Abstract

Linear regression with short source-detector separation channels (S-channels) as references is an efficient way to overcome significant physiological interference from the superficial layer for functional near-infrared spectroscopy (fNIRS). However, the co-located configuration of S-channels and long source-detector separation channels (L-channels) is difficult to achieve in practice. In this study, we recorded superficial interference with S-channels in multiple scalp regions. We found that superficial interference has overall frequency-specific and globally symmetrical patterns. The performance of linear regression is also dependent on these patterns, indicating the possibility of simplifying the S-channel configurations for multiregional fNIRS imaging.

© 2015 Optical Society of America

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References

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    [Crossref] [PubMed]
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    [Crossref] [PubMed]
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    [Crossref] [PubMed]
  4. Y. Minagawa-Kawai, H. van der Lely, F. Ramus, Y. Sato, R. Mazuka, and E. Dupoux, “Optical brain imaging reveals general auditory and language-specific processing in early infant development,” Cereb. Cortex 21(2), 254–261 (2011).
    [Crossref] [PubMed]
  5. R. J. Cooper, J. C. Hebden, H. O’Reilly, S. Mitra, A. W. Michell, N. L. Everdell, A. P. Gibson, and T. Austin, “Transient haemodynamic events in neurologically compromised infants: a simultaneous EEG and diffuse optical imaging study,” Neuroimage 55(4), 1610–1616 (2011).
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    [Crossref] [PubMed]
  7. T. J. Huppert, R. D. Hoge, S. G. Diamond, M. A. Franceschini, and D. A. Boas, “A temporal comparison of BOLD, ASL, and NIRS hemodynamic responses to motor stimuli in adult humans,” Neuroimage 29(2), 368–382 (2006).
    [Crossref] [PubMed]
  8. R. D. Hoge, M. A. Franceschini, R. J. Covolan, T. Huppert, J. B. Mandeville, and D. A. Boas, “Simultaneous recording of task-induced changes in blood oxygenation, volume, and flow using diffuse optical imaging and arterial spin-labeling MRI,” Neuroimage 25(3), 701–707 (2005).
    [Crossref] [PubMed]
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    [Crossref] [PubMed]
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  15. F. Tian, H. Niu, B. Khan, G. Alexandrakis, K. Behbehani, and H. Liu, “Enhanced Functional Brain Imaging by Using Adaptive Filtering and a Depth Compensation Algorithm in Diffuse Optical Tomography,” IEEE Trans. Med. Imaging 30(6), 1239–1251 (2011).
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  16. Q. Zhang, G. E. Strangman, and G. Ganis, “Adaptive filtering to reduce global interference in non-invasive NIRS measures of brain activation: how well and when does it work?” Neuroimage 45(3), 788–794 (2009).
    [Crossref] [PubMed]
  17. R. B. Saager and A. J. Berger, “Direct characterization and removal of interfering absorption trends in two-layer turbid media,” J. Opt. Soc. Am. A 22(9), 1874–1882 (2005).
    [Crossref] [PubMed]
  18. B. W. Zeff, B. R. White, H. Dehghani, B. L. Schlaggar, and J. P. Culver, “Retinotopic mapping of adult human visual cortex with high-density diffuse optical tomography,” Proc. Natl. Acad. Sci. U.S.A. 104(29), 12169–12174 (2007).
    [Crossref] [PubMed]
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    [PubMed]
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    [Crossref] [PubMed]
  21. S. Umeyama and T. Yamada, “Monte Carlo study of global interference cancellation by multidistance measurement of near-infrared spectroscopy,” J. Biomed. Opt. 14(6), 064025 (2009).
    [Crossref] [PubMed]
  22. T. Yamada, S. Umeyama, and K. Matsuda, “Multidistance probe arrangement to eliminate artifacts in functional near-infrared spectroscopy,” J. Biomed. Opt. 14(6), 064034 (2009).
    [Crossref] [PubMed]
  23. L. Gagnon, K. Perdue, D. N. Greve, D. Goldenholz, G. Kaskhedikar, and D. A. Boas, “Improved recovery of the hemodynamic response in diffuse optical imaging using short optode separations and state-space modeling,” Neuroimage 56(3), 1362–1371 (2011).
    [Crossref] [PubMed]
  24. M. A. Franceschini, D. K. Joseph, T. J. Huppert, S. G. Diamond, and D. A. Boas, “Diffuse optical imaging of the whole head,” J. Biomed. Opt. 11(5), 054007 (2006).
    [Crossref] [PubMed]
  25. Y. Zhang, D. H. Brooks, M. A. Franceschini, and D. A. Boas, “Eigenvector-based spatial filtering for reduction of physiological interference in diffuse optical imaging,” J. Biomed. Opt. 10(1), 011014 (2005).
    [Crossref] [PubMed]
  26. 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]
  27. L. Gagnon, R. J. Cooper, M. A. Yücel, K. L. Perdue, D. N. Greve, and D. A. Boas, “Short separation channel location impacts the performance of short channel regression in NIRS,” Neuroimage 59(3), 2518–2528 (2012).
    [Crossref] [PubMed]
  28. L. Gagnon, M. A. Yücel, D. A. Boas, and R. J. Cooper, “Further improvement in reducing superficial contamination in NIRS using double short separation measurements,” Neuroimage 85(Pt 1), 127–135 (2014).
    [Crossref] [PubMed]
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    [Crossref] [PubMed]
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    [Crossref] [PubMed]
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    [Crossref] [PubMed]
  32. G. H. Klem, H. O. Lüders, H. H. Jasper, C. Elger, and The International Federation of Clinical Neurophysiology, “The ten-twenty electrode system of the International Federation,” Electroencephalogr. Clin. Neurophysiol. Suppl. 52, 3–6 (1999).
    [PubMed]
  33. M. Cope and D. T. Delpy, “System for long-term measurement of cerebral blood and tissue oxygenation on newborn infants by near infra-red transillumination,” Med. Biol. Eng. Comput. 26(3), 289–294 (1988).
    [Crossref] [PubMed]
  34. 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]
  35. P. D. Welch, “Use of fast Fourier transform for estimation of power spectra - a method based on time averaging over short modified periodograms,” IEEE Trans. Acoust. Speech 15, 70–73 (1967).
  36. D. P. Auer, “Spontaneous low-frequency blood oxygenation level-dependent fluctuations and functional connectivity analysis of the ‘resting’ brain,” Magn. Reson. Imaging 26(7), 1055–1064 (2008).
    [Crossref] [PubMed]
  37. 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]
  38. M. D. Fox and M. E. Raichle, “Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging,” Nat. Rev. Neurosci. 8(9), 700–711 (2007).
    [Crossref] [PubMed]
  39. F. Tian and H. Liu, “Depth-compensated diffuse optical tomography enhanced by general linear model analysis and an anatomical atlas of human head,” Neuroimage 85(Pt 1), 166–180 (2014).
    [Crossref] [PubMed]
  40. Y. Tong, L. M. Hocke, L. D. Nickerson, S. C. Licata, K. P. Lindsey, and B. Frederick, “Evaluating the effects of systemic low frequency oscillations measured in the periphery on the independent component analysis results of resting state networks,” Neuroimage 76, 202–215 (2013).
    [Crossref] [PubMed]

2015 (1)

J. Huang, F. Wang, Y. Ding, H. Niu, F. Tian, H. Liu, and Y. Song, “Predicting N2pc from anticipatory HbO activity during sustained visuospatial attention: A concurrent fNIRS-ERP study,” Neuroimage 113, 225–234 (2015).
[Crossref] [PubMed]

2014 (4)

S. B. Erdoğan, M. A. Yücel, and A. Akın, “Analysis of task-evoked systemic interference in fNIRS measurements: insights from fMRI,” Neuroimage 87, 490–504 (2014).
[Crossref] [PubMed]

A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (2014).
[Crossref] [PubMed]

L. Gagnon, M. A. Yücel, D. A. Boas, and R. J. Cooper, “Further improvement in reducing superficial contamination in NIRS using double short separation measurements,” Neuroimage 85(Pt 1), 127–135 (2014).
[Crossref] [PubMed]

