Abstract

Functional near-infrared spectroscopy (fNIRS) is a neuroimaging technique that measures changes in oxy-hemoglobin (ΔHbO) and deoxy-hemoglobin (ΔHbR) concentration associated with brain activity. The signal acquired with fNIRS is naturally affected by disturbances engendering from ongoing physiological activity (e.g., cardiac, respiratory, Mayer wave) and random measurement noise. Despite its several drawbacks, the so-called conventional averaging (CA) is still widely used to estimate the hemodynamic response function (HRF) from noisy signal. One such drawback is related to the number of trials necessary to derive stable HRF functions adopting the CA approach, which must be substantial (N >> 50). In this work, a pre-processing procedure to remove artifacts followed by the application of a non-parametric Bayesian approach is proposed that capitalizes on a priori available knowledge about HRF and noise. Results with the proposed Bayesian approach were compared with CA and with a straightforward band-pass filtering approach. On simulated data, a five times lower estimation error on HRF was obtained with respect to that obtained by CA, and 2.5 times lower than that obtained by band pass filtering. On real data, the improvement achieved by the present method was attested by an increase in the contrast to noise ratio (CNR) and by a reduced variability in single trial estimation. An application of the present Bayesian approach is illustrated that was optimized to monitor changes in hemodynamic activity reflecting variations in visual short-term memory load in humans, which are notoriously hard to detect using functional magnetic resonance imaging (fMRI). In particular, statistical analyses of HRFs recorded during a memory task established with high reliability the crucial role of the intraparietal sulcus and the intra-occipital sulcus in posterior areas of the human brain in visual short-term memory maintenance.

© 2010 OSA

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  1. D. A. Boas, M. A. Franceschini, A. K. Dunn, and G. Strangman, “Noninvasive Imaging of Cerebral Activation with Diffuse Optical Tomography,”in Vivo Optical Imaging of Brain Function. E. D. (CRC Press), Chap 8, pp. 193–221, (2002)
  2. 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]
  3. H. Obrig and A. Villringer, “Beyond the visible--imaging the human brain with light,” J. Cereb. Blood Flow Metab. 23(1), 1–18 (2003).
    [CrossRef]
  4. S. P. Koch, S. Koendgen, R. Bourayou, J. Steinbrink, and H. Obrig, “Individual alpha-frequency correlates with amplitude of visual evoked potential and hemodynamic response,” Neuroimage 41(2), 233–242 (2008).
    [CrossRef] [PubMed]
  5. R. J. Cooper, N. L. Everdell, L. C. Enfield, A. P. Gibson, A. Worley, and J. C. Hebden, “Design and evaluation of a probe for simultaneous EEG and near-infrared imaging of cortical activation,” Phys. Med. Biol. 54(7), 2093–2102 (2009).
    [CrossRef] [PubMed]
  6. A. Gibson and H. Dehghani, “Diffuse optical imaging,” Philos. Transact. A Math. Phys. Eng. Sci. 367(1900), 3055–3072 (2009).
    [CrossRef] [PubMed]
  7. G. Jasdzewski, G. Strangman, J. Wagner, K. K. Kwong, R. A. Poldrack, and D. A. Boas, “Differences in the hemodynamic response to event-related motor and visual paradigms as measured by near-infrared spectroscopy,” Neuroimage 20(1), 479–488 (2003).
    [CrossRef] [PubMed]
  8. S. G. Diamond, T. J. Huppert, V. Kolehmainen, M. A. Franceschini, J. P. Kaipio, S. R. Arridge, and D. A. Boas, “Dynamic physiological modeling for functional diffuse optical tomography,” Neuroimage 30(1), 88–101 (2006).
    [CrossRef]
  9. V. Kolehmainen, S. Prince, S. R. Arridge, and J. P. Kaipio, “State-estimation approach to the nonstationary optical tomography problem,” J. Opt. Soc. Am. A 20(5), 876–889 (2003).
    [CrossRef]
  10. S. Prince, V. Kolehmainen, J. P. Kaipio, M. A. Franceschini, D. A. Boas, and S. R. Arridge, “Time-series estimation of biological factors in optical diffusion tomography,” Phys. Med. Biol. 48(11), 1491–1504 (2003).
    [CrossRef] [PubMed]
  11. A. F. Abdelnour and T. J. Huppert, “Real-time imaging of human brain function by near-infrared spectroscopy using an adaptive general linear model,” Neuroimage 46(1), 133–143 (2009).
    [CrossRef] [PubMed]
  12. Y. H. Zhang, D. H. Brooks, M. A. Franceschini, and D. A. Boas, “Eigenvector-based spatial filtering for reduction of physiological interference in diffuse optical imaging,” J. Biomed. Opt. 10(1), 011014 (2005).
    [CrossRef]
  13. M. L. Schroeter, M. M. Bücheler, K. Müller, K. Uludağ, H. Obrig, G. Lohmann, M. Tittgemeyer, A. Villringer, and D. Y. von Cramon, “Towards a standard analysis for functional near-infrared imaging,” Neuroimage 21(1), 283–290 (2004).
    [CrossRef] [PubMed]
  14. S. Tak, K. E. Jang, J. W. Jung, J. Jang, and J. C. Ye, “General Linear Model and Inference for Near Infrared Spectroscopy using Global Confidence Region Analysis,” in Proceedings of IEEE Conference on International Symposium on Biomedical Imaging (ISBI), pp. 476–479 (2008).
  15. J. C. Ye, S. Tak, K. E. Jang, J. Jung, and J. Jang, “NIRS-SPM: statistical parametric mapping for near-infrared spectroscopy,” Neuroimage 44(2), 428–447 (2009).
    [CrossRef]
  16. K. E. Jang, S. Tak, J. Jung, J. Jang, Y. Jeong, and J. C. Ye, “Wavelet minimum description length detrending for near-infrared spectroscopy,” J. Biomedical Opt . 14, 034004-(1–13) (2009).
  17. 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]
  18. C. B. Akgül, A. Akin, and B. Sankur, “Extraction of cognitive activity-related waveforms from functional near-infrared spectroscopy signals,” Med. Biol. Eng. Comput. 44(11), 945–958 (2006).
    [CrossRef] [PubMed]
  19. A. V. Medvedev, J. Kainerstorfer, S. V. Borisov, R. L. Barbour, and J. VanMeter, “Event-related fast optical signal in a rapid object recognition task: improving detection by the independent component analysis,” Brain Res. 1236, 145–158 (2008).
    [CrossRef] [PubMed]
  20. 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. U.S.A. 100(19), 10722–10727 (2003).
    [CrossRef] [PubMed]
  21. R. Sitaram, H. Zhang, C. Guan, M. Thulasidas, Y. Hoshi, A. Ishikawa, K. Shimizu, and N. Birbaumer, “Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain-computer interface,” Neuroimage 34(4), 1416–1427 (2007).
    [CrossRef] [PubMed]
  22. S. Cutini, P. Scatturin, E. Menon, P. S. Bisiacchi, L. Gamberini, M. Zorzi, and R. Dell’Acqua, “Selective activation of the superior frontal gyrus in task-switching: an event-related fNIRS study,” Neuroimage 42(2), 945–955 (2008).
    [CrossRef] [PubMed]
  23. H. Kojima and T. Suzuki, “Hemodynamic change in occipital lobe during visual search: visual attention allocation measured with NIRS,” Neuropsychologia 48(1), 349–352 (2010).
    [CrossRef]
  24. G. Sparacino, S. Milani, E. Arslan, and C. Cobelli, “A Bayesian approach to estimate evoked potentials,” Comput. Methods Programs Biomed. 68(3), 233–248 (2002).
    [CrossRef] [PubMed]
  25. R. Luria, P. Sessa, A. Gotler, P. Jolicoeur, and R. Dell’Acqua, “Visual short-term memory capacity for simple and complex objects,” J. Cogn. Neurosci. 22(3), 496–512 (2010).
    [CrossRef]
  26. J. J. Todd and R. Marois, “Capacity limit of visual short-term memory in human posterior parietal cortex,” Nature 428(6984), 751–754 (2004).
    [CrossRef] [PubMed]
  27. Y. Xu and M. M. Chun, “Dissociable neural mechanisms supporting visual short-term memory for objects,” Nature 440(7080), 91–95 (2006).
    [CrossRef]
  28. M. Cope and D. T. Delpy, “System for long-term measurement of cerebral blood and tissue oxygenation on newborn infants by near infra-red transillumination,” Med. Biol. Eng. Comput. 26(3), 289–294 (1988).
    [CrossRef] [PubMed]
  29. M. L. Schroeter, S. Zysset, F. Kruggel, and D. Y. von Cramon, “Age dependency of the hemodynamic response as measured by functional near-infrared spectroscopy,” Neuroimage 19(3), 555–564 (2003).
    [CrossRef] [PubMed]
  30. M. L. Schroeter, S. Cutini, M. M. Wahl, R. Scheid, and D. Yves von Cramon, “Neurovascular coupling is impaired in cerebral microangiopathy--An event-related Stroop study,” Neuroimage 34(1), 26–34 (2007).
    [CrossRef]
  31. A. Duncan, J. H. Meek, M. Clemence, C. E. Elwell, P. Fallon, L. Tyszczuk, M. Cope, and D. T. Delpy, “Measurement of cranial optical path length as a function of age using phase resolved near infrared spectroscopy,” Pediatr. Res. 39(5), 889–894 (1996).
    [CrossRef] [PubMed]
  32. M. A. Franceschini, V. Toronov, M. E. Filiaci, E. Gratton, and S. Fantini, “On-line optical imaging of the human brain with 160-ms temporal resolution,” Opt. Express 6(3), 49–57 (2000).
    [CrossRef] [PubMed]
  33. M. Okamoto, H. Dan, K. Sakamoto, K. Takeo, K. Shimizu, S. Kohno, I. Oda, S. Isobe, T. Suzuki, K. Kohyama, and I. Dan, “Three-dimensional probabilistic anatomical cranio-cerebral correlation via the international 10-20 system oriented for transcranial functional brain mapping,” Neuroimage 21(1), 99–111 (2004).
    [CrossRef] [PubMed]
  34. S. Cutini, P. Scatturin, and M. Zorzi, “A new method based on ICBM152 head surface for probe placement in multichannel fNIRS,” Neuroimage (to be published).
    [PubMed]
  35. M. R. Nuwer, G. Comi, R. Emerson, A. Fuglsang-Frederiksen, J. M. Guérit, H. Hinrichs, A. Ikeda, F. J. Luccas, and P. Rappelsburger, The International Federation of Clinical Neurophysiology, “IFCN standards for digital recording of clinical EEG,” Electroencephalogr. Clin. Neurophysiol. 106(3), 259–261 (1998).
    [CrossRef] [PubMed]
  36. A. K. Singh, M. Okamoto, H. Dan, V. Jurcak, and I. Dan, “Spatial registration of multichannel multi-subject fNIRS data to MNI space without MRI,” Neuroimage 27(4), 842–851 (2005).
    [CrossRef] [PubMed]
  37. F. E. Grubbs, “Procedures for detecting outlying observations in samples,” Technometrics 11(1), 1–21 (1969).
    [CrossRef]
  38. A. Devaraj, “Signal Processing for functional near-infrared neuroimaging,” Unpublished M. S. Thesis, Drexel University, (2005).
  39. M. A. Lindquist and T. D. Wager, “Validity and power in hemodynamic response modeling: a comparison study and a new approach,” Hum. Brain Mapp. 28(8), 764–784 (2007).
    [CrossRef]
  40. Q. Zhang, G. E. Strangman, and G. Ganis, “Adaptive filtering to reduce global interference in non-invasive NIRS measures of brain activation: how well and when does it work?” Neuroimage 45(3), 788–794 (2009).
    [CrossRef] [PubMed]
  41. 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]
  42. S. M. Zeki, A vision of the brain, (Blackwell Scientific Publications, Oxford, UK, 1993).
  43. R. Dell’Acqua, P. Sessa, P. Toffanin, R. Luria, and P. Jolicoeur, “Orienting attention to objects in visual short-term memory,” Neuropsychologia 48(2), 419–428 (2010).
    [CrossRef]
  44. P. Jolicoeur, P. Sessa, R. Dell’Acqua, and N. Robitaille, “On the control of visual spatial attention: evidence from human electrophysiology,” Psychol. Res. 70(6), 414–424 (2006).
    [CrossRef]
  45. N. Robitaille, R. Marois, J. J. Todd, S. Grimault, D. Cheyne, and P. Jolicoeur, “Distinguishing between lateralized and nonlateralized brain activity associated with visual short-term memory: fMRI, MEG, and EEG evidence from the same observers,” Neuroimage 53(4), 1334–1345 (2010).
    [CrossRef] [PubMed]
  46. J. P. Culver, A. M. Siegel, M. A. Franceschini, J. B. Mandeville, and D. A. Boas, “Evidence that cerebral blood volume can provide brain activation maps with better spatial resolution than deoxygenated hemoglobin,” Neuroimage 27(4), 947–959 (2005).
    [CrossRef] [PubMed]
  47. Y. Benjamini and Y. Hochberg, “Controlling the false discovery rate: a practical and powerful approach to multiple testing,” J. R. Stat. Soc., B 57, 289–300 (1995).
  48. G. K. Aguirre, E. Zarahn, and M. D’esposito, “The variability of human, BOLD hemodynamic responses,” Neuroimage 8(4), 360–369 (1998).
    [CrossRef] [PubMed]
  49. 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]

