Video Abstract
Improving optical contact for functional infrared brain spectroscopy and imaging with brush optodes

Abstract

A novel brush optode was designed and demonstrated to overcome poor optical contact with the scalp that can occur during functional near infrared spectroscopy (fNIRS) and imaging due to light obstruction by hair. The brush optodes were implemented as an attachment to existing commercial flat-faced (conventional) fiber bundle optodes. The goal was that the brush optodes would thread through hair and improve optical contact on subjects with dense hair. Simulations and experiments were performed to assess the magnitude of these improvements. FNIRS measurements on 17 subjects with varying hair colors (blonde, brown, and black) and hair densities (0–2.96 hairs/mm2) were performed during a finger tapping protocol for both flat and brush optodes. In addition to reaching a study success rate of almost 100% when using the brush optode extensions, the measurement setup times were reduced by a factor of three. Furthermore, the brush optodes enabled improvements in the activation signal-to-noise ratio (SNR) by up to a factor of ten as well as significant (p < 0.05) increases in the detected area of activation (dAoA). The measured improvements in SNR were matched by Monte Carlo (MC) simulations of photon propagation through scalp and hair. In addition, an analytical model was derived to mathematically estimate the observed light power losses due to different hair colors and hair densities. Interestingly, the derived analytical formula produced excellent estimates of the experimental data and MC simulation results despite several simplifying assumptions. The analytical model enables researchers to readily estimate the light power losses due to obstruction by hair for both flat-faced fiber bundles and individual fibers for a given subject.

© 2012 OSA

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Q. Zhang, X. Yan, and G. E. Strangman, “Development of motion resistant instrumentation for ambulatory near-infrared spectroscopy,” J. Biomed. Opt.16(8), 087008 (2011).
[CrossRef] [PubMed]

T. Funane, M. Kiguchi, H. Atsumori, H. Sato, K. Kubota, and H. Koizumi, “Synchronous activity of two people’s prefrontal cortices during a cooperative task measured by simultaneous near-infrared spectroscopy,” J. Biomed. Opt.16(7), 077011 (2011).
[CrossRef] [PubMed]

B. Khan, C. Wildey, R. Francis, F. Tian, M. I. Romero, M. R. Delgado, N. J. Clegg, L. Smith, H. Liu, D. L. MacFarlane, and G. Alexandrakis, “Functional near infrared brain imaging with a brush-fiber optode to improve optical contact on subjects with dense hair,” Proc. SPIE7883, 78834V (2011).
[CrossRef]

B. Khan, P. Chand, and G. Alexandrakis, “Spatiotemporal relations of primary sensorimotor and secondary motor activation patterns mapped by NIR imaging,” Biomed. Opt. Express2(12), 3367–3386 (2011).
[CrossRef] [PubMed]

F. Jimenez, A. Izeta, and E. Poblet, “Morphometric analysis of the human scalp hair follicle: practical implications for the hair transplant surgeon and hair regeneration studies,” Dermatol. Surg.37(1), 58–64 (2011).
[CrossRef] [PubMed]

2010

D. Yudovsky and L. Pilon, “Modeling the local excitation fluence rate and fluorescence emission in absorbing and strongly scattering multilayered media,” Appl. Opt.49(31), 6072–6084 (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 Neuroenergetics2, 0000–9999 (2010).
[PubMed]

S. M. Liao, N. M. Gregg, B. R. White, B. W. Zeff, K. A. Bjerkaas, T. E. Inder, and J. P. Culver, “Neonatal hemodynamic response to visual cortex activity: high-density near-infrared spectroscopy study,” J. Biomed. Opt.15(2), 026010 (2010).
[CrossRef] [PubMed]

H. W. Schytz, K. Ciftçi, A. Akin, M. Ashina, and H. Bolay, “Intact neurovascular coupling during executive function in migraine without aura: interictal near-infrared spectroscopy study,” Cephalalgia30(4), 457–466 (2010).
[PubMed]

F. Orihuela-Espina, D. R. Leff, D. R. James, A. W. Darzi, and G. Z. Yang, “Quality control and assurance in functional near infrared spectroscopy (fNIRS) experimentation,” Phys. Med. Biol.55(13), 3701–3724 (2010).
[CrossRef] [PubMed]

