Abstract

The ability to produce high-quality images of human brain function in any environment and during unconstrained movement of the subject has long been a goal of neuroimaging research. Diffuse optical tomography, which uses the intensity of back-scattered near-infrared light from multiple source-detector pairs to image changes in haemoglobin concentrations in the brain, is uniquely placed to achieve this goal. Here, we describe a new generation of modular, fibre-less, high-density diffuse optical tomography technology that provides exceptional sensitivity, a large dynamic range, a field-of-view sufficient to cover approximately one-third of the adult scalp, and also incorporates dedicated motion sensing into each module. Using in-vivo measures, we demonstrate a noise-equivalent power of 318 fW, and an effective dynamic range of 142 dB. We describe the application of this system to a novel somatomotor neuroimaging paradigm that involves subjects walking and texting on a smartphone. Our results demonstrate that wearable high-density diffuse optical tomography permits three-dimensional imaging of the human brain function during overt movement of the subject; images of somatomotor cortical activation can be obtained while subjects move in a relatively unconstrained manner, and these images are in good agreement with those obtained while the subjects remain stationary. The scalable nature of the technology we described here paves the way for the routine acquisition of high-quality, three-dimensional, whole-cortex diffuse optical tomography images of cerebral haemodynamics, both inside and outside of the laboratory environment, which has profound implications for neuroscience.

Published by The Optical Society under the terms of the Creative Commons Attribution 4.0 License. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

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2020 (2)

P. Pinti, I. Tachtsidis, A. Hamilton, J. Hirsch, C. Aichelburg, S. Gilbert, and P. W. Burgess, “The present and future use of functional near-infrared spectroscopy (fNIRS) for cognitive neuroscience,” Ann. N. Y. Acad. Sci. 1464(1), 5–29 (2020).
[Crossref]

A. von Lühmann, X. Li, K. R. Müller, D. A. Boas, and M. A. Yücel, “Improved physiological noise regression in fNIRS: A multimodal extension of the General Linear Model using temporally embedded Canonical Correlation Analysis,” NeuroImage 208, 116472 (2020).
[Crossref]

2019 (2)

A. von Lühmann, Z. Boukouvalas, K. R. Müller, and T. Adalı, “A new blind source separation framework for signal analysis and artifact rejection in functional Near-Infrared Spectroscopy,” NeuroImage 200, 72–88 (2019).
[Crossref]

S. Brigadoi, A. Ganglani, H. Zhao, and R. J. Cooper, “Integrating motion sensing and wearable, modular high-density diffuse optical tomography: preliminary results,” Proc. SPIE 11074, 1107405 (2019).
[Crossref]

2018 (1)

S. Lloyd-Fox, A. Blasi, G. Pasco, T. Gliga, E. Jones, D. Murphy, C. E. Elwell, T. Charman, M. H. Johnson, and B. A. S. I. S. Team, “Cortical responses before 6 months of life associate with later autism,” Eur. J. Neurosci. 47(6), 736–749 (2018).
[Crossref]

2017 (2)

H. Zhao and R. J. Cooper, “Review of recent progress toward a fiberless, whole-scalp diffuse optical tomography system,” Neurophotonics 5(1), 1 (2017).
[Crossref]

S. Brigadoi, P. Phan, D. Highton, S. Powell, R. J. Cooper, J. Hebden, M. Smith, I. Tachtsidis, C. E. Elwell, and A. P. Gibson, “Image reconstruction of oxidized cerebral cytochrome C oxidase changes from broadband near-infrared spectroscopy data,” Neurophotonics 4(2), 021105 (2017).
[Crossref]

2016 (4)

A. M. Winkler, G. R. Ridgway, G. Douaud, T. E. Nichols, and S. M. Smith, “Faster permutation inference in brain imaging,” NeuroImage 141, 502–516 (2016).
[Crossref]

D. Chitnis, D. Airantzis, D. Highton, R. Williams, P. Phan, V. Giagka, S. Powell, R. Cooper, I. Tachtsidis, M. Smith, C. E. Elwell, J. C. Hebden, and N. Everdell, “Towards a wearable near infrared spectroscopic probe for monitoring concentrations of multiple chromophores in biological tissue in vivo,” Rev. Sci. Instrum. 87(6), 065112 (2016).
[Crossref]

D. Wyzer, O. Lambercy, F. Scholkmann, and M. Wolf, “Wearable and modular functional near-infrared spectroscopy instrument with multidistance measurements at four wavelengths,” Neurophotonics 4(4), 041413 (2016).
[Crossref]

D. Chitnis, R. J. Cooper, L. Dempsey, S. Powell, S. Quaggia, D. Highton, C. Elwell, J. C. Hebden, and N. L. Everdell, “Functional imaging of the human brain using a modular, fibre-less, high-density diffuse optical tomography system,” Biomed. Opt. Express 7(10), 4275–4288 (2016).
[Crossref]

2015 (7)

A. D. Laura, R. J. Cooper, T. Roque, T. Correia, E. Magee, S. Powell, A. P. Gibson, and J. Hebden, “Data-driven approach to optimum wavelength selection for diffuse optical imaging,” J. Biomed. Opt. 20(1), 016003 (2015).
[Crossref]

S. Brigadoi and R. J. Cooper, “How short is short? Optimum source-detector distance for short-separation channels in functional near-infrared spectroscopy,” Neurophotonics 2(2), 025005 (2015).
[Crossref]

C. M. Aasted, M. A. Yücel, R. J. Cooper, J. Dubb, D. Tsuzuki, L. Becerra, M. P. Petkov, D. Borsook, I. Dan, and D. A. Boas, “Anatomical guidance for functional near-infrared spectroscopy: AtlasViewer tutorial,” Neurophotonics 2(2), 020801 (2015).
[Crossref]

L. J. Weiss-Croft and T. Baldeweg, “Maturation of language networks in children: A systematic review of 22years of functional MRI,” NeuroImage 123, 269–281 (2015).
[Crossref]

S. Lloyd-Fox, M. Papademetriou, M. K. Darboe, N. L. Everdell, R. Wegmuller, A. M. Prentice, S. E. Moore, and C. E. Elwell, “Functional near infrared spectroscopy (fNIRS) to assess cognitive function in infants in rural Africa,” Sci. Rep. 4(1), 4740 (2015).
[Crossref]

A. M. Chiarelli, E. L. Maclin, M. Fabiani, and G. Gratton, “A kurtosis-based wavelet algorithm for motion artifact correction of fNIRS data,” NeuroImage 112, 128–137 (2015).
[Crossref]

X. Cui, J. M. Baker, N. Liu, and A. L. Reiss, “Sensitivity of fNIRS measurement to head motion: An applied use of smartphones in the lab,” J. Neurosci. Methods 245, 37–43 (2015).
[Crossref]

2014 (7)

A. M. Winkler, G. R. Ridgway, M. A. Webster, S. M. Smith, and T. E. Nichols, “Permutation inference for the general linear model,” NeuroImage 92, 381–397 (2014).
[Crossref]

K. L. M. Koenraadt, E. G. J. Roelofsen, J. Duysens, and N. L. W. Keijsers, “Cortical control of normal gait and precision stepping: An fNIRS study,” NeuroImage 85, 415–422 (2014).
[Crossref]

D. A. Boas, C. E. Elwell, M. Ferrari, and G. Taga, “Twenty years of functional near-infrared spectroscopy: introduction for the special issue,” NeuroImage 85, 1–5 (2014).
[Crossref]

F. Scholkmann, S. Kleiser, A. J. Metz, R. Zimmermann, J. M. Pavia, U. Wolf, and M. Wolf, “A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology,” NeuroImage 85, 6–27 (2014).
[Crossref]

