Di Martino, A., Zang, Y.-F., Biswal, B., Castellanos, F. X., & Milham, M. P.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2011-02
- Volume
- 54
- Issue
- 4
- Pages
- 2950-2959
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2028897503
- Cited by
- 218
- References
- 22
- FWCI
- 7.06
- Type
- journal article
- Language
- en
- Open access
- green
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