2010 (4)

H. Kojima and T. Suzuki, “Hemodynamic change in occipital lobe during visual search: visual attention allocation measured with NIRS,” Neuropsychologia 48(1), 349–352 (2010).
[CrossRef]

R. Luria, P. Sessa, A. Gotler, P. Jolicoeur, and R. Dell’Acqua, “Visual short-term memory capacity for simple and complex objects,” J. Cogn. Neurosci. 22(3), 496–512 (2010).
[CrossRef]

R. Dell’Acqua, P. Sessa, P. Toffanin, R. Luria, and P. Jolicoeur, “Orienting attention to objects in visual short-term memory,” Neuropsychologia 48(2), 419–428 (2010).
[CrossRef]

N. Robitaille, R. Marois, J. J. Todd, S. Grimault, D. Cheyne, and P. Jolicoeur, “Distinguishing between lateralized and nonlateralized brain activity associated with visual short-term memory: fMRI, MEG, and EEG evidence from the same observers,” Neuroimage 53(4), 1334–1345 (2010).
[CrossRef] [PubMed]

2009 (6)

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

R. J. Cooper, N. L. Everdell, L. C. Enfield, A. P. Gibson, A. Worley, and J. C. Hebden, “Design and evaluation of a probe for simultaneous EEG and near-infrared imaging of cortical activation,” Phys. Med. Biol. 54(7), 2093–2102 (2009).
[CrossRef] [PubMed]

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

A. F. Abdelnour and T. J. Huppert, “Real-time imaging of human brain function by near-infrared spectroscopy using an adaptive general linear model,” Neuroimage 46(1), 133–143 (2009).
[CrossRef] [PubMed]

J. C. Ye, S. Tak, K. E. Jang, J. Jung, and J. Jang, “NIRS-SPM: statistical parametric mapping for near-infrared spectroscopy,” Neuroimage 44(2), 428–447 (2009).
[CrossRef]

K. E. Jang, S. Tak, J. Jung, J. Jang, Y. Jeong, and J. C. Ye, “Wavelet minimum description length detrending for near-infrared spectroscopy,” J. Biomedical Opt . 14, 034004-(1–13) (2009).

2008 (3)

S. P. Koch, S. Koendgen, R. Bourayou, J. Steinbrink, and H. Obrig, “Individual alpha-frequency correlates with amplitude of visual evoked potential and hemodynamic response,” Neuroimage 41(2), 233–242 (2008).
[CrossRef] [PubMed]

A. V. Medvedev, J. Kainerstorfer, S. V. Borisov, R. L. Barbour, and J. VanMeter, “Event-related fast optical signal in a rapid object recognition task: improving detection by the independent component analysis,” Brain Res. 1236, 145–158 (2008).
[CrossRef] [PubMed]

S. Cutini, P. Scatturin, E. Menon, P. S. Bisiacchi, L. Gamberini, M. Zorzi, and R. Dell’Acqua, “Selective activation of the superior frontal gyrus in task-switching: an event-related fNIRS study,” Neuroimage 42(2), 945–955 (2008).
[CrossRef] [PubMed]

2007 (4)

R. Sitaram, H. Zhang, C. Guan, M. Thulasidas, Y. Hoshi, A. Ishikawa, K. Shimizu, and N. Birbaumer, “Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain-computer interface,” Neuroimage 34(4), 1416–1427 (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]

M. L. Schroeter, S. Cutini, M. M. Wahl, R. Scheid, and D. Yves von Cramon, “Neurovascular coupling is impaired in cerebral microangiopathy--An event-related Stroop study,” Neuroimage 34(1), 26–34 (2007).
[CrossRef]

M. A. Lindquist and T. D. Wager, “Validity and power in hemodynamic response modeling: a comparison study and a new approach,” Hum. Brain Mapp. 28(8), 764–784 (2007).
[CrossRef]

2006 (6)

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]

P. Jolicoeur, P. Sessa, R. Dell’Acqua, and N. Robitaille, “On the control of visual spatial attention: evidence from human electrophysiology,” Psychol. Res. 70(6), 414–424 (2006).
[CrossRef]

Y. Xu and M. M. Chun, “Dissociable neural mechanisms supporting visual short-term memory for objects,” Nature 440(7080), 91–95 (2006).
[CrossRef]

C. B. Akgül, A. Akin, and B. Sankur, “Extraction of cognitive activity-related waveforms from functional near-infrared spectroscopy signals,” Med. Biol. Eng. Comput. 44(11), 945–958 (2006).
[CrossRef] [PubMed]

S. G. Diamond, T. J. Huppert, V. Kolehmainen, M. A. Franceschini, J. P. Kaipio, S. R. Arridge, and D. A. Boas, “Dynamic physiological modeling for functional diffuse optical tomography,” Neuroimage 30(1), 88–101 (2006).
[CrossRef]

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]

2005 (3)

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

A. K. Singh, M. Okamoto, H. Dan, V. Jurcak, and I. Dan, “Spatial registration of multichannel multi-subject fNIRS data to MNI space without MRI,” Neuroimage 27(4), 842–851 (2005).
[CrossRef] [PubMed]

J. P. Culver, A. M. Siegel, M. A. Franceschini, J. B. Mandeville, and D. A. Boas, “Evidence that cerebral blood volume can provide brain activation maps with better spatial resolution than deoxygenated hemoglobin,” Neuroimage 27(4), 947–959 (2005).
[CrossRef] [PubMed]

2004 (4)

M. Okamoto, H. Dan, K. Sakamoto, K. Takeo, K. Shimizu, S. Kohno, I. Oda, S. Isobe, T. Suzuki, K. Kohyama, and I. Dan, “Three-dimensional probabilistic anatomical cranio-cerebral correlation via the international 10-20 system oriented for transcranial functional brain mapping,” Neuroimage 21(1), 99–111 (2004).
[CrossRef] [PubMed]

J. J. Todd and R. Marois, “Capacity limit of visual short-term memory in human posterior parietal cortex,” Nature 428(6984), 751–754 (2004).
[CrossRef] [PubMed]

M. L. Schroeter, M. M. Bücheler, K. Müller, K. Uludağ, H. Obrig, G. Lohmann, M. Tittgemeyer, A. Villringer, and D. Y. von Cramon, “Towards a standard analysis for functional near-infrared imaging,” Neuroimage 21(1), 283–290 (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]

2003 (6)

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. U.S.A. 100(19), 10722–10727 (2003).
[CrossRef] [PubMed]

V. Kolehmainen, S. Prince, S. R. Arridge, and J. P. Kaipio, “State-estimation approach to the nonstationary optical tomography problem,” J. Opt. Soc. Am. A 20(5), 876–889 (2003).
[CrossRef]

S. Prince, V. Kolehmainen, J. P. Kaipio, M. A. Franceschini, D. A. Boas, and S. R. Arridge, “Time-series estimation of biological factors in optical diffusion tomography,” Phys. Med. Biol. 48(11), 1491–1504 (2003).
[CrossRef] [PubMed]

H. Obrig and A. Villringer, “Beyond the visible--imaging the human brain with light,” J. Cereb. Blood Flow Metab. 23(1), 1–18 (2003).
[CrossRef]

G. Jasdzewski, G. Strangman, J. Wagner, K. K. Kwong, R. A. Poldrack, and D. A. Boas, “Differences in the hemodynamic response to event-related motor and visual paradigms as measured by near-infrared spectroscopy,” Neuroimage 20(1), 479–488 (2003).
[CrossRef] [PubMed]

M. L. Schroeter, S. Zysset, F. Kruggel, and D. Y. von Cramon, “Age dependency of the hemodynamic response as measured by functional near-infrared spectroscopy,” Neuroimage 19(3), 555–564 (2003).
[CrossRef] [PubMed]

2002 (1)

G. Sparacino, S. Milani, E. Arslan, and C. Cobelli, “A Bayesian approach to estimate evoked potentials,” Comput. Methods Programs Biomed. 68(3), 233–248 (2002).
[CrossRef] [PubMed]

2000 (1)

M. A. Franceschini, V. Toronov, M. E. Filiaci, E. Gratton, and S. Fantini, “On-line optical imaging of the human brain with 160-ms temporal resolution,” Opt. Express 6(3), 49–57 (2000).
[CrossRef] [PubMed]

1998 (2)

M. R. Nuwer, G. Comi, R. Emerson, A. Fuglsang-Frederiksen, J. M. Guérit, H. Hinrichs, A. Ikeda, F. J. Luccas, and P. Rappelsburger, The International Federation of Clinical Neurophysiology, “IFCN standards for digital recording of clinical EEG,” Electroencephalogr. Clin. Neurophysiol. 106(3), 259–261 (1998).
[CrossRef] [PubMed]

G. K. Aguirre, E. Zarahn, and M. D’esposito, “The variability of human, BOLD hemodynamic responses,” Neuroimage 8(4), 360–369 (1998).
[CrossRef] [PubMed]

1996 (1)

A. Duncan, J. H. Meek, M. Clemence, C. E. Elwell, P. Fallon, L. Tyszczuk, M. Cope, and D. T. Delpy, “Measurement of cranial optical path length as a function of age using phase resolved near infrared spectroscopy,” Pediatr. Res. 39(5), 889–894 (1996).
[CrossRef] [PubMed]

1995 (1)

Y. Benjamini and Y. Hochberg, “Controlling the false discovery rate: a practical and powerful approach to multiple testing,” J. R. Stat. Soc., B 57, 289–300 (1995).

1988 (1)

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

1969 (1)

F. E. Grubbs, “Procedures for detecting outlying observations in samples,” Technometrics 11(1), 1–21 (1969).
[CrossRef]

Abdelnour, A. F.

A. F. Abdelnour and T. J. Huppert, “Real-time imaging of human brain function by near-infrared spectroscopy using an adaptive general linear model,” Neuroimage 46(1), 133–143 (2009).
[CrossRef] [PubMed]

Aguirre, G. K.

