Abstract

The brain is a complex network with time-varying functional connectivity (FC) and network organization. However, it remains largely unknown whether resting-state fNIRS measurements can be used to characterize dynamic characteristics of intrinsic brain organization. In this study, for the first time, we used the whole-cortical fNIRS time series and a sliding-window correlation approach to demonstrate that fNIRS measurement can be ultimately used to quantify the dynamic characteristics of resting-state brain connectivity. Our results reveal that the fNIRS-derived FC is time-varying, and the variability strength (Q) is correlated negatively with the time-averaged, static FC. Furthermore, the Q values also show significant differences in connectivity between different spatial locations (e.g., intrahemispheric and homotopic connections). The findings are reproducible across both sliding-window lengths and different brain scanning sessions, suggesting that the dynamic characteristics in fNIRS-derived cerebral functional correlation results from true cerebral fluctuation.

© 2015 Optical Society of America

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2014 (4)

E. A. Allen, E. Damaraju, S. M. Plis, E. B. Erhardt, T. Eichele, and V. D. Calhoun, “Tracking whole-brain connectivity dynamics in the resting state,” Cereb. Cortex 24(3), 663–676 (2014).
[Crossref] [PubMed]

A. Zalesky, A. Fornito, L. Cocchi, L. L. Gollo, and M. Breakspear, “Time-resolved resting-state brain networks,” Proc. Natl. Acad. Sci. USA 111(28), 10341–10346 (2014).
[Crossref] [PubMed]

H. Niu and Y. He, “Resting-state functional brain connectivity: lessons from functional near-infrared spectroscopy,” Neuroscientist 20(2), 173–188 (2014).
[Crossref] [PubMed]

M. Nasiriavanaki, J. Xia, H. Wan, A. Q. Bauer, J. P. Culver, and L. V. Wang, “High-resolution photoacoustic tomography of resting-state functional connectivity in the mouse brain,” Proc. Natl. Acad. Sci. U.S.A. 111(1), 21–26 (2014).
[Crossref] [PubMed]

2013 (6)

A. M. Hermundstad, D. S. Bassett, K. S. Brown, E. M. Aminoff, D. Clewett, S. Freeman, A. Frithsen, A. Johnson, C. M. Tipper, M. B. Miller, S. T. Grafton, and J. M. Carlson, “Structural foundations of resting-state and task-based functional connectivity in the human brain,” Proc. Natl. Acad. Sci. USA 110(15), 6169–6174 (2013).
[Crossref] [PubMed]

R. M. Hutchison, T. Womelsdorf, E. A. Allen, P. A. Bandettini, V. D. Calhoun, M. Corbetta, S. Della Penna, J. H. Duyn, G. H. Glover, J. Gonzalez-Castillo, D. A. Handwerker, S. Keilholz, V. Kiviniemi, D. A. Leopold, F. de Pasquale, O. Sporns, M. Walter, and C. Chang, “Dynamic functional connectivity: promise, issues, and interpretations,” Neuroimage 80, 360–378 (2013).
[Crossref] [PubMed]

R. M. Hutchison, T. Womelsdorf, J. S. Gati, S. Everling, and R. S. Menon, “Resting-state networks show dynamic functional connectivity in awake humans and anesthetized macaques,” Hum. Brain Mapp. 34(9), 2154–2177 (2013).
[Crossref] [PubMed]

J. A. Turner, E. Damaraju, T. G. van Erp, D. H. Mathalon, J. M. Ford, J. Voyvodic, B. A. Mueller, A. Belger, J. Bustillo, S. McEwen, S. G. Potkin, Fbirn, and V. D. Calhoun, “A multi-site resting state fMRI study on the amplitude of low frequency fluctuations in schizophrenia,” Front. Neurosci. 7, 137 (2013).
[Crossref] [PubMed]

H. Niu, Z. Li, X. Liao, J. Wang, T. Zhao, N. Shu, X. Zhao, and Y. He, “Test-retest reliability of graph metrics in functional brain networks: a resting-state fNIRS study,” PLoS ONE 8(9), e72425 (2013).
[Crossref] [PubMed]

N. A. Crossley, A. Mechelli, P. E. Vértes, T. T. Winton-Brown, A. X. Patel, C. E. Ginestet, P. McGuire, and E. T. Bullmore, “Cognitive relevance of the community structure of the human brain functional coactivation network,” Proc. Natl. Acad. Sci. U.S.A. 110(28), 11583–11588 (2013).
[Crossref] [PubMed]

2012 (6)

B. R. White, S. M. Liao, S. L. Ferradal, T. E. Inder, and J. P. Culver, “Bedside optical imaging of occipital resting-state functional connectivity in neonates,” Neuroimage 59(3), 2529–2538 (2012).
[Crossref] [PubMed]

D. A. Handwerker, V. Roopchansingh, J. Gonzalez-Castillo, and P. A. Bandettini, “Periodic changes in fMRI connectivity,” Neuroimage 63(3), 1712–1719 (2012).
[Crossref] [PubMed]

C. J. Chu, M. A. Kramer, J. Pathmanathan, M. T. Bianchi, M. B. Westover, L. Wizon, and S. S. Cash, “Emergence of stable functional networks in long-term human electroencephalography,” J. Neurosci. 32(8), 2703–2713 (2012).
[Crossref] [PubMed]

D. T. Jones, P. Vemuri, M. C. Murphy, J. L. Gunter, M. L. Senjem, M. M. Machulda, S. A. Przybelski, B. E. Gregg, K. Kantarci, D. S. Knopman, B. F. Boeve, R. C. Petersen, and C. R. Jack., “Non-stationarity in the “resting brain’s” modular architecture,” PLoS ONE 7(6), e39731 (2012).
[Crossref] [PubMed]

S. W. Davis, J. E. Kragel, D. J. Madden, and R. Cabeza, “The Architecture of Cross-Hemispheric Communication in the Aging Brain: Linking Behavior to Functional and Structural Connectivity,” Cereb. Cortex 22(1), 232–242 (2012).
[Crossref] [PubMed]

