Abstract

The fMRI-based functional connectome was shown to be sufficiently unique to allow individual identification (fingerprinting). We aimed to test whether a fNIRS-based connectome could also be used to identify individuals. Forty-four participants performed experimental protocols that consisted of two periods of resting-state interleaved by a cognitive task period. Connectome identification was performed for all possible pairwise combinations of the three periods. The influence of hemodynamic global variation was tested using global signal regression and principal component analysis. High identification accuracies well-above chance level (2.3%) were observed overall, being particularly high (93%) to the oxyhemoglobin signal between resting conditions. Our results suggest that fNIRS is a suitable technique to assess connectome fingerprints.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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    [Crossref] [PubMed]

2018 (6)

T. Kaufmann, D. Alnæs, C. L. Brandt, F. Bettella, S. Djurovic, O. A. Andreassen, and L. T. Westlye, “Stability of the Brain Functional Connectome Fingerprint in Individuals With Schizophrenia,” JAMA Psychiatry 75(7), 749–751 (2018).
[Crossref] [PubMed]

O. Miranda-Dominguez, E. Feczko, D. S. Grayson, H. Walum, J. T. Nigg, and D. A. Fair, “Heritability of the human connectome: A connectotyping study,” Netw Neurosci 2(2), 175–199 (2018).
[Crossref] [PubMed]

C. Horien, S. Noble, E. S. Finn, X. Shen, D. Scheinost, and R. T. Constable, “Considering factors affecting the connectome-based identification process: Comment on Waller et al,” Neuroimage 169, 172–175 (2018).
[Crossref] [PubMed]

E. Amico and J. Goñi, “Mapping hybrid functional-structural connectivity traits in the human connectome,” Netw Neurosci 2(3), 306–322 (2018).
[Crossref] [PubMed]

M. D. Pfeifer, F. Scholkmann, and R. Labruyère, “Signal Processing in Functional Near-Infrared Spectroscopy (fNIRS): Methodological Differences Lead to Different Statistical Results,” Front. Hum. Neurosci. 11, 641 (2018).
[Crossref] [PubMed]

C. Gratton, T. O. Laumann, A. N. Nielsen, D. J. Greene, E. M. Gordon, A. W. Gilmore, S. M. Nelson, R. S. Coalson, A. Z. Snyder, B. L. Schlaggar, N. U. F. Dosenbach, and S. E. Petersen, “Functional Brain Networks Are Dominated by Stable Group and Individual Factors, Not Cognitive or Daily Variation,” Neuron 98(2), 439–452 (2018).
[Crossref] [PubMed]

2017 (11)

J. B. Balardin, G. A. Zimeo Morais, R. A. Furucho, L. Trambaiolli, P. Vanzella, C. Biazoli, and J. R. Sato, “Imaging brain function with functional near-infrared spectroscopy in unconstrained environments,” Front. Hum. Neurosci. 11, 258 (2017).
[Crossref] [PubMed]

K. Murphy and M. D. Fox, “Towards a consensus regarding global signal regression for resting state functional connectivity MRI,” Neuroimage 154, 169–173 (2017).
[Crossref] [PubMed]

E. S. Finn, D. Scheinost, D. M. Finn, X. Shen, X. Papademetris, and R. T. Constable, “Can brain state be manipulated to emphasize individual differences in functional connectivity?” Neuroimage 160, 140–151 (2017).
[Crossref] [PubMed]

T. Vanderwal, J. Eilbott, E. S. Finn, R. C. Craddock, A. Turnbull, and F. X. Castellanos, “Individual differences in functional connectivity during naturalistic viewing conditions,” Neuroimage 157, 521–530 (2017).
[Crossref] [PubMed]

L. Waller, H. Walter, J. D. Kruschwitz, L. Reuter, S. Müller, S. Erk, and I. M. Veer, “Evaluating the replicability, specificity, and generalizability of connectome fingerprints,” Neuroimage 158, 371–377 (2017).
[Crossref] [PubMed]

T.-H. Lee, M. E. Miernicki, and E. H. Telzer, “Families that fire together smile together: Resting state connectome similarity and daily emotional synchrony in parent-child dyads,” Neuroimage 152, 31–37 (2017).
[Crossref] [PubMed]

J. B. Balardin, G. A. Zimeo Morais, R. A. Furucho, L. Trambaiolli, P. Vanzella, C. Biazoli, and J. R. Sato, “Imaging Brain Function with Functional Near-Infrared Spectroscopy in Unconstrained Environments,” Front. Hum. Neurosci. 11, 258 (2017).
[Crossref] [PubMed]

K. Murphy and M. D. Fox, “Towards a consensus regarding global signal regression for resting state functional connectivity MRI,” Neuroimage 154, 169–173 (2017).
[Crossref] [PubMed]

T. Kaufmann, D. Alnæs, N. T. Doan, C. L. Brandt, O. A. Andreassen, and L. T. Westlye, “Delayed stabilization and individualization in connectome development are related to psychiatric disorders,” Nat. Neurosci. 20(4), 513–515 (2017).
[Crossref] [PubMed]

C. E. Biazoli, G. A. Salum, P. M. Pan, A. Zugman, E. Amaro, L. A. Rohde, E. C. Miguel, A. P. Jackowski, R. A. Bressan, and J. R. Sato, “Commentary: Functional connectome fingerprint: identifying individuals using patterns of brain connectivity,” Front. Hum. Neurosci. 11, 47 (2017).
[Crossref] [PubMed]

J. R. Sato, T. P. White, and C. E. Biazoli, “Commentary: A test-retest dataset for assessing long-term reliability of brain morphology and resting-state brain activity,” Front. Neurosci. 11, 85 (2017).
[Crossref] [PubMed]

2015 (2)

E. S. Finn, X. Shen, D. Scheinost, M. D. Rosenberg, J. Huang, M. M. Chun, X. Papademetris, and R. T. Constable, “Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity,” Nat. Neurosci. 18(11), 1664–1671 (2015).
[Crossref] [PubMed]

M. U. Dalmis and A. Akin, “Similarity analysis of functional connectivity with functional near-infrared spectroscopy,” J. Biomed. Opt. 20(8), 086012 (2015).
[Crossref] [PubMed]

2014 (1)

O. Miranda-Dominguez, B. D. Mills, S. D. Carpenter, K. A. Grant, C. D. Kroenke, J. T. Nigg, and D. A. Fair, “Connectotyping: model based fingerprinting of the functional connectome,” PLoS One 9(11), e111048 (2014).
[Crossref] [PubMed]

2013 (1)

S. Mueller, D. Wang, M. D. Fox, B. T. T. Yeo, J. Sepulcre, M. R. Sabuncu, R. Shafee, J. Lu, and H. Liu, “Individual variability in functional connectivity architecture of the human brain,” Neuron 77(3), 586–595 (2013).
[Crossref] [PubMed]

2012 (1)

L. Duan, Y.-J. Zhang, and C.-Z. Zhu, “Quantitative comparison of resting-state functional connectivity derived from fNIRS and fMRI: A simultaneous recording study,” Neuroimage 60(4), 2008–2018 (2012).
[Crossref] [PubMed]

2011 (3)

X. Cui, S. Bray, D. M. Bryant, G. H. Glover, and A. L. Reiss, “A quantitative comparison of NIRS and fMRI across multiple cognitive tasks,” Neuroimage 54(4), 2808–2821 (2011).
[Crossref] [PubMed]

S. Sasai, F. Homae, H. Watanabe, and G. Taga, “Frequency-specific functional connectivity in the brain during resting state revealed by NIRS,” Neuroimage 56(1), 252–257 (2011).
[Crossref] [PubMed]

R. Kanai and G. Rees, “The structural basis of inter-individual differences in human behaviour and cognition,” Nat. Rev. Neurosci. 12(4), 231–242 (2011).
[Crossref] [PubMed]

2010 (2)

R. C. Mesquita, M. A. Franceschini, and D. A. Boas, “Resting state functional connectivity of the whole head with near-infrared spectroscopy,” Biomed. Opt. Express 1(1), 324–336 (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]

2006 (2)

N. U. F. Dosenbach, K. M. Visscher, E. D. Palmer, F. M. Miezin, K. K. Wenger, H. C. Kang, E. D. Burgund, A. L. Grimes, B. L. Schlaggar, and S. E. Petersen, “A core system for the implementation of task sets,” Neuron 50(5), 799–812 (2006).
[Crossref] [PubMed]

L. Kocsis, P. Herman, and A. Eke, “The modified Beer-Lambert law revisited,” Phys. Med. Biol. 51(5), N91–N98 (2006).
[Crossref] [PubMed]

Akin, A.