G. K. Aguirre, E. Zarahn, and M. D’esposito, “The variability of human, BOLD hemodynamic responses,” Neuroimage 8(4), 360–369 (1998).
[CrossRef] [PubMed]

Akgül, C. B.

C. B. Akgül, A. Akin, and B. Sankur, “Extraction of cognitive activity-related waveforms from functional near-infrared spectroscopy signals,” Med. Biol. Eng. Comput. 44(11), 945–958 (2006).
[CrossRef] [PubMed]

Akin, A.

C. B. Akgül, A. Akin, and B. Sankur, “Extraction of cognitive activity-related waveforms from functional near-infrared spectroscopy signals,” Med. Biol. Eng. Comput. 44(11), 945–958 (2006).
[CrossRef] [PubMed]

Arridge, S. R.

S. G. Diamond, T. J. Huppert, V. Kolehmainen, M. A. Franceschini, J. P. Kaipio, S. R. Arridge, and D. A. Boas, “Dynamic physiological modeling for functional diffuse optical tomography,” Neuroimage 30(1), 88–101 (2006).
[CrossRef]

S. Prince, V. Kolehmainen, J. P. Kaipio, M. A. Franceschini, D. A. Boas, and S. R. Arridge, “Time-series estimation of biological factors in optical diffusion tomography,” Phys. Med. Biol. 48(11), 1491–1504 (2003).
[CrossRef] [PubMed]

V. Kolehmainen, S. Prince, S. R. Arridge, and J. P. Kaipio, “State-estimation approach to the nonstationary optical tomography problem,” J. Opt. Soc. Am. A 20(5), 876–889 (2003).
[CrossRef]

Arslan, E.

G. Sparacino, S. Milani, E. Arslan, and C. Cobelli, “A Bayesian approach to estimate evoked potentials,” Comput. Methods Programs Biomed. 68(3), 233–248 (2002).
[CrossRef] [PubMed]

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. U.S.A. 100(19), 10722–10727 (2003).
[CrossRef] [PubMed]

Barbour, R. L.

A. V. Medvedev, J. Kainerstorfer, S. V. Borisov, R. L. Barbour, and J. VanMeter, “Event-related fast optical signal in a rapid object recognition task: improving detection by the independent component analysis,” Brain Res. 1236, 145–158 (2008).
[CrossRef] [PubMed]

Benjamini, Y.

Y. Benjamini and Y. Hochberg, “Controlling the false discovery rate: a practical and powerful approach to multiple testing,” J. R. Stat. Soc., B 57, 289–300 (1995).

Birbaumer, N.

R. Sitaram, H. Zhang, C. Guan, M. Thulasidas, Y. Hoshi, A. Ishikawa, K. Shimizu, and N. Birbaumer, “Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain-computer interface,” Neuroimage 34(4), 1416–1427 (2007).
[CrossRef] [PubMed]

Bisiacchi, P. S.

S. Cutini, P. Scatturin, E. Menon, P. S. Bisiacchi, L. Gamberini, M. Zorzi, and R. Dell’Acqua, “Selective activation of the superior frontal gyrus in task-switching: an event-related fNIRS study,” Neuroimage 42(2), 945–955 (2008).
[CrossRef] [PubMed]

Boas, D. A.

S. G. Diamond, T. J. Huppert, V. Kolehmainen, M. A. Franceschini, J. P. Kaipio, S. R. Arridge, and D. A. Boas, “Dynamic physiological modeling for functional diffuse optical tomography,” Neuroimage 30(1), 88–101 (2006).
[CrossRef]

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

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

J. P. Culver, A. M. Siegel, M. A. Franceschini, J. B. Mandeville, and D. A. Boas, “Evidence that cerebral blood volume can provide brain activation maps with better spatial resolution than deoxygenated hemoglobin,” Neuroimage 27(4), 947–959 (2005).
[CrossRef] [PubMed]

S. Prince, V. Kolehmainen, J. P. Kaipio, M. A. Franceschini, D. A. Boas, and S. R. Arridge, “Time-series estimation of biological factors in optical diffusion tomography,” Phys. Med. Biol. 48(11), 1491–1504 (2003).
[CrossRef] [PubMed]

G. Jasdzewski, G. Strangman, J. Wagner, K. K. Kwong, R. A. Poldrack, and D. A. Boas, “Differences in the hemodynamic response to event-related motor and visual paradigms as measured by near-infrared spectroscopy,” Neuroimage 20(1), 479–488 (2003).
[CrossRef] [PubMed]

Borisov, S. V.

A. V. Medvedev, J. Kainerstorfer, S. V. Borisov, R. L. Barbour, and J. VanMeter, “Event-related fast optical signal in a rapid object recognition task: improving detection by the independent component analysis,” Brain Res. 1236, 145–158 (2008).
[CrossRef] [PubMed]

Bourayou, R.

S. P. Koch, S. Koendgen, R. Bourayou, J. Steinbrink, and H. Obrig, “Individual alpha-frequency correlates with amplitude of visual evoked potential and hemodynamic response,” Neuroimage 41(2), 233–242 (2008).
[CrossRef] [PubMed]

Brooks, D. H.

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

Brown, E. N.

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

Bücheler, M. M.

M. L. Schroeter, M. M. Bücheler, K. Müller, K. Uludağ, H. Obrig, G. Lohmann, M. Tittgemeyer, A. Villringer, and D. Y. von Cramon, “Towards a standard analysis for functional near-infrared imaging,” Neuroimage 21(1), 283–290 (2004).
[CrossRef] [PubMed]

Bunce, S. C.

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

Cheyne, D.

N. Robitaille, R. Marois, J. J. Todd, S. Grimault, D. Cheyne, and P. Jolicoeur, “Distinguishing between lateralized and nonlateralized brain activity associated with visual short-term memory: fMRI, MEG, and EEG evidence from the same observers,” Neuroimage 53(4), 1334–1345 (2010).
[CrossRef] [PubMed]

Choi, J. H.

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]

Chun, M. M.

Y. Xu and M. M. Chun, “Dissociable neural mechanisms supporting visual short-term memory for objects,” Nature 440(7080), 91–95 (2006).
[CrossRef]

Clemence, M.

A. Duncan, J. H. Meek, M. Clemence, C. E. Elwell, P. Fallon, L. Tyszczuk, M. Cope, and D. T. Delpy, “Measurement of cranial optical path length as a function of age using phase resolved near infrared spectroscopy,” Pediatr. Res. 39(5), 889–894 (1996).
[CrossRef] [PubMed]

Cobelli, C.

G. Sparacino, S. Milani, E. Arslan, and C. Cobelli, “A Bayesian approach to estimate evoked potentials,” Comput. Methods Programs Biomed. 68(3), 233–248 (2002).
[CrossRef] [PubMed]

Comi, G.

M. R. Nuwer, G. Comi, R. Emerson, A. Fuglsang-Frederiksen, J. M. Guérit, H. Hinrichs, A. Ikeda, F. J. Luccas, and P. Rappelsburger, The International Federation of Clinical Neurophysiology, “IFCN standards for digital recording of clinical EEG,” Electroencephalogr. Clin. Neurophysiol. 106(3), 259–261 (1998).
[CrossRef] [PubMed]

Cooper, R. J.

R. J. Cooper, N. L. Everdell, L. C. Enfield, A. P. Gibson, A. Worley, and J. C. Hebden, “Design and evaluation of a probe for simultaneous EEG and near-infrared imaging of cortical activation,” Phys. Med. Biol. 54(7), 2093–2102 (2009).
[CrossRef] [PubMed]

Cope, M.

A. Duncan, J. H. Meek, M. Clemence, C. E. Elwell, P. Fallon, L. Tyszczuk, M. Cope, and D. T. Delpy, “Measurement of cranial optical path length as a function of age using phase resolved near infrared spectroscopy,” Pediatr. Res. 39(5), 889–894 (1996).
[CrossRef] [PubMed]

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

Culver, J. P.

J. P. Culver, A. M. Siegel, M. A. Franceschini, J. B. Mandeville, and D. A. Boas, “Evidence that cerebral blood volume can provide brain activation maps with better spatial resolution than deoxygenated hemoglobin,” Neuroimage 27(4), 947–959 (2005).
[CrossRef] [PubMed]

Cutini, S.

S. Cutini, P. Scatturin, E. Menon, P. S. Bisiacchi, L. Gamberini, M. Zorzi, and R. Dell’Acqua, “Selective activation of the superior frontal gyrus in task-switching: an event-related fNIRS study,” Neuroimage 42(2), 945–955 (2008).
[CrossRef] [PubMed]

M. L. Schroeter, S. Cutini, M. M. Wahl, R. Scheid, and D. Yves von Cramon, “Neurovascular coupling is impaired in cerebral microangiopathy--An event-related Stroop study,” Neuroimage 34(1), 26–34 (2007).
[CrossRef]

S. Cutini, P. Scatturin, and M. Zorzi, “A new method based on ICBM152 head surface for probe placement in multichannel fNIRS,” Neuroimage (to be published).
[PubMed]

D’esposito, M.

G. K. Aguirre, E. Zarahn, and M. D’esposito, “The variability of human, BOLD hemodynamic responses,” Neuroimage 8(4), 360–369 (1998).
[CrossRef] [PubMed]

Dan, H.

A. K. Singh, M. Okamoto, H. Dan, V. Jurcak, and I. Dan, “Spatial registration of multichannel multi-subject fNIRS data to MNI space without MRI,” Neuroimage 27(4), 842–851 (2005).
[CrossRef] [PubMed]

M. Okamoto, H. Dan, K. Sakamoto, K. Takeo, K. Shimizu, S. Kohno, I. Oda, S. Isobe, T. Suzuki, K. Kohyama, and I. Dan, “Three-dimensional probabilistic anatomical cranio-cerebral correlation via the international 10-20 system oriented for transcranial functional brain mapping,” Neuroimage 21(1), 99–111 (2004).
[CrossRef] [PubMed]

Dan, I.

A. K. Singh, M. Okamoto, H. Dan, V. Jurcak, and I. Dan, “Spatial registration of multichannel multi-subject fNIRS data to MNI space without MRI,” Neuroimage 27(4), 842–851 (2005).
[CrossRef] [PubMed]

M. Okamoto, H. Dan, K. Sakamoto, K. Takeo, K. Shimizu, S. Kohno, I. Oda, S. Isobe, T. Suzuki, K. Kohyama, and I. Dan, “Three-dimensional probabilistic anatomical cranio-cerebral correlation via the international 10-20 system oriented for transcranial functional brain mapping,” Neuroimage 21(1), 99–111 (2004).
[CrossRef] [PubMed]

De Lathauwer, L.

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]

Dehghani, H.

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

Dell’Acqua, R.

R. Dell’Acqua, P. Sessa, P. Toffanin, R. Luria, and P. Jolicoeur, “Orienting attention to objects in visual short-term memory,” Neuropsychologia 48(2), 419–428 (2010).
[CrossRef]

R. Luria, P. Sessa, A. Gotler, P. Jolicoeur, and R. Dell’Acqua, “Visual short-term memory capacity for simple and complex objects,” J. Cogn. Neurosci. 22(3), 496–512 (2010).
[CrossRef]

S. Cutini, P. Scatturin, E. Menon, P. S. Bisiacchi, L. Gamberini, M. Zorzi, and R. Dell’Acqua, “Selective activation of the superior frontal gyrus in task-switching: an event-related fNIRS study,” Neuroimage 42(2), 945–955 (2008).
[CrossRef] [PubMed]

P. Jolicoeur, P. Sessa, R. Dell’Acqua, and N. Robitaille, “On the control of visual spatial attention: evidence from human electrophysiology,” Psychol. Res. 70(6), 414–424 (2006).
[CrossRef]

Delpy, D. T.