H. Niu, J. Wang, T. Zhao, N. Shu, and Y. He, “Revealing topological organization of human brain functional networks with resting-state functional near infrared spectroscopy,” PLoS ONE 7(9), e45771 (2012).
[Crossref] [PubMed]

2011 (5)

M. A. Kramer, U. T. Eden, K. Q. Lepage, E. D. Kolaczyk, M. T. Bianchi, and S. S. Cash, “Emergence of persistent networks in long-term intracranial EEG recordings,” J. Neurosci. 31(44), 15757–15767 (2011).
[Crossref] [PubMed]

P. E. Holtzheimer and H. S. Mayberg, “Stuck in a rut: rethinking depression and its treatment,” Trends Neurosci. 34(1), 1–9 (2011).
[Crossref] [PubMed]

V. Kiviniemi, T. Vire, J. Remes, A. A. Elseoud, T. Starck, O. Tervonen, and J. Nikkinen, “A sliding time-window ICA reveals spatial variability of the default mode network in time,” Brain Connect 1(4), 339–347 (2011).
[Crossref] [PubMed]

H. Zhang, L. Duan, Y. J. Zhang, C. M. Lu, H. Liu, and C. Z. Zhu, “Test-retest assessment of independent component analysis-derived resting-state functional connectivity based on functional near-infrared spectroscopy,” Neuroimage 55(2), 607–615 (2011).
[Crossref] [PubMed]

D. S. Bassett, N. F. Wymbs, M. A. Porter, P. J. Mucha, J. M. Carlson, and S. T. Grafton, “Dynamic reconfiguration of human brain networks during learning,” Proc. Natl. Acad. Sci. U.S.A. 108(18), 7641–7646 (2011).
[Crossref] [PubMed]

2010 (10)

S. Sadaghiani, G. Hesselmann, K. J. Friston, and A. Kleinschmidt, “The relation of ongoing brain activity, evoked neural responses, and cognition,” Front. Syst. Neurosci. 4, 20 (2010).
[PubMed]

M. W. Cole, A. Bagic, R. Kass, and W. Schneider, “Prefrontal dynamics underlying rapid instructed task learning reverse with practice,” J. Neurosci. 30(42), 14245–14254 (2010).
[Crossref] [PubMed]

F. Homae, H. Watanabe, T. Otobe, T. Nakano, T. Go, Y. Konishi, and G. Taga, “Development of global cortical networks in early infancy,” J. Neurosci. 30(14), 4877–4882 (2010).
[Crossref] [PubMed]

U. Sakoğlu, G. D. Pearlson, K. A. Kiehl, Y. M. Wang, A. M. Michael, and V. D. Calhoun, “A method for evaluating dynamic functional network connectivity and task-modulation: application to schizophrenia,” MAGMA 23(5-6), 351–366 (2010).
[Crossref] [PubMed]

P. Delamillieure, G. Doucet, B. Mazoyer, M. R. Turbelin, N. Delcroix, E. Mellet, L. Zago, F. Crivello, L. Petit, N. Tzourio-Mazoyer, and M. Joliot, “The resting state questionnaire: An introspective questionnaire for evaluation of inner experience during the conscious resting state,” Brain Res. Bull. 81(6), 565–573 (2010).
[Crossref] [PubMed]

F. de Pasquale, S. Della Penna, A. Z. Snyder, C. Lewis, D. Mantini, L. Marzetti, P. Belardinelli, L. Ciancetta, V. Pizzella, G. L. Romani, and M. Corbetta, “Temporal dynamics of spontaneous MEG activity in brain networks,” Proc. Natl. Acad. Sci. U.S.A. 107(13), 6040–6045 (2010).
[Crossref] [PubMed]

C. Chang and G. H. Glover, “Time-frequency dynamics of resting-state brain connectivity measured with fMRI,” Neuroimage 50(1), 81–98 (2010).
[Crossref] [PubMed]

H. Zhang, Y. J. Zhang, C. M. Lu, S. Y. Ma, Y. F. Zang, and C. Z. Zhu, “Functional connectivity as revealed by independent component analysis of resting-state fNIRS measurements,” Neuroimage 51(3), 1150–1161 (2010).
[Crossref] [PubMed]

C. M. Lu, Y. J. Zhang, B. B. Biswal, Y. F. Zang, D. L. Peng, and C. Z. Zhu, “Use of fNIRS to assess resting state functional connectivity,” J. Neurosci. Methods 186(2), 242–249 (2010).
[Crossref] [PubMed]

Y. J. Zhang, C. M. Lu, B. B. Biswal, Y. F. Zang, D. L. Peng, and C. Z. Zhu, “Detecting resting-state functional connectivity in the language system using functional near-infrared spectroscopy,” J. Biomed. Opt. 15(4), 047003 (2010).
[Crossref] [PubMed]

2009 (4)

B. R. White, A. Z. Snyder, A. L. Cohen, S. E. Petersen, M. E. Raichle, B. L. Schlaggar, and J. P. Culver, “Resting-state functional connectivity in the human brain revealed with diffuse optical tomography,” Neuroimage 47(1), 148–156 (2009).
[Crossref] [PubMed]

D. L. Ringach, “Spontaneous and driven cortical activity: implications for computation,” Curr. Opin. Neurobiol. 19(4), 439–444 (2009).
[Crossref] [PubMed]

M. D. Greicius, K. Supekar, V. Menon, and R. F. Dougherty, “Resting-state functional connectivity reflects structural connectivity in the default mode network,” Cereb. Cortex 19(1), 72–78 (2009).
[Crossref] [PubMed]

M. P. van den Heuvel, R. C. W. Mandl, R. S. Kahn, and H. E. Hulshoff Pol, “Functionally linked resting-state networks reflect the underlying structural connectivity architecture of the human brain,” Hum. Brain Mapp. 30(10), 3127–3141 (2009).
[Crossref] [PubMed]

2008 (1)

D. E. Stark, D. S. Margulies, Z. E. Shehzad, P. Reiss, A. M. Kelly, L. Q. Uddin, D. G. Gee, A. K. Roy, M. T. Banich, F. X. Castellanos, and M. P. Milham, “Regional Variation in Interhemispheric Coordination of Intrinsic Hemodynamic Fluctuations,” J. Neurosci. 28(51), 13754–13764 (2008).
[Crossref] [PubMed]