A. V. Medvedev, J. M. Kainerstorfer, S. V. Borisov, A. H. Gandjbakhche, and J. Vanmeter, ““Seeing” electroencephalogram through the skull: imaging prefrontal cortex with fast optical signal,” J. Biomed. Opt.15(6), 061702 (2010).
[CrossRef] [PubMed]

B. Khan, F. Tian, K. Behbehani, M. I. Romero, M. R. Delgado, N. J. Clegg, L. Smith, D. Reid, H. Liu, and G. Alexandrakis, “Identification of abnormal motor cortex activation patterns in children with cerebral palsy by functional near-infrared spectroscopy,” J. Biomed. Opt.15(3), 036008 (2010).
[CrossRef] [PubMed]

F. Tian, M. R. Delgado, S. C. Dhamne, B. Khan, G. Alexandrakis, M. I. Romero, L. Smith, D. Reid, N. J. Clegg, and H. Liu, “Quantification of functional near infrared spectroscopy to assess cortical reorganization in children with cerebral palsy,” Opt. Express18(25), 25973–25986 (2010).
[CrossRef] [PubMed]

S. P. Koch, C. Habermehl, J. Mehnert, C. H. Schmitz, S. Holtze, A. Villringer, J. Steinbrink, and H. Obrig, “High-resolution optical functional mapping of the human somatosensory cortex,” Front Neuroenergetics2, 12 (2010).
[PubMed]

2009

F. Abdelnour, B. Schmidt, and T. J. Huppert, “Topographic localization of brain activation in diffuse optical imaging using spherical wavelets,” Phys. Med. Biol.54(20), 6383–6413 (2009).
[CrossRef] [PubMed]

X. Bai, Z. Liu, N. Zhang, W. Chen, and B. He, “Three-dimensional source imaging from simultaneously recorded ERP and BOLD-fMRI,” IEEE Trans. Neural Syst. Rehabil. Eng.17(2), 101–106 (2009).
[CrossRef] [PubMed]

K. Li, L. Guo, J. Nie, G. Li, and T. Liu, “Review of methods for functional brain connectivity detection using fMRI,” Comput. Med. Imaging Graph.33(2), 131–139 (2009).
[CrossRef] [PubMed]

D. H. Burns, S. Rosendahl, D. Bandilla, O. C. Maes, H. M. Chertkow, and H. M. Schipper, “Near-infrared spectroscopy of blood plasma for diagnosis of sporadic Alzheimer’s disease,” J. Alzheimers Dis.17(2), 391–397 (2009).
[PubMed]

A. Gibson and H. Dehghani, “Diffuse optical imaging,” Philos. Transact. A Math. Phys. Eng. Sci.367(1900), 3055–3072 (2009).
[CrossRef] [PubMed]

C. Terborg, K. Gröschel, A. Petrovitch, T. Ringer, S. Schnaudigel, O. W. Witte, and A. Kastrup, “Noninvasive assessment of cerebral perfusion and oxygenation in acute ischemic stroke by near-infrared spectroscopy,” Eur. Neurol.62(6), 338–343 (2009).
[CrossRef] [PubMed]

A. F. Abdelnour and T. Huppert, “Real-time imaging of human brain function by near-infrared spectroscopy using an adaptive general linear model,” Neuroimage46(1), 133–143 (2009).
[CrossRef] [PubMed]

T. J. Huppert, S. G. Diamond, M. A. Franceschini, and D. A. Boas, “HomER: a review of time-series analysis methods for near-infrared spectroscopy of the brain,” Appl. Opt.48(10), D280–D298 (2009).
[CrossRef] [PubMed]

S. H. Tseng, P. Bargo, A. Durkin, and N. Kollias, “Chromophore concentrations, absorption and scattering properties of human skin in-vivo,” Opt. Express17(17), 14599–14617 (2009).
[CrossRef] [PubMed]

A. Kharin, B. Varghese, R. Verhagen, and N. Uzunbajakava, “Optical properties of the medulla and the cortex of human scalp hair,” J. Biomed. Opt.14(2), 024035 (2009).
[CrossRef] [PubMed]

D. J. Cuccia, F. Bevilacqua, A. J. Durkin, F. R. Ayers, and B. J. Tromberg, “Quantitation and mapping of tissue optical properties using modulated imaging,” J. Biomed. Opt.14(2), 024012 (2009).
[CrossRef] [PubMed]