S. Brigadoi, L. Ceccherini, S. Cutini, F. Scarpa, P. Scatturin, J. Selb, L. Gagnon, D. A. Boas, and R. J. Cooper, “Motion artifacts in functional near-infrared spectroscopy: A comparison of motion correction techniques applied to real cognitive data,” NeuroImage 85, 181–191 (2014).
[Crossref]

M. Schweiger and S. R. Arridge, “The Toast++ software suite for forward and inverse modeling in optical tomography,” J. Biomed. Opt. 19(4), 040801 (2014).
[Crossref]

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]

2013 (2)

C. Weiss, C. Nettekoven, A. K. Rehme, V. Neuschmelting, A. Eisenbeis, R. Goldbrunner, and C. Grefkes, “Mapping the hand, foot and face representations in the primary motor cortex — Retest reliability of neuronavigated TMS versus functional MRI,” NeuroImage 66, 531–542 (2013).
[Crossref]

M. F. Glasser, S. N. Sotiropoulos, J. A. Wilson, T. S. Coalson, B. Fischl, J. L. Andersson, J. Xu, S. Jbabdi, M. Webster, J. R. Polimeni, D. C. Van Essen, and M. Jenkinson, and WU-Minn HCP Consortium, “The minimal preprocessing pipelines for the Human Connectome Project,” NeuroImage 80, 105–124 (2013).
[Crossref]

2012 (5)

D. C. Van Essen, M. F. Glasser, D. L. Dierker, J. Harwell, and T. Coalson, “Parcellations and Hemispheric Asymmetries of Human Cerebral Cortex Analyzed on Surface-Based Atlases,” Cereb. Cortex 22(10), 2241–2262 (2012).
[Crossref]

A. T. Eggebrecht, B. R. White, S. L. Ferradal, C. Chen, Y. Zhan, A. Z. Snyder, H. Dehghani, and J. P. Culver, “A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping,” NeuroImage 61(4), 1120–1128 (2012).
[Crossref]

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]

R. J. Cooper, J. Selb, L. Gagnon, D. Phillip, H. W. Schytz, H. K. Iversen, M. Ashina, and D. A. Boas, “A Systematic Comparison of Motion Artifact Correction Techniques for Functional Near-Infrared Spectroscopy,” Front. Neurosci. 6, 147 (2012).
[Crossref]

R. J. Cooper, M. Caffini, J. Dubb, Q. Fang, A. Custo, D. Tsuzuki, B. Fischl, W. Wells, I. Dan, and D. A. Boas, “Validating atlas-guided DOT: A comparison of diffuse optical tomography informed by atlas and subject-specific anatomies,” NeuroImage 62(3), 1999–2006 (2012).
[Crossref]

2011 (4)

R. Sperling, “The potential of functional MRI as a biomarker in early Alzheimer's disease,” Neurobiol. Aging 32, S37–S43 (2011).
[Crossref]

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]

B. B. Avants, N. J. Tustison, G. Song, P. A. Cook, A. Klein, and J. C. Gee, “A reproducible evaluation of ANTs similarity metric performance in brain image registration,” NeuroImage 54(3), 2033–2044 (2011).
[Crossref]

J. Virtanen, K. M. Kotilahti, R. Ilmoniemi, T. E. J. Noponen, and J. Virtanen, “Accelerometer-based method for correcting signal baseline changes caused by motion artifacts in medical near-infrared spectroscopy,” J. Biomed. Opt. 16(8), 087005 (2011).
[Crossref]

2010 (5)

F. C. Robertson, T. S. Douglas, and E. M. Meintjes, “Motion Artifact Removal for Functional Near Infrared Spectroscopy: A Comparison of Methods,” IEEE Trans. Biomed. Eng. 57(6), 1377–1387 (2010).
[Crossref]

B. R. White and J. P. Culver, “Quantitative evaluation of high-density diffuse optical tomography: in vivo resolution and mapping performance,” J. Biomed. Opt. 15(2), 026006 (2010).
[Crossref]

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. Neuroenerg. 2, 14 (2010).
[Crossref]

S. Lloyd-Fox, A. Blasi, and C. E. Elwell, “Illuminating the developing brain: The past, present and future of functional near infrared spectroscopy,” Neurosci. Biobehav. Rev. 34(3), 269–284 (2010).
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M. P. van den Heuvel and H. E. Hulshoff Pol, “Exploring the brain network: A review on resting-state fMRI functional connectivity,” Eur. Neuropsychopharmacol. 20(8), 519–534 (2010).
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2009 (1)

2008 (1)

J. D. Meier, T. N. Aflalo, S. Kastner, and M. S. A. Graziano, “Complex Organization of Human Primary Motor Cortex: A High-Resolution fMRI Study,” J. Neurophysiol. 100(4), 1800–1812 (2008).
[Crossref]

2007 (2)

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. 104(29), 12169–12174 (2007).
[Crossref]

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

2006 (1)

2005 (3)

A. Corlu, R. Choe, T. Durduran, K. Lee, M. Schweiger, S. R. Arridge, E. M. Hillman, and A. G. Yodh, “Diffuse optical tomography with spectral constraints and wavelength optimization,” Appl. Opt. 44(11), 2082–2093 (2005).
[Crossref]

A. P. Gibson, J. C. Hebden, and S. R. Arridge, “Recent advances in diffuse optical imaging,” Phys. Med. Biol. 50(4), R1–R43 (2005).
[Crossref]

J. Ashburner and K. J. Friston, “Unified segmentation,” NeuroImage 26(3), 839–851 (2005).
[Crossref]

2004 (1)

H. Chainay, A. Krainik, M. L. Tanguy, E. Gerardin, D. L. Bihan, and S. Lehéricy, “Foot, face and hand representation in the human supplementary motor area,” NeuroReport 15(5), 765–769 (2004).
[Crossref]

2003 (3)

G. Strangman, M. A. Franceschini, and D. A. Boas, “Factors affecting the accuracy of near-infrared spectroscopy concentration calculations for focal changes in oxygenation parameters,” NeuroImage 18(4), 865–879 (2003).
[Crossref]

Y. Hoshi, “Functional near-infrared optical imaging: Utility and limitations in human brain mapping,” Psychophysiology 40(4), 511–520 (2003).
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G. Taga, K. Asakawa, A. Maki, Y. Konishi, and H. Koizumi, “Brain imaging in awake infants by near-infrared optical topography,” Proc. Natl. Acad. Sci. 100(19), 10722–10727 (2003).
[Crossref]

2002 (1)

H. Zhao, Y. Tanikawa, F. Gao, Y. Onodera, A. Sassaroli, K. Tanaka, and Y. Yamada, “Maps of optical differential pathlength factor of human adult forehead, somatosensory motor and occipital regions at multi-wavelengths in NIR,” Phys. Med. Biol. 47(12), 3062075 (2002).
[Crossref]

1999 (1)

1997 (1)

T. A. Yousry, U. D. Schmid, H. Alkadhi, D. Schmidt, A. Peraud, A. Buettner, and P. Winkler, “Localization of the motor hand area to a knob on the precentral gyrus. A new landmark,” Brain 120(1), 141–157 (1997).
[Crossref]

1992 (1)

P. J. Besl and N. D. McKay, “A method for registration of 3-D shapes,” IEEE Trans. Pattern Anal. Mach. Intell. 14(2), 239–256 (1992).
[Crossref]

Aasted, C. M.