A. Duncan, J. H. Meek, M. Clemence, C. E. Elwell, P. Fallon, L. Tyszczuk, M. Cope, and D. T. Delpy, “Measurement of cranial optical path length as a function of age using phase resolved near infrared spectroscopy,” Pediatr. Res. 39(5), 889–894 (1996).
[CrossRef] [PubMed]

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

Diamond, S. G.

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

S. G. Diamond, T. J. Huppert, V. Kolehmainen, M. A. Franceschini, J. P. Kaipio, S. R. Arridge, and D. A. Boas, “Dynamic physiological modeling for functional diffuse optical tomography,” Neuroimage 30(1), 88–101 (2006).
[CrossRef]

Duncan, A.

A. Duncan, J. H. Meek, M. Clemence, C. E. Elwell, P. Fallon, L. Tyszczuk, M. Cope, and D. T. Delpy, “Measurement of cranial optical path length as a function of age using phase resolved near infrared spectroscopy,” Pediatr. Res. 39(5), 889–894 (1996).
[CrossRef] [PubMed]

Elwell, C. E.

A. Duncan, J. H. Meek, M. Clemence, C. E. Elwell, P. Fallon, L. Tyszczuk, M. Cope, and D. T. Delpy, “Measurement of cranial optical path length as a function of age using phase resolved near infrared spectroscopy,” Pediatr. Res. 39(5), 889–894 (1996).
[CrossRef] [PubMed]

Emerson, R.

M. R. Nuwer, G. Comi, R. Emerson, A. Fuglsang-Frederiksen, J. M. Guérit, H. Hinrichs, A. Ikeda, F. J. Luccas, and P. Rappelsburger, The International Federation of Clinical Neurophysiology, “IFCN standards for digital recording of clinical EEG,” Electroencephalogr. Clin. Neurophysiol. 106(3), 259–261 (1998).
[CrossRef] [PubMed]

Enfield, L. C.

R. J. Cooper, N. L. Everdell, L. C. Enfield, A. P. Gibson, A. Worley, and J. C. Hebden, “Design and evaluation of a probe for simultaneous EEG and near-infrared imaging of cortical activation,” Phys. Med. Biol. 54(7), 2093–2102 (2009).
[CrossRef] [PubMed]

Everdell, N. L.

R. J. Cooper, N. L. Everdell, L. C. Enfield, A. P. Gibson, A. Worley, and J. C. Hebden, “Design and evaluation of a probe for simultaneous EEG and near-infrared imaging of cortical activation,” Phys. Med. Biol. 54(7), 2093–2102 (2009).
[CrossRef] [PubMed]

Fallon, P.

A. Duncan, J. H. Meek, M. Clemence, C. E. Elwell, P. Fallon, L. Tyszczuk, M. Cope, and D. T. Delpy, “Measurement of cranial optical path length as a function of age using phase resolved near infrared spectroscopy,” Pediatr. Res. 39(5), 889–894 (1996).
[CrossRef] [PubMed]

Fantini, S.

M. A. Franceschini, V. Toronov, M. E. Filiaci, E. Gratton, and S. Fantini, “On-line optical imaging of the human brain with 160-ms temporal resolution,” Opt. Express 6(3), 49–57 (2000).
[CrossRef] [PubMed]

Filiaci, M. E.

M. A. Franceschini, V. Toronov, M. E. Filiaci, E. Gratton, and S. Fantini, “On-line optical imaging of the human brain with 160-ms temporal resolution,” Opt. Express 6(3), 49–57 (2000).
[CrossRef] [PubMed]

Franceschini, M. A.

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]

S. G. Diamond, T. J. Huppert, V. Kolehmainen, M. A. Franceschini, J. P. Kaipio, S. R. Arridge, and D. A. Boas, “Dynamic physiological modeling for functional diffuse optical tomography,” Neuroimage 30(1), 88–101 (2006).
[CrossRef]

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

J. P. Culver, A. M. Siegel, M. A. Franceschini, J. B. Mandeville, and D. A. Boas, “Evidence that cerebral blood volume can provide brain activation maps with better spatial resolution than deoxygenated hemoglobin,” Neuroimage 27(4), 947–959 (2005).
[CrossRef] [PubMed]

S. Prince, V. Kolehmainen, J. P. Kaipio, M. A. Franceschini, D. A. Boas, and S. R. Arridge, “Time-series estimation of biological factors in optical diffusion tomography,” Phys. Med. Biol. 48(11), 1491–1504 (2003).
[CrossRef] [PubMed]

M. A. Franceschini, V. Toronov, M. E. Filiaci, E. Gratton, and S. Fantini, “On-line optical imaging of the human brain with 160-ms temporal resolution,” Opt. Express 6(3), 49–57 (2000).
[CrossRef] [PubMed]

Fuglsang-Frederiksen, A.

M. R. Nuwer, G. Comi, R. Emerson, A. Fuglsang-Frederiksen, J. M. Guérit, H. Hinrichs, A. Ikeda, F. J. Luccas, and P. Rappelsburger, The International Federation of Clinical Neurophysiology, “IFCN standards for digital recording of clinical EEG,” Electroencephalogr. Clin. Neurophysiol. 106(3), 259–261 (1998).
[CrossRef] [PubMed]

Gamberini, L.

S. Cutini, P. Scatturin, E. Menon, P. S. Bisiacchi, L. Gamberini, M. Zorzi, and R. Dell’Acqua, “Selective activation of the superior frontal gyrus in task-switching: an event-related fNIRS study,” Neuroimage 42(2), 945–955 (2008).
[CrossRef] [PubMed]

Ganis, G.

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

Gibson, A.

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

Gibson, A. P.

R. J. Cooper, N. L. Everdell, L. C. Enfield, A. P. Gibson, A. Worley, and J. C. Hebden, “Design and evaluation of a probe for simultaneous EEG and near-infrared imaging of cortical activation,” Phys. Med. Biol. 54(7), 2093–2102 (2009).
[CrossRef] [PubMed]

Gotler, A.

R. Luria, P. Sessa, A. Gotler, P. Jolicoeur, and R. Dell’Acqua, “Visual short-term memory capacity for simple and complex objects,” J. Cogn. Neurosci. 22(3), 496–512 (2010).
[CrossRef]

Gratton, E.

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]

M. A. Franceschini, V. Toronov, M. E. Filiaci, E. Gratton, and S. Fantini, “On-line optical imaging of the human brain with 160-ms temporal resolution,” Opt. Express 6(3), 49–57 (2000).
[CrossRef] [PubMed]

Grimault, S.

N. Robitaille, R. Marois, J. J. Todd, S. Grimault, D. Cheyne, and P. Jolicoeur, “Distinguishing between lateralized and nonlateralized brain activity associated with visual short-term memory: fMRI, MEG, and EEG evidence from the same observers,” Neuroimage 53(4), 1334–1345 (2010).
[CrossRef] [PubMed]

Grubbs, F. E.

F. E. Grubbs, “Procedures for detecting outlying observations in samples,” Technometrics 11(1), 1–21 (1969).
[CrossRef]

Guan, C.

R. Sitaram, H. Zhang, C. Guan, M. Thulasidas, Y. Hoshi, A. Ishikawa, K. Shimizu, and N. Birbaumer, “Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain-computer interface,” Neuroimage 34(4), 1416–1427 (2007).
[CrossRef] [PubMed]

Guérit, J. M.

M. R. Nuwer, G. Comi, R. Emerson, A. Fuglsang-Frederiksen, J. M. Guérit, H. Hinrichs, A. Ikeda, F. J. Luccas, and P. Rappelsburger, The International Federation of Clinical Neurophysiology, “IFCN standards for digital recording of clinical EEG,” Electroencephalogr. Clin. Neurophysiol. 106(3), 259–261 (1998).
[CrossRef] [PubMed]

Hebden, J. C.

R. J. Cooper, N. L. Everdell, L. C. Enfield, A. P. Gibson, A. Worley, and J. C. Hebden, “Design and evaluation of a probe for simultaneous EEG and near-infrared imaging of cortical activation,” Phys. Med. Biol. 54(7), 2093–2102 (2009).
[CrossRef] [PubMed]

Hinrichs, H.

M. R. Nuwer, G. Comi, R. Emerson, A. Fuglsang-Frederiksen, J. M. Guérit, H. Hinrichs, A. Ikeda, F. J. Luccas, and P. Rappelsburger, The International Federation of Clinical Neurophysiology, “IFCN standards for digital recording of clinical EEG,” Electroencephalogr. Clin. Neurophysiol. 106(3), 259–261 (1998).
[CrossRef] [PubMed]

Hochberg, Y.

Y. Benjamini and Y. Hochberg, “Controlling the false discovery rate: a practical and powerful approach to multiple testing,” J. R. Stat. Soc., B 57, 289–300 (1995).

Hoshi, Y.

R. Sitaram, H. Zhang, C. Guan, M. Thulasidas, Y. Hoshi, A. Ishikawa, K. Shimizu, and N. Birbaumer, “Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain-computer interface,” Neuroimage 34(4), 1416–1427 (2007).
[CrossRef] [PubMed]

Huppert, T. J.

A. F. Abdelnour and T. J. Huppert, “Real-time imaging of human brain function by near-infrared spectroscopy using an adaptive general linear model,” Neuroimage 46(1), 133–143 (2009).
[CrossRef] [PubMed]

S. G. Diamond, T. J. Huppert, V. Kolehmainen, M. A. Franceschini, J. P. Kaipio, S. R. Arridge, and D. A. Boas, “Dynamic physiological modeling for functional diffuse optical tomography,” Neuroimage 30(1), 88–101 (2006).
[CrossRef]

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]

Ikeda, A.

M. R. Nuwer, G. Comi, R. Emerson, A. Fuglsang-Frederiksen, J. M. Guérit, H. Hinrichs, A. Ikeda, F. J. Luccas, and P. Rappelsburger, The International Federation of Clinical Neurophysiology, “IFCN standards for digital recording of clinical EEG,” Electroencephalogr. Clin. Neurophysiol. 106(3), 259–261 (1998).
[CrossRef] [PubMed]

Ishikawa, A.

R. Sitaram, H. Zhang, C. Guan, M. Thulasidas, Y. Hoshi, A. Ishikawa, K. Shimizu, and N. Birbaumer, “Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain-computer interface,” Neuroimage 34(4), 1416–1427 (2007).
[CrossRef] [PubMed]

Isobe, S.

M. Okamoto, H. Dan, K. Sakamoto, K. Takeo, K. Shimizu, S. Kohno, I. Oda, S. Isobe, T. Suzuki, K. Kohyama, and I. Dan, “Three-dimensional probabilistic anatomical cranio-cerebral correlation via the international 10-20 system oriented for transcranial functional brain mapping,” Neuroimage 21(1), 99–111 (2004).
[CrossRef] [PubMed]

Izzetoglu, K.

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

Izzetoglu, M.

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

Jang, J.

J. C. Ye, S. Tak, K. E. Jang, J. Jung, and J. Jang, “NIRS-SPM: statistical parametric mapping for near-infrared spectroscopy,” Neuroimage 44(2), 428–447 (2009).
[CrossRef]

K. E. Jang, S. Tak, J. Jung, J. Jang, Y. Jeong, and J. C. Ye, “Wavelet minimum description length detrending for near-infrared spectroscopy,” J. Biomedical Opt . 14, 034004-(1–13) (2009).