2008

M. Kubota, M. Inouchi, I. Dan, D. Tsuzuki, A. Ishikawa, and T. Scovel, “Fast (100-175 ms) components elicited bilaterally by language production as measured by three-wavelength optical imaging,” Brain Res.1226, 124–133 (2008).
[CrossRef] [PubMed]

2007

Q. Zhang, E. N. Brown, and G. E. Strangman, “Adaptive filtering for global interference cancellation and real-time recovery of evoked brain activity: a Monte Carlo simulation study,” J. Biomed. Opt.12(4), 044014 (2007).
[CrossRef] [PubMed]

2006

G. Muehllehner and J. S. Karp, “Positron emission tomography,” Phys. Med. Biol.51(13), R117–R137 (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,” Neuroimage29(2), 368–382 (2006).
[CrossRef] [PubMed]

A. K. Singh and I. Dan, “Exploring the false discovery rate in multichannel NIRS,” Neuroimage33(2), 542–549 (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]

C. Julien, “The enigma of Mayer waves: Facts and models,” Cardiovasc. Res.70(1), 12–21 (2006).
[CrossRef] [PubMed]

2005

J. Selb, J. J. Stott, M. A. Franceschini, A. G. Sorensen, and D. A. Boas, “Improved sensitivity to cerebral hemodynamics during brain activation with a time-gated optical system: analytical model and experimental validation,” J. Biomed. Opt.10(1), 011013 (2005).
[CrossRef] [PubMed]

B. Brooksby, S. Srinivasan, S. Jiang, H. Dehghani, B. W. Pogue, K. D. Paulsen, J. Weaver, C. Kogel, and S. P. Poplack, “Spectral priors improve near-infrared diffuse tomography more than spatial priors,” Opt. Lett.30(15), 1968–1970 (2005).
[CrossRef] [PubMed]

M. Izzetoglu, A. Devaraj, S. Bunce, and B. Onaral, “Motion artifact cancellation in NIR spectroscopy using Wiener filtering,” IEEE Trans. Biomed. Eng.52(5), 934–938 (2005).
[CrossRef] [PubMed]

2004

A. Li, Q. Zhang, J. P. Culver, E. L. Miller, and D. A. Boas, “Reconstructing chromosphere concentration images directly by continuous-wave diffuse optical tomography,” Opt. Lett.29(3), 256–258 (2004).
[CrossRef] [PubMed]

G. Morren, U. Wolf, P. Lemmerling, M. Wolf, J. H. Choi, E. Gratton, L. De Lathauwer, and S. Van Huffel, “Detection of fast neuronal signals in the motor cortex from functional near infrared spectroscopy measurements using independent component analysis,” Med. Biol. Eng. Comput.42(1), 92–99 (2004).
[CrossRef] [PubMed]

T. Suto, M. Fukuda, M. Ito, T. Uehara, and M. Mikuni, “Multichannel near-infrared spectroscopy in depression and schizophrenia: cognitive brain activation study,” Biol. Psychiatry55(5), 501–511 (2004).
[CrossRef] [PubMed]

2003

C. F. Beckmann, M. Jenkinson, and S. M. Smith, “General multilevel linear modeling for group analysis in FMRI,” Neuroimage20(2), 1052–1063 (2003).
[CrossRef] [PubMed]

B. Dilharreguy, R. A. Jones, and C. T. Moonen, “Influence of fMRI data sampling on the temporal characterization of the hemodynamic response,” Neuroimage19(4), 1820–1828 (2003).
[CrossRef] [PubMed]

1994

1990

W. F. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical properties of biological tissues,” IEEE J. Quantum Electron.26(12), 2166–2185 (1990).
[CrossRef]

1965

J. M. Barman, I. Astore, and V. Pecoraro, “The normal trichogram of the adult,” J. Invest. Dermatol.44, 233–236 (1965).
[PubMed]

Abdelnour, A. F.

A. F. Abdelnour and T. Huppert, “Real-time imaging of human brain function by near-infrared spectroscopy using an adaptive general linear model,” Neuroimage46(1), 133–143 (2009).
[CrossRef] [PubMed]

Abdelnour, F.

F. Abdelnour, B. Schmidt, and T. J. Huppert, “Topographic localization of brain activation in diffuse optical imaging using spherical wavelets,” Phys. Med. Biol.54(20), 6383–6413 (2009).
[CrossRef] [PubMed]

Akin, A.