2007 (1)

S. Kohno, I. Miyai, A. Seiyama, I. Oda, A. Ishikawa, S. Tsuneishi, T. Amita, and K. Shimizu, “Removal of the skin blood flow artifact in functional near-infrared spectroscopic imaging data through independent component analysis,” J. Biomed. Opt. 12(6), 062111 (2007).
[Crossref] [PubMed]

2005 (1)

T. P. Vogels, K. Rajan, and L. F. Abbott, “Neural network dynamics,” Annu. Rev. Neurosci. 28(1), 357–376 (2005).
[Crossref] [PubMed]

2004 (2)

O. Sporns and J. D. Zwi, “The small world of the cerebral cortex,” Neuroinformatics 2(2), 145–162 (2004).
[Crossref] [PubMed]

D. A. Boas, A. M. Dale, and M. A. Franceschini, “Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution, and accuracy,” Neuroimage 23(Suppl 1), S275–S288 (2004).
[Crossref] [PubMed]

2003 (1)

T. H. Bullock, “Have brain dynamics evolved? Should we look for unique dynamics in the sapient species?” Neural Comput. 15(9), 2013–2027 (2003).
[Crossref] [PubMed]

1998 (1)

M.-M. Mesulam, “From sensation to cognition,” Brain 121(6), 1013–1052 (1998).
[Crossref] [PubMed]

1997 (1)

A. Villringer and B. Chance, “Non-invasive optical spectroscopy and imaging of human brain function,” Trends Neurosci. 20(10), 435–442 (1997).
[Crossref] [PubMed]

1995 (1)

B. Biswal, F. Z. Yetkin, V. M. Haughton, and J. S. Hyde, “Functional connectivity in the motor cortex of resting human brain using echo-planar mri,” Magn. Reson. Med. 34(4), 537–541 (1995).
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Abbott, L. F.

T. P. Vogels, K. Rajan, and L. F. Abbott, “Neural network dynamics,” Annu. Rev. Neurosci. 28(1), 357–376 (2005).
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Allen, E. A.

E. A. Allen, E. Damaraju, S. M. Plis, E. B. Erhardt, T. Eichele, and V. D. Calhoun, “Tracking whole-brain connectivity dynamics in the resting state,” Cereb. Cortex 24(3), 663–676 (2014).
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R. M. Hutchison, T. Womelsdorf, E. A. Allen, P. A. Bandettini, V. D. Calhoun, M. Corbetta, S. Della Penna, J. H. Duyn, G. H. Glover, J. Gonzalez-Castillo, D. A. Handwerker, S. Keilholz, V. Kiviniemi, D. A. Leopold, F. de Pasquale, O. Sporns, M. Walter, and C. Chang, “Dynamic functional connectivity: promise, issues, and interpretations,” Neuroimage 80, 360–378 (2013).
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Aminoff, E. M.

A. M. Hermundstad, D. S. Bassett, K. S. Brown, E. M. Aminoff, D. Clewett, S. Freeman, A. Frithsen, A. Johnson, C. M. Tipper, M. B. Miller, S. T. Grafton, and J. M. Carlson, “Structural foundations of resting-state and task-based functional connectivity in the human brain,” Proc. Natl. Acad. Sci. USA 110(15), 6169–6174 (2013).
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Amita, T.

S. Kohno, I. Miyai, A. Seiyama, I. Oda, A. Ishikawa, S. Tsuneishi, T. Amita, and K. Shimizu, “Removal of the skin blood flow artifact in functional near-infrared spectroscopic imaging data through independent component analysis,” J. Biomed. Opt. 12(6), 062111 (2007).
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Bagic, A.

M. W. Cole, A. Bagic, R. Kass, and W. Schneider, “Prefrontal dynamics underlying rapid instructed task learning reverse with practice,” J. Neurosci. 30(42), 14245–14254 (2010).
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Bandettini, P. A.

R. M. Hutchison, T. Womelsdorf, E. A. Allen, P. A. Bandettini, V. D. Calhoun, M. Corbetta, S. Della Penna, J. H. Duyn, G. H. Glover, J. Gonzalez-Castillo, D. A. Handwerker, S. Keilholz, V. Kiviniemi, D. A. Leopold, F. de Pasquale, O. Sporns, M. Walter, and C. Chang, “Dynamic functional connectivity: promise, issues, and interpretations,” Neuroimage 80, 360–378 (2013).
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D. A. Handwerker, V. Roopchansingh, J. Gonzalez-Castillo, and P. A. Bandettini, “Periodic changes in fMRI connectivity,” Neuroimage 63(3), 1712–1719 (2012).
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Banich, M. T.

D. E. Stark, D. S. Margulies, Z. E. Shehzad, P. Reiss, A. M. Kelly, L. Q. Uddin, D. G. Gee, A. K. Roy, M. T. Banich, F. X. Castellanos, and M. P. Milham, “Regional Variation in Interhemispheric Coordination of Intrinsic Hemodynamic Fluctuations,” J. Neurosci. 28(51), 13754–13764 (2008).
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Bassett, D. S.

A. M. Hermundstad, D. S. Bassett, K. S. Brown, E. M. Aminoff, D. Clewett, S. Freeman, A. Frithsen, A. Johnson, C. M. Tipper, M. B. Miller, S. T. Grafton, and J. M. Carlson, “Structural foundations of resting-state and task-based functional connectivity in the human brain,” Proc. Natl. Acad. Sci. USA 110(15), 6169–6174 (2013).
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D. S. Bassett, N. F. Wymbs, M. A. Porter, P. J. Mucha, J. M. Carlson, and S. T. Grafton, “Dynamic reconfiguration of human brain networks during learning,” Proc. Natl. Acad. Sci. U.S.A. 108(18), 7641–7646 (2011).
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Bauer, A. Q.