M. U. Dalmis and A. Akin, “Similarity analysis of functional connectivity with functional near-infrared spectroscopy,” J. Biomed. Opt. 20(8), 086012 (2015).
[Crossref] [PubMed]

Alnæs, D.

T. Kaufmann, D. Alnæs, C. L. Brandt, F. Bettella, S. Djurovic, O. A. Andreassen, and L. T. Westlye, “Stability of the Brain Functional Connectome Fingerprint in Individuals With Schizophrenia,” JAMA Psychiatry 75(7), 749–751 (2018).
[Crossref] [PubMed]

T. Kaufmann, D. Alnæs, N. T. Doan, C. L. Brandt, O. A. Andreassen, and L. T. Westlye, “Delayed stabilization and individualization in connectome development are related to psychiatric disorders,” Nat. Neurosci. 20(4), 513–515 (2017).
[Crossref] [PubMed]

Amaro, E.

C. E. Biazoli, G. A. Salum, P. M. Pan, A. Zugman, E. Amaro, L. A. Rohde, E. C. Miguel, A. P. Jackowski, R. A. Bressan, and J. R. Sato, “Commentary: Functional connectome fingerprint: identifying individuals using patterns of brain connectivity,” Front. Hum. Neurosci. 11, 47 (2017).
[Crossref] [PubMed]

Amico, E.

E. Amico and J. Goñi, “Mapping hybrid functional-structural connectivity traits in the human connectome,” Netw Neurosci 2(3), 306–322 (2018).
[Crossref] [PubMed]

Andreassen, O. A.

T. Kaufmann, D. Alnæs, C. L. Brandt, F. Bettella, S. Djurovic, O. A. Andreassen, and L. T. Westlye, “Stability of the Brain Functional Connectome Fingerprint in Individuals With Schizophrenia,” JAMA Psychiatry 75(7), 749–751 (2018).
[Crossref] [PubMed]

T. Kaufmann, D. Alnæs, N. T. Doan, C. L. Brandt, O. A. Andreassen, and L. T. Westlye, “Delayed stabilization and individualization in connectome development are related to psychiatric disorders,” Nat. Neurosci. 20(4), 513–515 (2017).
[Crossref] [PubMed]

Balardin, J. B.

J. B. Balardin, G. A. Zimeo Morais, R. A. Furucho, L. Trambaiolli, P. Vanzella, C. Biazoli, and J. R. Sato, “Imaging Brain Function with Functional Near-Infrared Spectroscopy in Unconstrained Environments,” Front. Hum. Neurosci. 11, 258 (2017).
[Crossref] [PubMed]

J. B. Balardin, G. A. Zimeo Morais, R. A. Furucho, L. Trambaiolli, P. Vanzella, C. Biazoli, and J. R. Sato, “Imaging brain function with functional near-infrared spectroscopy in unconstrained environments,” Front. Hum. Neurosci. 11, 258 (2017).
[Crossref] [PubMed]

Bettella, F.

T. Kaufmann, D. Alnæs, C. L. Brandt, F. Bettella, S. Djurovic, O. A. Andreassen, and L. T. Westlye, “Stability of the Brain Functional Connectome Fingerprint in Individuals With Schizophrenia,” JAMA Psychiatry 75(7), 749–751 (2018).
[Crossref] [PubMed]

Biazoli, C.

J. B. Balardin, G. A. Zimeo Morais, R. A. Furucho, L. Trambaiolli, P. Vanzella, C. Biazoli, and J. R. Sato, “Imaging Brain Function with Functional Near-Infrared Spectroscopy in Unconstrained Environments,” Front. Hum. Neurosci. 11, 258 (2017).
[Crossref] [PubMed]

J. B. Balardin, G. A. Zimeo Morais, R. A. Furucho, L. Trambaiolli, P. Vanzella, C. Biazoli, and J. R. Sato, “Imaging brain function with functional near-infrared spectroscopy in unconstrained environments,” Front. Hum. Neurosci. 11, 258 (2017).
[Crossref] [PubMed]

Biazoli, C. E.

J. R. Sato, T. P. White, and C. E. Biazoli, “Commentary: A test-retest dataset for assessing long-term reliability of brain morphology and resting-state brain activity,” Front. Neurosci. 11, 85 (2017).
[Crossref] [PubMed]

C. E. Biazoli, G. A. Salum, P. M. Pan, A. Zugman, E. Amaro, L. A. Rohde, E. C. Miguel, A. P. Jackowski, R. A. Bressan, and J. R. Sato, “Commentary: Functional connectome fingerprint: identifying individuals using patterns of brain connectivity,” Front. Hum. Neurosci. 11, 47 (2017).
[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).
[Crossref] [PubMed]

Boas, D. A.

Brandt, C. L.

T. Kaufmann, D. Alnæs, C. L. Brandt, F. Bettella, S. Djurovic, O. A. Andreassen, and L. T. Westlye, “Stability of the Brain Functional Connectome Fingerprint in Individuals With Schizophrenia,” JAMA Psychiatry 75(7), 749–751 (2018).
[Crossref] [PubMed]

T. Kaufmann, D. Alnæs, N. T. Doan, C. L. Brandt, O. A. Andreassen, and L. T. Westlye, “Delayed stabilization and individualization in connectome development are related to psychiatric disorders,” Nat. Neurosci. 20(4), 513–515 (2017).
[Crossref] [PubMed]

Bray, S.

X. Cui, S. Bray, D. M. Bryant, G. H. Glover, and A. L. Reiss, “A quantitative comparison of NIRS and fMRI across multiple cognitive tasks,” Neuroimage 54(4), 2808–2821 (2011).
[Crossref] [PubMed]

Bressan, R. A.

C. E. Biazoli, G. A. Salum, P. M. Pan, A. Zugman, E. Amaro, L. A. Rohde, E. C. Miguel, A. P. Jackowski, R. A. Bressan, and J. R. Sato, “Commentary: Functional connectome fingerprint: identifying individuals using patterns of brain connectivity,” Front. Hum. Neurosci. 11, 47 (2017).
[Crossref] [PubMed]

Bryant, D. M.

X. Cui, S. Bray, D. M. Bryant, G. H. Glover, and A. L. Reiss, “A quantitative comparison of NIRS and fMRI across multiple cognitive tasks,” Neuroimage 54(4), 2808–2821 (2011).
[Crossref] [PubMed]

Burgund, E. D.

N. U. F. Dosenbach, K. M. Visscher, E. D. Palmer, F. M. Miezin, K. K. Wenger, H. C. Kang, E. D. Burgund, A. L. Grimes, B. L. Schlaggar, and S. E. Petersen, “A core system for the implementation of task sets,” Neuron 50(5), 799–812 (2006).
[Crossref] [PubMed]

Carpenter, S. D.

O. Miranda-Dominguez, B. D. Mills, S. D. Carpenter, K. A. Grant, C. D. Kroenke, J. T. Nigg, and D. A. Fair, “Connectotyping: model based fingerprinting of the functional connectome,” PLoS One 9(11), e111048 (2014).
[Crossref] [PubMed]

Castellanos, F. X.

T. Vanderwal, J. Eilbott, E. S. Finn, R. C. Craddock, A. Turnbull, and F. X. Castellanos, “Individual differences in functional connectivity during naturalistic viewing conditions,” Neuroimage 157, 521–530 (2017).
[Crossref] [PubMed]

Chun, M. M.

E. S. Finn, X. Shen, D. Scheinost, M. D. Rosenberg, J. Huang, M. M. Chun, X. Papademetris, and R. T. Constable, “Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity,” Nat. Neurosci. 18(11), 1664–1671 (2015).
[Crossref] [PubMed]

Coalson, R. S.

C. Gratton, T. O. Laumann, A. N. Nielsen, D. J. Greene, E. M. Gordon, A. W. Gilmore, S. M. Nelson, R. S. Coalson, A. Z. Snyder, B. L. Schlaggar, N. U. F. Dosenbach, and S. E. Petersen, “Functional Brain Networks Are Dominated by Stable Group and Individual Factors, Not Cognitive or Daily Variation,” Neuron 98(2), 439–452 (2018).
[Crossref] [PubMed]

Constable, R. T.