H. W. Schytz, K. Ciftçi, A. Akin, M. Ashina, and H. Bolay, “Intact neurovascular coupling during executive function in migraine without aura: interictal near-infrared spectroscopy study,” Cephalalgia30(4), 457–466 (2010).
[PubMed]

Alexandrakis, G.

B. Khan, C. Wildey, R. Francis, F. Tian, M. I. Romero, M. R. Delgado, N. J. Clegg, L. Smith, H. Liu, D. L. MacFarlane, and G. Alexandrakis, “Functional near infrared brain imaging with a brush-fiber optode to improve optical contact on subjects with dense hair,” Proc. SPIE7883, 78834V (2011).
[CrossRef]

B. Khan, P. Chand, and G. Alexandrakis, “Spatiotemporal relations of primary sensorimotor and secondary motor activation patterns mapped by NIR imaging,” Biomed. Opt. Express2(12), 3367–3386 (2011).
[CrossRef] [PubMed]

B. Khan, F. Tian, K. Behbehani, M. I. Romero, M. R. Delgado, N. J. Clegg, L. Smith, D. Reid, H. Liu, and G. Alexandrakis, “Identification of abnormal motor cortex activation patterns in children with cerebral palsy by functional near-infrared spectroscopy,” J. Biomed. Opt.15(3), 036008 (2010).
[CrossRef] [PubMed]

F. Tian, M. R. Delgado, S. C. Dhamne, B. Khan, G. Alexandrakis, M. I. Romero, L. Smith, D. Reid, N. J. Clegg, and H. Liu, “Quantification of functional near infrared spectroscopy to assess cortical reorganization in children with cerebral palsy,” Opt. Express18(25), 25973–25986 (2010).
[CrossRef] [PubMed]

Ashina, M.

H. W. Schytz, K. Ciftçi, A. Akin, M. Ashina, and H. Bolay, “Intact neurovascular coupling during executive function in migraine without aura: interictal near-infrared spectroscopy study,” Cephalalgia30(4), 457–466 (2010).
[PubMed]

Astore, I.

J. M. Barman, I. Astore, and V. Pecoraro, “The normal trichogram of the adult,” J. Invest. Dermatol.44, 233–236 (1965).
[PubMed]

Atsumori, H.

T. Funane, M. Kiguchi, H. Atsumori, H. Sato, K. Kubota, and H. Koizumi, “Synchronous activity of two people’s prefrontal cortices during a cooperative task measured by simultaneous near-infrared spectroscopy,” J. Biomed. Opt.16(7), 077011 (2011).
[CrossRef] [PubMed]

Ayers, F. R.

D. J. Cuccia, F. Bevilacqua, A. J. Durkin, F. R. Ayers, and B. J. Tromberg, “Quantitation and mapping of tissue optical properties using modulated imaging,” J. Biomed. Opt.14(2), 024012 (2009).
[CrossRef] [PubMed]

Bai, X.

X. Bai, Z. Liu, N. Zhang, W. Chen, and B. He, “Three-dimensional source imaging from simultaneously recorded ERP and BOLD-fMRI,” IEEE Trans. Neural Syst. Rehabil. Eng.17(2), 101–106 (2009).
[CrossRef] [PubMed]

Bandilla, D.

D. H. Burns, S. Rosendahl, D. Bandilla, O. C. Maes, H. M. Chertkow, and H. M. Schipper, “Near-infrared spectroscopy of blood plasma for diagnosis of sporadic Alzheimer’s disease,” J. Alzheimers Dis.17(2), 391–397 (2009).
[PubMed]

Bargo, P.

Barman, J. M.

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Franceschini, M. A.