M. Nasiriavanaki, J. Xia, H. Wan, A. Q. Bauer, J. P. Culver, and L. V. Wang, “High-resolution photoacoustic tomography of resting-state functional connectivity in the mouse brain,” Proc. Natl. Acad. Sci. U.S.A. 111(1), 21–26 (2014).
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Belardinelli, P.

F. de Pasquale, S. Della Penna, A. Z. Snyder, C. Lewis, D. Mantini, L. Marzetti, P. Belardinelli, L. Ciancetta, V. Pizzella, G. L. Romani, and M. Corbetta, “Temporal dynamics of spontaneous MEG activity in brain networks,” Proc. Natl. Acad. Sci. U.S.A. 107(13), 6040–6045 (2010).
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Belger, A.

J. A. Turner, E. Damaraju, T. G. van Erp, D. H. Mathalon, J. M. Ford, J. Voyvodic, B. A. Mueller, A. Belger, J. Bustillo, S. McEwen, S. G. Potkin, Fbirn, and V. D. Calhoun, “A multi-site resting state fMRI study on the amplitude of low frequency fluctuations in schizophrenia,” Front. Neurosci. 7, 137 (2013).
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Bianchi, M. T.

C. J. Chu, M. A. Kramer, J. Pathmanathan, M. T. Bianchi, M. B. Westover, L. Wizon, and S. S. Cash, “Emergence of stable functional networks in long-term human electroencephalography,” J. Neurosci. 32(8), 2703–2713 (2012).
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M. A. Kramer, U. T. Eden, K. Q. Lepage, E. D. Kolaczyk, M. T. Bianchi, and S. S. Cash, “Emergence of persistent networks in long-term intracranial EEG recordings,” J. Neurosci. 31(44), 15757–15767 (2011).
[Crossref] [PubMed]

Biswal, B.

B. Biswal, F. Z. Yetkin, V. M. Haughton, and J. S. Hyde, “Functional connectivity in the motor cortex of resting human brain using echo-planar mri,” Magn. Reson. Med. 34(4), 537–541 (1995).
[Crossref] [PubMed]

Biswal, B. B.

C. M. Lu, Y. J. Zhang, B. B. Biswal, Y. F. Zang, D. L. Peng, and C. Z. Zhu, “Use of fNIRS to assess resting state functional connectivity,” J. Neurosci. Methods 186(2), 242–249 (2010).
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Y. J. Zhang, C. M. Lu, B. B. Biswal, Y. F. Zang, D. L. Peng, and C. Z. Zhu, “Detecting resting-state functional connectivity in the language system using functional near-infrared spectroscopy,” J. Biomed. Opt. 15(4), 047003 (2010).
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Boas, D. A.

D. A. Boas, A. M. Dale, and M. A. Franceschini, “Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution, and accuracy,” Neuroimage 23(Suppl 1), S275–S288 (2004).
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Boeve, B. F.

D. T. Jones, P. Vemuri, M. C. Murphy, J. L. Gunter, M. L. Senjem, M. M. Machulda, S. A. Przybelski, B. E. Gregg, K. Kantarci, D. S. Knopman, B. F. Boeve, R. C. Petersen, and C. R. Jack., “Non-stationarity in the “resting brain’s” modular architecture,” PLoS ONE 7(6), e39731 (2012).
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Breakspear, M.

A. Zalesky, A. Fornito, L. Cocchi, L. L. Gollo, and M. Breakspear, “Time-resolved resting-state brain networks,” Proc. Natl. Acad. Sci. USA 111(28), 10341–10346 (2014).
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Brown, K. S.

A. M. Hermundstad, D. S. Bassett, K. S. Brown, E. M. Aminoff, D. Clewett, S. Freeman, A. Frithsen, A. Johnson, C. M. Tipper, M. B. Miller, S. T. Grafton, and J. M. Carlson, “Structural foundations of resting-state and task-based functional connectivity in the human brain,” Proc. Natl. Acad. Sci. USA 110(15), 6169–6174 (2013).
[Crossref] [PubMed]

Bullmore, E. T.

N. A. Crossley, A. Mechelli, P. E. Vértes, T. T. Winton-Brown, A. X. Patel, C. E. Ginestet, P. McGuire, and E. T. Bullmore, “Cognitive relevance of the community structure of the human brain functional coactivation network,” Proc. Natl. Acad. Sci. U.S.A. 110(28), 11583–11588 (2013).
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Bullock, T. H.

T. H. Bullock, “Have brain dynamics evolved? Should we look for unique dynamics in the sapient species?” Neural Comput. 15(9), 2013–2027 (2003).
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Bustillo, J.

J. A. Turner, E. Damaraju, T. G. van Erp, D. H. Mathalon, J. M. Ford, J. Voyvodic, B. A. Mueller, A. Belger, J. Bustillo, S. McEwen, S. G. Potkin, Fbirn, and V. D. Calhoun, “A multi-site resting state fMRI study on the amplitude of low frequency fluctuations in schizophrenia,” Front. Neurosci. 7, 137 (2013).
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Cabeza, R.

S. W. Davis, J. E. Kragel, D. J. Madden, and R. Cabeza, “The Architecture of Cross-Hemispheric Communication in the Aging Brain: Linking Behavior to Functional and Structural Connectivity,” Cereb. Cortex 22(1), 232–242 (2012).
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Calhoun, V. D.

E. A. Allen, E. Damaraju, S. M. Plis, E. B. Erhardt, T. Eichele, and V. D. Calhoun, “Tracking whole-brain connectivity dynamics in the resting state,” Cereb. Cortex 24(3), 663–676 (2014).
[Crossref] [PubMed]

R. M. Hutchison, T. Womelsdorf, E. A. Allen, P. A. Bandettini, V. D. Calhoun, M. Corbetta, S. Della Penna, J. H. Duyn, G. H. Glover, J. Gonzalez-Castillo, D. A. Handwerker, S. Keilholz, V. Kiviniemi, D. A. Leopold, F. de Pasquale, O. Sporns, M. Walter, and C. Chang, “Dynamic functional connectivity: promise, issues, and interpretations,” Neuroimage 80, 360–378 (2013).
[Crossref] [PubMed]

J. A. Turner, E. Damaraju, T. G. van Erp, D. H. Mathalon, J. M. Ford, J. Voyvodic, B. A. Mueller, A. Belger, J. Bustillo, S. McEwen, S. G. Potkin, Fbirn, and V. D. Calhoun, “A multi-site resting state fMRI study on the amplitude of low frequency fluctuations in schizophrenia,” Front. Neurosci. 7, 137 (2013).
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U. Sakoğlu, G. D. Pearlson, K. A. Kiehl, Y. M. Wang, A. M. Michael, and V. D. Calhoun, “A method for evaluating dynamic functional network connectivity and task-modulation: application to schizophrenia,” MAGMA 23(5-6), 351–366 (2010).
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Carlson, J. M.