F. Tian and H. Liu, “Depth-compensated diffuse optical tomography enhanced by general linear model analysis and an anatomical atlas of human head,” Neuroimage 85(Pt 1), 166–180 (2014).
[Crossref] [PubMed]

2013 (1)

Y. Tong, L. M. Hocke, L. D. Nickerson, S. C. Licata, K. P. Lindsey, and B. Frederick, “Evaluating the effects of systemic low frequency oscillations measured in the periphery on the independent component analysis results of resting state networks,” Neuroimage 76, 202–215 (2013).
[Crossref] [PubMed]

2012 (3)

E. Kirilina, A. Jelzow, A. Heine, M. Niessing, H. Wabnitz, R. Brühl, B. Ittermann, A. M. Jacobs, and I. Tachtsidis, “The physiological origin of task-evoked systemic artefacts in functional near infrared spectroscopy,” Neuroimage 61(1), 70–81 (2012).
[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]

L. Gagnon, R. J. Cooper, M. A. Yücel, K. L. Perdue, D. N. Greve, and D. A. Boas, “Short separation channel location impacts the performance of short channel regression in NIRS,” Neuroimage 59(3), 2518–2528 (2012).
[Crossref] [PubMed]

2011 (4)

L. Gagnon, K. Perdue, D. N. Greve, D. Goldenholz, G. Kaskhedikar, and D. A. Boas, “Improved recovery of the hemodynamic response in diffuse optical imaging using short optode separations and state-space modeling,” Neuroimage 56(3), 1362–1371 (2011).
[Crossref] [PubMed]

Y. Minagawa-Kawai, H. van der Lely, F. Ramus, Y. Sato, R. Mazuka, and E. Dupoux, “Optical brain imaging reveals general auditory and language-specific processing in early infant development,” Cereb. Cortex 21(2), 254–261 (2011).
[Crossref] [PubMed]

R. J. Cooper, J. C. Hebden, H. O’Reilly, S. Mitra, A. W. Michell, N. L. Everdell, A. P. Gibson, and T. Austin, “Transient haemodynamic events in neurologically compromised infants: a simultaneous EEG and diffuse optical imaging study,” Neuroimage 55(4), 1610–1616 (2011).
[Crossref] [PubMed]

F. Tian, H. Niu, B. Khan, G. Alexandrakis, K. Behbehani, and H. Liu, “Enhanced Functional Brain Imaging by Using Adaptive Filtering and a Depth Compensation Algorithm in Diffuse Optical Tomography,” IEEE Trans. Med. Imaging 30(6), 1239–1251 (2011).
[Crossref] [PubMed]

2010 (4)

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]

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]

N. M. Gregg, B. R. White, B. W. Zeff, A. J. Berger, and J. P. Culver, “Brain specificity of diffuse optical imaging: improvements from superficial signal regression and tomography,” Front Neuroenergetics 2, 14 (2010).
[PubMed]

2009 (4)

S. Umeyama and T. Yamada, “Monte Carlo study of global interference cancellation by multidistance measurement of near-infrared spectroscopy,” J. Biomed. Opt. 14(6), 064025 (2009).
[Crossref] [PubMed]

T. Yamada, S. Umeyama, and K. Matsuda, “Multidistance probe arrangement to eliminate artifacts in functional near-infrared spectroscopy,” J. Biomed. Opt. 14(6), 064034 (2009).
[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]

Q. Zhang, G. E. Strangman, and G. Ganis, “Adaptive filtering to reduce global interference in non-invasive NIRS measures of brain activation: how well and when does it work?” Neuroimage 45(3), 788–794 (2009).
[Crossref] [PubMed]

2008 (2)

R. Saager and A. Berger, “Measurement of layer-like hemodynamic trends in scalp and cortex: implications for physiological baseline suppression in functional near-infrared spectroscopy,” J. Biomed. Opt. 13(3), 034017 (2008).
[Crossref] [PubMed]

D. P. Auer, “Spontaneous low-frequency blood oxygenation level-dependent fluctuations and functional connectivity analysis of the ‘resting’ brain,” Magn. Reson. Imaging 26(7), 1055–1064 (2008).
[Crossref] [PubMed]

2007 (6)

M. D. Fox and M. E. Raichle, “Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging,” Nat. Rev. Neurosci. 8(9), 700–711 (2007).
[Crossref] [PubMed]

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]

B. W. Zeff, B. R. White, H. Dehghani, B. L. Schlaggar, and J. P. Culver, “Retinotopic mapping of adult human visual cortex with high-density diffuse optical tomography,” Proc. Natl. Acad. Sci. U.S.A. 104(29), 12169–12174 (2007).
[Crossref] [PubMed]

Q. Zhang, E. N. Brown, and G. E. Strangman, “Adaptive filtering to reduce global interference in evoked brain activity detection: a human subject case study,” J. Biomed. Opt. 12(6), 064009 (2007).
[Crossref] [PubMed]

Y. Hoshi, “Functional near-infrared spectroscopy: current status and future prospects,” J. Biomed. Opt. 12(6), 062106 (2007).
[Crossref] [PubMed]

F. Irani, S. M. Platek, S. Bunce, A. C. Ruocco, and D. Chute, “Functional near infrared spectroscopy (fNIRS): an emerging neuroimaging technology with important applications for the study of brain disorders,” Clin. Neuropsychol. 21(1), 9–37 (2007).
[Crossref] [PubMed]

2006 (3)

T. J. Huppert, R. D. Hoge, S. G. Diamond, M. A. Franceschini, and D. A. Boas, “A temporal comparison of BOLD, ASL, and NIRS hemodynamic responses to motor stimuli in adult humans,” Neuroimage 29(2), 368–382 (2006).
[Crossref] [PubMed]

S. C. Bunce, M. Izzetoglu, K. Izzetoglu, B. Onaral, and K. Pourrezaei, “Functional near-infrared spectroscopy,” IEEE Eng. Med. Biol. Mag. 25(4), 54–62 (2006).
[Crossref] [PubMed]

M. A. Franceschini, D. K. Joseph, T. J. Huppert, S. G. Diamond, and D. A. Boas, “Diffuse optical imaging of the whole head,” J. Biomed. Opt. 11(5), 054007 (2006).
[Crossref] [PubMed]

2005 (3)

Y. Zhang, D. H. Brooks, M. A. Franceschini, and D. A. Boas, “Eigenvector-based spatial filtering for reduction of physiological interference in diffuse optical imaging,” J. Biomed. Opt. 10(1), 011014 (2005).
[Crossref] [PubMed]

R. B. Saager and A. J. Berger, “Direct characterization and removal of interfering absorption trends in two-layer turbid media,” J. Opt. Soc. Am. A 22(9), 1874–1882 (2005).
[Crossref] [PubMed]

R. D. Hoge, M. A. Franceschini, R. J. Covolan, T. Huppert, J. B. Mandeville, and D. A. Boas, “Simultaneous recording of task-induced changes in blood oxygenation, volume, and flow using diffuse optical imaging and arterial spin-labeling MRI,” Neuroimage 25(3), 701–707 (2005).
[Crossref] [PubMed]

2004 (1)

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]

1999 (1)

G. H. Klem, H. O. Lüders, H. H. Jasper, C. Elger, and The International Federation of Clinical Neurophysiology, “The ten-twenty electrode system of the International Federation,” Electroencephalogr. Clin. Neurophysiol. Suppl. 52, 3–6 (1999).
[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).
[Crossref] [PubMed]

1988 (1)

M. Cope and D. T. Delpy, “System for long-term measurement of cerebral blood and tissue oxygenation on newborn infants by near infra-red transillumination,” Med. Biol. Eng. Comput. 26(3), 289–294 (1988).
[Crossref] [PubMed]

1967 (1)

P. D. Welch, “Use of fast Fourier transform for estimation of power spectra - a method based on time averaging over short modified periodograms,” IEEE Trans. Acoust. Speech 15, 70–73 (1967).

Akin, A.

S. B. Erdoğan, M. A. Yücel, and A. Akın, “Analysis of task-evoked systemic interference in fNIRS measurements: insights from fMRI,” Neuroimage 87, 490–504 (2014).
[Crossref] [PubMed]

Alexandrakis, G.

