Abstract

Functional near infrared (fNIR) imaging was used to identify spatiotemporal relations between spatially distinct cortical regions activated during various hand and arm motion protocols. Imaging was performed over a field of view (FOV, 12 x 8.4 cm) including the secondary motor, primary sensorimotor, and the posterior parietal cortices over a single brain hemisphere. This is a more extended FOV than typically used in current fNIR studies. Three subjects performed four motor tasks that induced activation over this extended FOV. The tasks included card flipping (pronation and supination) that, to our knowledge, has not been performed in previous functional magnetic resonance imaging (fMRI) or fNIR studies. An earlier rise and a longer duration of the hemodynamic activation response were found in tasks requiring increased physical or mental effort. Additionally, analysis of activation images by cluster component analysis (CCA) demonstrated that cortical regions can be grouped into clusters, which can be adjacent or distant from each other, that have similar temporal activation patterns depending on whether the performed motor task is guided by visual or tactile feedback. These analyses highlight the future potential of fNIR imaging to tackle clinically relevant questions regarding the spatiotemporal relations between different sensorimotor cortex regions, e.g. ones involved in the rehabilitation response to motor impairments.

© 2011 OSA

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2011

L. Holper, F. Scholkmann, D. E. Shalóm, and M. Wolf, “Extension of mental preparation positively affects motor imagery as compared to motor execution: A functional near-infrared spectroscopy study,” Cortex (2011).
[CrossRef] [PubMed]

M. S. Khorrami, S. H. Faro, A. Seshadri, S. Moonat, J. Lidicker, B. L. Hershey, and F. B. Mohamed, “Functional MRI of sensory motor cortex: comparison between finger-to-thumb and hand squeeze tasks,” J. Neuroimaging21(3), 236–240 (2011).
[CrossRef] [PubMed]

M. J. Donahue, H. Hoogduin, S. M. Smith, J. C. Siero, M. Chappell, N. Petridou, P. Jezzard, P. R. Luijten, and J. Hendrikse, “Spontaneous blood oxygenation level-dependent fMRI signal is modulated by behavioral state and correlates with evoked response in sensorimotor cortex: A 7.0-T fMRI study,” Hum. Brain Mapp.n/a (2011).
[CrossRef] [PubMed]

E. A. Stringer, L. M. Chen, R. M. Friedman, C. Gatenby, and J. C. Gore, “Differentiation of somatosensory cortices by high-resolution fMRI at 7 T,” Neuroimage54(2), 1012–1020 (2011).
[CrossRef] [PubMed]

2010

V. E. Gountouna, D. E. Job, A. M. McIntosh, T. W. Moorhead, G. K. Lymer, H. C. Whalley, J. Hall, G. D. Waiter, D. Brennan, D. J. McGonigle, T. S. Ahearn, J. Cavanagh, B. Condon, D. M. Hadley, I. Marshall, A. D. Murray, J. D. Steele, J. M. Wardlaw, and S. M. Lawrie, “Functional Magnetic Resonance Imaging (fMRI) reproducibility and variance components across visits and scanning sites with a finger tapping task,” Neuroimage49(1), 552–560 (2010).
[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. Express1(1), 324–336 (2010).
[CrossRef] [PubMed]

E. Azañón, M. R. Longo, S. Soto-Faraco, and P. Haggard, “The posterior parietal cortex remaps touch into external space,” Curr. Biol.20(14), 1304–1309 (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]

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] [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]

J. B. Zeller, M. J. Herrmann, A. C. Ehlis, T. Polak, and A. J. Fallgatter, “Altered parietal brain oxygenation in Alzheimer’s disease as assessed with near-infrared spectroscopy,” Am. J. Geriatr. Psychiatry18(5), 433–441 (2010).
[CrossRef] [PubMed]

2009

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]

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]

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?” Neuroimage45(3), 788–794 (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]

L. Holper, M. Biallas, and M. Wolf, “Task complexity relates to activation of cortical motor areas during uni- and bimanual performance: a functional NIRS study,” Neuroimage46(4), 1105–1113 (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]

