The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Tracking ongoing cognition in individuals using brief, whole-brain functional connectivity patterns
Open accessAbstract
Significance: Recently, it was shown that functional connectivity patterns exhibit complex spatiotemporal dynamics at the scale of tens of seconds. Of particular interest is the observation of a limited set of quasi-stable, whole-brain, recurring configurations—commonly referred to as functional connectivity states (FC states)—hypothesized to reflect the continuous flux of cognitive processes. Here, to test this hypothesis, subjects were continuously scanned as they engaged in and transitioned between mental states dictated by tasks. We demonstrate that there is a strong relationship between FC states and ongoing cognition that permits accurate tracking of mental states in individual subjects. We also demonstrate how informative changes in connectivity are not restricted solely to those regions with sustained elevations in activity during task performance.
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Cites
AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages
Cox, R. W. (1996) · Computers and Biomedical Research · doi:10.1006/cbmr.1996.0014 · Cited by 10,913
Hubert, L., & Arabie, P. (1985) · Journal of Classification · doi:10.1007/bf01908075 · Cited by 8,219
Correspondence 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
Large-scale automated synthesis of human functional neuroimaging data.
Yarkoni, T., Poldrack, R. A., Nichols, T. E., Van Essen, D. C., & Wager, T. D. (2011) · Nature Methods · doi:10.1038/nmeth.1635 · Cited by 3,686
Mesulam, M. (1998) · Brain · doi:10.1093/brain/121.6.1013 · Cited by 3,072
Tracking whole-brain connectivity dynamics in the resting state
Allen, E. A., Damaraju, E., Plis, S. M., Erhardt, E. B., Eichele, T., & Calhoun, V. D. (2014) · Cerebral Cortex · doi:10.1093/cercor/bhs352 · Cited by 2,992
Tononi, G. (1998) · Science · doi:10.1126/science.282.5395.1846 · Cited by 1,561
BOLD correlates of EEG topography reveal rapid resting-state network dynamics
Britz, J., Van De Ville, D., & Michel, C. M. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.02.052 · Cited by 1,070
The conscious access hypothesis: origins and recent evidence
Baars, B. J. (2002) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(00)01819-2 · Cited by 994
On spurious and real fluctuations of dynamic functional connectivity during rest
Leonardi, N., & Van De Ville, D. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.09.007 · Cited by 828
Cited by
Gratton, C., Laumann, T. O., Nielsen, A. N., Greene, D. J., Gordon, E. M., Gilmore, A. W., Nelson, S. M., Coalson, R. S., Snyder, A. Z., Schlaggar, B. L., et al. (2018) · Neuron · doi:10.1016/j.neuron.2018.03.035 · Cited by 846
Communication dynamics in complex brain networks
Avena-Koenigsberger, A., Misic, B., & Sporns, O. (2018) · Nature Reviews Neuroscience · doi:10.1038/nrn.2017.149 · Cited by 856
Questions and controversies in the study of time-varying functional connectivity in resting fMRI
Lurie, D. J., Kessler, D., Bassett, D. S., Betzel, R. F., Breakspear, M., Kheilholz, S., Kucyi, A., Liégeois, R., Lindquist, M. A., McIntosh, A. R., et al. (2020) · Network Neuroscience · doi:10.1162/netn_a_00116 · Cited by 648
On the stability of BOLD fMRI correlations
Laumann, T. O., Snyder, A. Z., Mitra, A., Gordon, E. M., Gratton, C., Adeyemo, B., Gilmore, A. W., Nelson, S. M., Berg, J. J., Greene, D. J., et al. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw265 · Cited by 516
The global signal in fMRI: Nuisance or Information?
Liu, T. T., Nalci, A., & Falahpour, M. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.02.036 · Cited by 411
Metadata
- Authors
- Gonzalez-Castillo, J., Hoy, C. W., Handwerker, D. A., Robinson, M. E., Buchanan, L. C., Saad, Z. S., & Bandettini, P. A.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2015-06-29
- Volume
- 112
- Issue
- 28
- Pages
- 8762-8767
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W1801278145
- Cited by
- 343
- References
- 16
- FWCI
- 18.44
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Gonzalez-Castillo, J., Hoy, C. W., Handwerker, D. A., Robinson, M. E., Buchanan, L. C., Saad, Z. S., & Bandettini, P. A. (2015). Tracking ongoing cognition in individuals using brief, whole-brain functional connectivity patterns. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1501242112
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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