T. J. Huppert, S. G. Diamond, M. A. Franceschini, and D. A. Boas, “HomER: a review of time-series analysis methods for near-infrared spectroscopy of the brain,” Appl. Opt.48(10), D280–D298 (2009).
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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 Neuroenergetics2, 0000–9999 (2010).
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T. Suto, M. Fukuda, M. Ito, T. Uehara, and M. Mikuni, “Multichannel near-infrared spectroscopy in depression and schizophrenia: cognitive brain activation study,” Biol. Psychiatry55(5), 501–511 (2004).
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M. Izzetoglu, A. Devaraj, S. Bunce, and B. Onaral, “Motion artifact cancellation in NIR spectroscopy using Wiener filtering,” IEEE Trans. Biomed. Eng.52(5), 934–938 (2005).
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F. Orihuela-Espina, D. R. Leff, D. R. James, A. W. Darzi, and G. Z. Yang, “Quality control and assurance in functional near infrared spectroscopy (fNIRS) experimentation,” Phys. Med. Biol.55(13), 3701–3724 (2010).
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Jimenez, F.

F. Jimenez, A. Izeta, and E. Poblet, “Morphometric analysis of the human scalp hair follicle: practical implications for the hair transplant surgeon and hair regeneration studies,” Dermatol. Surg.37(1), 58–64 (2011).
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B. Dilharreguy, R. A. Jones, and C. T. Moonen, “Influence of fMRI data sampling on the temporal characterization of the hemodynamic response,” Neuroimage19(4), 1820–1828 (2003).
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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).
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B. Khan, C. Wildey, R. Francis, F. Tian, M. I. Romero, M. R. Delgado, N. J. Clegg, L. Smith, H. Liu, D. L. MacFarlane, and G. Alexandrakis, “Functional near infrared brain imaging with a brush-fiber optode to improve optical contact on subjects with dense hair,” Proc. SPIE7883, 78834V (2011).
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[CrossRef] [PubMed]

B. Khan, F. Tian, K. Behbehani, M. I. Romero, M. R. Delgado, N. J. Clegg, L. Smith, D. Reid, H. Liu, and G. Alexandrakis, “Identification of abnormal motor cortex activation patterns in children with cerebral palsy by functional near-infrared spectroscopy,” J. Biomed. Opt.15(3), 036008 (2010).
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S. P. Koch, C. Habermehl, J. Mehnert, C. H. Schmitz, S. Holtze, A. Villringer, J. Steinbrink, and H. Obrig, “High-resolution optical functional mapping of the human somatosensory cortex,” Front Neuroenergetics2, 12 (2010).
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T. Funane, M. Kiguchi, H. Atsumori, H. Sato, K. Kubota, and H. Koizumi, “Synchronous activity of two people’s prefrontal cortices during a cooperative task measured by simultaneous near-infrared spectroscopy,” J. Biomed. Opt.16(7), 077011 (2011).
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Kubota, K.

T. Funane, M. Kiguchi, H. Atsumori, H. Sato, K. Kubota, and H. Koizumi, “Synchronous activity of two people’s prefrontal cortices during a cooperative task measured by simultaneous near-infrared spectroscopy,” J. Biomed. Opt.16(7), 077011 (2011).
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M. Kubota, M. Inouchi, I. Dan, D. Tsuzuki, A. Ishikawa, and T. Scovel, “Fast (100-175 ms) components elicited bilaterally by language production as measured by three-wavelength optical imaging,” Brain Res.1226, 124–133 (2008).
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F. Orihuela-Espina, D. R. Leff, D. R. James, A. W. Darzi, and G. Z. Yang, “Quality control and assurance in functional near infrared spectroscopy (fNIRS) experimentation,” Phys. Med. Biol.55(13), 3701–3724 (2010).
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G. Morren, U. Wolf, P. Lemmerling, M. Wolf, J. H. Choi, E. Gratton, L. De Lathauwer, and S. Van Huffel, “Detection of fast neuronal signals in the motor cortex from functional near infrared spectroscopy measurements using independent component analysis,” Med. Biol. Eng. Comput.42(1), 92–99 (2004).
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X. Bai, Z. Liu, N. Zhang, W. Chen, and B. He, “Three-dimensional source imaging from simultaneously recorded ERP and BOLD-fMRI,” IEEE Trans. Neural Syst. Rehabil. Eng.17(2), 101–106 (2009).
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B. Khan, C. Wildey, R. Francis, F. Tian, M. I. Romero, M. R. Delgado, N. J. Clegg, L. Smith, H. Liu, D. L. MacFarlane, and G. Alexandrakis, “Functional near infrared brain imaging with a brush-fiber optode to improve optical contact on subjects with dense hair,” Proc. SPIE7883, 78834V (2011).
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S. P. Koch, C. Habermehl, J. Mehnert, C. H. Schmitz, S. Holtze, A. Villringer, J. Steinbrink, and H. Obrig, “High-resolution optical functional mapping of the human somatosensory cortex,” Front Neuroenergetics2, 12 (2010).
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Poblet, E.