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]

2008

J. P. Kuhtz-Buschbeck, R. Gilster, S. Wolff, S. Ulmer, H. Siebner, and O. Jansen, “Brain activity is similar during precision and power gripping with light force: an fMRI study,” Neuroimage40(4), 1469–1481 (2008).
[CrossRef] [PubMed]

T. Ikegami and G. Taga, “Decrease in cortical activation during learning of a multi-joint discrete motor task,” Exp. Brain Res.191(2), 221–236 (2008).
[CrossRef] [PubMed]

H. Ohta, B. Yamagata, H. Tomioka, T. Takahashi, M. Yano, K. Nakagome, and M. Mimura, “Hypofrontality in panic disorder and major depressive disorder assessed by multi-channel near-infrared spectroscopy,” Depress. Anxiety25(12), 1053–1059 (2008).
[CrossRef] [PubMed]

2007

K. Takeda, Y. Gomi, I. Imai, N. Shimoda, M. Hiwatari, and H. Kato, “Shift of motor activation areas during recovery from hemiparesis after cerebral infarction: a longitudinal study with near-infrared spectroscopy,” Neurosci. Res.59(2), 136–144 (2007).
[CrossRef] [PubMed]

C. H. Juenger, M. Linder-Lucht, M. Wilke, S. Berweck, V. Mall, and M. Staudt, “Neuromodulation by constraint-induced movement therapy (CIMT) in congenital hemiparesis: an fMRI study,” Eur. J. Pediatr.166, 280–9999 (2007).

H. Juenger, M. Linder-Lucht, M. Walther, S. Berweck, V. Mall, and M. Staudt, “Cortical neuromodulation by constraint-induced movement therapy in congenital hemiparesis: an FMRI study,” Neuropediatrics38(3), 130–136 (2007).
[CrossRef] [PubMed]

M. Hatakenaka, I. Miyai, M. Mihara, S. Sakoda, and K. Kubota, “Frontal regions involved in learning of motor skill--A functional NIRS study,” Neuroimage34(1), 109–116 (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]

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]

Y. Xu, H. L. Graber, and R. L. Barbour, “Image correction algorithm for functional three-dimensional diffuse optical tomography brain imaging,” Appl. Opt.46(10), 1693–1704 (2007).
[CrossRef] [PubMed]

2006

A. K. Singh and I. Dan, “Exploring the false discovery rate in multichannel NIRS,” Neuroimage33(2), 542–549 (2006).
[CrossRef] [PubMed]

C. Julien, “The enigma of Mayer waves: Facts and models,” Cardiovasc. Res.70(1), 12–21 (2006).
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2005

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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2002

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2001

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2000

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1999

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1997

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1996

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1995

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1992

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1991

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Barbour, R. L.

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M. Lepage, G. Beaudoin, C. Boulet, I. O’Brien, W. Marcantoni, P. Bourgouin, and F. Richer, “Frontal cortex and the programming of repetitive tapping movements in man: lesion effects and functional neuroimaging,” Brain Res. Cogn. Brain Res.8(1), 17–25 (1999).
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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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Berbaum, K. S.

D. D. Dorfman, K. S. Berbaum, and C. E. Metz, “Receiver operating characteristic rating analysis. Generalization to the population of readers and patients with the jackknife method,” Invest. Radiol.27(9), 723–731 (1992).
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R. C. Mesquita, M. A. Franceschini, and D. A. Boas, “Resting state functional connectivity of the whole head with near-infrared spectroscopy,” Biomed. Opt. Express1(1), 324–336 (2010).
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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).
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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).
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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).
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D. A. Boas, A. M. Dale, and M. A. Franceschini, “Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution, and accuracy,” Neuroimage23(Suppl 1), S275–S288 (2004).
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M. A. Franceschini, S. Fantini, J. H. Thompson, J. P. Culver, and D. A. Boas, “Hemodynamic evoked response of the sensorimotor cortex measured noninvasively with near-infrared optical imaging,” Psychophysiology40(4), 548–560 (2003).
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G. Strangman, J. P. Culver, J. H. Thompson, and D. A. Boas, “A quantitative comparison of simultaneous BOLD fMRI and NIRS recordings during functional brain activation,” Neuroimage17(2), 719–731 (2002).
[CrossRef] [PubMed]