Jang, K. E.

K. E. Jang, S. Tak, J. Jung, J. Jang, Y. Jeong, and J. C. Ye, “Wavelet minimum description length detrending for near-infrared spectroscopy,” J. Biomedical Opt . 14, 034004-(1–13) (2009).

J. C. Ye, S. Tak, K. E. Jang, J. Jung, and J. Jang, “NIRS-SPM: statistical parametric mapping for near-infrared spectroscopy,” Neuroimage 44(2), 428–447 (2009).
[CrossRef]

Jasdzewski, G.

G. Jasdzewski, G. Strangman, J. Wagner, K. K. Kwong, R. A. Poldrack, and D. A. Boas, “Differences in the hemodynamic response to event-related motor and visual paradigms as measured by near-infrared spectroscopy,” Neuroimage 20(1), 479–488 (2003).
[CrossRef] [PubMed]

Jeong, Y.

K. E. Jang, S. Tak, J. Jung, J. Jang, Y. Jeong, and J. C. Ye, “Wavelet minimum description length detrending for near-infrared spectroscopy,” J. Biomedical Opt . 14, 034004-(1–13) (2009).

Jolicoeur, P.

R. Luria, P. Sessa, A. Gotler, P. Jolicoeur, and R. Dell’Acqua, “Visual short-term memory capacity for simple and complex objects,” J. Cogn. Neurosci. 22(3), 496–512 (2010).
[CrossRef]

R. Dell’Acqua, P. Sessa, P. Toffanin, R. Luria, and P. Jolicoeur, “Orienting attention to objects in visual short-term memory,” Neuropsychologia 48(2), 419–428 (2010).
[CrossRef]

N. Robitaille, R. Marois, J. J. Todd, S. Grimault, D. Cheyne, and P. Jolicoeur, “Distinguishing between lateralized and nonlateralized brain activity associated with visual short-term memory: fMRI, MEG, and EEG evidence from the same observers,” Neuroimage 53(4), 1334–1345 (2010).
[CrossRef] [PubMed]

P. Jolicoeur, P. Sessa, R. Dell’Acqua, and N. Robitaille, “On the control of visual spatial attention: evidence from human electrophysiology,” Psychol. Res. 70(6), 414–424 (2006).
[CrossRef]

Joseph, D. K.

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

Jung, J.

J. C. Ye, S. Tak, K. E. Jang, J. Jung, and J. Jang, “NIRS-SPM: statistical parametric mapping for near-infrared spectroscopy,” Neuroimage 44(2), 428–447 (2009).
[CrossRef]

K. E. Jang, S. Tak, J. Jung, J. Jang, Y. Jeong, and J. C. Ye, “Wavelet minimum description length detrending for near-infrared spectroscopy,” J. Biomedical Opt . 14, 034004-(1–13) (2009).

Jurcak, V.

A. K. Singh, M. Okamoto, H. Dan, V. Jurcak, and I. Dan, “Spatial registration of multichannel multi-subject fNIRS data to MNI space without MRI,” Neuroimage 27(4), 842–851 (2005).
[CrossRef] [PubMed]

Kainerstorfer, J.

A. V. Medvedev, J. Kainerstorfer, S. V. Borisov, R. L. Barbour, and J. VanMeter, “Event-related fast optical signal in a rapid object recognition task: improving detection by the independent component analysis,” Brain Res. 1236, 145–158 (2008).
[CrossRef] [PubMed]

Kaipio, J. P.

S. G. Diamond, T. J. Huppert, V. Kolehmainen, M. A. Franceschini, J. P. Kaipio, S. R. Arridge, and D. A. Boas, “Dynamic physiological modeling for functional diffuse optical tomography,” Neuroimage 30(1), 88–101 (2006).
[CrossRef]

S. Prince, V. Kolehmainen, J. P. Kaipio, M. A. Franceschini, D. A. Boas, and S. R. Arridge, “Time-series estimation of biological factors in optical diffusion tomography,” Phys. Med. Biol. 48(11), 1491–1504 (2003).
[CrossRef] [PubMed]

V. Kolehmainen, S. Prince, S. R. Arridge, and J. P. Kaipio, “State-estimation approach to the nonstationary optical tomography problem,” J. Opt. Soc. Am. A 20(5), 876–889 (2003).
[CrossRef]

Koch, S. P.

S. P. Koch, S. Koendgen, R. Bourayou, J. Steinbrink, and H. Obrig, “Individual alpha-frequency correlates with amplitude of visual evoked potential and hemodynamic response,” Neuroimage 41(2), 233–242 (2008).
[CrossRef] [PubMed]

Koendgen, S.

S. P. Koch, S. Koendgen, R. Bourayou, J. Steinbrink, and H. Obrig, “Individual alpha-frequency correlates with amplitude of visual evoked potential and hemodynamic response,” Neuroimage 41(2), 233–242 (2008).
[CrossRef] [PubMed]

Kohno, S.

M. Okamoto, H. Dan, K. Sakamoto, K. Takeo, K. Shimizu, S. Kohno, I. Oda, S. Isobe, T. Suzuki, K. Kohyama, and I. Dan, “Three-dimensional probabilistic anatomical cranio-cerebral correlation via the international 10-20 system oriented for transcranial functional brain mapping,” Neuroimage 21(1), 99–111 (2004).
[CrossRef] [PubMed]

Kohyama, K.

M. Okamoto, H. Dan, K. Sakamoto, K. Takeo, K. Shimizu, S. Kohno, I. Oda, S. Isobe, T. Suzuki, K. Kohyama, and I. Dan, “Three-dimensional probabilistic anatomical cranio-cerebral correlation via the international 10-20 system oriented for transcranial functional brain mapping,” Neuroimage 21(1), 99–111 (2004).
[CrossRef] [PubMed]

Koizumi, H.

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. U.S.A. 100(19), 10722–10727 (2003).
[CrossRef] [PubMed]

Kojima, H.

H. Kojima and T. Suzuki, “Hemodynamic change in occipital lobe during visual search: visual attention allocation measured with NIRS,” Neuropsychologia 48(1), 349–352 (2010).
[CrossRef]

Kolehmainen, V.

S. G. Diamond, T. J. Huppert, V. Kolehmainen, M. A. Franceschini, J. P. Kaipio, S. R. Arridge, and D. A. Boas, “Dynamic physiological modeling for functional diffuse optical tomography,” Neuroimage 30(1), 88–101 (2006).
[CrossRef]

S. Prince, V. Kolehmainen, J. P. Kaipio, M. A. Franceschini, D. A. Boas, and S. R. Arridge, “Time-series estimation of biological factors in optical diffusion tomography,” Phys. Med. Biol. 48(11), 1491–1504 (2003).
[CrossRef] [PubMed]

V. Kolehmainen, S. Prince, S. R. Arridge, and J. P. Kaipio, “State-estimation approach to the nonstationary optical tomography problem,” J. Opt. Soc. Am. A 20(5), 876–889 (2003).
[CrossRef]

Konishi, Y.

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. U.S.A. 100(19), 10722–10727 (2003).
[CrossRef] [PubMed]

Kruggel, F.

M. L. Schroeter, S. Zysset, F. Kruggel, and D. Y. von Cramon, “Age dependency of the hemodynamic response as measured by functional near-infrared spectroscopy,” Neuroimage 19(3), 555–564 (2003).
[CrossRef] [PubMed]

Kwong, K. K.

G. Jasdzewski, G. Strangman, J. Wagner, K. K. Kwong, R. A. Poldrack, and D. A. Boas, “Differences in the hemodynamic response to event-related motor and visual paradigms as measured by near-infrared spectroscopy,” Neuroimage 20(1), 479–488 (2003).
[CrossRef] [PubMed]

Lemmerling, P.

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]

Lindquist, M. A.

M. A. Lindquist and T. D. Wager, “Validity and power in hemodynamic response modeling: a comparison study and a new approach,” Hum. Brain Mapp. 28(8), 764–784 (2007).
[CrossRef]

Lohmann, G.

M. L. Schroeter, M. M. Bücheler, K. Müller, K. Uludağ, H. Obrig, G. Lohmann, M. Tittgemeyer, A. Villringer, and D. Y. von Cramon, “Towards a standard analysis for functional near-infrared imaging,” Neuroimage 21(1), 283–290 (2004).
[CrossRef] [PubMed]

Luccas, F. J.

M. R. Nuwer, G. Comi, R. Emerson, A. Fuglsang-Frederiksen, J. M. Guérit, H. Hinrichs, A. Ikeda, F. J. Luccas, and P. Rappelsburger, The International Federation of Clinical Neurophysiology, “IFCN standards for digital recording of clinical EEG,” Electroencephalogr. Clin. Neurophysiol. 106(3), 259–261 (1998).
[CrossRef] [PubMed]

Luria, R.

R. Luria, P. Sessa, A. Gotler, P. Jolicoeur, and R. Dell’Acqua, “Visual short-term memory capacity for simple and complex objects,” J. Cogn. Neurosci. 22(3), 496–512 (2010).
[CrossRef]

R. Dell’Acqua, P. Sessa, P. Toffanin, R. Luria, and P. Jolicoeur, “Orienting attention to objects in visual short-term memory,” Neuropsychologia 48(2), 419–428 (2010).
[CrossRef]

Maki, A.

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. U.S.A. 100(19), 10722–10727 (2003).
[CrossRef] [PubMed]

Mandeville, J. B.

J. P. Culver, A. M. Siegel, M. A. Franceschini, J. B. Mandeville, and D. A. Boas, “Evidence that cerebral blood volume can provide brain activation maps with better spatial resolution than deoxygenated hemoglobin,” Neuroimage 27(4), 947–959 (2005).
[CrossRef] [PubMed]

Marois, R.

N. Robitaille, R. Marois, J. J. Todd, S. Grimault, D. Cheyne, and P. Jolicoeur, “Distinguishing between lateralized and nonlateralized brain activity associated with visual short-term memory: fMRI, MEG, and EEG evidence from the same observers,” Neuroimage 53(4), 1334–1345 (2010).
[CrossRef] [PubMed]

J. J. Todd and R. Marois, “Capacity limit of visual short-term memory in human posterior parietal cortex,” Nature 428(6984), 751–754 (2004).
[CrossRef] [PubMed]

Medvedev, A. V.

A. V. Medvedev, J. Kainerstorfer, S. V. Borisov, R. L. Barbour, and J. VanMeter, “Event-related fast optical signal in a rapid object recognition task: improving detection by the independent component analysis,” Brain Res. 1236, 145–158 (2008).
[CrossRef] [PubMed]

Meek, J. H.

A. Duncan, J. H. Meek, M. Clemence, C. E. Elwell, P. Fallon, L. Tyszczuk, M. Cope, and D. T. Delpy, “Measurement of cranial optical path length as a function of age using phase resolved near infrared spectroscopy,” Pediatr. Res. 39(5), 889–894 (1996).
[CrossRef] [PubMed]

Menon, E.

S. Cutini, P. Scatturin, E. Menon, P. S. Bisiacchi, L. Gamberini, M. Zorzi, and R. Dell’Acqua, “Selective activation of the superior frontal gyrus in task-switching: an event-related fNIRS study,” Neuroimage 42(2), 945–955 (2008).
[CrossRef] [PubMed]

Milani, S.

G. Sparacino, S. Milani, E. Arslan, and C. Cobelli, “A Bayesian approach to estimate evoked potentials,” Comput. Methods Programs Biomed. 68(3), 233–248 (2002).
[CrossRef] [PubMed]

Morren, G.

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]

Müller, K.