C. Horien, S. Noble, E. S. Finn, X. Shen, D. Scheinost, and R. T. Constable, “Considering factors affecting the connectome-based identification process: Comment on Waller et al,” Neuroimage 169, 172–175 (2018).
[Crossref] [PubMed]

E. S. Finn, D. Scheinost, D. M. Finn, X. Shen, X. Papademetris, and R. T. Constable, “Can brain state be manipulated to emphasize individual differences in functional connectivity?” Neuroimage 160, 140–151 (2017).
[Crossref] [PubMed]

E. S. Finn, X. Shen, D. Scheinost, M. D. Rosenberg, J. Huang, M. M. Chun, X. Papademetris, and R. T. Constable, “Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity,” Nat. Neurosci. 18(11), 1664–1671 (2015).
[Crossref] [PubMed]

Craddock, R. C.

T. Vanderwal, J. Eilbott, E. S. Finn, R. C. Craddock, A. Turnbull, and F. X. Castellanos, “Individual differences in functional connectivity during naturalistic viewing conditions,” Neuroimage 157, 521–530 (2017).
[Crossref] [PubMed]

Cui, X.

X. Cui, S. Bray, D. M. Bryant, G. H. Glover, and A. L. Reiss, “A quantitative comparison of NIRS and fMRI across multiple cognitive tasks,” Neuroimage 54(4), 2808–2821 (2011).
[Crossref] [PubMed]

Dalmis, M. U.

M. U. Dalmis and A. Akin, “Similarity analysis of functional connectivity with functional near-infrared spectroscopy,” J. Biomed. Opt. 20(8), 086012 (2015).
[Crossref] [PubMed]

Djurovic, S.

T. Kaufmann, D. Alnæs, C. L. Brandt, F. Bettella, S. Djurovic, O. A. Andreassen, and L. T. Westlye, “Stability of the Brain Functional Connectome Fingerprint in Individuals With Schizophrenia,” JAMA Psychiatry 75(7), 749–751 (2018).
[Crossref] [PubMed]

Doan, N. T.

T. Kaufmann, D. Alnæs, N. T. Doan, C. L. Brandt, O. A. Andreassen, and L. T. Westlye, “Delayed stabilization and individualization in connectome development are related to psychiatric disorders,” Nat. Neurosci. 20(4), 513–515 (2017).
[Crossref] [PubMed]

Dosenbach, N. U. F.

C. Gratton, T. O. Laumann, A. N. Nielsen, D. J. Greene, E. M. Gordon, A. W. Gilmore, S. M. Nelson, R. S. Coalson, A. Z. Snyder, B. L. Schlaggar, N. U. F. Dosenbach, and S. E. Petersen, “Functional Brain Networks Are Dominated by Stable Group and Individual Factors, Not Cognitive or Daily Variation,” Neuron 98(2), 439–452 (2018).
[Crossref] [PubMed]

N. U. F. Dosenbach, K. M. Visscher, E. D. Palmer, F. M. Miezin, K. K. Wenger, H. C. Kang, E. D. Burgund, A. L. Grimes, B. L. Schlaggar, and S. E. Petersen, “A core system for the implementation of task sets,” Neuron 50(5), 799–812 (2006).
[Crossref] [PubMed]

Duan, L.

L. Duan, Y.-J. Zhang, and C.-Z. Zhu, “Quantitative comparison of resting-state functional connectivity derived from fNIRS and fMRI: A simultaneous recording study,” Neuroimage 60(4), 2008–2018 (2012).
[Crossref] [PubMed]

Eilbott, J.

T. Vanderwal, J. Eilbott, E. S. Finn, R. C. Craddock, A. Turnbull, and F. X. Castellanos, “Individual differences in functional connectivity during naturalistic viewing conditions,” Neuroimage 157, 521–530 (2017).
[Crossref] [PubMed]

Eke, A.

L. Kocsis, P. Herman, and A. Eke, “The modified Beer-Lambert law revisited,” Phys. Med. Biol. 51(5), N91–N98 (2006).
[Crossref] [PubMed]

Erk, S.

L. Waller, H. Walter, J. D. Kruschwitz, L. Reuter, S. Müller, S. Erk, and I. M. Veer, “Evaluating the replicability, specificity, and generalizability of connectome fingerprints,” Neuroimage 158, 371–377 (2017).
[Crossref] [PubMed]

Fair, D. A.

O. Miranda-Dominguez, E. Feczko, D. S. Grayson, H. Walum, J. T. Nigg, and D. A. Fair, “Heritability of the human connectome: A connectotyping study,” Netw Neurosci 2(2), 175–199 (2018).
[Crossref] [PubMed]

O. Miranda-Dominguez, B. D. Mills, S. D. Carpenter, K. A. Grant, C. D. Kroenke, J. T. Nigg, and D. A. Fair, “Connectotyping: model based fingerprinting of the functional connectome,” PLoS One 9(11), e111048 (2014).
[Crossref] [PubMed]

Feczko, E.

O. Miranda-Dominguez, E. Feczko, D. S. Grayson, H. Walum, J. T. Nigg, and D. A. Fair, “Heritability of the human connectome: A connectotyping study,” Netw Neurosci 2(2), 175–199 (2018).
[Crossref] [PubMed]

Finn, D. M.

E. S. Finn, D. Scheinost, D. M. Finn, X. Shen, X. Papademetris, and R. T. Constable, “Can brain state be manipulated to emphasize individual differences in functional connectivity?” Neuroimage 160, 140–151 (2017).
[Crossref] [PubMed]

Finn, E. S.

C. Horien, S. Noble, E. S. Finn, X. Shen, D. Scheinost, and R. T. Constable, “Considering factors affecting the connectome-based identification process: Comment on Waller et al,” Neuroimage 169, 172–175 (2018).
[Crossref] [PubMed]

T. Vanderwal, J. Eilbott, E. S. Finn, R. C. Craddock, A. Turnbull, and F. X. Castellanos, “Individual differences in functional connectivity during naturalistic viewing conditions,” Neuroimage 157, 521–530 (2017).
[Crossref] [PubMed]

E. S. Finn, D. Scheinost, D. M. Finn, X. Shen, X. Papademetris, and R. T. Constable, “Can brain state be manipulated to emphasize individual differences in functional connectivity?” Neuroimage 160, 140–151 (2017).
[Crossref] [PubMed]

E. S. Finn, X. Shen, D. Scheinost, M. D. Rosenberg, J. Huang, M. M. Chun, X. Papademetris, and R. T. Constable, “Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity,” Nat. Neurosci. 18(11), 1664–1671 (2015).
[Crossref] [PubMed]

Fox, M. D.

K. Murphy and M. D. Fox, “Towards a consensus regarding global signal regression for resting state functional connectivity MRI,” Neuroimage 154, 169–173 (2017).
[Crossref] [PubMed]

K. Murphy and M. D. Fox, “Towards a consensus regarding global signal regression for resting state functional connectivity MRI,” Neuroimage 154, 169–173 (2017).
[Crossref] [PubMed]

S. Mueller, D. Wang, M. D. Fox, B. T. T. Yeo, J. Sepulcre, M. R. Sabuncu, R. Shafee, J. Lu, and H. Liu, “Individual variability in functional connectivity architecture of the human brain,” Neuron 77(3), 586–595 (2013).
[Crossref] [PubMed]

Franceschini, M. A.

Furucho, R. A.

J. B. Balardin, G. A. Zimeo Morais, R. A. Furucho, L. Trambaiolli, P. Vanzella, C. Biazoli, and J. R. Sato, “Imaging brain function with functional near-infrared spectroscopy in unconstrained environments,” Front. Hum. Neurosci. 11, 258 (2017).
[Crossref] [PubMed]

J. B. Balardin, G. A. Zimeo Morais, R. A. Furucho, L. Trambaiolli, P. Vanzella, C. Biazoli, and J. R. Sato, “Imaging Brain Function with Functional Near-Infrared Spectroscopy in Unconstrained Environments,” Front. Hum. Neurosci. 11, 258 (2017).
[Crossref] [PubMed]

Gilmore, A. W.

C. Gratton, T. O. Laumann, A. N. Nielsen, D. J. Greene, E. M. Gordon, A. W. Gilmore, S. M. Nelson, R. S. Coalson, A. Z. Snyder, B. L. Schlaggar, N. U. F. Dosenbach, and S. E. Petersen, “Functional Brain Networks Are Dominated by Stable Group and Individual Factors, Not Cognitive or Daily Variation,” Neuron 98(2), 439–452 (2018).
[Crossref] [PubMed]

Glover, G. H.