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M. Lepage, G. Beaudoin, C. Boulet, I. O’Brien, W. Marcantoni, P. Bourgouin, and F. Richer, “Frontal cortex and the programming of repetitive tapping movements in man: lesion effects and functional neuroimaging,” Brain Res. Cogn. Brain Res.8(1), 17–25 (1999).
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Bouman, C. A.

S. Chen, C. A. Bouman, and M. J. Lowe, “Clustered components analysis for functional MRI,” IEEE Trans. Med. Imaging23(1), 85–98 (2004).
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Bourgouin, P.

M. Lepage, G. Beaudoin, C. Boulet, I. O’Brien, W. Marcantoni, P. Bourgouin, and F. Richer, “Frontal cortex and the programming of repetitive tapping movements in man: lesion effects and functional neuroimaging,” Brain Res. Cogn. Brain Res.8(1), 17–25 (1999).
[CrossRef] [PubMed]

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F. Bremmer, A. Schlack, N. J. Shah, O. Zafiris, M. Kubischik, K. Hoffmann, K. Zilles, and G. R. Fink, “Polymodal motion processing in posterior parietal and premotor cortex: a human fMRI study strongly implies equivalencies between humans and monkeys,” Neuron29(1), 287–296 (2001).
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V. E. Gountouna, D. E. Job, A. M. McIntosh, T. W. Moorhead, G. K. Lymer, H. C. Whalley, J. Hall, G. D. Waiter, D. Brennan, D. J. McGonigle, T. S. Ahearn, J. Cavanagh, B. Condon, D. M. Hadley, I. Marshall, A. D. Murray, J. D. Steele, J. M. Wardlaw, and S. M. Lawrie, “Functional Magnetic Resonance Imaging (fMRI) reproducibility and variance components across visits and scanning sites with a finger tapping task,” Neuroimage49(1), 552–560 (2010).
[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).
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Brooksby, B.

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).
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Bunce, S.

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]

K. Izzetoglu, S. Bunce, M. Izzetoglu, B. Onaral, and K. Pourrezaei, “Functional near-infrared neuroimaging,” Conf. Proc. IEEE Eng. Med. Biol. Soc.7, 5333–5336 (2004).
[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]

Burns, D. H.

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).
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H. Burton, N. S. Abend, A. M. MacLeod, R. J. Sinclair, A. Z. Snyder, and M. E. Raichle, “Tactile attention tasks enhance activation in somatosensory regions of parietal cortex: a positron emission tomography study,” Cereb. Cortex9(7), 662–674 (1999).
[CrossRef] [PubMed]

Cavanagh, J.

V. E. Gountouna, D. E. Job, A. M. McIntosh, T. W. Moorhead, G. K. Lymer, H. C. Whalley, J. Hall, G. D. Waiter, D. Brennan, D. J. McGonigle, T. S. Ahearn, J. Cavanagh, B. Condon, D. M. Hadley, I. Marshall, A. D. Murray, J. D. Steele, J. M. Wardlaw, and S. M. Lawrie, “Functional Magnetic Resonance Imaging (fMRI) reproducibility and variance components across visits and scanning sites with a finger tapping task,” Neuroimage49(1), 552–560 (2010).
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Chappell, M.

M. J. Donahue, H. Hoogduin, S. M. Smith, J. C. Siero, M. Chappell, N. Petridou, P. Jezzard, P. R. Luijten, and J. Hendrikse, “Spontaneous blood oxygenation level-dependent fMRI signal is modulated by behavioral state and correlates with evoked response in sensorimotor cortex: A 7.0-T fMRI study,” Hum. Brain Mapp.n/a (2011).
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E. A. Stringer, L. M. Chen, R. M. Friedman, C. Gatenby, and J. C. Gore, “Differentiation of somatosensory cortices by high-resolution fMRI at 7 T,” Neuroimage54(2), 1012–1020 (2011).
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Chen, S.