M. L. Schroeter, M. M. Bücheler, K. Müller, K. Uludağ, H. Obrig, G. Lohmann, M. Tittgemeyer, A. Villringer, and D. Y. von Cramon, “Towards a standard analysis for functional near-infrared imaging,” Neuroimage 21(1), 283–290 (2004).
[CrossRef] [PubMed]

Nuwer, M. R.

M. R. Nuwer, G. Comi, R. Emerson, A. Fuglsang-Frederiksen, J. M. Guérit, H. Hinrichs, A. Ikeda, F. J. Luccas, and P. Rappelsburger, The International Federation of Clinical Neurophysiology, “IFCN standards for digital recording of clinical EEG,” Electroencephalogr. Clin. Neurophysiol. 106(3), 259–261 (1998).
[CrossRef] [PubMed]

Obrig, H.

S. P. Koch, S. Koendgen, R. Bourayou, J. Steinbrink, and H. Obrig, “Individual alpha-frequency correlates with amplitude of visual evoked potential and hemodynamic response,” Neuroimage 41(2), 233–242 (2008).
[CrossRef] [PubMed]

M. L. Schroeter, M. M. Bücheler, K. Müller, K. Uludağ, H. Obrig, G. Lohmann, M. Tittgemeyer, A. Villringer, and D. Y. von Cramon, “Towards a standard analysis for functional near-infrared imaging,” Neuroimage 21(1), 283–290 (2004).
[CrossRef] [PubMed]

H. Obrig and A. Villringer, “Beyond the visible--imaging the human brain with light,” J. Cereb. Blood Flow Metab. 23(1), 1–18 (2003).
[CrossRef]

Oda, I.

M. Okamoto, H. Dan, K. Sakamoto, K. Takeo, K. Shimizu, S. Kohno, I. Oda, S. Isobe, T. Suzuki, K. Kohyama, and I. Dan, “Three-dimensional probabilistic anatomical cranio-cerebral correlation via the international 10-20 system oriented for transcranial functional brain mapping,” Neuroimage 21(1), 99–111 (2004).
[CrossRef] [PubMed]

Okamoto, M.

A. K. Singh, M. Okamoto, H. Dan, V. Jurcak, and I. Dan, “Spatial registration of multichannel multi-subject fNIRS data to MNI space without MRI,” Neuroimage 27(4), 842–851 (2005).
[CrossRef] [PubMed]

M. Okamoto, H. Dan, K. Sakamoto, K. Takeo, K. Shimizu, S. Kohno, I. Oda, S. Isobe, T. Suzuki, K. Kohyama, and I. Dan, “Three-dimensional probabilistic anatomical cranio-cerebral correlation via the international 10-20 system oriented for transcranial functional brain mapping,” Neuroimage 21(1), 99–111 (2004).
[CrossRef] [PubMed]

Onaral, B.

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

Poldrack, R. A.

G. Jasdzewski, G. Strangman, J. Wagner, K. K. Kwong, R. A. Poldrack, and D. A. Boas, “Differences in the hemodynamic response to event-related motor and visual paradigms as measured by near-infrared spectroscopy,” Neuroimage 20(1), 479–488 (2003).
[CrossRef] [PubMed]

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).
[CrossRef] [PubMed]

Prince, S.

V. Kolehmainen, S. Prince, S. R. Arridge, and J. P. Kaipio, “State-estimation approach to the nonstationary optical tomography problem,” J. Opt. Soc. Am. A 20(5), 876–889 (2003).
[CrossRef]

S. Prince, V. Kolehmainen, J. P. Kaipio, M. A. Franceschini, D. A. Boas, and S. R. Arridge, “Time-series estimation of biological factors in optical diffusion tomography,” Phys. Med. Biol. 48(11), 1491–1504 (2003).
[CrossRef] [PubMed]

Rappelsburger, P.

M. R. Nuwer, G. Comi, R. Emerson, A. Fuglsang-Frederiksen, J. M. Guérit, H. Hinrichs, A. Ikeda, F. J. Luccas, and P. Rappelsburger, The International Federation of Clinical Neurophysiology, “IFCN standards for digital recording of clinical EEG,” Electroencephalogr. Clin. Neurophysiol. 106(3), 259–261 (1998).
[CrossRef] [PubMed]

Robitaille, N.

N. Robitaille, R. Marois, J. J. Todd, S. Grimault, D. Cheyne, and P. Jolicoeur, “Distinguishing between lateralized and nonlateralized brain activity associated with visual short-term memory: fMRI, MEG, and EEG evidence from the same observers,” Neuroimage 53(4), 1334–1345 (2010).
[CrossRef] [PubMed]

P. Jolicoeur, P. Sessa, R. Dell’Acqua, and N. Robitaille, “On the control of visual spatial attention: evidence from human electrophysiology,” Psychol. Res. 70(6), 414–424 (2006).
[CrossRef]

Sakamoto, K.

M. Okamoto, H. Dan, K. Sakamoto, K. Takeo, K. Shimizu, S. Kohno, I. Oda, S. Isobe, T. Suzuki, K. Kohyama, and I. Dan, “Three-dimensional probabilistic anatomical cranio-cerebral correlation via the international 10-20 system oriented for transcranial functional brain mapping,” Neuroimage 21(1), 99–111 (2004).
[CrossRef] [PubMed]

Sankur, B.

C. B. Akgül, A. Akin, and B. Sankur, “Extraction of cognitive activity-related waveforms from functional near-infrared spectroscopy signals,” Med. Biol. Eng. Comput. 44(11), 945–958 (2006).
[CrossRef] [PubMed]

Scatturin, P.

S. Cutini, P. Scatturin, E. Menon, P. S. Bisiacchi, L. Gamberini, M. Zorzi, and R. Dell’Acqua, “Selective activation of the superior frontal gyrus in task-switching: an event-related fNIRS study,” Neuroimage 42(2), 945–955 (2008).
[CrossRef] [PubMed]

S. Cutini, P. Scatturin, and M. Zorzi, “A new method based on ICBM152 head surface for probe placement in multichannel fNIRS,” Neuroimage (to be published).
[PubMed]

Scheid, R.

M. L. Schroeter, S. Cutini, M. M. Wahl, R. Scheid, and D. Yves von Cramon, “Neurovascular coupling is impaired in cerebral microangiopathy--An event-related Stroop study,” Neuroimage 34(1), 26–34 (2007).
[CrossRef]

Schroeter, M. L.

M. L. Schroeter, S. Cutini, M. M. Wahl, R. Scheid, and D. Yves von Cramon, “Neurovascular coupling is impaired in cerebral microangiopathy--An event-related Stroop study,” Neuroimage 34(1), 26–34 (2007).
[CrossRef]

M. L. Schroeter, M. M. Bücheler, K. Müller, K. Uludağ, H. Obrig, G. Lohmann, M. Tittgemeyer, A. Villringer, and D. Y. von Cramon, “Towards a standard analysis for functional near-infrared imaging,” Neuroimage 21(1), 283–290 (2004).
[CrossRef] [PubMed]

M. L. Schroeter, S. Zysset, F. Kruggel, and D. Y. von Cramon, “Age dependency of the hemodynamic response as measured by functional near-infrared spectroscopy,” Neuroimage 19(3), 555–564 (2003).
[CrossRef] [PubMed]

Sessa, P.

R. Dell’Acqua, P. Sessa, P. Toffanin, R. Luria, and P. Jolicoeur, “Orienting attention to objects in visual short-term memory,” Neuropsychologia 48(2), 419–428 (2010).
[CrossRef]

R. Luria, P. Sessa, A. Gotler, P. Jolicoeur, and R. Dell’Acqua, “Visual short-term memory capacity for simple and complex objects,” J. Cogn. Neurosci. 22(3), 496–512 (2010).
[CrossRef]

P. Jolicoeur, P. Sessa, R. Dell’Acqua, and N. Robitaille, “On the control of visual spatial attention: evidence from human electrophysiology,” Psychol. Res. 70(6), 414–424 (2006).
[CrossRef]

Shimizu, K.

R. Sitaram, H. Zhang, C. Guan, M. Thulasidas, Y. Hoshi, A. Ishikawa, K. Shimizu, and N. Birbaumer, “Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain-computer interface,” Neuroimage 34(4), 1416–1427 (2007).
[CrossRef] [PubMed]

M. Okamoto, H. Dan, K. Sakamoto, K. Takeo, K. Shimizu, S. Kohno, I. Oda, S. Isobe, T. Suzuki, K. Kohyama, and I. Dan, “Three-dimensional probabilistic anatomical cranio-cerebral correlation via the international 10-20 system oriented for transcranial functional brain mapping,” Neuroimage 21(1), 99–111 (2004).
[CrossRef] [PubMed]

Siegel, A. M.

J. P. Culver, A. M. Siegel, M. A. Franceschini, J. B. Mandeville, and D. A. Boas, “Evidence that cerebral blood volume can provide brain activation maps with better spatial resolution than deoxygenated hemoglobin,” Neuroimage 27(4), 947–959 (2005).
[CrossRef] [PubMed]

Singh, A. K.

A. K. Singh, M. Okamoto, H. Dan, V. Jurcak, and I. Dan, “Spatial registration of multichannel multi-subject fNIRS data to MNI space without MRI,” Neuroimage 27(4), 842–851 (2005).
[CrossRef] [PubMed]

Sitaram, R.

R. Sitaram, H. Zhang, C. Guan, M. Thulasidas, Y. Hoshi, A. Ishikawa, K. Shimizu, and N. Birbaumer, “Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain-computer interface,” Neuroimage 34(4), 1416–1427 (2007).
[CrossRef] [PubMed]

Sparacino, G.

G. Sparacino, S. Milani, E. Arslan, and C. Cobelli, “A Bayesian approach to estimate evoked potentials,” Comput. Methods Programs Biomed. 68(3), 233–248 (2002).
[CrossRef] [PubMed]

Steinbrink, J.

S. P. Koch, S. Koendgen, R. Bourayou, J. Steinbrink, and H. Obrig, “Individual alpha-frequency correlates with amplitude of visual evoked potential and hemodynamic response,” Neuroimage 41(2), 233–242 (2008).
[CrossRef] [PubMed]

Strangman, G.

G. Jasdzewski, G. Strangman, J. Wagner, K. K. Kwong, R. A. Poldrack, and D. A. Boas, “Differences in the hemodynamic response to event-related motor and visual paradigms as measured by near-infrared spectroscopy,” Neuroimage 20(1), 479–488 (2003).
[CrossRef] [PubMed]

Strangman, G. E.

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

Suzuki, T.

H. Kojima and T. Suzuki, “Hemodynamic change in occipital lobe during visual search: visual attention allocation measured with NIRS,” Neuropsychologia 48(1), 349–352 (2010).
[CrossRef]

M. Okamoto, H. Dan, K. Sakamoto, K. Takeo, K. Shimizu, S. Kohno, I. Oda, S. Isobe, T. Suzuki, K. Kohyama, and I. Dan, “Three-dimensional probabilistic anatomical cranio-cerebral correlation via the international 10-20 system oriented for transcranial functional brain mapping,” Neuroimage 21(1), 99–111 (2004).
[CrossRef] [PubMed]

Taga, G.

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. U.S.A. 100(19), 10722–10727 (2003).
[CrossRef] [PubMed]

Tak, S.

J. C. Ye, S. Tak, K. E. Jang, J. Jung, and J. Jang, “NIRS-SPM: statistical parametric mapping for near-infrared spectroscopy,” Neuroimage 44(2), 428–447 (2009).
[CrossRef]

K. E. Jang, S. Tak, J. Jung, J. Jang, Y. Jeong, and J. C. Ye, “Wavelet minimum description length detrending for near-infrared spectroscopy,” J. Biomedical Opt . 14, 034004-(1–13) (2009).