A. M. Hermundstad, D. S. Bassett, K. S. Brown, E. M. Aminoff, D. Clewett, S. Freeman, A. Frithsen, A. Johnson, C. M. Tipper, M. B. Miller, S. T. Grafton, and J. M. Carlson, “Structural foundations of resting-state and task-based functional connectivity in the human brain,” Proc. Natl. Acad. Sci. USA 110(15), 6169–6174 (2013).
[Crossref] [PubMed]

D. S. Bassett, N. F. Wymbs, M. A. Porter, P. J. Mucha, J. M. Carlson, and S. T. Grafton, “Dynamic reconfiguration of human brain networks during learning,” Proc. Natl. Acad. Sci. U.S.A. 108(18), 7641–7646 (2011).
[Crossref] [PubMed]

Cash, S. S.

C. J. Chu, M. A. Kramer, J. Pathmanathan, M. T. Bianchi, M. B. Westover, L. Wizon, and S. S. Cash, “Emergence of stable functional networks in long-term human electroencephalography,” J. Neurosci. 32(8), 2703–2713 (2012).
[Crossref] [PubMed]

M. A. Kramer, U. T. Eden, K. Q. Lepage, E. D. Kolaczyk, M. T. Bianchi, and S. S. Cash, “Emergence of persistent networks in long-term intracranial EEG recordings,” J. Neurosci. 31(44), 15757–15767 (2011).
[Crossref] [PubMed]

Castellanos, F. X.

D. E. Stark, D. S. Margulies, Z. E. Shehzad, P. Reiss, A. M. Kelly, L. Q. Uddin, D. G. Gee, A. K. Roy, M. T. Banich, F. X. Castellanos, and M. P. Milham, “Regional Variation in Interhemispheric Coordination of Intrinsic Hemodynamic Fluctuations,” J. Neurosci. 28(51), 13754–13764 (2008).
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Chance, B.

A. Villringer and B. Chance, “Non-invasive optical spectroscopy and imaging of human brain function,” Trends Neurosci. 20(10), 435–442 (1997).
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Chang, C.

R. M. Hutchison, T. Womelsdorf, E. A. Allen, P. A. Bandettini, V. D. Calhoun, M. Corbetta, S. Della Penna, J. H. Duyn, G. H. Glover, J. Gonzalez-Castillo, D. A. Handwerker, S. Keilholz, V. Kiviniemi, D. A. Leopold, F. de Pasquale, O. Sporns, M. Walter, and C. Chang, “Dynamic functional connectivity: promise, issues, and interpretations,” Neuroimage 80, 360–378 (2013).
[Crossref] [PubMed]

C. Chang and G. H. Glover, “Time-frequency dynamics of resting-state brain connectivity measured with fMRI,” Neuroimage 50(1), 81–98 (2010).
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Chu, C. J.

C. J. Chu, M. A. Kramer, J. Pathmanathan, M. T. Bianchi, M. B. Westover, L. Wizon, and S. S. Cash, “Emergence of stable functional networks in long-term human electroencephalography,” J. Neurosci. 32(8), 2703–2713 (2012).
[Crossref] [PubMed]

Ciancetta, L.

F. de Pasquale, S. Della Penna, A. Z. Snyder, C. Lewis, D. Mantini, L. Marzetti, P. Belardinelli, L. Ciancetta, V. Pizzella, G. L. Romani, and M. Corbetta, “Temporal dynamics of spontaneous MEG activity in brain networks,” Proc. Natl. Acad. Sci. U.S.A. 107(13), 6040–6045 (2010).
[Crossref] [PubMed]

Clewett, D.

A. M. Hermundstad, D. S. Bassett, K. S. Brown, E. M. Aminoff, D. Clewett, S. Freeman, A. Frithsen, A. Johnson, C. M. Tipper, M. B. Miller, S. T. Grafton, and J. M. Carlson, “Structural foundations of resting-state and task-based functional connectivity in the human brain,” Proc. Natl. Acad. Sci. USA 110(15), 6169–6174 (2013).
[Crossref] [PubMed]

Cocchi, L.

A. Zalesky, A. Fornito, L. Cocchi, L. L. Gollo, and M. Breakspear, “Time-resolved resting-state brain networks,” Proc. Natl. Acad. Sci. USA 111(28), 10341–10346 (2014).
[Crossref] [PubMed]

Cohen, A. L.

B. R. White, A. Z. Snyder, A. L. Cohen, S. E. Petersen, M. E. Raichle, B. L. Schlaggar, and J. P. Culver, “Resting-state functional connectivity in the human brain revealed with diffuse optical tomography,” Neuroimage 47(1), 148–156 (2009).
[Crossref] [PubMed]

Cole, M. W.

M. W. Cole, A. Bagic, R. Kass, and W. Schneider, “Prefrontal dynamics underlying rapid instructed task learning reverse with practice,” J. Neurosci. 30(42), 14245–14254 (2010).
[Crossref] [PubMed]

Corbetta, M.