F. Jimenez, A. Izeta, and E. Poblet, “Morphometric analysis of the human scalp hair follicle: practical implications for the hair transplant surgeon and hair regeneration studies,” Dermatol. Surg.37(1), 58–64 (2011).
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Poplack, S. P.

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F. Tian, M. R. Delgado, S. C. Dhamne, B. Khan, G. Alexandrakis, M. I. Romero, L. Smith, D. Reid, N. J. Clegg, and H. Liu, “Quantification of functional near infrared spectroscopy to assess cortical reorganization in children with cerebral palsy,” Opt. Express18(25), 25973–25986 (2010).
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C. Terborg, K. Gröschel, A. Petrovitch, T. Ringer, S. Schnaudigel, O. W. Witte, and A. Kastrup, “Noninvasive assessment of cerebral perfusion and oxygenation in acute ischemic stroke by near-infrared spectroscopy,” Eur. Neurol.62(6), 338–343 (2009).
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B. Khan, C. Wildey, R. Francis, F. Tian, M. I. Romero, M. R. Delgado, N. J. Clegg, L. Smith, H. Liu, D. L. MacFarlane, and G. Alexandrakis, “Functional near infrared brain imaging with a brush-fiber optode to improve optical contact on subjects with dense hair,” Proc. SPIE7883, 78834V (2011).
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H. W. Schytz, K. Ciftçi, A. Akin, M. Ashina, and H. Bolay, “Intact neurovascular coupling during executive function in migraine without aura: interictal near-infrared spectroscopy study,” Cephalalgia30(4), 457–466 (2010).
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F. Tian, M. R. Delgado, S. C. Dhamne, B. Khan, G. Alexandrakis, M. I. Romero, L. Smith, D. Reid, N. J. Clegg, and H. Liu, “Quantification of functional near infrared spectroscopy to assess cortical reorganization in children with cerebral palsy,” Opt. Express18(25), 25973–25986 (2010).
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S. P. Koch, C. Habermehl, J. Mehnert, C. H. Schmitz, S. Holtze, A. Villringer, J. Steinbrink, and H. Obrig, “High-resolution optical functional mapping of the human somatosensory cortex,” Front Neuroenergetics2, 12 (2010).
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T. Suto, M. Fukuda, M. Ito, T. Uehara, and M. Mikuni, “Multichannel near-infrared spectroscopy in depression and schizophrenia: cognitive brain activation study,” Biol. Psychiatry55(5), 501–511 (2004).
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C. Terborg, K. Gröschel, A. Petrovitch, T. Ringer, S. Schnaudigel, O. W. Witte, and A. Kastrup, “Noninvasive assessment of cerebral perfusion and oxygenation in acute ischemic stroke by near-infrared spectroscopy,” Eur. Neurol.62(6), 338–343 (2009).
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B. Khan, C. Wildey, R. Francis, F. Tian, M. I. Romero, M. R. Delgado, N. J. Clegg, L. Smith, H. Liu, D. L. MacFarlane, and G. Alexandrakis, “Functional near infrared brain imaging with a brush-fiber optode to improve optical contact on subjects with dense hair,” Proc. SPIE7883, 78834V (2011).
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T. Suto, M. Fukuda, M. Ito, T. Uehara, and M. Mikuni, “Multichannel near-infrared spectroscopy in depression and schizophrenia: cognitive brain activation study,” Biol. Psychiatry55(5), 501–511 (2004).
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C. Terborg, K. Gröschel, A. Petrovitch, T. Ringer, S. Schnaudigel, O. W. Witte, and A. Kastrup, “Noninvasive assessment of cerebral perfusion and oxygenation in acute ischemic stroke by near-infrared spectroscopy,” Eur. Neurol.62(6), 338–343 (2009).
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G. Morren, U. Wolf, P. Lemmerling, M. Wolf, J. H. Choi, E. Gratton, L. De Lathauwer, and S. Van Huffel, “Detection of fast neuronal signals in the motor cortex from functional near infrared spectroscopy measurements using independent component analysis,” Med. Biol. Eng. Comput.42(1), 92–99 (2004).
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Q. Zhang, X. Yan, and G. E. Strangman, “Development of motion resistant instrumentation for ambulatory near-infrared spectroscopy,” J. Biomed. Opt.16(8), 087008 (2011).
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F. Orihuela-Espina, D. R. Leff, D. R. James, A. W. Darzi, and G. Z. Yang, “Quality control and assurance in functional near infrared spectroscopy (fNIRS) experimentation,” Phys. Med. Biol.55(13), 3701–3724 (2010).
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X. Bai, Z. Liu, N. Zhang, W. Chen, and B. He, “Three-dimensional source imaging from simultaneously recorded ERP and BOLD-fMRI,” IEEE Trans. Neural Syst. Rehabil. Eng.17(2), 101–106 (2009).
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Appl. Opt.