F. Tian, H. Niu, B. Khan, G. Alexandrakis, K. Behbehani, and H. Liu, “Enhanced Functional Brain Imaging by Using Adaptive Filtering and a Depth Compensation Algorithm in Diffuse Optical Tomography,” IEEE Trans. Med. Imaging 30(6), 1239–1251 (2011).
[Crossref] [PubMed]

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).
[Crossref] [PubMed]

Auer, D. P.

D. P. Auer, “Spontaneous low-frequency blood oxygenation level-dependent fluctuations and functional connectivity analysis of the ‘resting’ brain,” Magn. Reson. Imaging 26(7), 1055–1064 (2008).
[Crossref] [PubMed]

Austin, T.

R. J. Cooper, J. C. Hebden, H. O’Reilly, S. Mitra, A. W. Michell, N. L. Everdell, A. P. Gibson, and T. Austin, “Transient haemodynamic events in neurologically compromised infants: a simultaneous EEG and diffuse optical imaging study,” Neuroimage 55(4), 1610–1616 (2011).
[Crossref] [PubMed]

Behbehani, K.

F. Tian, H. Niu, B. Khan, G. Alexandrakis, K. Behbehani, and H. Liu, “Enhanced Functional Brain Imaging by Using Adaptive Filtering and a Depth Compensation Algorithm in Diffuse Optical Tomography,” IEEE Trans. Med. Imaging 30(6), 1239–1251 (2011).
[Crossref] [PubMed]

Berger, A.

R. Saager and A. Berger, “Measurement of layer-like hemodynamic trends in scalp and cortex: implications for physiological baseline suppression in functional near-infrared spectroscopy,” J. Biomed. Opt. 13(3), 034017 (2008).
[Crossref] [PubMed]

Berger, A. J.

N. M. Gregg, B. R. White, B. W. Zeff, A. J. Berger, and J. P. Culver, “Brain specificity of diffuse optical imaging: improvements from superficial signal regression and tomography,” Front Neuroenergetics 2, 14 (2010).
[PubMed]

R. B. Saager and A. J. Berger, “Direct characterization and removal of interfering absorption trends in two-layer turbid media,” J. Opt. Soc. Am. A 22(9), 1874–1882 (2005).
[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).
[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]

Boas, D. A.

L. Gagnon, M. A. Yücel, D. A. Boas, and R. J. Cooper, “Further improvement in reducing superficial contamination in NIRS using double short separation measurements,” Neuroimage 85(Pt 1), 127–135 (2014).
[Crossref] [PubMed]

L. Gagnon, R. J. Cooper, M. A. Yücel, K. L. Perdue, D. N. Greve, and D. A. Boas, “Short separation channel location impacts the performance of short channel regression in NIRS,” Neuroimage 59(3), 2518–2528 (2012).
[Crossref] [PubMed]

L. Gagnon, K. Perdue, D. N. Greve, D. Goldenholz, G. Kaskhedikar, and D. A. Boas, “Improved recovery of the hemodynamic response in diffuse optical imaging using short optode separations and state-space modeling,” Neuroimage 56(3), 1362–1371 (2011).
[Crossref] [PubMed]

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]

T. J. Huppert, R. D. Hoge, S. G. Diamond, M. A. Franceschini, and D. A. Boas, “A temporal comparison of BOLD, ASL, and NIRS hemodynamic responses to motor stimuli in adult humans,” Neuroimage 29(2), 368–382 (2006).
[Crossref] [PubMed]

M. A. Franceschini, D. K. Joseph, T. J. Huppert, S. G. Diamond, and D. A. Boas, “Diffuse optical imaging of the whole head,” J. Biomed. Opt. 11(5), 054007 (2006).
[Crossref] [PubMed]

Y. Zhang, D. H. Brooks, M. A. Franceschini, and D. A. Boas, “Eigenvector-based spatial filtering for reduction of physiological interference in diffuse optical imaging,” J. Biomed. Opt. 10(1), 011014 (2005).
[Crossref] [PubMed]

R. D. Hoge, M. A. Franceschini, R. J. Covolan, T. Huppert, J. B. Mandeville, and D. A. Boas, “Simultaneous recording of task-induced changes in blood oxygenation, volume, and flow using diffuse optical imaging and arterial spin-labeling MRI,” Neuroimage 25(3), 701–707 (2005).
[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]

Brooks, D. H.

Y. Zhang, D. H. Brooks, M. A. Franceschini, and D. A. Boas, “Eigenvector-based spatial filtering for reduction of physiological interference in diffuse optical imaging,” J. Biomed. Opt. 10(1), 011014 (2005).
[Crossref] [PubMed]

Brown, E. N.

Q. Zhang, E. N. Brown, and G. E. Strangman, “Adaptive filtering to reduce global interference in evoked brain activity detection: a human subject case study,” J. Biomed. Opt. 12(6), 064009 (2007).
[Crossref] [PubMed]

Brühl, R.

E. Kirilina, A. Jelzow, A. Heine, M. Niessing, H. Wabnitz, R. Brühl, B. Ittermann, A. M. Jacobs, and I. Tachtsidis, “The physiological origin of task-evoked systemic artefacts in functional near infrared spectroscopy,” Neuroimage 61(1), 70–81 (2012).
[Crossref] [PubMed]

Bunce, S.

F. Irani, S. M. Platek, S. Bunce, A. C. Ruocco, and D. Chute, “Functional near infrared spectroscopy (fNIRS): an emerging neuroimaging technology with important applications for the study of brain disorders,” Clin. Neuropsychol. 21(1), 9–37 (2007).
[Crossref] [PubMed]

Bunce, S. C.

S. C. Bunce, M. Izzetoglu, K. Izzetoglu, B. Onaral, and K. Pourrezaei, “Functional near-infrared spectroscopy,” IEEE Eng. Med. Biol. Mag. 25(4), 54–62 (2006).
[Crossref] [PubMed]

Chute, D.

F. Irani, S. M. Platek, S. Bunce, A. C. Ruocco, and D. Chute, “Functional near infrared spectroscopy (fNIRS): an emerging neuroimaging technology with important applications for the study of brain disorders,” Clin. Neuropsychol. 21(1), 9–37 (2007).
[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]

Cooper, R. J.

L. Gagnon, M. A. Yücel, D. A. Boas, and R. J. Cooper, “Further improvement in reducing superficial contamination in NIRS using double short separation measurements,” Neuroimage 85(Pt 1), 127–135 (2014).
[Crossref] [PubMed]

L. Gagnon, R. J. Cooper, M. A. Yücel, K. L. Perdue, D. N. Greve, and D. A. Boas, “Short separation channel location impacts the performance of short channel regression in NIRS,” Neuroimage 59(3), 2518–2528 (2012).
[Crossref] [PubMed]

R. J. Cooper, J. C. Hebden, H. O’Reilly, S. Mitra, A. W. Michell, N. L. Everdell, A. P. Gibson, and T. Austin, “Transient haemodynamic events in neurologically compromised infants: a simultaneous EEG and diffuse optical imaging study,” Neuroimage 55(4), 1610–1616 (2011).
[Crossref] [PubMed]

Cope, M.

M. Cope and D. T. Delpy, “System for long-term measurement of cerebral blood and tissue oxygenation on newborn infants by near infra-red transillumination,” Med. Biol. Eng. Comput. 26(3), 289–294 (1988).
[Crossref] [PubMed]

Covolan, R. J.

R. D. Hoge, M. A. Franceschini, R. J. Covolan, T. Huppert, J. B. Mandeville, and D. A. Boas, “Simultaneous recording of task-induced changes in blood oxygenation, volume, and flow using diffuse optical imaging and arterial spin-labeling MRI,” Neuroimage 25(3), 701–707 (2005).
[Crossref] [PubMed]

Culver, J. P.

A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (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]

N. M. Gregg, B. R. White, B. W. Zeff, A. J. Berger, and J. P. Culver, “Brain specificity of diffuse optical imaging: improvements from superficial signal regression and tomography,” Front Neuroenergetics 2, 14 (2010).
[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]

B. W. Zeff, B. R. White, H. Dehghani, B. L. Schlaggar, and J. P. Culver, “Retinotopic mapping of adult human visual cortex with high-density diffuse optical tomography,” Proc. Natl. Acad. Sci. U.S.A. 104(29), 12169–12174 (2007).
[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]

Dehghani, H.