C. M. Aasted, M. A. Yücel, R. J. Cooper, J. Dubb, D. Tsuzuki, L. Becerra, M. P. Petkov, D. Borsook, I. Dan, and D. A. Boas, “Anatomical guidance for functional near-infrared spectroscopy: AtlasViewer tutorial,” Neurophotonics 2(2), 020801 (2015).
[Crossref]

Adali, T.

A. von Lühmann, Z. Boukouvalas, K. R. Müller, and T. Adalı, “A new blind source separation framework for signal analysis and artifact rejection in functional Near-Infrared Spectroscopy,” NeuroImage 200, 72–88 (2019).
[Crossref]

Aflalo, T. N.

J. D. Meier, T. N. Aflalo, S. Kastner, and M. S. A. Graziano, “Complex Organization of Human Primary Motor Cortex: A High-Resolution fMRI Study,” J. Neurophysiol. 100(4), 1800–1812 (2008).
[Crossref]

Aichelburg, C.

P. Pinti, I. Tachtsidis, A. Hamilton, J. Hirsch, C. Aichelburg, S. Gilbert, and P. W. Burgess, “The present and future use of functional near-infrared spectroscopy (fNIRS) for cognitive neuroscience,” Ann. N. Y. Acad. Sci. 1464(1), 5–29 (2020).
[Crossref]

Airantzis, D.

D. Chitnis, D. Airantzis, D. Highton, R. Williams, P. Phan, V. Giagka, S. Powell, R. Cooper, I. Tachtsidis, M. Smith, C. E. Elwell, J. C. Hebden, and N. Everdell, “Towards a wearable near infrared spectroscopic probe for monitoring concentrations of multiple chromophores in biological tissue in vivo,” Rev. Sci. Instrum. 87(6), 065112 (2016).
[Crossref]

Alkadhi, H.

T. A. Yousry, U. D. Schmid, H. Alkadhi, D. Schmidt, A. Peraud, A. Buettner, and P. Winkler, “Localization of the motor hand area to a knob on the precentral gyrus. A new landmark,” Brain 120(1), 141–157 (1997).
[Crossref]

Andersson, J. L.

M. F. Glasser, S. N. Sotiropoulos, J. A. Wilson, T. S. Coalson, B. Fischl, J. L. Andersson, J. Xu, S. Jbabdi, M. Webster, J. R. Polimeni, D. C. Van Essen, and M. Jenkinson, and WU-Minn HCP Consortium, “The minimal preprocessing pipelines for the Human Connectome Project,” NeuroImage 80, 105–124 (2013).
[Crossref]

Arridge, S.

S. Arridge and R. J. Cooper, “Optical Image Reconstruction in Brain Mapping,” A. W. Toga, Ed., pp. 217–222, Academic Press, Waltham (2015).

Arridge, S. R.

M. Schweiger and S. R. Arridge, “The Toast++ software suite for forward and inverse modeling in optical tomography,” J. Biomed. Opt. 19(4), 040801 (2014).
[Crossref]

A. Corlu, R. Choe, T. Durduran, K. Lee, M. Schweiger, S. R. Arridge, E. M. Hillman, and A. G. Yodh, “Diffuse optical tomography with spectral constraints and wavelength optimization,” Appl. Opt. 44(11), 2082–2093 (2005).
[Crossref]

A. P. Gibson, J. C. Hebden, and S. R. Arridge, “Recent advances in diffuse optical imaging,” Phys. Med. Biol. 50(4), R1–R43 (2005).
[Crossref]

Asakawa, K.

G. Taga, K. Asakawa, A. Maki, Y. Konishi, and H. Koizumi, “Brain imaging in awake infants by near-infrared optical topography,” Proc. Natl. Acad. Sci. 100(19), 10722–10727 (2003).
[Crossref]

Ashburner, J.

J. Ashburner and K. J. Friston, “Unified segmentation,” NeuroImage 26(3), 839–851 (2005).
[Crossref]

Ashina, M.

R. J. Cooper, J. Selb, L. Gagnon, D. Phillip, H. W. Schytz, H. K. Iversen, M. Ashina, and D. A. Boas, “A Systematic Comparison of Motion Artifact Correction Techniques for Functional Near-Infrared Spectroscopy,” Front. Neurosci. 6, 147 (2012).
[Crossref]

Avants, B. B.

B. B. Avants, N. J. Tustison, G. Song, P. A. Cook, A. Klein, and J. C. Gee, “A reproducible evaluation of ANTs similarity metric performance in brain image registration,” NeuroImage 54(3), 2033–2044 (2011).
[Crossref]

Baker, J. M.

X. Cui, J. M. Baker, N. Liu, and A. L. Reiss, “Sensitivity of fNIRS measurement to head motion: An applied use of smartphones in the lab,” J. Neurosci. Methods 245, 37–43 (2015).
[Crossref]

Baldeweg, T.

L. J. Weiss-Croft and T. Baldeweg, “Maturation of language networks in children: A systematic review of 22years of functional MRI,” NeuroImage 123, 269–281 (2015).
[Crossref]

Barnett, A. H.

Becerra, L.

C. M. Aasted, M. A. Yücel, R. J. Cooper, J. Dubb, D. Tsuzuki, L. Becerra, M. P. Petkov, D. Borsook, I. Dan, and D. A. Boas, “Anatomical guidance for functional near-infrared spectroscopy: AtlasViewer tutorial,” Neurophotonics 2(2), 020801 (2015).
[Crossref]

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. Neuroenerg. 2, 14 (2010).
[Crossref]

Besl, P. J.

P. J. Besl and N. D. McKay, “A method for registration of 3-D shapes,” IEEE Trans. Pattern Anal. Mach. Intell. 14(2), 239–256 (1992).
[Crossref]

Bevilacqua, F.

Bihan, D. L.

H. Chainay, A. Krainik, M. L. Tanguy, E. Gerardin, D. L. Bihan, and S. Lehéricy, “Foot, face and hand representation in the human supplementary motor area,” NeuroReport 15(5), 765–769 (2004).
[Crossref]

Blasi, A.

S. Lloyd-Fox, A. Blasi, G. Pasco, T. Gliga, E. Jones, D. Murphy, C. E. Elwell, T. Charman, M. H. Johnson, and B. A. S. I. S. Team, “Cortical responses before 6 months of life associate with later autism,” Eur. J. Neurosci. 47(6), 736–749 (2018).
[Crossref]

S. Lloyd-Fox, A. Blasi, and C. E. Elwell, “Illuminating the developing brain: The past, present and future of functional near infrared spectroscopy,” Neurosci. Biobehav. Rev. 34(3), 269–284 (2010).
[Crossref]

Boas, D. A.