X. Cui, S. Bray, D. M. Bryant, G. H. Glover, and A. L. Reiss, “A quantitative comparison of NIRS and fMRI across multiple cognitive tasks,” Neuroimage 54(4), 2808–2821 (2011).
[Crossref] [PubMed]

Goñi, J.

E. Amico and J. Goñi, “Mapping hybrid functional-structural connectivity traits in the human connectome,” Netw Neurosci 2(3), 306–322 (2018).
[Crossref] [PubMed]

Gordon, E. M.

C. Gratton, T. O. Laumann, A. N. Nielsen, D. J. Greene, E. M. Gordon, A. W. Gilmore, S. M. Nelson, R. S. Coalson, A. Z. Snyder, B. L. Schlaggar, N. U. F. Dosenbach, and S. E. Petersen, “Functional Brain Networks Are Dominated by Stable Group and Individual Factors, Not Cognitive or Daily Variation,” Neuron 98(2), 439–452 (2018).
[Crossref] [PubMed]

Grant, K. A.

O. Miranda-Dominguez, B. D. Mills, S. D. Carpenter, K. A. Grant, C. D. Kroenke, J. T. Nigg, and D. A. Fair, “Connectotyping: model based fingerprinting of the functional connectome,” PLoS One 9(11), e111048 (2014).
[Crossref] [PubMed]

Gratton, C.

C. Gratton, T. O. Laumann, A. N. Nielsen, D. J. Greene, E. M. Gordon, A. W. Gilmore, S. M. Nelson, R. S. Coalson, A. Z. Snyder, B. L. Schlaggar, N. U. F. Dosenbach, and S. E. Petersen, “Functional Brain Networks Are Dominated by Stable Group and Individual Factors, Not Cognitive or Daily Variation,” Neuron 98(2), 439–452 (2018).
[Crossref] [PubMed]

Grayson, D. S.

O. Miranda-Dominguez, E. Feczko, D. S. Grayson, H. Walum, J. T. Nigg, and D. A. Fair, “Heritability of the human connectome: A connectotyping study,” Netw Neurosci 2(2), 175–199 (2018).
[Crossref] [PubMed]

Greene, D. J.

C. Gratton, T. O. Laumann, A. N. Nielsen, D. J. Greene, E. M. Gordon, A. W. Gilmore, S. M. Nelson, R. S. Coalson, A. Z. Snyder, B. L. Schlaggar, N. U. F. Dosenbach, and S. E. Petersen, “Functional Brain Networks Are Dominated by Stable Group and Individual Factors, Not Cognitive or Daily Variation,” Neuron 98(2), 439–452 (2018).
[Crossref] [PubMed]

Grimes, A. L.

N. U. F. Dosenbach, K. M. Visscher, E. D. Palmer, F. M. Miezin, K. K. Wenger, H. C. Kang, E. D. Burgund, A. L. Grimes, B. L. Schlaggar, and S. E. Petersen, “A core system for the implementation of task sets,” Neuron 50(5), 799–812 (2006).
[Crossref] [PubMed]

Herman, P.

L. Kocsis, P. Herman, and A. Eke, “The modified Beer-Lambert law revisited,” Phys. Med. Biol. 51(5), N91–N98 (2006).
[Crossref] [PubMed]

Homae, F.

S. Sasai, F. Homae, H. Watanabe, and G. Taga, “Frequency-specific functional connectivity in the brain during resting state revealed by NIRS,” Neuroimage 56(1), 252–257 (2011).
[Crossref] [PubMed]

Horien, C.

C. Horien, S. Noble, E. S. Finn, X. Shen, D. Scheinost, and R. T. Constable, “Considering factors affecting the connectome-based identification process: Comment on Waller et al,” Neuroimage 169, 172–175 (2018).
[Crossref] [PubMed]

Huang, J.

E. S. Finn, X. Shen, D. Scheinost, M. D. Rosenberg, J. Huang, M. M. Chun, X. Papademetris, and R. T. Constable, “Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity,” Nat. Neurosci. 18(11), 1664–1671 (2015).
[Crossref] [PubMed]

Jackowski, A. P.

C. E. Biazoli, G. A. Salum, P. M. Pan, A. Zugman, E. Amaro, L. A. Rohde, E. C. Miguel, A. P. Jackowski, R. A. Bressan, and J. R. Sato, “Commentary: Functional connectome fingerprint: identifying individuals using patterns of brain connectivity,” Front. Hum. Neurosci. 11, 47 (2017).
[Crossref] [PubMed]

Kanai, R.

R. Kanai and G. Rees, “The structural basis of inter-individual differences in human behaviour and cognition,” Nat. Rev. Neurosci. 12(4), 231–242 (2011).
[Crossref] [PubMed]

Kang, H. C.

N. U. F. Dosenbach, K. M. Visscher, E. D. Palmer, F. M. Miezin, K. K. Wenger, H. C. Kang, E. D. Burgund, A. L. Grimes, B. L. Schlaggar, and S. E. Petersen, “A core system for the implementation of task sets,” Neuron 50(5), 799–812 (2006).
[Crossref] [PubMed]

Kaufmann, T.

T. Kaufmann, D. Alnæs, C. L. Brandt, F. Bettella, S. Djurovic, O. A. Andreassen, and L. T. Westlye, “Stability of the Brain Functional Connectome Fingerprint in Individuals With Schizophrenia,” JAMA Psychiatry 75(7), 749–751 (2018).
[Crossref] [PubMed]

T. Kaufmann, D. Alnæs, N. T. Doan, C. L. Brandt, O. A. Andreassen, and L. T. Westlye, “Delayed stabilization and individualization in connectome development are related to psychiatric disorders,” Nat. Neurosci. 20(4), 513–515 (2017).
[Crossref] [PubMed]

Kocsis, L.

L. Kocsis, P. Herman, and A. Eke, “The modified Beer-Lambert law revisited,” Phys. Med. Biol. 51(5), N91–N98 (2006).
[Crossref] [PubMed]

Kroenke, C. D.

O. Miranda-Dominguez, B. D. Mills, S. D. Carpenter, K. A. Grant, C. D. Kroenke, J. T. Nigg, and D. A. Fair, “Connectotyping: model based fingerprinting of the functional connectome,” PLoS One 9(11), e111048 (2014).
[Crossref] [PubMed]

Kruschwitz, J. D.

L. Waller, H. Walter, J. D. Kruschwitz, L. Reuter, S. Müller, S. Erk, and I. M. Veer, “Evaluating the replicability, specificity, and generalizability of connectome fingerprints,” Neuroimage 158, 371–377 (2017).
[Crossref] [PubMed]

Labruyère, R.

M. D. Pfeifer, F. Scholkmann, and R. Labruyère, “Signal Processing in Functional Near-Infrared Spectroscopy (fNIRS): Methodological Differences Lead to Different Statistical Results,” Front. Hum. Neurosci. 11, 641 (2018).
[Crossref] [PubMed]

Laumann, T. O.

C. Gratton, T. O. Laumann, A. N. Nielsen, D. J. Greene, E. M. Gordon, A. W. Gilmore, S. M. Nelson, R. S. Coalson, A. Z. Snyder, B. L. Schlaggar, N. U. F. Dosenbach, and S. E. Petersen, “Functional Brain Networks Are Dominated by Stable Group and Individual Factors, Not Cognitive or Daily Variation,” Neuron 98(2), 439–452 (2018).
[Crossref] [PubMed]

Lee, T.-H.

T.-H. Lee, M. E. Miernicki, and E. H. Telzer, “Families that fire together smile together: Resting state connectome similarity and daily emotional synchrony in parent-child dyads,” Neuroimage 152, 31–37 (2017).
[Crossref] [PubMed]

Liu, H.

S. Mueller, D. Wang, M. D. Fox, B. T. T. Yeo, J. Sepulcre, M. R. Sabuncu, R. Shafee, J. Lu, and H. Liu, “Individual variability in functional connectivity architecture of the human brain,” Neuron 77(3), 586–595 (2013).
[Crossref] [PubMed]

Lu, C. M.

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]

Lu, J.

S. Mueller, D. Wang, M. D. Fox, B. T. T. Yeo, J. Sepulcre, M. R. Sabuncu, R. Shafee, J. Lu, and H. Liu, “Individual variability in functional connectivity architecture of the human brain,” Neuron 77(3), 586–595 (2013).
[Crossref] [PubMed]

Mesquita, R. C.