A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (2014).
[Crossref] [PubMed]

B. W. Zeff, B. R. White, H. Dehghani, B. L. Schlaggar, and J. P. Culver, “Retinotopic mapping of adult human visual cortex with high-density diffuse optical tomography,” Proc. Natl. Acad. Sci. U.S.A. 104(29), 12169–12174 (2007).
[Crossref] [PubMed]

Delpy, D. T.

M. Cope and D. T. Delpy, “System for long-term measurement of cerebral blood and tissue oxygenation on newborn infants by near infra-red transillumination,” Med. Biol. Eng. Comput. 26(3), 289–294 (1988).
[Crossref] [PubMed]

Diamond, S. G.

M. A. Franceschini, D. K. Joseph, T. J. Huppert, S. G. Diamond, and D. A. Boas, “Diffuse optical imaging of the whole head,” J. Biomed. Opt. 11(5), 054007 (2006).
[Crossref] [PubMed]

T. J. Huppert, R. D. Hoge, S. G. Diamond, M. A. Franceschini, and D. A. Boas, “A temporal comparison of BOLD, ASL, and NIRS hemodynamic responses to motor stimuli in adult humans,” Neuroimage 29(2), 368–382 (2006).
[Crossref] [PubMed]

Ding, Y.

J. Huang, F. Wang, Y. Ding, H. Niu, F. Tian, H. Liu, and Y. Song, “Predicting N2pc from anticipatory HbO activity during sustained visuospatial attention: A concurrent fNIRS-ERP study,” Neuroimage 113, 225–234 (2015).
[Crossref] [PubMed]

Dupoux, E.

Y. Minagawa-Kawai, H. van der Lely, F. Ramus, Y. Sato, R. Mazuka, and E. Dupoux, “Optical brain imaging reveals general auditory and language-specific processing in early infant development,” Cereb. Cortex 21(2), 254–261 (2011).
[Crossref] [PubMed]

Eggebrecht, A. T.

A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (2014).
[Crossref] [PubMed]

Elger, C.

G. H. Klem, H. O. Lüders, H. H. Jasper, C. Elger, and The International Federation of Clinical Neurophysiology, “The ten-twenty electrode system of the International Federation,” Electroencephalogr. Clin. Neurophysiol. Suppl. 52, 3–6 (1999).
[PubMed]

Erdogan, S. B.

S. B. Erdoğan, M. A. Yücel, and A. Akın, “Analysis of task-evoked systemic interference in fNIRS measurements: insights from fMRI,” Neuroimage 87, 490–504 (2014).
[Crossref] [PubMed]

Everdell, N. L.

R. J. Cooper, J. C. Hebden, H. O’Reilly, S. Mitra, A. W. Michell, N. L. Everdell, A. P. Gibson, and T. Austin, “Transient haemodynamic events in neurologically compromised infants: a simultaneous EEG and diffuse optical imaging study,” Neuroimage 55(4), 1610–1616 (2011).
[Crossref] [PubMed]

Ferradal, S. L.

A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (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]

Fox, M. D.

M. D. Fox and M. E. Raichle, “Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging,” Nat. Rev. Neurosci. 8(9), 700–711 (2007).
[Crossref] [PubMed]

Franceschini, M. A.

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]

T. J. Huppert, R. D. Hoge, S. G. Diamond, M. A. Franceschini, and D. A. Boas, “A temporal comparison of BOLD, ASL, and NIRS hemodynamic responses to motor stimuli in adult humans,” Neuroimage 29(2), 368–382 (2006).
[Crossref] [PubMed]

M. A. Franceschini, D. K. Joseph, T. J. Huppert, S. G. Diamond, and D. A. Boas, “Diffuse optical imaging of the whole head,” J. Biomed. Opt. 11(5), 054007 (2006).
[Crossref] [PubMed]

Y. Zhang, D. H. Brooks, M. A. Franceschini, and D. A. Boas, “Eigenvector-based spatial filtering for reduction of physiological interference in diffuse optical imaging,” J. Biomed. Opt. 10(1), 011014 (2005).
[Crossref] [PubMed]

R. D. Hoge, M. A. Franceschini, R. J. Covolan, T. Huppert, J. B. Mandeville, and D. A. Boas, “Simultaneous recording of task-induced changes in blood oxygenation, volume, and flow using diffuse optical imaging and arterial spin-labeling MRI,” Neuroimage 25(3), 701–707 (2005).
[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]

Frederick, B.

Y. Tong, L. M. Hocke, L. D. Nickerson, S. C. Licata, K. P. Lindsey, and B. Frederick, “Evaluating the effects of systemic low frequency oscillations measured in the periphery on the independent component analysis results of resting state networks,” Neuroimage 76, 202–215 (2013).
[Crossref] [PubMed]

Gagnon, L.

L. Gagnon, M. A. Yücel, D. A. Boas, and R. J. Cooper, “Further improvement in reducing superficial contamination in NIRS using double short separation measurements,” Neuroimage 85(Pt 1), 127–135 (2014).
[Crossref] [PubMed]

L. Gagnon, R. J. Cooper, M. A. Yücel, K. L. Perdue, D. N. Greve, and D. A. Boas, “Short separation channel location impacts the performance of short channel regression in NIRS,” Neuroimage 59(3), 2518–2528 (2012).
[Crossref] [PubMed]

L. Gagnon, K. Perdue, D. N. Greve, D. Goldenholz, G. Kaskhedikar, and D. A. Boas, “Improved recovery of the hemodynamic response in diffuse optical imaging using short optode separations and state-space modeling,” Neuroimage 56(3), 1362–1371 (2011).
[Crossref] [PubMed]

Ganis, G.

Q. Zhang, G. E. Strangman, and G. Ganis, “Adaptive filtering to reduce global interference in non-invasive NIRS measures of brain activation: how well and when does it work?” Neuroimage 45(3), 788–794 (2009).
[Crossref] [PubMed]

Gibson, A. P.

R. J. Cooper, J. C. Hebden, H. O’Reilly, S. Mitra, A. W. Michell, N. L. Everdell, A. P. Gibson, and T. Austin, “Transient haemodynamic events in neurologically compromised infants: a simultaneous EEG and diffuse optical imaging study,” Neuroimage 55(4), 1610–1616 (2011).
[Crossref] [PubMed]

Goldenholz, D.

L. Gagnon, K. Perdue, D. N. Greve, D. Goldenholz, G. Kaskhedikar, and D. A. Boas, “Improved recovery of the hemodynamic response in diffuse optical imaging using short optode separations and state-space modeling,” Neuroimage 56(3), 1362–1371 (2011).
[Crossref] [PubMed]

Gregg, N. M.

N. M. Gregg, B. R. White, B. W. Zeff, A. J. Berger, and J. P. Culver, “Brain specificity of diffuse optical imaging: improvements from superficial signal regression and tomography,” Front Neuroenergetics 2, 14 (2010).
[PubMed]

Greve, D. N.

L. Gagnon, R. J. Cooper, M. A. Yücel, K. L. Perdue, D. N. Greve, and D. A. Boas, “Short separation channel location impacts the performance of short channel regression in NIRS,” Neuroimage 59(3), 2518–2528 (2012).
[Crossref] [PubMed]

L. Gagnon, K. Perdue, D. N. Greve, D. Goldenholz, G. Kaskhedikar, and D. A. Boas, “Improved recovery of the hemodynamic response in diffuse optical imaging using short optode separations and state-space modeling,” Neuroimage 56(3), 1362–1371 (2011).
[Crossref] [PubMed]

Hassanpour, M. S.

A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (2014).
[Crossref] [PubMed]

Haughton, V. M.

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]

Hebden, J. C.

R. J. Cooper, J. C. Hebden, H. O’Reilly, S. Mitra, A. W. Michell, N. L. Everdell, A. P. Gibson, and T. Austin, “Transient haemodynamic events in neurologically compromised infants: a simultaneous EEG and diffuse optical imaging study,” Neuroimage 55(4), 1610–1616 (2011).
[Crossref] [PubMed]

Heine, A.