S. Chen, C. A. Bouman, and M. J. Lowe, “Clustered components analysis for functional MRI,” IEEE Trans. Med. Imaging23(1), 85–98 (2004).
[CrossRef] [PubMed]

Chertkow, H. M.

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]

Choi, J. H.

G. Morren, M. Wolf, P. Lemmerling, U. 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]

Clegg, N. J.

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]

Condon, B.

V. E. Gountouna, D. E. Job, A. M. McIntosh, T. W. Moorhead, G. K. Lymer, H. C. Whalley, J. Hall, G. D. Waiter, D. Brennan, D. J. McGonigle, T. S. Ahearn, J. Cavanagh, B. Condon, D. M. Hadley, I. Marshall, A. D. Murray, J. D. Steele, J. M. Wardlaw, and S. M. Lawrie, “Functional Magnetic Resonance Imaging (fMRI) reproducibility and variance components across visits and scanning sites with a finger tapping task,” Neuroimage49(1), 552–560 (2010).
[CrossRef] [PubMed]

Culver, J. P.

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]

M. A. Franceschini, S. Fantini, J. H. Thompson, J. P. Culver, and D. A. Boas, “Hemodynamic evoked response of the sensorimotor cortex measured noninvasively with near-infrared optical imaging,” Psychophysiology40(4), 548–560 (2003).
[CrossRef] [PubMed]

G. Strangman, J. P. Culver, J. H. Thompson, and D. A. Boas, “A quantitative comparison of simultaneous BOLD fMRI and NIRS recordings during functional brain activation,” Neuroimage17(2), 719–731 (2002).
[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,” Neuroimage23(Suppl 1), S275–S288 (2004).
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A. K. Singh and I. Dan, “Exploring the false discovery rate in multichannel NIRS,” Neuroimage33(2), 542–549 (2006).
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G. Morren, M. Wolf, P. Lemmerling, U. 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]

Dehghani, H.

Deiber, M. P.

M. P. Deiber, V. Ibañez, N. Sadato, and M. Hallett, “Cerebral structures participating in motor preparation in humans: a positron emission tomography study,” J. Neurophysiol.75(1), 233–247 (1996).
[PubMed]

Delgado, M. R.

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]

Dettmers, C.

F. Hamzei, J. Liepert, C. Dettmers, C. Weiller, and M. Rijntjes, “Two different reorganization patterns after rehabilitative therapy: an exploratory study with fMRI and TMS,” Neuroimage31(2), 710–720 (2006).
[CrossRef] [PubMed]

Devaraj, A.

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]

Devlin, J. T.