Takeo, K.

M. Okamoto, H. Dan, K. Sakamoto, K. Takeo, K. Shimizu, S. Kohno, I. Oda, S. Isobe, T. Suzuki, K. Kohyama, and I. Dan, “Three-dimensional probabilistic anatomical cranio-cerebral correlation via the international 10-20 system oriented for transcranial functional brain mapping,” Neuroimage 21(1), 99–111 (2004).
[CrossRef] [PubMed]

Thulasidas, M.

R. Sitaram, H. Zhang, C. Guan, M. Thulasidas, Y. Hoshi, A. Ishikawa, K. Shimizu, and N. Birbaumer, “Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain-computer interface,” Neuroimage 34(4), 1416–1427 (2007).
[CrossRef] [PubMed]

Tittgemeyer, M.

M. L. Schroeter, M. M. Bücheler, K. Müller, K. Uludağ, H. Obrig, G. Lohmann, M. Tittgemeyer, A. Villringer, and D. Y. von Cramon, “Towards a standard analysis for functional near-infrared imaging,” Neuroimage 21(1), 283–290 (2004).
[CrossRef] [PubMed]

Todd, J. J.

N. Robitaille, R. Marois, J. J. Todd, S. Grimault, D. Cheyne, and P. Jolicoeur, “Distinguishing between lateralized and nonlateralized brain activity associated with visual short-term memory: fMRI, MEG, and EEG evidence from the same observers,” Neuroimage 53(4), 1334–1345 (2010).
[CrossRef] [PubMed]

J. J. Todd and R. Marois, “Capacity limit of visual short-term memory in human posterior parietal cortex,” Nature 428(6984), 751–754 (2004).
[CrossRef] [PubMed]

Toffanin, P.

R. Dell’Acqua, P. Sessa, P. Toffanin, R. Luria, and P. Jolicoeur, “Orienting attention to objects in visual short-term memory,” Neuropsychologia 48(2), 419–428 (2010).
[CrossRef]

Toronov, V.

M. A. Franceschini, V. Toronov, M. E. Filiaci, E. Gratton, and S. Fantini, “On-line optical imaging of the human brain with 160-ms temporal resolution,” Opt. Express 6(3), 49–57 (2000).
[CrossRef] [PubMed]

Tyszczuk, L.

A. Duncan, J. H. Meek, M. Clemence, C. E. Elwell, P. Fallon, L. Tyszczuk, M. Cope, and D. T. Delpy, “Measurement of cranial optical path length as a function of age using phase resolved near infrared spectroscopy,” Pediatr. Res. 39(5), 889–894 (1996).
[CrossRef] [PubMed]

Uludag, K.

M. L. Schroeter, M. M. Bücheler, K. Müller, K. Uludağ, H. Obrig, G. Lohmann, M. Tittgemeyer, A. Villringer, and D. Y. von Cramon, “Towards a standard analysis for functional near-infrared imaging,” Neuroimage 21(1), 283–290 (2004).
[CrossRef] [PubMed]

Van Huffel, S.

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]

VanMeter, J.

A. V. Medvedev, J. Kainerstorfer, S. V. Borisov, R. L. Barbour, and J. VanMeter, “Event-related fast optical signal in a rapid object recognition task: improving detection by the independent component analysis,” Brain Res. 1236, 145–158 (2008).
[CrossRef] [PubMed]

Villringer, A.

M. L. Schroeter, M. M. Bücheler, K. Müller, K. Uludağ, H. Obrig, G. Lohmann, M. Tittgemeyer, A. Villringer, and D. Y. von Cramon, “Towards a standard analysis for functional near-infrared imaging,” Neuroimage 21(1), 283–290 (2004).
[CrossRef] [PubMed]

H. Obrig and A. Villringer, “Beyond the visible--imaging the human brain with light,” J. Cereb. Blood Flow Metab. 23(1), 1–18 (2003).
[CrossRef]

von Cramon, D. Y.

M. L. Schroeter, M. M. Bücheler, K. Müller, K. Uludağ, H. Obrig, G. Lohmann, M. Tittgemeyer, A. Villringer, and D. Y. von Cramon, “Towards a standard analysis for functional near-infrared imaging,” Neuroimage 21(1), 283–290 (2004).
[CrossRef] [PubMed]

M. L. Schroeter, S. Zysset, F. Kruggel, and D. Y. von Cramon, “Age dependency of the hemodynamic response as measured by functional near-infrared spectroscopy,” Neuroimage 19(3), 555–564 (2003).
[CrossRef] [PubMed]

Wager, T. D.

M. A. Lindquist and T. D. Wager, “Validity and power in hemodynamic response modeling: a comparison study and a new approach,” Hum. Brain Mapp. 28(8), 764–784 (2007).
[CrossRef]

Wagner, J.

G. Jasdzewski, G. Strangman, J. Wagner, K. K. Kwong, R. A. Poldrack, and D. A. Boas, “Differences in the hemodynamic response to event-related motor and visual paradigms as measured by near-infrared spectroscopy,” Neuroimage 20(1), 479–488 (2003).
[CrossRef] [PubMed]

Wahl, M. M.

M. L. Schroeter, S. Cutini, M. M. Wahl, R. Scheid, and D. Yves von Cramon, “Neurovascular coupling is impaired in cerebral microangiopathy--An event-related Stroop study,” Neuroimage 34(1), 26–34 (2007).
[CrossRef]

Wolf, M.

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]

Wolf, U.

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]

Worley, A.

R. J. Cooper, N. L. Everdell, L. C. Enfield, A. P. Gibson, A. Worley, and J. C. Hebden, “Design and evaluation of a probe for simultaneous EEG and near-infrared imaging of cortical activation,” Phys. Med. Biol. 54(7), 2093–2102 (2009).
[CrossRef] [PubMed]

Xu, Y.

Y. Xu and M. M. Chun, “Dissociable neural mechanisms supporting visual short-term memory for objects,” Nature 440(7080), 91–95 (2006).
[CrossRef]

Ye, J. C.

J. C. Ye, S. Tak, K. E. Jang, J. Jung, and J. Jang, “NIRS-SPM: statistical parametric mapping for near-infrared spectroscopy,” Neuroimage 44(2), 428–447 (2009).
[CrossRef]

K. E. Jang, S. Tak, J. Jung, J. Jang, Y. Jeong, and J. C. Ye, “Wavelet minimum description length detrending for near-infrared spectroscopy,” J. Biomedical Opt . 14, 034004-(1–13) (2009).

Yves von Cramon, D.

M. L. Schroeter, S. Cutini, M. M. Wahl, R. Scheid, and D. Yves von Cramon, “Neurovascular coupling is impaired in cerebral microangiopathy--An event-related Stroop study,” Neuroimage 34(1), 26–34 (2007).
[CrossRef]

Zarahn, E.

G. K. Aguirre, E. Zarahn, and M. D’esposito, “The variability of human, BOLD hemodynamic responses,” Neuroimage 8(4), 360–369 (1998).
[CrossRef] [PubMed]

Zhang, H.

R. Sitaram, H. Zhang, C. Guan, M. Thulasidas, Y. Hoshi, A. Ishikawa, K. Shimizu, and N. Birbaumer, “Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain-computer interface,” Neuroimage 34(4), 1416–1427 (2007).
[CrossRef] [PubMed]

Zhang, Q.

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

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

Zhang, Y. H.

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

Zorzi, M.

S. Cutini, P. Scatturin, E. Menon, P. S. Bisiacchi, L. Gamberini, M. Zorzi, and R. Dell’Acqua, “Selective activation of the superior frontal gyrus in task-switching: an event-related fNIRS study,” Neuroimage 42(2), 945–955 (2008).
[CrossRef] [PubMed]

S. Cutini, P. Scatturin, and M. Zorzi, “A new method based on ICBM152 head surface for probe placement in multichannel fNIRS,” Neuroimage (to be published).
[PubMed]

Zysset, S.

M. L. Schroeter, S. Zysset, F. Kruggel, and D. Y. von Cramon, “Age dependency of the hemodynamic response as measured by functional near-infrared spectroscopy,” Neuroimage 19(3), 555–564 (2003).
[CrossRef] [PubMed]

Brain Res. (1)

A. V. Medvedev, J. Kainerstorfer, S. V. Borisov, R. L. Barbour, and J. VanMeter, “Event-related fast optical signal in a rapid object recognition task: improving detection by the independent component analysis,” Brain Res. 1236, 145–158 (2008).
[CrossRef] [PubMed]

Comput. Methods Programs Biomed. (1)

G. Sparacino, S. Milani, E. Arslan, and C. Cobelli, “A Bayesian approach to estimate evoked potentials,” Comput. Methods Programs Biomed. 68(3), 233–248 (2002).
[CrossRef] [PubMed]

Electroencephalogr. Clin. Neurophysiol. (1)

M. R. Nuwer, G. Comi, R. Emerson, A. Fuglsang-Frederiksen, J. M. Guérit, H. Hinrichs, A. Ikeda, F. J. Luccas, and P. Rappelsburger, The International Federation of Clinical Neurophysiology, “IFCN standards for digital recording of clinical EEG,” Electroencephalogr. Clin. Neurophysiol. 106(3), 259–261 (1998).
[CrossRef] [PubMed]

Hum. Brain Mapp. (1)

M. A. Lindquist and T. D. Wager, “Validity and power in hemodynamic response modeling: a comparison study and a new approach,” Hum. Brain Mapp. 28(8), 764–784 (2007).
[CrossRef]

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

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

J. Biomed. Opt. (3)

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

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]

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]

J. Biomedical Opt (1)

K. E. Jang, S. Tak, J. Jung, J. Jang, Y. Jeong, and J. C. Ye, “Wavelet minimum description length detrending for near-infrared spectroscopy,” J. Biomedical Opt . 14, 034004-(1–13) (2009).

J. Cereb. Blood Flow Metab. (1)

H. Obrig and A. Villringer, “Beyond the visible--imaging the human brain with light,” J. Cereb. Blood Flow Metab. 23(1), 1–18 (2003).
[CrossRef]

J. Cogn. Neurosci. (1)

R. Luria, P. Sessa, A. Gotler, P. Jolicoeur, and R. Dell’Acqua, “Visual short-term memory capacity for simple and complex objects,” J. Cogn. Neurosci. 22(3), 496–512 (2010).
[CrossRef]

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

V. Kolehmainen, S. Prince, S. R. Arridge, and J. P. Kaipio, “State-estimation approach to the nonstationary optical tomography problem,” J. Opt. Soc. Am. A 20(5), 876–889 (2003).
[CrossRef]

J. R. Stat. Soc., B (1)

Y. Benjamini and Y. Hochberg, “Controlling the false discovery rate: a practical and powerful approach to multiple testing,” J. R. Stat. Soc., B 57, 289–300 (1995).