R. M. Hutchison, T. Womelsdorf, E. A. Allen, P. A. Bandettini, V. D. Calhoun, M. Corbetta, S. Della Penna, J. H. Duyn, G. H. Glover, J. Gonzalez-Castillo, D. A. Handwerker, S. Keilholz, V. Kiviniemi, D. A. Leopold, F. de Pasquale, O. Sporns, M. Walter, and C. Chang, “Dynamic functional connectivity: promise, issues, and interpretations,” Neuroimage 80, 360–378 (2013).
[Crossref] [PubMed]

F. de Pasquale, S. Della Penna, A. Z. Snyder, C. Lewis, D. Mantini, L. Marzetti, P. Belardinelli, L. Ciancetta, V. Pizzella, G. L. Romani, and M. Corbetta, “Temporal dynamics of spontaneous MEG activity in brain networks,” Proc. Natl. Acad. Sci. U.S.A. 107(13), 6040–6045 (2010).
[Crossref] [PubMed]

Crivello, F.

P. Delamillieure, G. Doucet, B. Mazoyer, M. R. Turbelin, N. Delcroix, E. Mellet, L. Zago, F. Crivello, L. Petit, N. Tzourio-Mazoyer, and M. Joliot, “The resting state questionnaire: An introspective questionnaire for evaluation of inner experience during the conscious resting state,” Brain Res. Bull. 81(6), 565–573 (2010).
[Crossref] [PubMed]

Crossley, N. A.

N. A. Crossley, A. Mechelli, P. E. Vértes, T. T. Winton-Brown, A. X. Patel, C. E. Ginestet, P. McGuire, and E. T. Bullmore, “Cognitive relevance of the community structure of the human brain functional coactivation network,” Proc. Natl. Acad. Sci. U.S.A. 110(28), 11583–11588 (2013).
[Crossref] [PubMed]

Culver, J. P.

M. Nasiriavanaki, J. Xia, H. Wan, A. Q. Bauer, J. P. Culver, and L. V. Wang, “High-resolution photoacoustic tomography of resting-state functional connectivity in the mouse brain,” Proc. Natl. Acad. Sci. U.S.A. 111(1), 21–26 (2014).
[Crossref] [PubMed]

B. R. White, S. M. Liao, S. L. Ferradal, T. E. Inder, and J. P. Culver, “Bedside optical imaging of occipital resting-state functional connectivity in neonates,” Neuroimage 59(3), 2529–2538 (2012).
[Crossref] [PubMed]

B. R. White, A. Z. Snyder, A. L. Cohen, S. E. Petersen, M. E. Raichle, B. L. Schlaggar, and J. P. Culver, “Resting-state functional connectivity in the human brain revealed with diffuse optical tomography,” Neuroimage 47(1), 148–156 (2009).
[Crossref] [PubMed]

Dale, A. M.

D. A. Boas, A. M. Dale, and M. A. Franceschini, “Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution, and accuracy,” Neuroimage 23(Suppl 1), S275–S288 (2004).
[Crossref] [PubMed]

Damaraju, E.

E. A. Allen, E. Damaraju, S. M. Plis, E. B. Erhardt, T. Eichele, and V. D. Calhoun, “Tracking whole-brain connectivity dynamics in the resting state,” Cereb. Cortex 24(3), 663–676 (2014).
[Crossref] [PubMed]

J. A. Turner, E. Damaraju, T. G. van Erp, D. H. Mathalon, J. M. Ford, J. Voyvodic, B. A. Mueller, A. Belger, J. Bustillo, S. McEwen, S. G. Potkin, Fbirn, and V. D. Calhoun, “A multi-site resting state fMRI study on the amplitude of low frequency fluctuations in schizophrenia,” Front. Neurosci. 7, 137 (2013).
[Crossref] [PubMed]

Davis, S. W.

S. W. Davis, J. E. Kragel, D. J. Madden, and R. Cabeza, “The Architecture of Cross-Hemispheric Communication in the Aging Brain: Linking Behavior to Functional and Structural Connectivity,” Cereb. Cortex 22(1), 232–242 (2012).
[Crossref] [PubMed]

de Pasquale, F.

R. M. Hutchison, T. Womelsdorf, E. A. Allen, P. A. Bandettini, V. D. Calhoun, M. Corbetta, S. Della Penna, J. H. Duyn, G. H. Glover, J. Gonzalez-Castillo, D. A. Handwerker, S. Keilholz, V. Kiviniemi, D. A. Leopold, F. de Pasquale, O. Sporns, M. Walter, and C. Chang, “Dynamic functional connectivity: promise, issues, and interpretations,” Neuroimage 80, 360–378 (2013).
[Crossref] [PubMed]

F. de Pasquale, S. Della Penna, A. Z. Snyder, C. Lewis, D. Mantini, L. Marzetti, P. Belardinelli, L. Ciancetta, V. Pizzella, G. L. Romani, and M. Corbetta, “Temporal dynamics of spontaneous MEG activity in brain networks,” Proc. Natl. Acad. Sci. U.S.A. 107(13), 6040–6045 (2010).
[Crossref] [PubMed]

Delamillieure, P.

P. Delamillieure, G. Doucet, B. Mazoyer, M. R. Turbelin, N. Delcroix, E. Mellet, L. Zago, F. Crivello, L. Petit, N. Tzourio-Mazoyer, and M. Joliot, “The resting state questionnaire: An introspective questionnaire for evaluation of inner experience during the conscious resting state,” Brain Res. Bull. 81(6), 565–573 (2010).
[Crossref] [PubMed]

Delcroix, N.

P. Delamillieure, G. Doucet, B. Mazoyer, M. R. Turbelin, N. Delcroix, E. Mellet, L. Zago, F. Crivello, L. Petit, N. Tzourio-Mazoyer, and M. Joliot, “The resting state questionnaire: An introspective questionnaire for evaluation of inner experience during the conscious resting state,” Brain Res. Bull. 81(6), 565–573 (2010).
[Crossref] [PubMed]

Della Penna, S.