A. von Lühmann, X. Li, K. R. Müller, D. A. Boas, and M. A. Yücel, “Improved physiological noise regression in fNIRS: A multimodal extension of the General Linear Model using temporally embedded Canonical Correlation Analysis,” NeuroImage 208, 116472 (2020).
[Crossref]

C. M. Aasted, M. A. Yücel, R. J. Cooper, J. Dubb, D. Tsuzuki, L. Becerra, M. P. Petkov, D. Borsook, I. Dan, and D. A. Boas, “Anatomical guidance for functional near-infrared spectroscopy: AtlasViewer tutorial,” Neurophotonics 2(2), 020801 (2015).
[Crossref]

D. A. Boas, C. E. Elwell, M. Ferrari, and G. Taga, “Twenty years of functional near-infrared spectroscopy: introduction for the special issue,” NeuroImage 85, 1–5 (2014).
[Crossref]

S. Brigadoi, L. Ceccherini, S. Cutini, F. Scarpa, P. Scatturin, J. Selb, L. Gagnon, D. A. Boas, and R. J. Cooper, “Motion artifacts in functional near-infrared spectroscopy: A comparison of motion correction techniques applied to real cognitive data,” NeuroImage 85, 181–191 (2014).
[Crossref]

R. J. Cooper, J. Selb, L. Gagnon, D. Phillip, H. W. Schytz, H. K. Iversen, M. Ashina, and D. A. Boas, “A Systematic Comparison of Motion Artifact Correction Techniques for Functional Near-Infrared Spectroscopy,” Front. Neurosci. 6, 147 (2012).
[Crossref]

R. J. Cooper, M. Caffini, J. Dubb, Q. Fang, A. Custo, D. Tsuzuki, B. Fischl, W. Wells, I. Dan, and D. A. Boas, “Validating atlas-guided DOT: A comparison of diffuse optical tomography informed by atlas and subject-specific anatomies,” NeuroImage 62(3), 1999–2006 (2012).
[Crossref]

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]

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]

A. Custo, W. M. Wells, A. H. Barnett, E. M. C. Hillman, and D. A. Boas, “Effective scattering coefficient of the cerebral spinal fluid in adult head models for diffuse optical imaging,” Appl. Opt. 45(19), 4747–4755 (2006).
[Crossref]

G. Strangman, M. A. Franceschini, and D. A. Boas, “Factors affecting the accuracy of near-infrared spectroscopy concentration calculations for focal changes in oxygenation parameters,” NeuroImage 18(4), 865–879 (2003).
[Crossref]

F. Qianqian and D. A. Boas, “Tetrahedral mesh generation from volumetric binary and grayscale images,” 2009 IEEE Int. Symp. Biomed. Imaging Nano Macro, 1142–1145 (2009).

Borsook, D.

C. M. Aasted, M. A. Yücel, R. J. Cooper, J. Dubb, D. Tsuzuki, L. Becerra, M. P. Petkov, D. Borsook, I. Dan, and D. A. Boas, “Anatomical guidance for functional near-infrared spectroscopy: AtlasViewer tutorial,” Neurophotonics 2(2), 020801 (2015).
[Crossref]

Boukouvalas, Z.

A. von Lühmann, Z. Boukouvalas, K. R. Müller, and T. Adalı, “A new blind source separation framework for signal analysis and artifact rejection in functional Near-Infrared Spectroscopy,” NeuroImage 200, 72–88 (2019).
[Crossref]

Brigadoi, S.

S. Brigadoi, A. Ganglani, H. Zhao, and R. J. Cooper, “Integrating motion sensing and wearable, modular high-density diffuse optical tomography: preliminary results,” Proc. SPIE 11074, 1107405 (2019).
[Crossref]

S. Brigadoi, P. Phan, D. Highton, S. Powell, R. J. Cooper, J. Hebden, M. Smith, I. Tachtsidis, C. E. Elwell, and A. P. Gibson, “Image reconstruction of oxidized cerebral cytochrome C oxidase changes from broadband near-infrared spectroscopy data,” Neurophotonics 4(2), 021105 (2017).
[Crossref]

S. Brigadoi and R. J. Cooper, “How short is short? Optimum source-detector distance for short-separation channels in functional near-infrared spectroscopy,” Neurophotonics 2(2), 025005 (2015).
[Crossref]

S. Brigadoi, L. Ceccherini, S. Cutini, F. Scarpa, P. Scatturin, J. Selb, L. Gagnon, D. A. Boas, and R. J. Cooper, “Motion artifacts in functional near-infrared spectroscopy: A comparison of motion correction techniques applied to real cognitive data,” NeuroImage 85, 181–191 (2014).
[Crossref]

Buettner, A.

T. A. Yousry, U. D. Schmid, H. Alkadhi, D. Schmidt, A. Peraud, A. Buettner, and P. Winkler, “Localization of the motor hand area to a knob on the precentral gyrus. A new landmark,” Brain 120(1), 141–157 (1997).
[Crossref]

Burgess, P. W.

P. Pinti, I. Tachtsidis, A. Hamilton, J. Hirsch, C. Aichelburg, S. Gilbert, and P. W. Burgess, “The present and future use of functional near-infrared spectroscopy (fNIRS) for cognitive neuroscience,” Ann. N. Y. Acad. Sci. 1464(1), 5–29 (2020).
[Crossref]

Caffini, M.

R. J. Cooper, M. Caffini, J. Dubb, Q. Fang, A. Custo, D. Tsuzuki, B. Fischl, W. Wells, I. Dan, and D. A. Boas, “Validating atlas-guided DOT: A comparison of diffuse optical tomography informed by atlas and subject-specific anatomies,” NeuroImage 62(3), 1999–2006 (2012).
[Crossref]

Ceccherini, L.

S. Brigadoi, L. Ceccherini, S. Cutini, F. Scarpa, P. Scatturin, J. Selb, L. Gagnon, D. A. Boas, and R. J. Cooper, “Motion artifacts in functional near-infrared spectroscopy: A comparison of motion correction techniques applied to real cognitive data,” NeuroImage 85, 181–191 (2014).
[Crossref]

Chainay, H.

H. Chainay, A. Krainik, M. L. Tanguy, E. Gerardin, D. L. Bihan, and S. Lehéricy, “Foot, face and hand representation in the human supplementary motor area,” NeuroReport 15(5), 765–769 (2004).
[Crossref]

Charman, T.

S. Lloyd-Fox, A. Blasi, G. Pasco, T. Gliga, E. Jones, D. Murphy, C. E. Elwell, T. Charman, M. H. Johnson, and B. A. S. I. S. Team, “Cortical responses before 6 months of life associate with later autism,” Eur. J. Neurosci. 47(6), 736–749 (2018).
[Crossref]

Chen, C.

A. T. Eggebrecht, B. R. White, S. L. Ferradal, C. Chen, Y. Zhan, A. Z. Snyder, H. Dehghani, and J. P. Culver, “A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping,” NeuroImage 61(4), 1120–1128 (2012).
[Crossref]

Chiarelli, A. M.

A. M. Chiarelli, E. L. Maclin, M. Fabiani, and G. Gratton, “A kurtosis-based wavelet algorithm for motion artifact correction of fNIRS data,” NeuroImage 112, 128–137 (2015).
[Crossref]

Chitnis, D.

D. Chitnis, R. J. Cooper, L. Dempsey, S. Powell, S. Quaggia, D. Highton, C. Elwell, J. C. Hebden, and N. L. Everdell, “Functional imaging of the human brain using a modular, fibre-less, high-density diffuse optical tomography system,” Biomed. Opt. Express 7(10), 4275–4288 (2016).
[Crossref]

D. Chitnis, D. Airantzis, D. Highton, R. Williams, P. Phan, V. Giagka, S. Powell, R. Cooper, I. Tachtsidis, M. Smith, C. E. Elwell, J. C. Hebden, and N. Everdell, “Towards a wearable near infrared spectroscopic probe for monitoring concentrations of multiple chromophores in biological tissue in vivo,” Rev. Sci. Instrum. 87(6), 065112 (2016).
[Crossref]

Choe, R.

Coalson, T.

D. C. Van Essen, M. F. Glasser, D. L. Dierker, J. Harwell, and T. Coalson, “Parcellations and Hemispheric Asymmetries of Human Cerebral Cortex Analyzed on Surface-Based Atlases,” Cereb. Cortex 22(10), 2241–2262 (2012).
[Crossref]

Coalson, T. S.