Miernicki, M. E.

T.-H. Lee, M. E. Miernicki, and E. H. Telzer, “Families that fire together smile together: Resting state connectome similarity and daily emotional synchrony in parent-child dyads,” Neuroimage 152, 31–37 (2017).
[Crossref] [PubMed]

Miezin, F. M.

N. U. F. Dosenbach, K. M. Visscher, E. D. Palmer, F. M. Miezin, K. K. Wenger, H. C. Kang, E. D. Burgund, A. L. Grimes, B. L. Schlaggar, and S. E. Petersen, “A core system for the implementation of task sets,” Neuron 50(5), 799–812 (2006).
[Crossref] [PubMed]

Miguel, E. C.

C. E. Biazoli, G. A. Salum, P. M. Pan, A. Zugman, E. Amaro, L. A. Rohde, E. C. Miguel, A. P. Jackowski, R. A. Bressan, and J. R. Sato, “Commentary: Functional connectome fingerprint: identifying individuals using patterns of brain connectivity,” Front. Hum. Neurosci. 11, 47 (2017).
[Crossref] [PubMed]

Mills, B. D.

O. Miranda-Dominguez, B. D. Mills, S. D. Carpenter, K. A. Grant, C. D. Kroenke, J. T. Nigg, and D. A. Fair, “Connectotyping: model based fingerprinting of the functional connectome,” PLoS One 9(11), e111048 (2014).
[Crossref] [PubMed]

Miranda-Dominguez, O.

O. Miranda-Dominguez, E. Feczko, D. S. Grayson, H. Walum, J. T. Nigg, and D. A. Fair, “Heritability of the human connectome: A connectotyping study,” Netw Neurosci 2(2), 175–199 (2018).
[Crossref] [PubMed]

O. Miranda-Dominguez, B. D. Mills, S. D. Carpenter, K. A. Grant, C. D. Kroenke, J. T. Nigg, and D. A. Fair, “Connectotyping: model based fingerprinting of the functional connectome,” PLoS One 9(11), e111048 (2014).
[Crossref] [PubMed]

Mueller, S.

S. Mueller, D. Wang, M. D. Fox, B. T. T. Yeo, J. Sepulcre, M. R. Sabuncu, R. Shafee, J. Lu, and H. Liu, “Individual variability in functional connectivity architecture of the human brain,” Neuron 77(3), 586–595 (2013).
[Crossref] [PubMed]

Müller, S.

L. Waller, H. Walter, J. D. Kruschwitz, L. Reuter, S. Müller, S. Erk, and I. M. Veer, “Evaluating the replicability, specificity, and generalizability of connectome fingerprints,” Neuroimage 158, 371–377 (2017).
[Crossref] [PubMed]

Murphy, K.

K. Murphy and M. D. Fox, “Towards a consensus regarding global signal regression for resting state functional connectivity MRI,” Neuroimage 154, 169–173 (2017).
[Crossref] [PubMed]

K. Murphy and M. D. Fox, “Towards a consensus regarding global signal regression for resting state functional connectivity MRI,” Neuroimage 154, 169–173 (2017).
[Crossref] [PubMed]

Nelson, S. M.

C. Gratton, T. O. Laumann, A. N. Nielsen, D. J. Greene, E. M. Gordon, A. W. Gilmore, S. M. Nelson, R. S. Coalson, A. Z. Snyder, B. L. Schlaggar, N. U. F. Dosenbach, and S. E. Petersen, “Functional Brain Networks Are Dominated by Stable Group and Individual Factors, Not Cognitive or Daily Variation,” Neuron 98(2), 439–452 (2018).
[Crossref] [PubMed]

Nielsen, A. N.

C. Gratton, T. O. Laumann, A. N. Nielsen, D. J. Greene, E. M. Gordon, A. W. Gilmore, S. M. Nelson, R. S. Coalson, A. Z. Snyder, B. L. Schlaggar, N. U. F. Dosenbach, and S. E. Petersen, “Functional Brain Networks Are Dominated by Stable Group and Individual Factors, Not Cognitive or Daily Variation,” Neuron 98(2), 439–452 (2018).
[Crossref] [PubMed]

Nigg, J. T.

O. Miranda-Dominguez, E. Feczko, D. S. Grayson, H. Walum, J. T. Nigg, and D. A. Fair, “Heritability of the human connectome: A connectotyping study,” Netw Neurosci 2(2), 175–199 (2018).
[Crossref] [PubMed]

O. Miranda-Dominguez, B. D. Mills, S. D. Carpenter, K. A. Grant, C. D. Kroenke, J. T. Nigg, and D. A. Fair, “Connectotyping: model based fingerprinting of the functional connectome,” PLoS One 9(11), e111048 (2014).
[Crossref] [PubMed]

Noble, S.

C. Horien, S. Noble, E. S. Finn, X. Shen, D. Scheinost, and R. T. Constable, “Considering factors affecting the connectome-based identification process: Comment on Waller et al,” Neuroimage 169, 172–175 (2018).
[Crossref] [PubMed]

Palmer, E. D.

N. U. F. Dosenbach, K. M. Visscher, E. D. Palmer, F. M. Miezin, K. K. Wenger, H. C. Kang, E. D. Burgund, A. L. Grimes, B. L. Schlaggar, and S. E. Petersen, “A core system for the implementation of task sets,” Neuron 50(5), 799–812 (2006).
[Crossref] [PubMed]

Pan, P. M.

C. E. Biazoli, G. A. Salum, P. M. Pan, A. Zugman, E. Amaro, L. A. Rohde, E. C. Miguel, A. P. Jackowski, R. A. Bressan, and J. R. Sato, “Commentary: Functional connectome fingerprint: identifying individuals using patterns of brain connectivity,” Front. Hum. Neurosci. 11, 47 (2017).
[Crossref] [PubMed]

Papademetris, X.

E. S. Finn, D. Scheinost, D. M. Finn, X. Shen, X. Papademetris, and R. T. Constable, “Can brain state be manipulated to emphasize individual differences in functional connectivity?” Neuroimage 160, 140–151 (2017).
[Crossref] [PubMed]

E. S. Finn, X. Shen, D. Scheinost, M. D. Rosenberg, J. Huang, M. M. Chun, X. Papademetris, and R. T. Constable, “Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity,” Nat. Neurosci. 18(11), 1664–1671 (2015).
[Crossref] [PubMed]

Peng, D. L.

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]

Petersen, S. E.

C. Gratton, T. O. Laumann, A. N. Nielsen, D. J. Greene, E. M. Gordon, A. W. Gilmore, S. M. Nelson, R. S. Coalson, A. Z. Snyder, B. L. Schlaggar, N. U. F. Dosenbach, and S. E. Petersen, “Functional Brain Networks Are Dominated by Stable Group and Individual Factors, Not Cognitive or Daily Variation,” Neuron 98(2), 439–452 (2018).
[Crossref] [PubMed]

N. U. F. Dosenbach, K. M. Visscher, E. D. Palmer, F. M. Miezin, K. K. Wenger, H. C. Kang, E. D. Burgund, A. L. Grimes, B. L. Schlaggar, and S. E. Petersen, “A core system for the implementation of task sets,” Neuron 50(5), 799–812 (2006).
[Crossref] [PubMed]

Pfeifer, M. D.

M. D. Pfeifer, F. Scholkmann, and R. Labruyère, “Signal Processing in Functional Near-Infrared Spectroscopy (fNIRS): Methodological Differences Lead to Different Statistical Results,” Front. Hum. Neurosci. 11, 641 (2018).
[Crossref] [PubMed]

Rees, G.

R. Kanai and G. Rees, “The structural basis of inter-individual differences in human behaviour and cognition,” Nat. Rev. Neurosci. 12(4), 231–242 (2011).
[Crossref] [PubMed]

Reiss, A. L.

X. Cui, S. Bray, D. M. Bryant, G. H. Glover, and A. L. Reiss, “A quantitative comparison of NIRS and fMRI across multiple cognitive tasks,” Neuroimage 54(4), 2808–2821 (2011).
[Crossref] [PubMed]

Reuter, L.

L. Waller, H. Walter, J. D. Kruschwitz, L. Reuter, S. Müller, S. Erk, and I. M. Veer, “Evaluating the replicability, specificity, and generalizability of connectome fingerprints,” Neuroimage 158, 371–377 (2017).
[Crossref] [PubMed]

Rohde, L. A.