R. M. Hutchison, T. Womelsdorf, E. A. Allen, P. A. Bandettini, V. D. Calhoun, M. Corbetta, S. Della Penna, J. H. Duyn, G. H. Glover, J. Gonzalez-Castillo, D. A. Handwerker, S. Keilholz, V. Kiviniemi, D. A. Leopold, F. de Pasquale, O. Sporns, M. Walter, and C. Chang, “Dynamic functional connectivity: promise, issues, and interpretations,” Neuroimage 80, 360–378 (2013).
[Crossref] [PubMed]

F. de Pasquale, S. Della Penna, A. Z. Snyder, C. Lewis, D. Mantini, L. Marzetti, P. Belardinelli, L. Ciancetta, V. Pizzella, G. L. Romani, and M. Corbetta, “Temporal dynamics of spontaneous MEG activity in brain networks,” Proc. Natl. Acad. Sci. U.S.A. 107(13), 6040–6045 (2010).
[Crossref] [PubMed]

Doucet, G.

P. Delamillieure, G. Doucet, B. Mazoyer, M. R. Turbelin, N. Delcroix, E. Mellet, L. Zago, F. Crivello, L. Petit, N. Tzourio-Mazoyer, and M. Joliot, “The resting state questionnaire: An introspective questionnaire for evaluation of inner experience during the conscious resting state,” Brain Res. Bull. 81(6), 565–573 (2010).
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Dougherty, R. F.

M. D. Greicius, K. Supekar, V. Menon, and R. F. Dougherty, “Resting-state functional connectivity reflects structural connectivity in the default mode network,” Cereb. Cortex 19(1), 72–78 (2009).
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Duan, L.

H. Zhang, L. Duan, Y. J. Zhang, C. M. Lu, H. Liu, and C. Z. Zhu, “Test-retest assessment of independent component analysis-derived resting-state functional connectivity based on functional near-infrared spectroscopy,” Neuroimage 55(2), 607–615 (2011).
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Duyn, J. H.

R. M. Hutchison, T. Womelsdorf, E. A. Allen, P. A. Bandettini, V. D. Calhoun, M. Corbetta, S. Della Penna, J. H. Duyn, G. H. Glover, J. Gonzalez-Castillo, D. A. Handwerker, S. Keilholz, V. Kiviniemi, D. A. Leopold, F. de Pasquale, O. Sporns, M. Walter, and C. Chang, “Dynamic functional connectivity: promise, issues, and interpretations,” Neuroimage 80, 360–378 (2013).
[Crossref] [PubMed]

Eden, U. T.

M. A. Kramer, U. T. Eden, K. Q. Lepage, E. D. Kolaczyk, M. T. Bianchi, and S. S. Cash, “Emergence of persistent networks in long-term intracranial EEG recordings,” J. Neurosci. 31(44), 15757–15767 (2011).
[Crossref] [PubMed]

Eichele, T.

E. A. Allen, E. Damaraju, S. M. Plis, E. B. Erhardt, T. Eichele, and V. D. Calhoun, “Tracking whole-brain connectivity dynamics in the resting state,” Cereb. Cortex 24(3), 663–676 (2014).
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Elseoud, A. A.

V. Kiviniemi, T. Vire, J. Remes, A. A. Elseoud, T. Starck, O. Tervonen, and J. Nikkinen, “A sliding time-window ICA reveals spatial variability of the default mode network in time,” Brain Connect 1(4), 339–347 (2011).
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Erhardt, E. B.

E. A. Allen, E. Damaraju, S. M. Plis, E. B. Erhardt, T. Eichele, and V. D. Calhoun, “Tracking whole-brain connectivity dynamics in the resting state,” Cereb. Cortex 24(3), 663–676 (2014).
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Everling, S.

R. M. Hutchison, T. Womelsdorf, J. S. Gati, S. Everling, and R. S. Menon, “Resting-state networks show dynamic functional connectivity in awake humans and anesthetized macaques,” Hum. Brain Mapp. 34(9), 2154–2177 (2013).
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Fbirn,

J. A. Turner, E. Damaraju, T. G. van Erp, D. H. Mathalon, J. M. Ford, J. Voyvodic, B. A. Mueller, A. Belger, J. Bustillo, S. McEwen, S. G. Potkin, Fbirn, and V. D. Calhoun, “A multi-site resting state fMRI study on the amplitude of low frequency fluctuations in schizophrenia,” Front. Neurosci. 7, 137 (2013).
[Crossref] [PubMed]

Ferradal, S. L.

B. R. White, S. M. Liao, S. L. Ferradal, T. E. Inder, and J. P. Culver, “Bedside optical imaging of occipital resting-state functional connectivity in neonates,” Neuroimage 59(3), 2529–2538 (2012).
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A. Zalesky, A. Fornito, L. Cocchi, L. L. Gollo, and M. Breakspear, “Time-resolved resting-state brain networks,” Proc. Natl. Acad. Sci. USA 111(28), 10341–10346 (2014).
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B. Biswal, F. Z. Yetkin, V. M. Haughton, and J. S. Hyde, “Functional connectivity in the motor cortex of resting human brain using echo-planar mri,” Magn. Reson. Med. 34(4), 537–541 (1995).
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B. Biswal, F. Z. Yetkin, V. M. Haughton, and J. S. Hyde, “Functional connectivity in the motor cortex of resting human brain using echo-planar mri,” Magn. Reson. Med. 34(4), 537–541 (1995).
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D. T. Jones, P. Vemuri, M. C. Murphy, J. L. Gunter, M. L. Senjem, M. M. Machulda, S. A. Przybelski, B. E. Gregg, K. Kantarci, D. S. Knopman, B. F. Boeve, R. C. Petersen, and C. R. Jack., “Non-stationarity in the “resting brain’s” modular architecture,” PLoS ONE 7(6), e39731 (2012).
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D. T. Jones, P. Vemuri, M. C. Murphy, J. L. Gunter, M. L. Senjem, M. M. Machulda, S. A. Przybelski, B. E. Gregg, K. Kantarci, D. S. Knopman, B. F. Boeve, R. C. Petersen, and C. R. Jack., “Non-stationarity in the “resting brain’s” modular architecture,” PLoS ONE 7(6), e39731 (2012).
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Madden, D. J.

S. W. Davis, J. E. Kragel, D. J. Madden, and R. Cabeza, “The Architecture of Cross-Hemispheric Communication in the Aging Brain: Linking Behavior to Functional and Structural Connectivity,” Cereb. Cortex 22(1), 232–242 (2012).
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Mandl, R. C. W.