M. F. Glasser, S. N. Sotiropoulos, J. A. Wilson, T. S. Coalson, B. Fischl, J. L. Andersson, J. Xu, S. Jbabdi, M. Webster, J. R. Polimeni, D. C. Van Essen, and M. Jenkinson, and WU-Minn HCP Consortium, “The minimal preprocessing pipelines for the Human Connectome Project,” NeuroImage 80, 105–124 (2013).
[Crossref]

Cook, P. A.

B. B. Avants, N. J. Tustison, G. Song, P. A. Cook, A. Klein, and J. C. Gee, “A reproducible evaluation of ANTs similarity metric performance in brain image registration,” NeuroImage 54(3), 2033–2044 (2011).
[Crossref]

Cooper, R.

D. Chitnis, D. Airantzis, D. Highton, R. Williams, P. Phan, V. Giagka, S. Powell, R. Cooper, I. Tachtsidis, M. Smith, C. E. Elwell, J. C. Hebden, and N. Everdell, “Towards a wearable near infrared spectroscopic probe for monitoring concentrations of multiple chromophores in biological tissue in vivo,” Rev. Sci. Instrum. 87(6), 065112 (2016).
[Crossref]

Cooper, R. J.

S. Brigadoi, A. Ganglani, H. Zhao, and R. J. Cooper, “Integrating motion sensing and wearable, modular high-density diffuse optical tomography: preliminary results,” Proc. SPIE 11074, 1107405 (2019).
[Crossref]

H. Zhao and R. J. Cooper, “Review of recent progress toward a fiberless, whole-scalp diffuse optical tomography system,” Neurophotonics 5(1), 1 (2017).
[Crossref]

S. Brigadoi, P. Phan, D. Highton, S. Powell, R. J. Cooper, J. Hebden, M. Smith, I. Tachtsidis, C. E. Elwell, and A. P. Gibson, “Image reconstruction of oxidized cerebral cytochrome C oxidase changes from broadband near-infrared spectroscopy data,” Neurophotonics 4(2), 021105 (2017).
[Crossref]

D. Chitnis, R. J. Cooper, L. Dempsey, S. Powell, S. Quaggia, D. Highton, C. Elwell, J. C. Hebden, and N. L. Everdell, “Functional imaging of the human brain using a modular, fibre-less, high-density diffuse optical tomography system,” Biomed. Opt. Express 7(10), 4275–4288 (2016).
[Crossref]

S. Brigadoi and R. J. Cooper, “How short is short? Optimum source-detector distance for short-separation channels in functional near-infrared spectroscopy,” Neurophotonics 2(2), 025005 (2015).
[Crossref]

A. D. Laura, R. J. Cooper, T. Roque, T. Correia, E. Magee, S. Powell, A. P. Gibson, and J. Hebden, “Data-driven approach to optimum wavelength selection for diffuse optical imaging,” J. Biomed. Opt. 20(1), 016003 (2015).
[Crossref]

C. M. Aasted, M. A. Yücel, R. J. Cooper, J. Dubb, D. Tsuzuki, L. Becerra, M. P. Petkov, D. Borsook, I. Dan, and D. A. Boas, “Anatomical guidance for functional near-infrared spectroscopy: AtlasViewer tutorial,” Neurophotonics 2(2), 020801 (2015).
[Crossref]

S. Brigadoi, L. Ceccherini, S. Cutini, F. Scarpa, P. Scatturin, J. Selb, L. Gagnon, D. A. Boas, and R. J. Cooper, “Motion artifacts in functional near-infrared spectroscopy: A comparison of motion correction techniques applied to real cognitive data,” NeuroImage 85, 181–191 (2014).
[Crossref]

R. J. Cooper, M. Caffini, J. Dubb, Q. Fang, A. Custo, D. Tsuzuki, B. Fischl, W. Wells, I. Dan, and D. A. Boas, “Validating atlas-guided DOT: A comparison of diffuse optical tomography informed by atlas and subject-specific anatomies,” NeuroImage 62(3), 1999–2006 (2012).
[Crossref]

R. J. Cooper, J. Selb, L. Gagnon, D. Phillip, H. W. Schytz, H. K. Iversen, M. Ashina, and D. A. Boas, “A Systematic Comparison of Motion Artifact Correction Techniques for Functional Near-Infrared Spectroscopy,” Front. Neurosci. 6, 147 (2012).
[Crossref]

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]

S. Arridge and R. J. Cooper, “Optical Image Reconstruction in Brain Mapping,” A. W. Toga, Ed., pp. 217–222, Academic Press, Waltham (2015).

Corlu, A.

Correia, T.

A. D. Laura, R. J. Cooper, T. Roque, T. Correia, E. Magee, S. Powell, A. P. Gibson, and J. Hebden, “Data-driven approach to optimum wavelength selection for diffuse optical imaging,” J. Biomed. Opt. 20(1), 016003 (2015).
[Crossref]

Cui, X.

X. Cui, J. M. Baker, N. Liu, and A. L. Reiss, “Sensitivity of fNIRS measurement to head motion: An applied use of smartphones in the lab,” J. Neurosci. Methods 245, 37–43 (2015).
[Crossref]

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]

A. T. Eggebrecht, B. R. White, S. L. Ferradal, C. Chen, Y. Zhan, A. Z. Snyder, H. Dehghani, and J. P. Culver, “A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping,” NeuroImage 61(4), 1120–1128 (2012).
[Crossref]

B. R. White and J. P. Culver, “Quantitative evaluation of high-density diffuse optical tomography: in vivo resolution and mapping performance,” J. Biomed. Opt. 15(2), 026006 (2010).
[Crossref]

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. Neuroenerg. 2, 14 (2010).
[Crossref]

H. Dehghani, B. R. White, B. W. Zeff, A. Tizzard, and J. P. Culver, “Depth sensitivity and image reconstruction analysis of dense imaging arrays for mapping brain function with diffuse optical tomography,” Appl. Opt. 48(10), D137–D143 (2009).
[Crossref]

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. 104(29), 12169–12174 (2007).
[Crossref]

Custo, A.

R. J. Cooper, M. Caffini, J. Dubb, Q. Fang, A. Custo, D. Tsuzuki, B. Fischl, W. Wells, I. Dan, and D. A. Boas, “Validating atlas-guided DOT: A comparison of diffuse optical tomography informed by atlas and subject-specific anatomies,” NeuroImage 62(3), 1999–2006 (2012).
[Crossref]

A. Custo, W. M. Wells, A. H. Barnett, E. M. C. Hillman, and D. A. Boas, “Effective scattering coefficient of the cerebral spinal fluid in adult head models for diffuse optical imaging,” Appl. Opt. 45(19), 4747–4755 (2006).
[Crossref]

Cutini, S.

S. Brigadoi, L. Ceccherini, S. Cutini, F. Scarpa, P. Scatturin, J. Selb, L. Gagnon, D. A. Boas, and R. J. Cooper, “Motion artifacts in functional near-infrared spectroscopy: A comparison of motion correction techniques applied to real cognitive data,” NeuroImage 85, 181–191 (2014).
[Crossref]

Dan, I.

C. M. Aasted, M. A. Yücel, R. J. Cooper, J. Dubb, D. Tsuzuki, L. Becerra, M. P. Petkov, D. Borsook, I. Dan, and D. A. Boas, “Anatomical guidance for functional near-infrared spectroscopy: AtlasViewer tutorial,” Neurophotonics 2(2), 020801 (2015).
[Crossref]

R. J. Cooper, M. Caffini, J. Dubb, Q. Fang, A. Custo, D. Tsuzuki, B. Fischl, W. Wells, I. Dan, and D. A. Boas, “Validating atlas-guided DOT: A comparison of diffuse optical tomography informed by atlas and subject-specific anatomies,” NeuroImage 62(3), 1999–2006 (2012).
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D. C. Van Essen, M. F. Glasser, D. L. Dierker, J. Harwell, and T. Coalson, “Parcellations and Hemispheric Asymmetries of Human Cerebral Cortex Analyzed on Surface-Based Atlases,” Cereb. Cortex 22(10), 2241–2262 (2012).
[Crossref]

Virtanen, J.