Med. Biol. Eng. Comput. (3)

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]

C. B. Akgül, A. Akin, and B. Sankur, “Extraction of cognitive activity-related waveforms from functional near-infrared spectroscopy signals,” Med. Biol. Eng. Comput. 44(11), 945–958 (2006).
[CrossRef] [PubMed]

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

Nature (2)

J. J. Todd and R. Marois, “Capacity limit of visual short-term memory in human posterior parietal cortex,” Nature 428(6984), 751–754 (2004).
[CrossRef] [PubMed]

Y. Xu and M. M. Chun, “Dissociable neural mechanisms supporting visual short-term memory for objects,” Nature 440(7080), 91–95 (2006).
[CrossRef]

Neuroimage (17)

R. Sitaram, H. Zhang, C. Guan, M. Thulasidas, Y. Hoshi, A. Ishikawa, K. Shimizu, and N. Birbaumer, “Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain-computer interface,” Neuroimage 34(4), 1416–1427 (2007).
[CrossRef] [PubMed]

S. Cutini, P. Scatturin, E. Menon, P. S. Bisiacchi, L. Gamberini, M. Zorzi, and R. Dell’Acqua, “Selective activation of the superior frontal gyrus in task-switching: an event-related fNIRS study,” Neuroimage 42(2), 945–955 (2008).
[CrossRef] [PubMed]

M. L. Schroeter, S. Zysset, F. Kruggel, and D. Y. von Cramon, “Age dependency of the hemodynamic response as measured by functional near-infrared spectroscopy,” Neuroimage 19(3), 555–564 (2003).
[CrossRef] [PubMed]

M. L. Schroeter, S. Cutini, M. M. Wahl, R. Scheid, and D. Yves von Cramon, “Neurovascular coupling is impaired in cerebral microangiopathy--An event-related Stroop study,” Neuroimage 34(1), 26–34 (2007).
[CrossRef]

A. K. Singh, M. Okamoto, H. Dan, V. Jurcak, and I. Dan, “Spatial registration of multichannel multi-subject fNIRS data to MNI space without MRI,” Neuroimage 27(4), 842–851 (2005).
[CrossRef] [PubMed]

A. F. Abdelnour and T. J. Huppert, “Real-time imaging of human brain function by near-infrared spectroscopy using an adaptive general linear model,” Neuroimage 46(1), 133–143 (2009).
[CrossRef] [PubMed]

J. C. Ye, S. Tak, K. E. Jang, J. Jung, and J. Jang, “NIRS-SPM: statistical parametric mapping for near-infrared spectroscopy,” Neuroimage 44(2), 428–447 (2009).
[CrossRef]

M. L. Schroeter, M. M. Bücheler, K. Müller, K. Uludağ, H. Obrig, G. Lohmann, M. Tittgemeyer, A. Villringer, and D. Y. von Cramon, “Towards a standard analysis for functional near-infrared imaging,” Neuroimage 21(1), 283–290 (2004).
[CrossRef] [PubMed]

S. P. Koch, S. Koendgen, R. Bourayou, J. Steinbrink, and H. Obrig, “Individual alpha-frequency correlates with amplitude of visual evoked potential and hemodynamic response,” Neuroimage 41(2), 233–242 (2008).
[CrossRef] [PubMed]

G. Jasdzewski, G. Strangman, J. Wagner, K. K. Kwong, R. A. Poldrack, and D. A. Boas, “Differences in the hemodynamic response to event-related motor and visual paradigms as measured by near-infrared spectroscopy,” Neuroimage 20(1), 479–488 (2003).
[CrossRef] [PubMed]

S. G. Diamond, T. J. Huppert, V. Kolehmainen, M. A. Franceschini, J. P. Kaipio, S. R. Arridge, and D. A. Boas, “Dynamic physiological modeling for functional diffuse optical tomography,” Neuroimage 30(1), 88–101 (2006).
[CrossRef]

G. K. Aguirre, E. Zarahn, and M. D’esposito, “The variability of human, BOLD hemodynamic responses,” Neuroimage 8(4), 360–369 (1998).
[CrossRef] [PubMed]

N. Robitaille, R. Marois, J. J. Todd, S. Grimault, D. Cheyne, and P. Jolicoeur, “Distinguishing between lateralized and nonlateralized brain activity associated with visual short-term memory: fMRI, MEG, and EEG evidence from the same observers,” Neuroimage 53(4), 1334–1345 (2010).
[CrossRef] [PubMed]

J. P. Culver, A. M. Siegel, M. A. Franceschini, J. B. Mandeville, and D. A. Boas, “Evidence that cerebral blood volume can provide brain activation maps with better spatial resolution than deoxygenated hemoglobin,” Neuroimage 27(4), 947–959 (2005).
[CrossRef] [PubMed]

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

M. Okamoto, H. Dan, K. Sakamoto, K. Takeo, K. Shimizu, S. Kohno, I. Oda, S. Isobe, T. Suzuki, K. Kohyama, and I. Dan, “Three-dimensional probabilistic anatomical cranio-cerebral correlation via the international 10-20 system oriented for transcranial functional brain mapping,” Neuroimage 21(1), 99–111 (2004).
[CrossRef] [PubMed]

S. Cutini, P. Scatturin, and M. Zorzi, “A new method based on ICBM152 head surface for probe placement in multichannel fNIRS,” Neuroimage (to be published).
[PubMed]

Neuropsychologia (2)

R. Dell’Acqua, P. Sessa, P. Toffanin, R. Luria, and P. Jolicoeur, “Orienting attention to objects in visual short-term memory,” Neuropsychologia 48(2), 419–428 (2010).
[CrossRef]

H. Kojima and T. Suzuki, “Hemodynamic change in occipital lobe during visual search: visual attention allocation measured with NIRS,” Neuropsychologia 48(1), 349–352 (2010).
[CrossRef]

Opt. Express (1)

M. A. Franceschini, V. Toronov, M. E. Filiaci, E. Gratton, and S. Fantini, “On-line optical imaging of the human brain with 160-ms temporal resolution,” Opt. Express 6(3), 49–57 (2000).
[CrossRef] [PubMed]

Pediatr. Res. (1)

A. Duncan, J. H. Meek, M. Clemence, C. E. Elwell, P. Fallon, L. Tyszczuk, M. Cope, and D. T. Delpy, “Measurement of cranial optical path length as a function of age using phase resolved near infrared spectroscopy,” Pediatr. Res. 39(5), 889–894 (1996).
[CrossRef] [PubMed]

Philos. Transact. A Math. Phys. Eng. Sci. (1)

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

Phys. Med. Biol. (2)

R. J. Cooper, N. L. Everdell, L. C. Enfield, A. P. Gibson, A. Worley, and J. C. Hebden, “Design and evaluation of a probe for simultaneous EEG and near-infrared imaging of cortical activation,” Phys. Med. Biol. 54(7), 2093–2102 (2009).
[CrossRef] [PubMed]

S. Prince, V. Kolehmainen, J. P. Kaipio, M. A. Franceschini, D. A. Boas, and S. R. Arridge, “Time-series estimation of biological factors in optical diffusion tomography,” Phys. Med. Biol. 48(11), 1491–1504 (2003).
[CrossRef] [PubMed]

Proc. Natl. Acad. Sci. U.S.A. (1)

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. U.S.A. 100(19), 10722–10727 (2003).
[CrossRef] [PubMed]

Psychol. Res. (1)

P. Jolicoeur, P. Sessa, R. Dell’Acqua, and N. Robitaille, “On the control of visual spatial attention: evidence from human electrophysiology,” Psychol. Res. 70(6), 414–424 (2006).
[CrossRef]

Technometrics (1)

F. E. Grubbs, “Procedures for detecting outlying observations in samples,” Technometrics 11(1), 1–21 (1969).
[CrossRef]

Other (4)

A. Devaraj, “Signal Processing for functional near-infrared neuroimaging,” Unpublished M. S. Thesis, Drexel University, (2005).

S. Tak, K. E. Jang, J. W. Jung, J. Jang, and J. C. Ye, “General Linear Model and Inference for Near Infrared Spectroscopy using Global Confidence Region Analysis,” in Proceedings of IEEE Conference on International Symposium on Biomedical Imaging (ISBI), pp. 476–479 (2008).

D. A. Boas, M. A. Franceschini, A. K. Dunn, and G. Strangman, “Noninvasive Imaging of Cerebral Activation with Diffuse Optical Tomography,”in Vivo Optical Imaging of Brain Function. E. D. (CRC Press), Chap 8, pp. 193–221, (2002)

S. M. Zeki, A vision of the brain, (Blackwell Scientific Publications, Oxford, UK, 1993).

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Figures (7)

Fig. 1
Fig. 1

Sequence of visual events on each trial of the present experiment (see text for a full description).

Fig. 2
Fig. 2

Probe placement on the ICBM152 template (occipital view). (a) Sources (red circles) and detectors (black circles) overlaid on the head surface of the ICBM152-PM template; (b) Cerebral projections of sources (white circles) and detectors (black circles) overlaid on the ICBM152 brain template.

Fig. 3
Fig. 3

Two representative simulated subjects (1 and 12). True HRF (green) and HRF estimated with CA (blue), Bayesian filtering (red) and Band-pass filtering (magenta).

Fig. 4
Fig. 4

(a) Representative ΔHbO trial, raw data (blue), Bayesian filtered data (red) and band-pass filtered data (yellow), channel A4 of subject 1, trial 5; (b) Estimated HRF using CA (blue), Bayesian filter (red) and band-pass filter (yellow) in channel A2 of subject 9, N = 37.

Fig. 5
Fig. 5

(a) Representative ΔHbR trial, raw data (blue), Bayesian filtered data (red) and band-pass filtered data (yellow), channel D3 of subject 8, trial 52; (b) Estimated HRF using CA (blue), Bayesian filter (red) and band-pass filter (yellow) in channel D3 of subject 8, N = 55.

Fig. 6
Fig. 6

Occipital and top views of the statistical maps of contralateral vs. ipsilateral comparison, for ΔHbO. The maps have been overlaid onto the ICBM152 brain template. For illustrative purposes, the upper part of the figure shows examples of memory arrays with the hemifields including the to-be-memorized colored squares (contralateral to the hemisphere where the enhanced concentration of HbT and HbO was observed in the present study) cued by arrow heads. Note however that colored squares and arrow heads were never displayed synchronously during the experiment (see Fig. 1).

Fig. 7
Fig. 7

Mean response profiles for ΔHbO (red) and ΔHbR (green) (left panel) and ΔHbT (right panel) recorded at B4/D4 (IPS/IOS). Dashed line: ipsilateral activation function. Solid line: contralateral activation function.

Tables (4)

Tables Icon

Table 1 Estimation error, computed on the true HRF, obtained, from N = XX simulated trials, using conventional averaging (CA), Bayesian filtering (Bayesian) and band-pass filter (Band-pass).

Tables Icon

Table 2 CNR values (mean ± SD) in single trial and in estimated HRF, for ΔHbO and ΔHbR. They were obtained using conventional averaging (CA), Bayesian filter (Bayesian) and band-pass filter (Band-pass).

Tables Icon

Table 3 p-values obtained with Bayesian filter and band-pass filter in the contralateral condition, for ΔHbO and ΔHbT.

Tables Icon

Table 4 p-values obtained with Bayesian filter and band-pass filter by Contralateral vs Ipsilateral, for ΔHbO and ΔHbT.

Equations (10)

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

DPF HbO  = 5 .13 + 0 .07 × (age 0 .81 ), DPF HbR  = 4 .67 + 0 .062 × (age 0 .877 ) .
y =  ​ u + v,
Σ v  = σ 2  ( A T  A ) -1 ,
Σ u  = λ 2  ( F T  F ) -1 ,
u k  = u k-1  + ε k ;                 k = 1, 2,  ... , n;              u 0  = 0
u ^   =   (   A T   A   +   γ   F T   F   ) - 1   A T   A   y ,
u ¯   =   (   i = 1 , ... , N   u ^ i   )   /   N ,
u t r u e ( t )   =   α   ×   [   Γ ( t , τ 1 , φ 1 )   -   β   ×   Γ ( t , τ 2 , φ 2 )   ] ,
v ( t )   =   i = { 1 , 2 , 3 } [ a i   ×   sin (   2 π   f i   t   +   θ i   ) ]   +   η ( t ) .
E   =   100   ×     u t r u e   -   u ¯   2   u t r u e   2 ,

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