C. E. Biazoli, G. A. Salum, P. M. Pan, A. Zugman, E. Amaro, L. A. Rohde, E. C. Miguel, A. P. Jackowski, R. A. Bressan, and J. R. Sato, “Commentary: Functional connectome fingerprint: identifying individuals using patterns of brain connectivity,” Front. Hum. Neurosci. 11, 47 (2017).
[Crossref] [PubMed]

Rosenberg, M. D.

E. S. Finn, X. Shen, D. Scheinost, M. D. Rosenberg, J. Huang, M. M. Chun, X. Papademetris, and R. T. Constable, “Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity,” Nat. Neurosci. 18(11), 1664–1671 (2015).
[Crossref] [PubMed]

Sabuncu, M. R.

S. Mueller, D. Wang, M. D. Fox, B. T. T. Yeo, J. Sepulcre, M. R. Sabuncu, R. Shafee, J. Lu, and H. Liu, “Individual variability in functional connectivity architecture of the human brain,” Neuron 77(3), 586–595 (2013).
[Crossref] [PubMed]

Salum, G. A.

C. E. Biazoli, G. A. Salum, P. M. Pan, A. Zugman, E. Amaro, L. A. Rohde, E. C. Miguel, A. P. Jackowski, R. A. Bressan, and J. R. Sato, “Commentary: Functional connectome fingerprint: identifying individuals using patterns of brain connectivity,” Front. Hum. Neurosci. 11, 47 (2017).
[Crossref] [PubMed]

Sasai, S.

S. Sasai, F. Homae, H. Watanabe, and G. Taga, “Frequency-specific functional connectivity in the brain during resting state revealed by NIRS,” Neuroimage 56(1), 252–257 (2011).
[Crossref] [PubMed]

Sato, J. R.

C. E. Biazoli, G. A. Salum, P. M. Pan, A. Zugman, E. Amaro, L. A. Rohde, E. C. Miguel, A. P. Jackowski, R. A. Bressan, and J. R. Sato, “Commentary: Functional connectome fingerprint: identifying individuals using patterns of brain connectivity,” Front. Hum. Neurosci. 11, 47 (2017).
[Crossref] [PubMed]

J. R. Sato, T. P. White, and C. E. Biazoli, “Commentary: A test-retest dataset for assessing long-term reliability of brain morphology and resting-state brain activity,” Front. Neurosci. 11, 85 (2017).
[Crossref] [PubMed]

J. B. Balardin, G. A. Zimeo Morais, R. A. Furucho, L. Trambaiolli, P. Vanzella, C. Biazoli, and J. R. Sato, “Imaging Brain Function with Functional Near-Infrared Spectroscopy in Unconstrained Environments,” Front. Hum. Neurosci. 11, 258 (2017).
[Crossref] [PubMed]

J. B. Balardin, G. A. Zimeo Morais, R. A. Furucho, L. Trambaiolli, P. Vanzella, C. Biazoli, and J. R. Sato, “Imaging brain function with functional near-infrared spectroscopy in unconstrained environments,” Front. Hum. Neurosci. 11, 258 (2017).
[Crossref] [PubMed]

Scheinost, D.

C. Horien, S. Noble, E. S. Finn, X. Shen, D. Scheinost, and R. T. Constable, “Considering factors affecting the connectome-based identification process: Comment on Waller et al,” Neuroimage 169, 172–175 (2018).
[Crossref] [PubMed]

E. S. Finn, D. Scheinost, D. M. Finn, X. Shen, X. Papademetris, and R. T. Constable, “Can brain state be manipulated to emphasize individual differences in functional connectivity?” Neuroimage 160, 140–151 (2017).
[Crossref] [PubMed]

E. S. Finn, X. Shen, D. Scheinost, M. D. Rosenberg, J. Huang, M. M. Chun, X. Papademetris, and R. T. Constable, “Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity,” Nat. Neurosci. 18(11), 1664–1671 (2015).
[Crossref] [PubMed]

Schlaggar, B. L.

C. Gratton, T. O. Laumann, A. N. Nielsen, D. J. Greene, E. M. Gordon, A. W. Gilmore, S. M. Nelson, R. S. Coalson, A. Z. Snyder, B. L. Schlaggar, N. U. F. Dosenbach, and S. E. Petersen, “Functional Brain Networks Are Dominated by Stable Group and Individual Factors, Not Cognitive or Daily Variation,” Neuron 98(2), 439–452 (2018).
[Crossref] [PubMed]

N. U. F. Dosenbach, K. M. Visscher, E. D. Palmer, F. M. Miezin, K. K. Wenger, H. C. Kang, E. D. Burgund, A. L. Grimes, B. L. Schlaggar, and S. E. Petersen, “A core system for the implementation of task sets,” Neuron 50(5), 799–812 (2006).
[Crossref] [PubMed]

Scholkmann, F.

M. D. Pfeifer, F. Scholkmann, and R. Labruyère, “Signal Processing in Functional Near-Infrared Spectroscopy (fNIRS): Methodological Differences Lead to Different Statistical Results,” Front. Hum. Neurosci. 11, 641 (2018).
[Crossref] [PubMed]

Sepulcre, J.

S. Mueller, D. Wang, M. D. Fox, B. T. T. Yeo, J. Sepulcre, M. R. Sabuncu, R. Shafee, J. Lu, and H. Liu, “Individual variability in functional connectivity architecture of the human brain,” Neuron 77(3), 586–595 (2013).
[Crossref] [PubMed]

Shafee, R.

S. Mueller, D. Wang, M. D. Fox, B. T. T. Yeo, J. Sepulcre, M. R. Sabuncu, R. Shafee, J. Lu, and H. Liu, “Individual variability in functional connectivity architecture of the human brain,” Neuron 77(3), 586–595 (2013).
[Crossref] [PubMed]

Shen, X.

C. Horien, S. Noble, E. S. Finn, X. Shen, D. Scheinost, and R. T. Constable, “Considering factors affecting the connectome-based identification process: Comment on Waller et al,” Neuroimage 169, 172–175 (2018).
[Crossref] [PubMed]

E. S. Finn, D. Scheinost, D. M. Finn, X. Shen, X. Papademetris, and R. T. Constable, “Can brain state be manipulated to emphasize individual differences in functional connectivity?” Neuroimage 160, 140–151 (2017).
[Crossref] [PubMed]

E. S. Finn, X. Shen, D. Scheinost, M. D. Rosenberg, J. Huang, M. M. Chun, X. Papademetris, and R. T. Constable, “Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity,” Nat. Neurosci. 18(11), 1664–1671 (2015).
[Crossref] [PubMed]

Snyder, A. Z.

C. Gratton, T. O. Laumann, A. N. Nielsen, D. J. Greene, E. M. Gordon, A. W. Gilmore, S. M. Nelson, R. S. Coalson, A. Z. Snyder, B. L. Schlaggar, N. U. F. Dosenbach, and S. E. Petersen, “Functional Brain Networks Are Dominated by Stable Group and Individual Factors, Not Cognitive or Daily Variation,” Neuron 98(2), 439–452 (2018).
[Crossref] [PubMed]

Taga, G.

S. Sasai, F. Homae, H. Watanabe, and G. Taga, “Frequency-specific functional connectivity in the brain during resting state revealed by NIRS,” Neuroimage 56(1), 252–257 (2011).
[Crossref] [PubMed]

Telzer, E. H.

T.-H. Lee, M. E. Miernicki, and E. H. Telzer, “Families that fire together smile together: Resting state connectome similarity and daily emotional synchrony in parent-child dyads,” Neuroimage 152, 31–37 (2017).
[Crossref] [PubMed]

Trambaiolli, L.

J. B. Balardin, G. A. Zimeo Morais, R. A. Furucho, L. Trambaiolli, P. Vanzella, C. Biazoli, and J. R. Sato, “Imaging Brain Function with Functional Near-Infrared Spectroscopy in Unconstrained Environments,” Front. Hum. Neurosci. 11, 258 (2017).
[Crossref] [PubMed]

J. B. Balardin, G. A. Zimeo Morais, R. A. Furucho, L. Trambaiolli, P. Vanzella, C. Biazoli, and J. R. Sato, “Imaging brain function with functional near-infrared spectroscopy in unconstrained environments,” Front. Hum. Neurosci. 11, 258 (2017).
[Crossref] [PubMed]

Turnbull, A.