E. Kirilina, A. Jelzow, A. Heine, M. Niessing, H. Wabnitz, R. Brühl, B. Ittermann, A. M. Jacobs, and I. Tachtsidis, “The physiological origin of task-evoked systemic artefacts in functional near infrared spectroscopy,” Neuroimage 61(1), 70–81 (2012).
[Crossref] [PubMed]

Hershey, T.

A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (2014).
[Crossref] [PubMed]

Hocke, L. M.

Y. Tong, L. M. Hocke, L. D. Nickerson, S. C. Licata, K. P. Lindsey, and B. Frederick, “Evaluating the effects of systemic low frequency oscillations measured in the periphery on the independent component analysis results of resting state networks,” Neuroimage 76, 202–215 (2013).
[Crossref] [PubMed]

Hoge, R. D.

T. J. Huppert, R. D. Hoge, S. G. Diamond, M. A. Franceschini, and D. A. Boas, “A temporal comparison of BOLD, ASL, and NIRS hemodynamic responses to motor stimuli in adult humans,” Neuroimage 29(2), 368–382 (2006).
[Crossref] [PubMed]

R. D. Hoge, M. A. Franceschini, R. J. Covolan, T. Huppert, J. B. Mandeville, and D. A. Boas, “Simultaneous recording of task-induced changes in blood oxygenation, volume, and flow using diffuse optical imaging and arterial spin-labeling MRI,” Neuroimage 25(3), 701–707 (2005).
[Crossref] [PubMed]

Hoshi, Y.

Y. Hoshi, “Functional near-infrared spectroscopy: current status and future prospects,” J. Biomed. Opt. 12(6), 062106 (2007).
[Crossref] [PubMed]

Huang, J.

J. Huang, F. Wang, Y. Ding, H. Niu, F. Tian, H. Liu, and Y. Song, “Predicting N2pc from anticipatory HbO activity during sustained visuospatial attention: A concurrent fNIRS-ERP study,” Neuroimage 113, 225–234 (2015).
[Crossref] [PubMed]

Huppert, T.

R. D. Hoge, M. A. Franceschini, R. J. Covolan, T. Huppert, J. B. Mandeville, and D. A. Boas, “Simultaneous recording of task-induced changes in blood oxygenation, volume, and flow using diffuse optical imaging and arterial spin-labeling MRI,” Neuroimage 25(3), 701–707 (2005).
[Crossref] [PubMed]

Huppert, T. J.

T. J. Huppert, R. D. Hoge, S. G. Diamond, M. A. Franceschini, and D. A. Boas, “A temporal comparison of BOLD, ASL, and NIRS hemodynamic responses to motor stimuli in adult humans,” Neuroimage 29(2), 368–382 (2006).
[Crossref] [PubMed]

M. A. Franceschini, D. K. Joseph, T. J. Huppert, S. G. Diamond, and D. A. Boas, “Diffuse optical imaging of the whole head,” J. Biomed. Opt. 11(5), 054007 (2006).
[Crossref] [PubMed]

Hyde, J. S.

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]

Inder, T. E.

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]

Irani, F.

F. Irani, S. M. Platek, S. Bunce, A. C. Ruocco, and D. Chute, “Functional near infrared spectroscopy (fNIRS): an emerging neuroimaging technology with important applications for the study of brain disorders,” Clin. Neuropsychol. 21(1), 9–37 (2007).
[Crossref] [PubMed]

Ishikawa, A.

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]

Ittermann, B.

E. Kirilina, A. Jelzow, A. Heine, M. Niessing, H. Wabnitz, R. Brühl, B. Ittermann, A. M. Jacobs, and I. Tachtsidis, “The physiological origin of task-evoked systemic artefacts in functional near infrared spectroscopy,” Neuroimage 61(1), 70–81 (2012).
[Crossref] [PubMed]

Izzetoglu, K.

S. C. Bunce, M. Izzetoglu, K. Izzetoglu, B. Onaral, and K. Pourrezaei, “Functional near-infrared spectroscopy,” IEEE Eng. Med. Biol. Mag. 25(4), 54–62 (2006).
[Crossref] [PubMed]

Izzetoglu, M.

S. C. Bunce, M. Izzetoglu, K. Izzetoglu, B. Onaral, and K. Pourrezaei, “Functional near-infrared spectroscopy,” IEEE Eng. Med. Biol. Mag. 25(4), 54–62 (2006).
[Crossref] [PubMed]

Jacobs, A. M.

E. Kirilina, A. Jelzow, A. Heine, M. Niessing, H. Wabnitz, R. Brühl, B. Ittermann, A. M. Jacobs, and I. Tachtsidis, “The physiological origin of task-evoked systemic artefacts in functional near infrared spectroscopy,” Neuroimage 61(1), 70–81 (2012).
[Crossref] [PubMed]

Jasper, H. H.

G. H. Klem, H. O. Lüders, H. H. Jasper, C. Elger, and The International Federation of Clinical Neurophysiology, “The ten-twenty electrode system of the International Federation,” Electroencephalogr. Clin. Neurophysiol. Suppl. 52, 3–6 (1999).
[PubMed]

Jelzow, A.

E. Kirilina, A. Jelzow, A. Heine, M. Niessing, H. Wabnitz, R. Brühl, B. Ittermann, A. M. Jacobs, and I. Tachtsidis, “The physiological origin of task-evoked systemic artefacts in functional near infrared spectroscopy,” Neuroimage 61(1), 70–81 (2012).
[Crossref] [PubMed]

Joseph, D. K.

M. A. Franceschini, D. K. Joseph, T. J. Huppert, S. G. Diamond, and D. A. Boas, “Diffuse optical imaging of the whole head,” J. Biomed. Opt. 11(5), 054007 (2006).
[Crossref] [PubMed]

Kaskhedikar, G.

L. Gagnon, K. Perdue, D. N. Greve, D. Goldenholz, G. Kaskhedikar, and D. A. Boas, “Improved recovery of the hemodynamic response in diffuse optical imaging using short optode separations and state-space modeling,” Neuroimage 56(3), 1362–1371 (2011).
[Crossref] [PubMed]

Khan, B.

F. Tian, H. Niu, B. Khan, G. Alexandrakis, K. Behbehani, and H. Liu, “Enhanced Functional Brain Imaging by Using Adaptive Filtering and a Depth Compensation Algorithm in Diffuse Optical Tomography,” IEEE Trans. Med. Imaging 30(6), 1239–1251 (2011).
[Crossref] [PubMed]

Kirilina, E.

E. Kirilina, A. Jelzow, A. Heine, M. Niessing, H. Wabnitz, R. Brühl, B. Ittermann, A. M. Jacobs, and I. Tachtsidis, “The physiological origin of task-evoked systemic artefacts in functional near infrared spectroscopy,” Neuroimage 61(1), 70–81 (2012).
[Crossref] [PubMed]

Klem, G. H.

G. H. Klem, H. O. Lüders, H. H. Jasper, C. Elger, and The International Federation of Clinical Neurophysiology, “The ten-twenty electrode system of the International Federation,” Electroencephalogr. Clin. Neurophysiol. Suppl. 52, 3–6 (1999).
[PubMed]

Kohno, S.

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]

Liao, S. M.

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]

Licata, S. C.

Y. Tong, L. M. Hocke, L. D. Nickerson, S. C. Licata, K. P. Lindsey, and B. Frederick, “Evaluating the effects of systemic low frequency oscillations measured in the periphery on the independent component analysis results of resting state networks,” Neuroimage 76, 202–215 (2013).
[Crossref] [PubMed]

Lindsey, K. P.

Y. Tong, L. M. Hocke, L. D. Nickerson, S. C. Licata, K. P. Lindsey, and B. Frederick, “Evaluating the effects of systemic low frequency oscillations measured in the periphery on the independent component analysis results of resting state networks,” Neuroimage 76, 202–215 (2013).
[Crossref] [PubMed]

Liu, H.