Biol. Psychiatry

T. Suto, M. Fukuda, M. Ito, T. Uehara, and M. Mikuni, “Multichannel near-infrared spectroscopy in depression and schizophrenia: cognitive brain activation study,” Biol. Psychiatry55(5), 501–511 (2004).
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Biomed. Opt. Express

Brain Res.

M. Kubota, M. Inouchi, I. Dan, D. Tsuzuki, A. Ishikawa, and T. Scovel, “Fast (100-175 ms) components elicited bilaterally by language production as measured by three-wavelength optical imaging,” Brain Res.1226, 124–133 (2008).
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Cardiovasc. Res.

C. Julien, “The enigma of Mayer waves: Facts and models,” Cardiovasc. Res.70(1), 12–21 (2006).
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Cephalalgia

H. W. Schytz, K. Ciftçi, A. Akin, M. Ashina, and H. Bolay, “Intact neurovascular coupling during executive function in migraine without aura: interictal near-infrared spectroscopy study,” Cephalalgia30(4), 457–466 (2010).
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Comput. Med. Imaging Graph.

K. Li, L. Guo, J. Nie, G. Li, and T. Liu, “Review of methods for functional brain connectivity detection using fMRI,” Comput. Med. Imaging Graph.33(2), 131–139 (2009).
[CrossRef] [PubMed]

Dermatol. Surg.

F. Jimenez, A. Izeta, and E. Poblet, “Morphometric analysis of the human scalp hair follicle: practical implications for the hair transplant surgeon and hair regeneration studies,” Dermatol. Surg.37(1), 58–64 (2011).
[CrossRef] [PubMed]

Eur. Neurol.

C. Terborg, K. Gröschel, A. Petrovitch, T. Ringer, S. Schnaudigel, O. W. Witte, and A. Kastrup, “Noninvasive assessment of cerebral perfusion and oxygenation in acute ischemic stroke by near-infrared spectroscopy,” Eur. Neurol.62(6), 338–343 (2009).
[CrossRef] [PubMed]

Front Neuroenergetics

S. P. Koch, C. Habermehl, J. Mehnert, C. H. Schmitz, S. Holtze, A. Villringer, J. Steinbrink, and H. Obrig, “High-resolution optical functional mapping of the human somatosensory cortex,” Front Neuroenergetics2, 12 (2010).
[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 Neuroenergetics2, 0000–9999 (2010).
[PubMed]

IEEE J. Quantum Electron.

W. F. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical properties of biological tissues,” IEEE J. Quantum Electron.26(12), 2166–2185 (1990).
[CrossRef]

IEEE Trans. Biomed. Eng.

M. Izzetoglu, A. Devaraj, S. Bunce, and B. Onaral, “Motion artifact cancellation in NIR spectroscopy using Wiener filtering,” IEEE Trans. Biomed. Eng.52(5), 934–938 (2005).
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IEEE Trans. Neural Syst. Rehabil. Eng.

X. Bai, Z. Liu, N. Zhang, W. Chen, and B. He, “Three-dimensional source imaging from simultaneously recorded ERP and BOLD-fMRI,” IEEE Trans. Neural Syst. Rehabil. Eng.17(2), 101–106 (2009).
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Figures (11)

Fig. 1
Fig. 1

Pictures of the brush-fiber optode showing (a) the brush-fiber end to be placed on an individual’s head, (b) how the brush optode fibers could thread through hair to attain improved optical contact, and (c) the distal end of the brush optode that was designed to attach onto the commercial system’s flat-ended fiber bundles.