T. Vanderwal, J. Eilbott, E. S. Finn, R. C. Craddock, A. Turnbull, and F. X. Castellanos, “Individual differences in functional connectivity during naturalistic viewing conditions,” Neuroimage 157, 521–530 (2017).
[Crossref] [PubMed]

Vanderwal, T.

T. Vanderwal, J. Eilbott, E. S. Finn, R. C. Craddock, A. Turnbull, and F. X. Castellanos, “Individual differences in functional connectivity during naturalistic viewing conditions,” Neuroimage 157, 521–530 (2017).
[Crossref] [PubMed]

Vanzella, P.

J. B. Balardin, G. A. Zimeo Morais, R. A. Furucho, L. Trambaiolli, P. Vanzella, C. Biazoli, and J. R. Sato, “Imaging Brain Function with Functional Near-Infrared Spectroscopy in Unconstrained Environments,” Front. Hum. Neurosci. 11, 258 (2017).
[Crossref] [PubMed]

J. B. Balardin, G. A. Zimeo Morais, R. A. Furucho, L. Trambaiolli, P. Vanzella, C. Biazoli, and J. R. Sato, “Imaging brain function with functional near-infrared spectroscopy in unconstrained environments,” Front. Hum. Neurosci. 11, 258 (2017).
[Crossref] [PubMed]

Veer, I. M.

L. Waller, H. Walter, J. D. Kruschwitz, L. Reuter, S. Müller, S. Erk, and I. M. Veer, “Evaluating the replicability, specificity, and generalizability of connectome fingerprints,” Neuroimage 158, 371–377 (2017).
[Crossref] [PubMed]

Visscher, K. M.

N. U. F. Dosenbach, K. M. Visscher, E. D. Palmer, F. M. Miezin, K. K. Wenger, H. C. Kang, E. D. Burgund, A. L. Grimes, B. L. Schlaggar, and S. E. Petersen, “A core system for the implementation of task sets,” Neuron 50(5), 799–812 (2006).
[Crossref] [PubMed]

Waller, L.

L. Waller, H. Walter, J. D. Kruschwitz, L. Reuter, S. Müller, S. Erk, and I. M. Veer, “Evaluating the replicability, specificity, and generalizability of connectome fingerprints,” Neuroimage 158, 371–377 (2017).
[Crossref] [PubMed]

Walter, H.

L. Waller, H. Walter, J. D. Kruschwitz, L. Reuter, S. Müller, S. Erk, and I. M. Veer, “Evaluating the replicability, specificity, and generalizability of connectome fingerprints,” Neuroimage 158, 371–377 (2017).
[Crossref] [PubMed]

Walum, H.

O. Miranda-Dominguez, E. Feczko, D. S. Grayson, H. Walum, J. T. Nigg, and D. A. Fair, “Heritability of the human connectome: A connectotyping study,” Netw Neurosci 2(2), 175–199 (2018).
[Crossref] [PubMed]

Wang, D.

S. Mueller, D. Wang, M. D. Fox, B. T. T. Yeo, J. Sepulcre, M. R. Sabuncu, R. Shafee, J. Lu, and H. Liu, “Individual variability in functional connectivity architecture of the human brain,” Neuron 77(3), 586–595 (2013).
[Crossref] [PubMed]

Watanabe, H.

S. Sasai, F. Homae, H. Watanabe, and G. Taga, “Frequency-specific functional connectivity in the brain during resting state revealed by NIRS,” Neuroimage 56(1), 252–257 (2011).
[Crossref] [PubMed]

Wenger, K. K.

N. U. F. Dosenbach, K. M. Visscher, E. D. Palmer, F. M. Miezin, K. K. Wenger, H. C. Kang, E. D. Burgund, A. L. Grimes, B. L. Schlaggar, and S. E. Petersen, “A core system for the implementation of task sets,” Neuron 50(5), 799–812 (2006).
[Crossref] [PubMed]

Westlye, L. T.

T. Kaufmann, D. Alnæs, C. L. Brandt, F. Bettella, S. Djurovic, O. A. Andreassen, and L. T. Westlye, “Stability of the Brain Functional Connectome Fingerprint in Individuals With Schizophrenia,” JAMA Psychiatry 75(7), 749–751 (2018).
[Crossref] [PubMed]

T. Kaufmann, D. Alnæs, N. T. Doan, C. L. Brandt, O. A. Andreassen, and L. T. Westlye, “Delayed stabilization and individualization in connectome development are related to psychiatric disorders,” Nat. Neurosci. 20(4), 513–515 (2017).
[Crossref] [PubMed]

White, T. P.

J. R. Sato, T. P. White, and C. E. Biazoli, “Commentary: A test-retest dataset for assessing long-term reliability of brain morphology and resting-state brain activity,” Front. Neurosci. 11, 85 (2017).
[Crossref] [PubMed]

Yeo, B. T. T.

S. Mueller, D. Wang, M. D. Fox, B. T. T. Yeo, J. Sepulcre, M. R. Sabuncu, R. Shafee, J. Lu, and H. Liu, “Individual variability in functional connectivity architecture of the human brain,” Neuron 77(3), 586–595 (2013).
[Crossref] [PubMed]

Zang, Y. F.

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]

Zhang, Y. J.

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]

Zhang, Y.-J.

L. Duan, Y.-J. Zhang, and C.-Z. Zhu, “Quantitative comparison of resting-state functional connectivity derived from fNIRS and fMRI: A simultaneous recording study,” Neuroimage 60(4), 2008–2018 (2012).
[Crossref] [PubMed]

Zhu, C. Z.

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]

Zhu, C.-Z.

L. Duan, Y.-J. Zhang, and C.-Z. Zhu, “Quantitative comparison of resting-state functional connectivity derived from fNIRS and fMRI: A simultaneous recording study,” Neuroimage 60(4), 2008–2018 (2012).
[Crossref] [PubMed]

Zimeo Morais, G. A.

J. B. Balardin, G. A. Zimeo Morais, R. A. Furucho, L. Trambaiolli, P. Vanzella, C. Biazoli, and J. R. Sato, “Imaging Brain Function with Functional Near-Infrared Spectroscopy in Unconstrained Environments,” Front. Hum. Neurosci. 11, 258 (2017).
[Crossref] [PubMed]

J. B. Balardin, G. A. Zimeo Morais, R. A. Furucho, L. Trambaiolli, P. Vanzella, C. Biazoli, and J. R. Sato, “Imaging brain function with functional near-infrared spectroscopy in unconstrained environments,” Front. Hum. Neurosci. 11, 258 (2017).
[Crossref] [PubMed]

Zugman, A.

C. E. Biazoli, G. A. Salum, P. M. Pan, A. Zugman, E. Amaro, L. A. Rohde, E. C. Miguel, A. P. Jackowski, R. A. Bressan, and J. R. Sato, “Commentary: Functional connectome fingerprint: identifying individuals using patterns of brain connectivity,” Front. Hum. Neurosci. 11, 47 (2017).
[Crossref] [PubMed]

Biomed. Opt. Express (1)

Front. Hum. Neurosci. (4)

J. B. Balardin, G. A. Zimeo Morais, R. A. Furucho, L. Trambaiolli, P. Vanzella, C. Biazoli, and J. R. Sato, “Imaging Brain Function with Functional Near-Infrared Spectroscopy in Unconstrained Environments,” Front. Hum. Neurosci. 11, 258 (2017).
[Crossref] [PubMed]

C. E. Biazoli, G. A. Salum, P. M. Pan, A. Zugman, E. Amaro, L. A. Rohde, E. C. Miguel, A. P. Jackowski, R. A. Bressan, and J. R. Sato, “Commentary: Functional connectome fingerprint: identifying individuals using patterns of brain connectivity,” Front. Hum. Neurosci. 11, 47 (2017).
[Crossref] [PubMed]

M. D. Pfeifer, F. Scholkmann, and R. Labruyère, “Signal Processing in Functional Near-Infrared Spectroscopy (fNIRS): Methodological Differences Lead to Different Statistical Results,” Front. Hum. Neurosci. 11, 641 (2018).
[Crossref] [PubMed]

J. B. Balardin, G. A. Zimeo Morais, R. A. Furucho, L. Trambaiolli, P. Vanzella, C. Biazoli, and J. R. Sato, “Imaging brain function with functional near-infrared spectroscopy in unconstrained environments,” Front. Hum. Neurosci. 11, 258 (2017).
[Crossref] [PubMed]