M. P. van den Heuvel, R. C. W. Mandl, R. S. Kahn, and H. E. Hulshoff Pol, “Functionally linked resting-state networks reflect the underlying structural connectivity architecture of the human brain,” Hum. Brain Mapp. 30(10), 3127–3141 (2009).
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F. de Pasquale, S. Della Penna, A. Z. Snyder, C. Lewis, D. Mantini, L. Marzetti, P. Belardinelli, L. Ciancetta, V. Pizzella, G. L. Romani, and M. Corbetta, “Temporal dynamics of spontaneous MEG activity in brain networks,” Proc. Natl. Acad. Sci. U.S.A. 107(13), 6040–6045 (2010).
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F. de Pasquale, S. Della Penna, A. Z. Snyder, C. Lewis, D. Mantini, L. Marzetti, P. Belardinelli, L. Ciancetta, V. Pizzella, G. L. Romani, and M. Corbetta, “Temporal dynamics of spontaneous MEG activity in brain networks,” Proc. Natl. Acad. Sci. U.S.A. 107(13), 6040–6045 (2010).
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J. A. Turner, E. Damaraju, T. G. van Erp, D. H. Mathalon, J. M. Ford, J. Voyvodic, B. A. Mueller, A. Belger, J. Bustillo, S. McEwen, S. G. Potkin, Fbirn, and V. D. Calhoun, “A multi-site resting state fMRI study on the amplitude of low frequency fluctuations in schizophrenia,” Front. Neurosci. 7, 137 (2013).
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U. Sakoğlu, G. D. Pearlson, K. A. Kiehl, Y. M. Wang, A. M. Michael, and V. D. Calhoun, “A method for evaluating dynamic functional network connectivity and task-modulation: application to schizophrenia,” MAGMA 23(5-6), 351–366 (2010).
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B. R. White, S. M. Liao, S. L. Ferradal, T. E. Inder, and J. P. Culver, “Bedside optical imaging of occipital resting-state functional connectivity in neonates,” Neuroimage 59(3), 2529–2538 (2012).
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B. R. White, A. Z. Snyder, A. L. Cohen, S. E. Petersen, M. E. Raichle, B. L. Schlaggar, and J. P. Culver, “Resting-state functional connectivity in the human brain revealed with diffuse optical tomography,” Neuroimage 47(1), 148–156 (2009).
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Figures (7)

Fig. 1
Fig. 1 Illustration of fNIRS-based FC analysis. (A)Photograph of whole-head fNIRS data acquisition on a participant. (B) The schematic of whole-head imaging pad (12 sources, red, and 24 detectors, blue). The sources and detectors were symmetrically placed on the left and right hemispheres and constituted 46 measurement channels, which allowed for the whole brain (i.e., frontal, temporal, parietal, and occipital lobes to be measured. (C) Static FC analysis. The static FC was calculated from time series of entire scanning between any two channels. (D) Dynamic FC analysis. The dynamic FC was calculated using sliding-window correlation approach. In this approach, a time window of fixed length was selected, and data points within that window were used to calculate the FC. The window was then shifted in time by a fixed number of data points. This process results in quantification of the time-varying FC over the duration of the scan.
Fig. 2
Fig. 2 FC dynamics derived from HbO (left) and HbR (right) signals. (A) An example of dynamic FC maps displayed at an interval of 4 s on an arbitrary participant (Subject 14). (B) The Pearson “between-map” correlation coefficients, rm , calculated between the successive dynamic FC maps and the static FC map from Subject 14. The dotted straight line represents the mean and standard derivation of rm across the 10-min time window. (C) Similar calculation to (B) on all 18 subjects. The sliding-window length used to evaluate dynamic FC was 60 s.
Fig. 3
Fig. 3 Pattern comparison between FC variability strength, Q, and static FC strength. (A)The group-averaged Q values, (B) static FC strength and (C) the linear relationship between them derived from HbO and HbR, respectively. The values of index Q were quantified as the area under the curve of the power amplitude of the FC time series across the low-frequency band (< 0.1Hz).
Fig. 4
Fig. 4 Q difference and the static FC-strength difference in spatially different connectivity groups. (A) Configurations of selected connectivity groups (homotopic, long and short intrahemispheric and heterotopic connections) (B) Group-averaged power spectra of the dynamic FC time series in the four connectivity groups. The subplot showed the average of the power spectra across connections in each group. The lines with blue, red, yellow and green color represent the homotopic, long and short intrahemispheric and heterotopic connections, respectively. (C) Group differences in values of index Q between connectivity groups. (D) Group differences in static FC strength between connectivity groups. In (C and D), one and two asterisks represent significant group differences with permutation test at p <0.05 and 0.01 (Bonferroni-corrected), respectively. Error bars indicate standard deviations.
Fig. 5
Fig. 5 Reproducibility of the primary findings derived from HbO and HbR signals over two various sliding-window lengths (30 s and 90 s). (A, B) The negative correlation relationship between index Q and the static connectivity strength. (C, D) The group differences in values of index Q between connectivity groups. (E, F). The group-averaged power spectra of dynamic FC time series in the four connectivity groups. The lines with blue, red, yellow and green color represent the homotopic, long and short intrahemispheric and heterotopic connections, respectively. All these results show good reproducibility over varying sliding-window lengths.
Fig. 6
Fig. 6 Reproducibility of our primary findings derived from HbO and HbR signals across different fNIRS test data sets (Session 2). (A) The negative correlation relationship between index Q and static connectivity strength. (B, C) The group differences in values of index Q among four connectivity groups as well as the static connectivity strength among groups, respectively. The SWC approach with 60 s lengths was used to derive the dynamic FC.
Fig. 7
Fig. 7 Power spectral analyses of dynamic FC time series for all 18 subjects and two types of hemoglobin concentration signals (HbO and HbR). The sliding-window length was 60 s. In each panel, there are 46 × 45/2 power spectra curves that are overlapped and become a gray-shaded area.

Tables (1)

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Table 1 Correlation coefficient, r, between Q and static FC strength at the individual level

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