J. Virtanen, K. M. Kotilahti, R. Ilmoniemi, T. E. J. Noponen, and J. Virtanen, “Accelerometer-based method for correcting signal baseline changes caused by motion artifacts in medical near-infrared spectroscopy,” J. Biomed. Opt. 16(8), 087005 (2011).
[Crossref]

J. Virtanen, K. M. Kotilahti, R. Ilmoniemi, T. E. J. Noponen, and J. Virtanen, “Accelerometer-based method for correcting signal baseline changes caused by motion artifacts in medical near-infrared spectroscopy,” J. Biomed. Opt. 16(8), 087005 (2011).
[Crossref]

von Lühmann, A.

A. von Lühmann, X. Li, K. R. Müller, D. A. Boas, and M. A. Yücel, “Improved physiological noise regression in fNIRS: A multimodal extension of the General Linear Model using temporally embedded Canonical Correlation Analysis,” NeuroImage 208, 116472 (2020).
[Crossref]

A. von Lühmann, Z. Boukouvalas, K. R. Müller, and T. Adalı, “A new blind source separation framework for signal analysis and artifact rejection in functional Near-Infrared Spectroscopy,” NeuroImage 200, 72–88 (2019).
[Crossref]

Webster, M.

M. F. Glasser, S. N. Sotiropoulos, J. A. Wilson, T. S. Coalson, B. Fischl, J. L. Andersson, J. Xu, S. Jbabdi, M. Webster, J. R. Polimeni, D. C. Van Essen, and M. Jenkinson, and WU-Minn HCP Consortium, “The minimal preprocessing pipelines for the Human Connectome Project,” NeuroImage 80, 105–124 (2013).
[Crossref]

Webster, M. A.

A. M. Winkler, G. R. Ridgway, M. A. Webster, S. M. Smith, and T. E. Nichols, “Permutation inference for the general linear model,” NeuroImage 92, 381–397 (2014).
[Crossref]

Wegmuller, R.

S. Lloyd-Fox, M. Papademetriou, M. K. Darboe, N. L. Everdell, R. Wegmuller, A. M. Prentice, S. E. Moore, and C. E. Elwell, “Functional near infrared spectroscopy (fNIRS) to assess cognitive function in infants in rural Africa,” Sci. Rep. 4(1), 4740 (2015).
[Crossref]

Weiss, C.

C. Weiss, C. Nettekoven, A. K. Rehme, V. Neuschmelting, A. Eisenbeis, R. Goldbrunner, and C. Grefkes, “Mapping the hand, foot and face representations in the primary motor cortex — Retest reliability of neuronavigated TMS versus functional MRI,” NeuroImage 66, 531–542 (2013).
[Crossref]

Weiss-Croft, L. J.

L. J. Weiss-Croft and T. Baldeweg, “Maturation of language networks in children: A systematic review of 22years of functional MRI,” NeuroImage 123, 269–281 (2015).
[Crossref]

Wells, W.

R. J. Cooper, M. Caffini, J. Dubb, Q. Fang, A. Custo, D. Tsuzuki, B. Fischl, W. Wells, I. Dan, and D. A. Boas, “Validating atlas-guided DOT: A comparison of diffuse optical tomography informed by atlas and subject-specific anatomies,” NeuroImage 62(3), 1999–2006 (2012).
[Crossref]

Wells, W. M.

White, B. R.

A. T. Eggebrecht, B. R. White, S. L. Ferradal, C. Chen, Y. Zhan, A. Z. Snyder, H. Dehghani, and J. P. Culver, “A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping,” NeuroImage 61(4), 1120–1128 (2012).
[Crossref]

B. R. White and J. P. Culver, “Quantitative evaluation of high-density diffuse optical tomography: in vivo resolution and mapping performance,” J. Biomed. Opt. 15(2), 026006 (2010).
[Crossref]

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. Neuroenerg. 2, 14 (2010).
[Crossref]

H. Dehghani, B. R. White, B. W. Zeff, A. Tizzard, and J. P. Culver, “Depth sensitivity and image reconstruction analysis of dense imaging arrays for mapping brain function with diffuse optical tomography,” Appl. Opt. 48(10), D137–D143 (2009).
[Crossref]

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. 104(29), 12169–12174 (2007).
[Crossref]

Williams, R.

D. Chitnis, D. Airantzis, D. Highton, R. Williams, P. Phan, V. Giagka, S. Powell, R. Cooper, I. Tachtsidis, M. Smith, C. E. Elwell, J. C. Hebden, and N. Everdell, “Towards a wearable near infrared spectroscopic probe for monitoring concentrations of multiple chromophores in biological tissue in vivo,” Rev. Sci. Instrum. 87(6), 065112 (2016).
[Crossref]

Wilson, J. A.

M. F. Glasser, S. N. Sotiropoulos, J. A. Wilson, T. S. Coalson, B. Fischl, J. L. Andersson, J. Xu, S. Jbabdi, M. Webster, J. R. Polimeni, D. C. Van Essen, and M. Jenkinson, and WU-Minn HCP Consortium, “The minimal preprocessing pipelines for the Human Connectome Project,” NeuroImage 80, 105–124 (2013).
[Crossref]

Winkler, A. M.

A. M. Winkler, G. R. Ridgway, G. Douaud, T. E. Nichols, and S. M. Smith, “Faster permutation inference in brain imaging,” NeuroImage 141, 502–516 (2016).
[Crossref]

A. M. Winkler, G. R. Ridgway, M. A. Webster, S. M. Smith, and T. E. Nichols, “Permutation inference for the general linear model,” NeuroImage 92, 381–397 (2014).
[Crossref]

Winkler, P.

T. A. Yousry, U. D. Schmid, H. Alkadhi, D. Schmidt, A. Peraud, A. Buettner, and P. Winkler, “Localization of the motor hand area to a knob on the precentral gyrus. A new landmark,” Brain 120(1), 141–157 (1997).
[Crossref]

Wolf, M.

D. Wyzer, O. Lambercy, F. Scholkmann, and M. Wolf, “Wearable and modular functional near-infrared spectroscopy instrument with multidistance measurements at four wavelengths,” Neurophotonics 4(4), 041413 (2016).
[Crossref]

F. Scholkmann, S. Kleiser, A. J. Metz, R. Zimmermann, J. M. Pavia, U. Wolf, and M. Wolf, “A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology,” NeuroImage 85, 6–27 (2014).
[Crossref]

Wolf, U.

F. Scholkmann, S. Kleiser, A. J. Metz, R. Zimmermann, J. M. Pavia, U. Wolf, and M. Wolf, “A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology,” NeuroImage 85, 6–27 (2014).
[Crossref]

Wyzer, D.

D. Wyzer, O. Lambercy, F. Scholkmann, and M. Wolf, “Wearable and modular functional near-infrared spectroscopy instrument with multidistance measurements at four wavelengths,” Neurophotonics 4(4), 041413 (2016).
[Crossref]

Xu, J.

M. F. Glasser, S. N. Sotiropoulos, J. A. Wilson, T. S. Coalson, B. Fischl, J. L. Andersson, J. Xu, S. Jbabdi, M. Webster, J. R. Polimeni, D. C. Van Essen, and M. Jenkinson, and WU-Minn HCP Consortium, “The minimal preprocessing pipelines for the Human Connectome Project,” NeuroImage 80, 105–124 (2013).
[Crossref]

Yamada, Y.