M. F. Rushworth, H. Johansen-Berg, S. M. Göbel, and J. T. Devlin, “The left parietal and premotor cortices: motor attention and selection,” Neuroimage20(Suppl 1), S89–S100 (2003).
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M. S. Khorrami, S. H. Faro, A. Seshadri, S. Moonat, J. Lidicker, B. L. Hershey, and F. B. Mohamed, “Functional MRI of sensory motor cortex: comparison between finger-to-thumb and hand squeeze tasks,” J. Neuroimaging21(3), 236–240 (2011).
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H. Sato, Y. Fuchino, M. Kiguchi, T. Katura, A. Maki, T. Yoro, and H. Koizumi, “Intersubject variability of near-infrared spectroscopy signals during sensorimotor cortex activation,” J. Biomed. Opt.10(4), 044001 (2005).
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M. Hatakenaka, I. Miyai, M. Mihara, S. Sakoda, and K. Kubota, “Frontal regions involved in learning of motor skill--A functional NIRS study,” Neuroimage34(1), 109–116 (2007).
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M. Lepage, G. Beaudoin, C. Boulet, I. O’Brien, W. Marcantoni, P. Bourgouin, and F. Richer, “Frontal cortex and the programming of repetitive tapping movements in man: lesion effects and functional neuroimaging,” Brain Res. Cogn. Brain Res.8(1), 17–25 (1999).
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M. S. Khorrami, S. H. Faro, A. Seshadri, S. Moonat, J. Lidicker, B. L. Hershey, and F. B. Mohamed, “Functional MRI of sensory motor cortex: comparison between finger-to-thumb and hand squeeze tasks,” J. Neuroimaging21(3), 236–240 (2011).
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F. Hamzei, J. Liepert, C. Dettmers, C. Weiller, and M. Rijntjes, “Two different reorganization patterns after rehabilitative therapy: an exploratory study with fMRI and TMS,” Neuroimage31(2), 710–720 (2006).
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H. Juenger, M. Linder-Lucht, M. Walther, S. Berweck, V. Mall, and M. Staudt, “Cortical neuromodulation by constraint-induced movement therapy in congenital hemiparesis: an FMRI study,” Neuropediatrics38(3), 130–136 (2007).
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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).
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H. Juenger, M. Linder-Lucht, M. Walther, S. Berweck, V. Mall, and M. Staudt, “Cortical neuromodulation by constraint-induced movement therapy in congenital hemiparesis: an FMRI study,” Neuropediatrics38(3), 130–136 (2007).
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Marcantoni, W.

M. Lepage, G. Beaudoin, C. Boulet, I. O’Brien, W. Marcantoni, P. Bourgouin, and F. Richer, “Frontal cortex and the programming of repetitive tapping movements in man: lesion effects and functional neuroimaging,” Brain Res. Cogn. Brain Res.8(1), 17–25 (1999).
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S. Van Oostende, P. Van Hecke, S. Sunaert, B. Nuttin, and G. Marchal, “FMRI studies of the supplementary motor area and the premotor cortex,” Neuroimage6(3), 181–190 (1997).
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V. E. Gountouna, D. E. Job, A. M. McIntosh, T. W. Moorhead, G. K. Lymer, H. C. Whalley, J. Hall, G. D. Waiter, D. Brennan, D. J. McGonigle, T. S. Ahearn, J. Cavanagh, B. Condon, D. M. Hadley, I. Marshall, A. D. Murray, J. D. Steele, J. M. Wardlaw, and S. M. Lawrie, “Functional Magnetic Resonance Imaging (fMRI) reproducibility and variance components across visits and scanning sites with a finger tapping task,” Neuroimage49(1), 552–560 (2010).
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A. Maki, Y. Yamashita, Y. Ito, E. Watanabe, Y. Mayanagi, and H. Koizumi, “Spatial and temporal analysis of human motor activity using noninvasive NIR topography,” Med. Phys.22(12), 1997–2005 (1995).
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V. E. Gountouna, D. E. Job, A. M. McIntosh, T. W. Moorhead, G. K. Lymer, H. C. Whalley, J. Hall, G. D. Waiter, D. Brennan, D. J. McGonigle, T. S. Ahearn, J. Cavanagh, B. Condon, D. M. Hadley, I. Marshall, A. D. Murray, J. D. Steele, J. M. Wardlaw, and S. M. Lawrie, “Functional Magnetic Resonance Imaging (fMRI) reproducibility and variance components across visits and scanning sites with a finger tapping task,” Neuroimage49(1), 552–560 (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).
[PubMed]

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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).
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M. Hatakenaka, I. Miyai, M. Mihara, S. Sakoda, and K. Kubota, “Frontal regions involved in learning of motor skill--A functional NIRS study,” Neuroimage34(1), 109–116 (2007).
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Miller, E. L.

Mimura, M.

H. Ohta, B. Yamagata, H. Tomioka, T. Takahashi, M. Yano, K. Nakagome, and M. Mimura, “Hypofrontality in panic disorder and major depressive disorder assessed by multi-channel near-infrared spectroscopy,” Depress. Anxiety25(12), 1053–1059 (2008).
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Miyai, I.