J. Huang, F. Wang, Y. Ding, H. Niu, F. Tian, H. Liu, and Y. Song, “Predicting N2pc from anticipatory HbO activity during sustained visuospatial attention: A concurrent fNIRS-ERP study,” Neuroimage 113, 225–234 (2015).
[Crossref] [PubMed]

F. Tian and H. Liu, “Depth-compensated diffuse optical tomography enhanced by general linear model analysis and an anatomical atlas of human head,” Neuroimage 85(Pt 1), 166–180 (2014).
[Crossref] [PubMed]

F. Tian, H. Niu, B. Khan, G. Alexandrakis, K. Behbehani, and H. Liu, “Enhanced Functional Brain Imaging by Using Adaptive Filtering and a Depth Compensation Algorithm in Diffuse Optical Tomography,” IEEE Trans. Med. Imaging 30(6), 1239–1251 (2011).
[Crossref] [PubMed]

Lu, C. M.

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]

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]

Lüders, H. O.

G. H. Klem, H. O. Lüders, H. H. Jasper, C. Elger, and The International Federation of Clinical Neurophysiology, “The ten-twenty electrode system of the International Federation,” Electroencephalogr. Clin. Neurophysiol. Suppl. 52, 3–6 (1999).
[PubMed]

Mandeville, J. B.

R. D. Hoge, M. A. Franceschini, R. J. Covolan, T. Huppert, J. B. Mandeville, and D. A. Boas, “Simultaneous recording of task-induced changes in blood oxygenation, volume, and flow using diffuse optical imaging and arterial spin-labeling MRI,” Neuroimage 25(3), 701–707 (2005).
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Matsuda, K.

T. Yamada, S. Umeyama, and K. Matsuda, “Multidistance probe arrangement to eliminate artifacts in functional near-infrared spectroscopy,” J. Biomed. Opt. 14(6), 064034 (2009).
[Crossref] [PubMed]

Mazuka, R.

Y. Minagawa-Kawai, H. van der Lely, F. Ramus, Y. Sato, R. Mazuka, and E. Dupoux, “Optical brain imaging reveals general auditory and language-specific processing in early infant development,” Cereb. Cortex 21(2), 254–261 (2011).
[Crossref] [PubMed]

Mesquita, R. C.

Michell, A. W.

R. J. Cooper, J. C. Hebden, H. O’Reilly, S. Mitra, A. W. Michell, N. L. Everdell, A. P. Gibson, and T. Austin, “Transient haemodynamic events in neurologically compromised infants: a simultaneous EEG and diffuse optical imaging study,” Neuroimage 55(4), 1610–1616 (2011).
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Minagawa-Kawai, Y.

Y. Minagawa-Kawai, H. van der Lely, F. Ramus, Y. Sato, R. Mazuka, and E. Dupoux, “Optical brain imaging reveals general auditory and language-specific processing in early infant development,” Cereb. Cortex 21(2), 254–261 (2011).
[Crossref] [PubMed]

Mitra, S.

R. J. Cooper, J. C. Hebden, H. O’Reilly, S. Mitra, A. W. Michell, N. L. Everdell, A. P. Gibson, and T. Austin, “Transient haemodynamic events in neurologically compromised infants: a simultaneous EEG and diffuse optical imaging study,” Neuroimage 55(4), 1610–1616 (2011).
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Miyai, I.

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]

Nickerson, L. D.

Y. Tong, L. M. Hocke, L. D. Nickerson, S. C. Licata, K. P. Lindsey, and B. Frederick, “Evaluating the effects of systemic low frequency oscillations measured in the periphery on the independent component analysis results of resting state networks,” Neuroimage 76, 202–215 (2013).
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Niessing, M.

E. Kirilina, A. Jelzow, A. Heine, M. Niessing, H. Wabnitz, R. Brühl, B. Ittermann, A. M. Jacobs, and I. Tachtsidis, “The physiological origin of task-evoked systemic artefacts in functional near infrared spectroscopy,” Neuroimage 61(1), 70–81 (2012).
[Crossref] [PubMed]

Niu, H.

J. Huang, F. Wang, Y. Ding, H. Niu, F. Tian, H. Liu, and Y. Song, “Predicting N2pc from anticipatory HbO activity during sustained visuospatial attention: A concurrent fNIRS-ERP study,” Neuroimage 113, 225–234 (2015).
[Crossref] [PubMed]

F. Tian, H. Niu, B. Khan, G. Alexandrakis, K. Behbehani, and H. Liu, “Enhanced Functional Brain Imaging by Using Adaptive Filtering and a Depth Compensation Algorithm in Diffuse Optical Tomography,” IEEE Trans. Med. Imaging 30(6), 1239–1251 (2011).
[Crossref] [PubMed]

O’Reilly, H.

R. J. Cooper, J. C. Hebden, H. O’Reilly, S. Mitra, A. W. Michell, N. L. Everdell, A. P. Gibson, and T. Austin, “Transient haemodynamic events in neurologically compromised infants: a simultaneous EEG and diffuse optical imaging study,” Neuroimage 55(4), 1610–1616 (2011).
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Oda, I.

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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Onaral, B.

S. C. Bunce, M. Izzetoglu, K. Izzetoglu, B. Onaral, and K. Pourrezaei, “Functional near-infrared spectroscopy,” IEEE Eng. Med. Biol. Mag. 25(4), 54–62 (2006).
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Peng, D. L.

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]

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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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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F. Irani, S. M. Platek, S. Bunce, A. C. Ruocco, and D. Chute, “Functional near infrared spectroscopy (fNIRS): an emerging neuroimaging technology with important applications for the study of brain disorders,” Clin. Neuropsychol. 21(1), 9–37 (2007).
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S. C. Bunce, M. Izzetoglu, K. Izzetoglu, B. Onaral, and K. Pourrezaei, “Functional near-infrared spectroscopy,” IEEE Eng. Med. Biol. Mag. 25(4), 54–62 (2006).
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[Crossref] [PubMed]

Robichaux-Viehoever, A.

A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (2014).
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Ruocco, A. C.

F. Irani, S. M. Platek, S. Bunce, A. C. Ruocco, and D. Chute, “Functional near infrared spectroscopy (fNIRS): an emerging neuroimaging technology with important applications for the study of brain disorders,” Clin. Neuropsychol. 21(1), 9–37 (2007).
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R. Saager and A. Berger, “Measurement of layer-like hemodynamic trends in scalp and cortex: implications for physiological baseline suppression in functional near-infrared spectroscopy,” J. Biomed. Opt. 13(3), 034017 (2008).
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Saager, R. B.

Sato, Y.

Y. Minagawa-Kawai, H. van der Lely, F. Ramus, Y. Sato, R. Mazuka, and E. Dupoux, “Optical brain imaging reveals general auditory and language-specific processing in early infant development,” Cereb. Cortex 21(2), 254–261 (2011).
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Schlaggar, B. 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).
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B. W. Zeff, B. R. White, H. Dehghani, B. L. Schlaggar, and J. P. Culver, “Retinotopic mapping of adult human visual cortex with high-density diffuse optical tomography,” Proc. Natl. Acad. Sci. U.S.A. 104(29), 12169–12174 (2007).
[Crossref] [PubMed]

Seiyama, A.

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]

Shimizu, K.

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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Snyder, A. Z.

A. T. Eggebrecht, S. L. Ferradal, A. Robichaux-Viehoever, M. S. Hassanpour, H. Dehghani, A. Z. Snyder, T. Hershey, and J. P. Culver, “Mapping distributed brain function and networks with diffuse optical tomography,” Nat. Photonics 8(6), 448–454 (2014).
[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]

Song, Y.

J. Huang, F. Wang, Y. Ding, H. Niu, F. Tian, H. Liu, and Y. Song, “Predicting N2pc from anticipatory HbO activity during sustained visuospatial attention: A concurrent fNIRS-ERP study,” Neuroimage 113, 225–234 (2015).
[Crossref] [PubMed]

Strangman, G. E.

Q. Zhang, G. E. Strangman, and G. Ganis, “Adaptive filtering to reduce global interference in non-invasive NIRS measures of brain activation: how well and when does it work?” Neuroimage 45(3), 788–794 (2009).
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Q. Zhang, E. N. Brown, and G. E. Strangman, “Adaptive filtering to reduce global interference in evoked brain activity detection: a human subject case study,” J. Biomed. Opt. 12(6), 064009 (2007).
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Tachtsidis, I.