H. Zhao, Y. Tanikawa, F. Gao, Y. Onodera, A. Sassaroli, K. Tanaka, and Y. Yamada, “Maps of optical differential pathlength factor of human adult forehead, somatosensory motor and occipital regions at multi-wavelengths in NIR,” Phys. Med. Biol. 47(12), 3062075 (2002).
[Crossref]

Yodh, A. G.

Yousry, T. A.

T. A. Yousry, U. D. Schmid, H. Alkadhi, D. Schmidt, A. Peraud, A. Buettner, and P. Winkler, “Localization of the motor hand area to a knob on the precentral gyrus. A new landmark,” Brain 120(1), 141–157 (1997).
[Crossref]

Yücel, M. A.

A. von Lühmann, X. Li, K. R. Müller, D. A. Boas, and M. A. Yücel, “Improved physiological noise regression in fNIRS: A multimodal extension of the General Linear Model using temporally embedded Canonical Correlation Analysis,” NeuroImage 208, 116472 (2020).
[Crossref]

C. M. Aasted, M. A. Yücel, R. J. Cooper, J. Dubb, D. Tsuzuki, L. Becerra, M. P. Petkov, D. Borsook, I. Dan, and D. A. Boas, “Anatomical guidance for functional near-infrared spectroscopy: AtlasViewer tutorial,” Neurophotonics 2(2), 020801 (2015).
[Crossref]

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]

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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. Neuroenerg. 2, 14 (2010).
[Crossref]

H. Dehghani, B. R. White, B. W. Zeff, A. Tizzard, and J. P. Culver, “Depth sensitivity and image reconstruction analysis of dense imaging arrays for mapping brain function with diffuse optical tomography,” Appl. Opt. 48(10), D137–D143 (2009).
[Crossref]

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. 104(29), 12169–12174 (2007).
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A. T. Eggebrecht, B. R. White, S. L. Ferradal, C. Chen, Y. Zhan, A. Z. Snyder, H. Dehghani, and J. P. Culver, “A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping,” NeuroImage 61(4), 1120–1128 (2012).
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Zhao, H.

S. Brigadoi, A. Ganglani, H. Zhao, and R. J. Cooper, “Integrating motion sensing and wearable, modular high-density diffuse optical tomography: preliminary results,” Proc. SPIE 11074, 1107405 (2019).
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H. Zhao and R. J. Cooper, “Review of recent progress toward a fiberless, whole-scalp diffuse optical tomography system,” Neurophotonics 5(1), 1 (2017).
[Crossref]

H. Zhao, Y. Tanikawa, F. Gao, Y. Onodera, A. Sassaroli, K. Tanaka, and Y. Yamada, “Maps of optical differential pathlength factor of human adult forehead, somatosensory motor and occipital regions at multi-wavelengths in NIR,” Phys. Med. Biol. 47(12), 3062075 (2002).
[Crossref]

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F. Scholkmann, S. Kleiser, A. J. Metz, R. Zimmermann, J. M. Pavia, U. Wolf, and M. Wolf, “A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology,” NeuroImage 85, 6–27 (2014).
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D. C. Van Essen, M. F. Glasser, D. L. Dierker, J. Harwell, and T. Coalson, “Parcellations and Hemispheric Asymmetries of Human Cerebral Cortex Analyzed on Surface-Based Atlases,” Cereb. Cortex 22(10), 2241–2262 (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. Neuroenerg. 2, 14 (2010).
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Front. Neurosci. (1)

R. J. Cooper, J. Selb, L. Gagnon, D. Phillip, H. W. Schytz, H. K. Iversen, M. Ashina, and D. A. Boas, “A Systematic Comparison of Motion Artifact Correction Techniques for Functional Near-Infrared Spectroscopy,” Front. Neurosci. 6, 147 (2012).
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J. Virtanen, K. M. Kotilahti, R. Ilmoniemi, T. E. J. Noponen, and J. Virtanen, “Accelerometer-based method for correcting signal baseline changes caused by motion artifacts in medical near-infrared spectroscopy,” J. Biomed. Opt. 16(8), 087005 (2011).
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B. R. White and J. P. Culver, “Quantitative evaluation of high-density diffuse optical tomography: in vivo resolution and mapping performance,” J. Biomed. Opt. 15(2), 026006 (2010).
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J. D. Meier, T. N. Aflalo, S. Kastner, and M. S. A. Graziano, “Complex Organization of Human Primary Motor Cortex: A High-Resolution fMRI Study,” J. Neurophysiol. 100(4), 1800–1812 (2008).
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NeuroImage (19)

S. Brigadoi, L. Ceccherini, S. Cutini, F. Scarpa, P. Scatturin, J. Selb, L. Gagnon, D. A. Boas, and R. J. Cooper, “Motion artifacts in functional near-infrared spectroscopy: A comparison of motion correction techniques applied to real cognitive data,” NeuroImage 85, 181–191 (2014).
[Crossref]

R. J. Cooper, M. Caffini, J. Dubb, Q. Fang, A. Custo, D. Tsuzuki, B. Fischl, W. Wells, I. Dan, and D. A. Boas, “Validating atlas-guided DOT: A comparison of diffuse optical tomography informed by atlas and subject-specific anatomies,” NeuroImage 62(3), 1999–2006 (2012).
[Crossref]

A. T. Eggebrecht, B. R. White, S. L. Ferradal, C. Chen, Y. Zhan, A. Z. Snyder, H. Dehghani, and J. P. Culver, “A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping,” NeuroImage 61(4), 1120–1128 (2012).
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K. L. M. Koenraadt, E. G. J. Roelofsen, J. Duysens, and N. L. W. Keijsers, “Cortical control of normal gait and precision stepping: An fNIRS study,” NeuroImage 85, 415–422 (2014).
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C. Weiss, C. Nettekoven, A. K. Rehme, V. Neuschmelting, A. Eisenbeis, R. Goldbrunner, and C. Grefkes, “Mapping the hand, foot and face representations in the primary motor cortex — Retest reliability of neuronavigated TMS versus functional MRI,” NeuroImage 66, 531–542 (2013).
[Crossref]

A. von Lühmann, Z. Boukouvalas, K. R. Müller, and T. Adalı, “A new blind source separation framework for signal analysis and artifact rejection in functional Near-Infrared Spectroscopy,” NeuroImage 200, 72–88 (2019).
[Crossref]

A. von Lühmann, X. Li, K. R. Müller, D. A. Boas, and M. A. Yücel, “Improved physiological noise regression in fNIRS: A multimodal extension of the General Linear Model using temporally embedded Canonical Correlation Analysis,” NeuroImage 208, 116472 (2020).
[Crossref]

L. J. Weiss-Croft and T. Baldeweg, “Maturation of language networks in children: A systematic review of 22years of functional MRI,” NeuroImage 123, 269–281 (2015).
[Crossref]

D. A. Boas, C. E. Elwell, M. Ferrari, and G. Taga, “Twenty years of functional near-infrared spectroscopy: introduction for the special issue,” NeuroImage 85, 1–5 (2014).
[Crossref]

F. Scholkmann, S. Kleiser, A. J. Metz, R. Zimmermann, J. M. Pavia, U. Wolf, and M. Wolf, “A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology,” NeuroImage 85, 6–27 (2014).
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G. Strangman, M. A. Franceschini, and D. A. Boas, “Factors affecting the accuracy of near-infrared spectroscopy concentration calculations for focal changes in oxygenation parameters,” NeuroImage 18(4), 865–879 (2003).
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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).
[Crossref]