M. Hatakenaka, I. Miyai, M. Mihara, S. Sakoda, and K. Kubota, “Frontal regions involved in learning of motor skill--A functional NIRS study,” Neuroimage34(1), 109–116 (2007).
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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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I. Miyai, H. Yagura, I. Oda, I. Konishi, H. Eda, T. Suzuki, and K. Kubota, “Premotor cortex is involved in restoration of gait in stroke,” Ann. Neurol.52(2), 188–194 (2002).
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M. S. Khorrami, S. H. Faro, A. Seshadri, S. Moonat, J. Lidicker, B. L. Hershey, and F. B. Mohamed, “Functional MRI of sensory motor cortex: comparison between finger-to-thumb and hand squeeze tasks,” J. Neuroimaging21(3), 236–240 (2011).
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M. S. Khorrami, S. H. Faro, A. Seshadri, S. Moonat, J. Lidicker, B. L. Hershey, and F. B. Mohamed, “Functional MRI of sensory motor cortex: comparison between finger-to-thumb and hand squeeze tasks,” J. Neuroimaging21(3), 236–240 (2011).
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V. E. Gountouna, D. E. Job, A. M. McIntosh, T. W. Moorhead, G. K. Lymer, H. C. Whalley, J. Hall, G. D. Waiter, D. Brennan, D. J. McGonigle, T. S. Ahearn, J. Cavanagh, B. Condon, D. M. Hadley, I. Marshall, A. D. Murray, J. D. Steele, J. M. Wardlaw, and S. M. Lawrie, “Functional Magnetic Resonance Imaging (fMRI) reproducibility and variance components across visits and scanning sites with a finger tapping task,” Neuroimage49(1), 552–560 (2010).
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G. Morren, M. Wolf, P. Lemmerling, U. 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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V. B. Mountcastle, J. C. Lynch, A. Georgopoulos, H. Sakata, and C. Acuna, “Posterior parietal association cortex of the monkey: command functions for operations within extrapersonal space,” J. Neurophysiol.38(4), 871–908 (1975).
[PubMed]

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V. E. Gountouna, D. E. Job, A. M. McIntosh, T. W. Moorhead, G. K. Lymer, H. C. Whalley, J. Hall, G. D. Waiter, D. Brennan, D. J. McGonigle, T. S. Ahearn, J. Cavanagh, B. Condon, D. M. Hadley, I. Marshall, A. D. Murray, J. D. Steele, J. M. Wardlaw, and S. M. Lawrie, “Functional Magnetic Resonance Imaging (fMRI) reproducibility and variance components across visits and scanning sites with a finger tapping task,” Neuroimage49(1), 552–560 (2010).
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H. Ohta, B. Yamagata, H. Tomioka, T. Takahashi, M. Yano, K. Nakagome, and M. Mimura, “Hypofrontality in panic disorder and major depressive disorder assessed by multi-channel near-infrared spectroscopy,” Depress. Anxiety25(12), 1053–1059 (2008).
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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).
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S. Van Oostende, P. Van Hecke, S. Sunaert, B. Nuttin, and G. Marchal, “FMRI studies of the supplementary motor area and the premotor cortex,” Neuroimage6(3), 181–190 (1997).
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M. Lepage, G. Beaudoin, C. Boulet, I. O’Brien, W. Marcantoni, P. Bourgouin, and F. Richer, “Frontal cortex and the programming of repetitive tapping movements in man: lesion effects and functional neuroimaging,” Brain Res. Cogn. Brain Res.8(1), 17–25 (1999).
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Obrig, H.

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]

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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]

I. Miyai, H. Yagura, I. Oda, I. Konishi, H. Eda, T. Suzuki, and K. Kubota, “Premotor cortex is involved in restoration of gait in stroke,” Ann. Neurol.52(2), 188–194 (2002).
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H. Ohta, B. Yamagata, H. Tomioka, T. Takahashi, M. Yano, K. Nakagome, and M. Mimura, “Hypofrontality in panic disorder and major depressive disorder assessed by multi-channel near-infrared spectroscopy,” Depress. Anxiety25(12), 1053–1059 (2008).
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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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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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K. Izzetoglu, S. Bunce, M. Izzetoglu, B. Onaral, and K. Pourrezaei, “Functional near-infrared neuroimaging,” Conf. Proc. IEEE Eng. Med. Biol. Soc.7, 5333–5336 (2004).
[PubMed]

Paulsen, K. D.