E. Kirilina, A. Jelzow, A. Heine, M. Niessing, H. Wabnitz, R. Brühl, B. Ittermann, A. M. Jacobs, and I. Tachtsidis, “The physiological origin of task-evoked systemic artefacts in functional near infrared spectroscopy,” Neuroimage 61(1), 70–81 (2012).
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Tian, F.

J. Huang, F. Wang, Y. Ding, H. Niu, F. Tian, H. Liu, and Y. Song, “Predicting N2pc from anticipatory HbO activity during sustained visuospatial attention: A concurrent fNIRS-ERP study,” Neuroimage 113, 225–234 (2015).
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F. Tian and H. Liu, “Depth-compensated diffuse optical tomography enhanced by general linear model analysis and an anatomical atlas of human head,” Neuroimage 85(Pt 1), 166–180 (2014).
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F. Tian, H. Niu, B. Khan, G. Alexandrakis, K. Behbehani, and H. Liu, “Enhanced Functional Brain Imaging by Using Adaptive Filtering and a Depth Compensation Algorithm in Diffuse Optical Tomography,” IEEE Trans. Med. Imaging 30(6), 1239–1251 (2011).
[Crossref] [PubMed]

Tong, Y.

Y. Tong, L. M. Hocke, L. D. Nickerson, S. C. Licata, K. P. Lindsey, and B. Frederick, “Evaluating the effects of systemic low frequency oscillations measured in the periphery on the independent component analysis results of resting state networks,” Neuroimage 76, 202–215 (2013).
[Crossref] [PubMed]

Tsuneishi, S.

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]

Umeyama, S.

T. Yamada, S. Umeyama, and K. Matsuda, “Multidistance probe arrangement to eliminate artifacts in functional near-infrared spectroscopy,” J. Biomed. Opt. 14(6), 064034 (2009).
[Crossref] [PubMed]

S. Umeyama and T. Yamada, “Monte Carlo study of global interference cancellation by multidistance measurement of near-infrared spectroscopy,” J. Biomed. Opt. 14(6), 064025 (2009).
[Crossref] [PubMed]

van der Lely, H.

Y. Minagawa-Kawai, H. van der Lely, F. Ramus, Y. Sato, R. Mazuka, and E. Dupoux, “Optical brain imaging reveals general auditory and language-specific processing in early infant development,” Cereb. Cortex 21(2), 254–261 (2011).
[Crossref] [PubMed]

Wabnitz, H.

E. Kirilina, A. Jelzow, A. Heine, M. Niessing, H. Wabnitz, R. Brühl, B. Ittermann, A. M. Jacobs, and I. Tachtsidis, “The physiological origin of task-evoked systemic artefacts in functional near infrared spectroscopy,” Neuroimage 61(1), 70–81 (2012).
[Crossref] [PubMed]

Wang, F.

J. Huang, F. Wang, Y. Ding, H. Niu, F. Tian, H. Liu, and Y. Song, “Predicting N2pc from anticipatory HbO activity during sustained visuospatial attention: A concurrent fNIRS-ERP study,” Neuroimage 113, 225–234 (2015).
[Crossref] [PubMed]

Welch, P. D.

P. D. Welch, “Use of fast Fourier transform for estimation of power spectra - a method based on time averaging over short modified periodograms,” IEEE Trans. Acoust. Speech 15, 70–73 (1967).

White, B. R.

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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N. M. Gregg, B. R. White, B. W. Zeff, A. J. Berger, and J. P. Culver, “Brain specificity of diffuse optical imaging: improvements from superficial signal regression and tomography,” Front Neuroenergetics 2, 14 (2010).
[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]

B. W. Zeff, B. R. White, H. Dehghani, B. L. Schlaggar, and J. P. Culver, “Retinotopic mapping of adult human visual cortex with high-density diffuse optical tomography,” Proc. Natl. Acad. Sci. U.S.A. 104(29), 12169–12174 (2007).
[Crossref] [PubMed]

Yamada, T.

S. Umeyama and T. Yamada, “Monte Carlo study of global interference cancellation by multidistance measurement of near-infrared spectroscopy,” J. Biomed. Opt. 14(6), 064025 (2009).
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T. Yamada, S. Umeyama, and K. Matsuda, “Multidistance probe arrangement to eliminate artifacts in functional near-infrared spectroscopy,” J. Biomed. Opt. 14(6), 064034 (2009).
[Crossref] [PubMed]

Yetkin, F. Z.

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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Yücel, M. A.

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L. Gagnon, M. A. Yücel, D. A. Boas, and R. J. Cooper, “Further improvement in reducing superficial contamination in NIRS using double short separation measurements,” Neuroimage 85(Pt 1), 127–135 (2014).
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L. Gagnon, R. J. Cooper, M. A. Yücel, K. L. Perdue, D. N. Greve, and D. A. Boas, “Short separation channel location impacts the performance of short channel regression in NIRS,” Neuroimage 59(3), 2518–2528 (2012).
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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]

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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Zeff, B. W.

N. M. Gregg, B. R. White, B. W. Zeff, A. J. Berger, and J. P. Culver, “Brain specificity of diffuse optical imaging: improvements from superficial signal regression and tomography,” Front Neuroenergetics 2, 14 (2010).
[PubMed]

B. W. Zeff, B. R. White, H. Dehghani, B. L. Schlaggar, and J. P. Culver, “Retinotopic mapping of adult human visual cortex with high-density diffuse optical tomography,” Proc. Natl. Acad. Sci. U.S.A. 104(29), 12169–12174 (2007).
[Crossref] [PubMed]

Zhang, Q.

Q. Zhang, G. E. Strangman, and G. Ganis, “Adaptive filtering to reduce global interference in non-invasive NIRS measures of brain activation: how well and when does it work?” Neuroimage 45(3), 788–794 (2009).
[Crossref] [PubMed]

Q. Zhang, E. N. Brown, and G. E. Strangman, “Adaptive filtering to reduce global interference in evoked brain activity detection: a human subject case study,” J. Biomed. Opt. 12(6), 064009 (2007).
[Crossref] [PubMed]

Zhang, Y.

Y. Zhang, D. H. Brooks, M. A. Franceschini, and D. A. Boas, “Eigenvector-based spatial filtering for reduction of physiological interference in diffuse optical imaging,” J. Biomed. Opt. 10(1), 011014 (2005).
[Crossref] [PubMed]

Zhang, Y. J.

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]

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.

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]

Biomed. Opt. Express (1)

Cereb. Cortex (1)

Y. Minagawa-Kawai, H. van der Lely, F. Ramus, Y. Sato, R. Mazuka, and E. Dupoux, “Optical brain imaging reveals general auditory and language-specific processing in early infant development,” Cereb. Cortex 21(2), 254–261 (2011).
[Crossref] [PubMed]

Clin. Neuropsychol. (1)

F. Irani, S. M. Platek, S. Bunce, A. C. Ruocco, and D. Chute, “Functional near infrared spectroscopy (fNIRS): an emerging neuroimaging technology with important applications for the study of brain disorders,” Clin. Neuropsychol. 21(1), 9–37 (2007).
[Crossref] [PubMed]

Electroencephalogr. Clin. Neurophysiol. Suppl. (1)

G. H. Klem, H. O. Lüders, H. H. Jasper, C. Elger, and The International Federation of Clinical Neurophysiology, “The ten-twenty electrode system of the International Federation,” Electroencephalogr. Clin. Neurophysiol. Suppl. 52, 3–6 (1999).
[PubMed]

Front Neuroenergetics (1)

N. M. Gregg, B. R. White, B. W. Zeff, A. J. Berger, and J. P. Culver, “Brain specificity of diffuse optical imaging: improvements from superficial signal regression and tomography,” Front Neuroenergetics 2, 14 (2010).
[PubMed]

IEEE Eng. Med. Biol. Mag. (1)

S. C. Bunce, M. Izzetoglu, K. Izzetoglu, B. Onaral, and K. Pourrezaei, “Functional near-infrared spectroscopy,” IEEE Eng. Med. Biol. Mag. 25(4), 54–62 (2006).
[Crossref] [PubMed]

IEEE Trans. Acoust. Speech (1)

P. D. Welch, “Use of fast Fourier transform for estimation of power spectra - a method based on time averaging over short modified periodograms,” IEEE Trans. Acoust. Speech 15, 70–73 (1967).