Front. Neurosci. (1)

J. R. Sato, T. P. White, and C. E. Biazoli, “Commentary: A test-retest dataset for assessing long-term reliability of brain morphology and resting-state brain activity,” Front. Neurosci. 11, 85 (2017).
[Crossref] [PubMed]

J. Biomed. Opt. (1)

M. U. Dalmis and A. Akin, “Similarity analysis of functional connectivity with functional near-infrared spectroscopy,” J. Biomed. Opt. 20(8), 086012 (2015).
[Crossref] [PubMed]

J. Neurosci. Methods (1)

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]

JAMA Psychiatry (1)

T. Kaufmann, D. Alnæs, C. L. Brandt, F. Bettella, S. Djurovic, O. A. Andreassen, and L. T. Westlye, “Stability of the Brain Functional Connectome Fingerprint in Individuals With Schizophrenia,” JAMA Psychiatry 75(7), 749–751 (2018).
[Crossref] [PubMed]

Nat. Neurosci. (2)

T. Kaufmann, D. Alnæs, N. T. Doan, C. L. Brandt, O. A. Andreassen, and L. T. Westlye, “Delayed stabilization and individualization in connectome development are related to psychiatric disorders,” Nat. Neurosci. 20(4), 513–515 (2017).
[Crossref] [PubMed]

E. S. Finn, X. Shen, D. Scheinost, M. D. Rosenberg, J. Huang, M. M. Chun, X. Papademetris, and R. T. Constable, “Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity,” Nat. Neurosci. 18(11), 1664–1671 (2015).
[Crossref] [PubMed]

Nat. Rev. Neurosci. (1)

R. Kanai and G. Rees, “The structural basis of inter-individual differences in human behaviour and cognition,” Nat. Rev. Neurosci. 12(4), 231–242 (2011).
[Crossref] [PubMed]

Netw Neurosci (2)

O. Miranda-Dominguez, E. Feczko, D. S. Grayson, H. Walum, J. T. Nigg, and D. A. Fair, “Heritability of the human connectome: A connectotyping study,” Netw Neurosci 2(2), 175–199 (2018).
[Crossref] [PubMed]

E. Amico and J. Goñi, “Mapping hybrid functional-structural connectivity traits in the human connectome,” Netw Neurosci 2(3), 306–322 (2018).
[Crossref] [PubMed]

Neuroimage (10)

E. S. Finn, D. Scheinost, D. M. Finn, X. Shen, X. Papademetris, and R. T. Constable, “Can brain state be manipulated to emphasize individual differences in functional connectivity?” Neuroimage 160, 140–151 (2017).
[Crossref] [PubMed]

C. Horien, S. Noble, E. S. Finn, X. Shen, D. Scheinost, and R. T. Constable, “Considering factors affecting the connectome-based identification process: Comment on Waller et al,” Neuroimage 169, 172–175 (2018).
[Crossref] [PubMed]

T. Vanderwal, J. Eilbott, E. S. Finn, R. C. Craddock, A. Turnbull, and F. X. Castellanos, “Individual differences in functional connectivity during naturalistic viewing conditions,” Neuroimage 157, 521–530 (2017).
[Crossref] [PubMed]

L. Waller, H. Walter, J. D. Kruschwitz, L. Reuter, S. Müller, S. Erk, and I. M. Veer, “Evaluating the replicability, specificity, and generalizability of connectome fingerprints,” Neuroimage 158, 371–377 (2017).
[Crossref] [PubMed]

T.-H. Lee, M. E. Miernicki, and E. H. Telzer, “Families that fire together smile together: Resting state connectome similarity and daily emotional synchrony in parent-child dyads,” Neuroimage 152, 31–37 (2017).
[Crossref] [PubMed]

K. Murphy and M. D. Fox, “Towards a consensus regarding global signal regression for resting state functional connectivity MRI,” Neuroimage 154, 169–173 (2017).
[Crossref] [PubMed]

S. Sasai, F. Homae, H. Watanabe, and G. Taga, “Frequency-specific functional connectivity in the brain during resting state revealed by NIRS,” Neuroimage 56(1), 252–257 (2011).
[Crossref] [PubMed]

K. Murphy and M. D. Fox, “Towards a consensus regarding global signal regression for resting state functional connectivity MRI,” Neuroimage 154, 169–173 (2017).
[Crossref] [PubMed]

L. Duan, Y.-J. Zhang, and C.-Z. Zhu, “Quantitative comparison of resting-state functional connectivity derived from fNIRS and fMRI: A simultaneous recording study,” Neuroimage 60(4), 2008–2018 (2012).
[Crossref] [PubMed]

X. Cui, S. Bray, D. M. Bryant, G. H. Glover, and A. L. Reiss, “A quantitative comparison of NIRS and fMRI across multiple cognitive tasks,” Neuroimage 54(4), 2808–2821 (2011).
[Crossref] [PubMed]

Neuron (3)

N. U. F. Dosenbach, K. M. Visscher, E. D. Palmer, F. M. Miezin, K. K. Wenger, H. C. Kang, E. D. Burgund, A. L. Grimes, B. L. Schlaggar, and S. E. Petersen, “A core system for the implementation of task sets,” Neuron 50(5), 799–812 (2006).
[Crossref] [PubMed]

S. Mueller, D. Wang, M. D. Fox, B. T. T. Yeo, J. Sepulcre, M. R. Sabuncu, R. Shafee, J. Lu, and H. Liu, “Individual variability in functional connectivity architecture of the human brain,” Neuron 77(3), 586–595 (2013).
[Crossref] [PubMed]

C. Gratton, T. O. Laumann, A. N. Nielsen, D. J. Greene, E. M. Gordon, A. W. Gilmore, S. M. Nelson, R. S. Coalson, A. Z. Snyder, B. L. Schlaggar, N. U. F. Dosenbach, and S. E. Petersen, “Functional Brain Networks Are Dominated by Stable Group and Individual Factors, Not Cognitive or Daily Variation,” Neuron 98(2), 439–452 (2018).
[Crossref] [PubMed]

Phys. Med. Biol. (1)

L. Kocsis, P. Herman, and A. Eke, “The modified Beer-Lambert law revisited,” Phys. Med. Biol. 51(5), N91–N98 (2006).
[Crossref] [PubMed]

PLoS One (1)

O. Miranda-Dominguez, B. D. Mills, S. D. Carpenter, K. A. Grant, C. D. Kroenke, J. T. Nigg, and D. A. Fair, “Connectotyping: model based fingerprinting of the functional connectome,” PLoS One 9(11), e111048 (2014).
[Crossref] [PubMed]

Other (2)

F. L. Ribeiro, W. H. L. Pinaya, J. R. Sato, and C. E. B. Junior, “Unique individual factors shape brain hubs organization of the human functional connectome,” Bioarxiv https://www.biorxiv.org/content/10.1101/437335v1 (2018).

R. M. Forti, A. Alessio, and R. C. Mesquita, “Characterization of the NIRS Hemodynamic Response Function with Independent Component Analysis,” in Biomedical Optics 2014 (2014).

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Figures (4)

Fig. 1
Fig. 1 (a) The configuration of the fNIRS channel assembly was based on the 10-20 system. Pairs of optodes were placed to maximize left hemisphere coverage. (b) To compute a “fingerprint matrix”, the Pearson correlation was calculated between each individual connectivity matrix from one period database (e.g rest 1) with all the other connectivity matrices from the database representing another period (e.g rest 2 or task). Thus, row represent the target connectome and column the predictor. In other words, each pixel (i,j) represent the correlation of a connectome i of one participant from one database (e.g., rest 1) with connectome j of any given participant from the other database (e.g., rest 2), and a correct individual identification corresponds to a maximal correlation coefficient at the diagonal. Accuracy can be determined by the total number of correct identifications divided by the number of participants.
Fig. 2
Fig. 2 Individual identification accuracies based on the fingerprint procedure for each possible comparison between targets and predictors of individual connectivity matrices, for oxy and deoxyhemoglobin signals.
Fig. 3
Fig. 3 Accuracy values for the comparisons between oxy and deoxyhemoglobin data, for the conditions (rest 1, task, rest 2).
Fig. 4
Fig. 4 Histograms of the results of a hundred thousand permutations, simulating random individual identification.

Tables (1)

Tables Icon

Table 1 Task’s description

Metrics