Fig. 2
Fig. 2

Probe configuration setup on a human subject. The Cz position according to the EEG International 10/20 system and its relation to the location of the probe configuration is shown. The filled ‘X’ symbols identify the locations of detectors, and the filled circles identify the locations of sources.

Fig. 3
Fig. 3

Schematics of (a) the overall MC simulation setup, and (b) a zoomed-in view of the hair layers, hair follicles, and the placement of a couple of brush fibers among the 64 brush fibers used in the simulations. In (a), the red solid lines are the simulated rays inside the scalp tissue (10 x 10 x 4 mm3), becoming red dashed lines once they left the scalp tissue. In (b), the short light blue cylinder indicates a brush fiber blocked by hair, and the long light blue cylinder a brush fiber that had good optical contact with the scalp.

Fig. 4
Fig. 4

A comparison of ΔHbO and ΔHb (a) SNR, (b) CBR, and (c) dAoA between flat and brush optode sets. The single (p<0.05), double (p < 0.005), and triple (p < 0.0005) asterisks identify the significance in activation metric mean difference between the flat and brush optode measurements.

Fig. 5
Fig. 5

(a) A scatter plot comparing the activation SNR (dB) of the flat optodes (x-axis) versus that of the brush-fiber optodes (y-axis). The blue circles (short hair subjects) and red circles (long hair subjects) are SNR data points, the red-dashed line indicates the line of equality between the two SNRs, and the red-solid line shows a linear fit through the data. ∆HbO averaged time-plots are shown for (b) a bald subject (0 hairs/mm2) and (c) a subject with 2.8 hairs/mm2.

Fig. 6
Fig. 6

ΔHbO activation images (µMolar scale) for the same subject (black hair at a density of 2.2 hairs/mm2) using (a) the flat optodes and (b) the brush optodes. The sources (grey filled circles) and detectors (grey filled Xs) are used to show the source and detector locations. (c) In regions where activation could be detected by both the flat and brush optodes, the latter resulted in significantly higher SNR (shown in dB). There were also locations where the flat optodes detected no significant activation where the brush optodes did (d).

Fig. 7
Fig. 7

ΔHbO activation images, with color scales in µMolar, for four individual subjects with similar hair densities (~2.8 hairs/mm2) and hair lengths (20–23 mm), but different hair colors. Source positions are identified by the grey filled circles and the detector positions by the grey filled Xs.

Fig. 8
Fig. 8

Scatter plots comparing the ΔHbO trend in (a) SNR, (b) CBR, and (c) dAoA for all short hair subjects (n = 13) for both the flat optodes () and brush optodes (X). Similar plots were made for long hair subjects (n = 4) (d)-(f). The single (p<0.05), double (p < 0.005), and triple (p < 0.0005) asterisks identify the significance in activation metric mean difference between the flat and brush optode measurements.

Fig. 9
Fig. 9

ΔHbO activation images (color scales in µMolar) for four individual subjects with similar hair color (black), but different hair densities for both flat and brush optode sets. Source positions are identified by the grey filled circles and the detector positions by the grey filled Xs.

Fig. 10
Fig. 10

Scatter plot comparing the ΔHbO trend in (a) SNR, (b) CBR, and (c) dAoA for short hair subjects of all hair colors (n = 13) for both the flat optodes (∆) and brush optodes (X). The single (p<0.05), double (p < 0.005), and triple (p < 0.0005) asterisks identify the significance in activation metric mean difference between the flat and brush optode measurements.

Fig. 11
Fig. 11

The percent power loss with respect to bald subjects when using either the flat or the brush optodes. Comparison of the experimental (Exp), MC simulated (MC), and analytical formula (AF) results is performed across hair densities for each hair color.

Tables (1)

Tables Icon

Table 1 The obstruction fraction (OF) of brush optodes, the volume fraction of the hair follicles in the scalp (VFHF) and of the hair layers between the scalp and the detector fiber (VFH), the linear hair density (Hmm) and number of hair layers (L), and the volume-averaged μa and μ's for the scalp and hair layers as a function of hair root density

Equations (5)

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SN R s,d =10×log( P s,d / P d )
SNR=10×log( β / σ )
CBR=( μ A μ B )/ σ B
D Eff =1 z z 2 + r 2
OF= H R mm × D H π ( D d /2)

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