Petridou, N.

M. J. Donahue, H. Hoogduin, S. M. Smith, J. C. Siero, M. Chappell, N. Petridou, P. Jezzard, P. R. Luijten, and J. Hendrikse, “Spontaneous blood oxygenation level-dependent fMRI signal is modulated by behavioral state and correlates with evoked response in sensorimotor cortex: A 7.0-T fMRI study,” Hum. Brain Mapp.n/a (2011).
[CrossRef] [PubMed]

Petrovitch, A.

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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Polak, T.

J. B. Zeller, M. J. Herrmann, A. C. Ehlis, T. Polak, and A. J. Fallgatter, “Altered parietal brain oxygenation in Alzheimer’s disease as assessed with near-infrared spectroscopy,” Am. J. Geriatr. Psychiatry18(5), 433–441 (2010).
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Pourrezaei, 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).
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K. Izzetoglu, S. Bunce, M. Izzetoglu, B. Onaral, and K. Pourrezaei, “Functional near-infrared neuroimaging,” Conf. Proc. IEEE Eng. Med. Biol. Soc.7, 5333–5336 (2004).
[PubMed]

Raichle, M. E.

H. Burton, N. S. Abend, A. M. MacLeod, R. J. Sinclair, A. Z. Snyder, and M. E. Raichle, “Tactile attention tasks enhance activation in somatosensory regions of parietal cortex: a positron emission tomography study,” Cereb. Cortex9(7), 662–674 (1999).
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G. Strangman, R. Goldstein, S. L. Rauch, and J. Stein, “Near-infrared spectroscopy and imaging for investigating stroke rehabilitation: test-retest reliability and review of the literature,” Arch. Phys. Med. Rehabil.87(12Suppl 2), 12–19 (2006).
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Reid, D.

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]

Richer, F.

M. Lepage, G. Beaudoin, C. Boulet, I. O’Brien, W. Marcantoni, P. Bourgouin, and F. Richer, “Frontal cortex and the programming of repetitive tapping movements in man: lesion effects and functional neuroimaging,” Brain Res. Cogn. Brain Res.8(1), 17–25 (1999).
[CrossRef] [PubMed]

Rijntjes, M.

F. Hamzei, J. Liepert, C. Dettmers, C. Weiller, and M. Rijntjes, “Two different reorganization patterns after rehabilitative therapy: an exploratory study with fMRI and TMS,” Neuroimage31(2), 710–720 (2006).
[CrossRef] [PubMed]

Ringer, T.

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]

Robertson, F. C.

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).
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Figures (7)

Fig. 1
Fig. 1

(a) The stand constructed to relieve the subjects from supporting the entire weight of the fibers. In addition, a soft yet sturdy holder was made to hold the fibers in place on top of the subject’s head with good optical contact. (b) Bifurcated fiber bundle source-detector geometry where the ‘X’ symbols are detectors, and the ‘O’ symbols are sources, covering a 12 x 8.4 cm FOV. The encircled areas (black ovals) indicate the short distance source-detector pairs used to detect scalp hemodynamics.

Fig. 2
Fig. 2

(a) Flowchart of the algorithm used to remove source-detector pairs with low SNR due to poor optical contact. (b) In time-averaged activation images produced with data from the remaining source-detector pairs [panel (1)], pixel-wise T-tests were performed with corresponding baseline values to identify regions of activation [panel (2)]. Subsequently, source-detector pairs (connected solid circles) were clustered according to their similarity in temporal activation patterns [panel (3); S1/PPC – blue, M1/S1 – red]. Panel (4) shows cluster-averaged time-series data for activation in the M1/S1 region (red curve) and the S1/PPC region (blue curve).