IEEE Trans. Med. Imaging (1)

F. Tian, H. Niu, B. Khan, G. Alexandrakis, K. Behbehani, and H. Liu, “Enhanced Functional Brain Imaging by Using Adaptive Filtering and a Depth Compensation Algorithm in Diffuse Optical Tomography,” IEEE Trans. Med. Imaging 30(6), 1239–1251 (2011).
[Crossref] [PubMed]

J. Biomed. Opt. (9)

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]

Q. Zhang, E. N. Brown, and G. E. Strangman, “Adaptive filtering to reduce global interference in evoked brain activity detection: a human subject case study,” J. Biomed. Opt. 12(6), 064009 (2007).
[Crossref] [PubMed]

R. Saager and A. Berger, “Measurement of layer-like hemodynamic trends in scalp and cortex: implications for physiological baseline suppression in functional near-infrared spectroscopy,” J. Biomed. Opt. 13(3), 034017 (2008).
[Crossref] [PubMed]

S. Umeyama and T. Yamada, “Monte Carlo study of global interference cancellation by multidistance measurement of near-infrared spectroscopy,” J. Biomed. Opt. 14(6), 064025 (2009).
[Crossref] [PubMed]

T. Yamada, S. Umeyama, and K. Matsuda, “Multidistance probe arrangement to eliminate artifacts in functional near-infrared spectroscopy,” J. Biomed. Opt. 14(6), 064034 (2009).
[Crossref] [PubMed]

Y. Hoshi, “Functional near-infrared spectroscopy: current status and future prospects,” J. Biomed. Opt. 12(6), 062106 (2007).
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M. A. Franceschini, D. K. Joseph, T. J. Huppert, S. G. Diamond, and D. A. Boas, “Diffuse optical imaging of the whole head,” J. Biomed. Opt. 11(5), 054007 (2006).
[Crossref] [PubMed]

Y. Zhang, D. H. Brooks, M. A. Franceschini, and D. A. Boas, “Eigenvector-based spatial filtering for reduction of physiological interference in diffuse optical imaging,” J. Biomed. Opt. 10(1), 011014 (2005).
[Crossref] [PubMed]

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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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).
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J. Opt. Soc. Am. A (1)

Magn. Reson. Imaging (1)

D. P. Auer, “Spontaneous low-frequency blood oxygenation level-dependent fluctuations and functional connectivity analysis of the ‘resting’ brain,” Magn. Reson. Imaging 26(7), 1055–1064 (2008).
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Magn. Reson. Med. (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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Med. Biol. Eng. Comput. (1)

M. Cope and D. T. Delpy, “System for long-term measurement of cerebral blood and tissue oxygenation on newborn infants by near infra-red transillumination,” Med. Biol. Eng. Comput. 26(3), 289–294 (1988).
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Nat. Photonics (1)

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Figures (12)

Fig. 1
Fig. 1 Geometry of fNIRS probe and types of S-channel pairs in the first experiment: (A) Schematic arrangement of the sources, detectors and channels in the probe to record superficial interference at multiple regions over the head; (B) Illustration of the local-level S-channel pairs. (C) Illustration of the three types of global-level S-channel pairs: symmetrical pairs (syS-ch), ipsilateral pairs (ipS-ch), and contralateral-asymmetrical pairs (caS-ch).
Fig. 2
Fig. 2 Geometry of fNIRS probe and types of S-channels (S-ch) in the second experiment. All the L-channels were located around the bilateral sensorimotor cortices. Using one L-channel (thick red line) as an example, all S-channels could be categorized into four types according to their locations: local S-channels (orange, in the same sensorimotor region as the selected L-channel), symmetrical-middle S-channels (black, in the sensorimotor region symmetrical to the selected L-channel), posterior S-channels (blue), and anterior S-channels (green).
Fig. 3
Fig. 3 Power (mean ± standard error) of the four physiological fluctuations measured by the S-channels in multiple scalp regions: (A) power of HbO-related components, and (B) power of HbR-related components. In each graph, “A” represents the anterior region, “L” represents the lateral region, “M” represents the middle region, and “P” represents the posterior region.
Fig. 4
Fig. 4 Similarities of superficial interference in the whole-frequency domain (<2 Hz) measured by S-channels in multiple scalp regions. (A) Spatial distributions of S-channel pairs with similarities > 0.4 that were calculated based on HbO data. The colored lines represent the S-channel pairs in different ranges of similarity values. (B) Spatial distributions of S-channel pairs with similarities > 0.4 that were calculated based on HbR data. The colored lines represent the S-channel pairs in different ranges of similarity values. (C) Grand-averaged similarities of superficial interference at the local level and global level based on HbO data. (D) Grand-averaged similarities of superficial interference at the local level and global level based on HbR data. The error bars in (C) and (D) represent the standard deviations.
Fig. 5
Fig. 5 Similarities of superficial interference in four specific frequency bands based on HbO data: (A) the very low-frequency fluctuations between 0.01 and 0.05 Hz, (B) the Mayer waves between 0.07 and 0.15 Hz, (C) the respiratory waves between 0.2 and 0.4 Hz, and (D) the cardiac pulsations between 0.8 and 2 Hz. In each respective graph, the colored lines represent the S-channel pairs in different ranges of similarity values, and the error bars represent the standard deviations.
Fig. 6
Fig. 6 Similarities of superficial interference in four specific frequency bands based on HbR data: (A) the very low-frequency fluctuations between 0.01 and 0.05 Hz, (B) the Mayer waves between 0.07 and 0.15 Hz, (C) the respiratory waves between 0.2 and 0.4 Hz, and (D) the cardiac pulsations between 0.8 and 2 Hz. In each respective graph, the colored lines represent the S-channel pairs in different ranges of similarity values, and the error bars represent the standard deviations.
Fig. 7
Fig. 7 Cross-region similarities of superficial interference (the two paired S-channels were located in two different scalp regions). (A) and (C): The frequency-specific mean similarity matrices that were based on the HbO and HbR data, respectively. As shown in the legend, the upper triangular part of the similarity matrix is for the regions within the same hemisphere (ipsilateral pairs), and the lower triangular part is for the regions between two hemispheres (contralateral pairs). (B) and (D): Comparisons between the cross-anterior similarities (one of the two paired channels in similarity calculation was located in the anterior region) and not-cross-anterior similarities (neither of the two paired channels in similarity calculation was located in the anterior region). The error bars in (C) and (D) represent the standard deviations.
Fig. 8
Fig. 8 Block-averaged motor responses from the L-channels within ROI for a representative subject. In each graph, the solid curves represent the block-averaged time courses, and the shaded areas indicate the standard errors across the seven blocks. Please note that the duration of finger tapping varied from 20 to 30 seconds among the seven blocks.
Fig. 9
Fig. 9 Denoising performance of linear regression in the second experiment: (A) R values between the denoised HbO time series using the four global regressors and the standard HbO time series using the local regressors. (B) MSE values between the denoised HbO time series using the four global regressors and the standard HbO time series. (C) and (D) R and MES results from the HbR data. The error bars in each graph represent the standard deviations.
Fig. 10
Fig. 10 Block-averaged motor responses from the four L-channels within the ROIs for a representative subject. In each graph, the red line represents the true task-evoked brain response, the non-red line represents the recovered task-evoked brain response after line regression, and the shaded areas indicate the standard errors of the recovered brain response across the seven blocks.
Fig. 11
Fig. 11 Grand-averaged motor responses from the L-channels within ROIs for all the nine subjects. In each graph, the red line represents the true task-evoked brain response, the non-red line represents the recovered task-evoked brain response after line regression, and the shaded areas indicate the standard errors of the recovered brain response across the seven blocks.
Fig. 12
Fig. 12 Denoising performance of linear regression with different regressors in the simulative experiment: (A) and (C) R values between the true task-evoked brain responses and the recovered task-evoked brain responses; (C) and (D) MSE values between the true task-evoked brain responses and the recovered task-evoked brain responses.

Tables (1)

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Table 1 The absolute time lags (mean ± standard deviation, in seconds) of superficial interference for the whole-frequency data and the four typical physiological interferences.

Equations (2)

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Y=βX+ε
Z= 1 2 ln( 1+R 1R )

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