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).
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B. B. Avants, N. J. Tustison, G. Song, P. A. Cook, A. Klein, and J. C. Gee, “A reproducible evaluation of ANTs similarity metric performance in brain image registration,” NeuroImage 54(3), 2033–2044 (2011).
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A. M. Winkler, G. R. Ridgway, M. A. Webster, S. M. Smith, and T. E. Nichols, “Permutation inference for the general linear model,” NeuroImage 92, 381–397 (2014).
[Crossref]

A. M. Winkler, G. R. Ridgway, G. Douaud, T. E. Nichols, and S. M. Smith, “Faster permutation inference in brain imaging,” NeuroImage 141, 502–516 (2016).
[Crossref]

M. F. Glasser, S. N. Sotiropoulos, J. A. Wilson, T. S. Coalson, B. Fischl, J. L. Andersson, J. Xu, S. Jbabdi, M. Webster, J. R. Polimeni, D. C. Van Essen, and M. Jenkinson, and WU-Minn HCP Consortium, “The minimal preprocessing pipelines for the Human Connectome Project,” NeuroImage 80, 105–124 (2013).
[Crossref]

Neurophotonics (5)

S. Brigadoi, P. Phan, D. Highton, S. Powell, R. J. Cooper, J. Hebden, M. Smith, I. Tachtsidis, C. E. Elwell, and A. P. Gibson, “Image reconstruction of oxidized cerebral cytochrome C oxidase changes from broadband near-infrared spectroscopy data,” Neurophotonics 4(2), 021105 (2017).
[Crossref]

C. M. Aasted, M. A. Yücel, R. J. Cooper, J. Dubb, D. Tsuzuki, L. Becerra, M. P. Petkov, D. Borsook, I. Dan, and D. A. Boas, “Anatomical guidance for functional near-infrared spectroscopy: AtlasViewer tutorial,” Neurophotonics 2(2), 020801 (2015).
[Crossref]

S. Brigadoi and R. J. Cooper, “How short is short? Optimum source-detector distance for short-separation channels in functional near-infrared spectroscopy,” Neurophotonics 2(2), 025005 (2015).
[Crossref]

H. Zhao and R. J. Cooper, “Review of recent progress toward a fiberless, whole-scalp diffuse optical tomography system,” Neurophotonics 5(1), 1 (2017).
[Crossref]

D. Wyzer, O. Lambercy, F. Scholkmann, and M. Wolf, “Wearable and modular functional near-infrared spectroscopy instrument with multidistance measurements at four wavelengths,” Neurophotonics 4(4), 041413 (2016).
[Crossref]

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H. Chainay, A. Krainik, M. L. Tanguy, E. Gerardin, D. L. Bihan, and S. Lehéricy, “Foot, face and hand representation in the human supplementary motor area,” NeuroReport 15(5), 765–769 (2004).
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Phys. Med. Biol. (2)

H. Zhao, Y. Tanikawa, F. Gao, Y. Onodera, A. Sassaroli, K. Tanaka, and Y. Yamada, “Maps of optical differential pathlength factor of human adult forehead, somatosensory motor and occipital regions at multi-wavelengths in NIR,” Phys. Med. Biol. 47(12), 3062075 (2002).
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A. P. Gibson, J. C. Hebden, and S. R. Arridge, “Recent advances in diffuse optical imaging,” Phys. Med. Biol. 50(4), R1–R43 (2005).
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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. 104(29), 12169–12174 (2007).
[Crossref]

Proc. SPIE (1)

S. Brigadoi, A. Ganglani, H. Zhao, and R. J. Cooper, “Integrating motion sensing and wearable, modular high-density diffuse optical tomography: preliminary results,” Proc. SPIE 11074, 1107405 (2019).
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Psychophysiology (1)

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Rev. Sci. Instrum. (1)

D. Chitnis, D. Airantzis, D. Highton, R. Williams, P. Phan, V. Giagka, S. Powell, R. Cooper, I. Tachtsidis, M. Smith, C. E. Elwell, J. C. Hebden, and N. Everdell, “Towards a wearable near infrared spectroscopic probe for monitoring concentrations of multiple chromophores in biological tissue in vivo,” Rev. Sci. Instrum. 87(6), 065112 (2016).
[Crossref]

Sci. Rep. (1)

S. Lloyd-Fox, M. Papademetriou, M. K. Darboe, N. L. Everdell, R. Wegmuller, A. M. Prentice, S. E. Moore, and C. E. Elwell, “Functional near infrared spectroscopy (fNIRS) to assess cognitive function in infants in rural Africa,” Sci. Rep. 4(1), 4740 (2015).
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Figures (7)

Fig. 1.
Fig. 1. The completed 12-module HD-DOT imaging system. a) Photographs of both sides of the module PCB with key components indicated; b) an exploded view of the module encapsulation layers; c) a photograph of 12 modules in a 2 × 6 formation; d) a system-level diagram showing the 12 modules, control unit, PC, and cabling; e) the system in place on a subject, with neoprene cap; f) diagrams illustrating the anatomical positioning of the 12-module array on the head of our subjects; and g) the group-average sensitivity map calculated via photon transport modelling indicating the regions of the cortex to which the array was sensitive.
Fig. 2.
Fig. 2. A timing diagram of the dual integration data acquisition scheme. Integration A corresponds to the short integration period (0.5 ms) and B, the long integration period (6.3 ms). The LED overlap time τovp can be optimized on a subject-by-subject basis.
Fig. 3.
Fig. 3. HD-DOT haemodynamic images at the subject and group level. Part (a) depicts example 3D orthogonal slices through peak ΔHbO response DOT maps in response to texting with the right hand while seated, texting with the right hand whilst walking, and walking, each thresholded at 30% of the peak response. Group-average haemodynamic response maps, displayed in the Conte 69 template pial space, are shown in part (b). Images b(i-v) show the ΔHbO maps for each of the five conditions, while b(vi-x) the equivalent ΔHbR images.
Fig. 4.
Fig. 4. Group T-stat maps for the contrast of task ΔHbO > baseline ΔHbO for each of the five conditions. The upper row (a-e) consists of the unmasked T­-statistic maps, while the lower row (f-j) shows the masked T-stat maps in which only values that remain significant after correction are displayed.
Fig. 5.
Fig. 5. Overlap images comparing the spatial distribution of seated and walking functional T-stat maps. (a) shows masks of the region in which the T-stat map exceeds 30% of its maximum for seated texting right (green) and walking texting right (blue). The regions where these masks coincide is shown in dark red. The equivalent image for texting with the left hand is shown in (b).
Fig. 6.
Fig. 6. The relationship between motion sensor data and DOT artifacts. a) A selected period of accelerometery data from one module (in blue) and the unfiltered change-in-absorbance signal at 740 nm for a channel associated with that same module (in green). The overlaid pink shaded regions indicate periods identified as motion artifacts using the DOT data (see “Methods”) while the yellow shaded periods identify features from the MPU signal. Note the discrepancies between the two. Panel b) presents equivalent data for the walking paradigm. Note the overt periods of increased acceleration variance during the walking blocks. Motion artifacts identified in the DOT data do not coincide with detectable changes in the accelerometer signal, which appears dominated by the acceleration associated with the walking task itself. Panel c) Provides a summary of the concordance between the DOT- and MPU-derived artifact envelopes across all datasets.
Fig. 7.
Fig. 7. Phantom characterization of the thermal stability of the 12-module HD-DOT system.

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