Fig. 3
Fig. 3

HbO activation images, having color scales in µMolar, were time-averaged between 5 – 20 s for each task on both visits for all three subjects. The white dashed lines were used to approximately separate the PMC/SMA, M1, S1, and PPC cortical regions, as identified on the far right edge of the figure.

Fig. 4
Fig. 4

A time series of HbO activation images for Subject 1, having color scales in µMolar, were time-averaged for every 5 s block over a 30 s period of 15 s stimulation – 15 s rest for a single subject performing all five protocols The white, dashed lines were used to differentiate between the PMC/SMA, M1, S1, and PPC cortical regions, as identified on the far right edge of the figure.

Fig. 5
Fig. 5

T-maps and clustered source-detector maps for HbO (left columns) and Hb (right columns) for Subject 1 performing the finger tapping, sensory stimulation, and palm squeezing protocols (rows). The white dashed lines indicate approximate boundaries for the PMC/SMA, M1, S1, and PPC regions. The connected circles in the cluster maps indicate the source-detector pairs that CCA grouped in the same cluster as they had similar time-series activation profiles [Tapping: M1/S1 – red, S1/PPC – blue; Sensory Stimulation: S1/PPC – blue; Palm Squeezing: M1/S1 – red; S1/PPC – blue].

Fig. 6
Fig. 6

HbO T-maps and clustered source-detector maps for sequential finger tapping (left columns) and card flipping (right columns) for each Subject (rows). The white dashed lines indicate approximate boundaries for the PMC/SMA, M1, S1, and PPC regions. The connected circles in the cluster maps indicate the source-detector pairs that CCA grouped in the same cluster as they had similar time-series activation profiles [Sequential Tapping: M1 – red, S1/PPC and SMA/PMC – blue; Card Flipping: M1 and SMA/PMC – red, S1/PPC – blue].

Fig. 7
Fig. 7

Group analysis T-maps and the clustered fNIR signals for sequential tapping and card flipping. The white dashed lines were used to approximately separate the PMC/SMA, M1, S1, and PPC regions. The connected circles in the cluster maps indicate the source-detector pairs that CCA grouped in the same cluster as they had similar time-series activation profiles [Sequential Tapping: M1/S1 – red, S1/PPC and M1/PMC/SMA – blue; Card Flipping: M1/SMA/PMC – red, S1/PPC - blue.

Tables (2)

Tables Icon

Table 1 Summary of the HbO activated cortical regions and their TtPs for each protocol

Tables Icon

Table 2 Summary of the HbO activated cortical regions and their durations for each protocol

Equations (14)

Equations on this page are rendered with MathJax. Learn more.

SN R s,d =10×log( P s,d / P d )
CoM= X Y w x,y d x,y
y λ = A λ x λ
x λ = A λ T ( A λ T A λ +α s max I) 1 y λ = A inv,λ y λ
X λ = Y λ T A inv,λ T
X λ =(H θ λ  + v) A inv,λ T
θ λ  =  ( H T H ) 1 H T X λ A λ T
θ ~ λ = θ λ θ λ = ( H T H ) 1 H T v A inv,λ T A λ T
R sn,λ = 1 SD E[ θ λ θ λ T ]
R n,λ = 1 SD E[ θ ~ λ θ ~ λ T ]
R s,λ = R sn,λ R n,λ = U λ Λ λ U λ T
θ * λ = U λ T * θ λ
Δ[Hb] = (ε HbO λ2 ·Δ OD λ1 -ε HbO λ1 ·Δ OD λ2 ) / (L·(ε Hb λ1 ·ε HbO λ2 -ε Hb λ2 ·ε HbO λ1 ) )  
Δ[HbO] = (ε Hb λ2 ·Δ OD λ1 -ε Hb λ1 ·Δ OD λ2 ) / (L·(ε Hb λ2 ·ε HbO λ1 -ε Hb λ1 ·ε HbO λ2 ) )  

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