Abstract

The analysis of diffuse optical imaging (DOI) data has seen significant developments over the last few years. When compared to fMRI, signals originating from optical imaging are tainted by more physiology and the separation of activation from this background can be difficult in some cases. In this work, we show that the use of time-frequency techniques based on wavelets distinguish different physiological sources from the evoked response to a given stimulus. In particular, we show that analytical complex wavelets identify synchronies in the signal at different scales. These synchronies are then used to extract activation information from the DOI data in order to estimate the evoked hemodynamic response or to define a new type of contrast between two conditions. This work presents both simulations and applications with real data (visual stimulation and motor tasks experiments).

© 2008 Optical Society of America

Full Article  |  PDF Article

References

  • View by:
  • |
  • |
  • |

  1. F. Jobsis, "Noninvasive infrared monitoring of cerebral and myocardial sufficiency and circulatory parameters," Science 198, 1264-1267 (1977).
    [CrossRef] [PubMed]
  2. A. Yodh and B. Chance, "Spectroscopy and imaging with diffusing light," Phys. Today 48, 34-40 (1995).
    [CrossRef]
  3. G. Gratton, M. Fabiani, T. Elbert and B. Rockstroh, "Seeing right through you: applications of optical imaging to the study of the human brain," Psychophysiology 40, 487-491 (2003).
    [CrossRef] [PubMed]
  4. A. A. Baird, J. Kagan, T. Gaudette, K. A. Walz, N. Hershlag and D. A. Boas, "Frontal lobe activation during object permanence: data from near-infrared spectroscopy," NeuroImage. 16, 1120-1126 (2002).
    [CrossRef] [PubMed]
  5. H. Kato, M. Izumiyama, H. Koizumi, A. Takahashi and Y. Itoyama, "Near-infrared spectroscopic topography as a tool to monitor motor reorganization after hemiparetic stroke: a comparison with functional MRI," Stroke 33, 2032-2036 (2002).
    [CrossRef] [PubMed]
  6. J. Cohen-Adad, S. Chapuisat, J. Doyon, J.M. Lina, H. Benali and F. Lesage, "Application of the general linear model to response estimation in optical imaging," Medical Imaging Analysis 11, 616-629 (2007).
    [CrossRef]
  7. 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, 88-101 (2006).
    [CrossRef]
  8. 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, 054007 (2006).
    [CrossRef] [PubMed]
  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, 876-889 (2003).
    [CrossRef]
  10. A. Li, G. Boverman, Y. H. Zhang, D. Brooks, E. L. Miller, M. E. Kilmer, Q. Zhang, E. M. C. Hillman and D. A. Boas, "Optimal linear inverse solution with multiple priors in diffuse optical tomography," Appl. Opt. 44, 1948-1956 (2005).
    [CrossRef] [PubMed]
  11. S. Prince, V. Kolehmainen, J. P. Kaipio, M. A. Franceschini, D. Boas and S. R. Arridge, "Time-series estimation of biological factors in optical diffusion tomography," Phys. Med. Biol. 48, 1491-504 (2003).
    [CrossRef] [PubMed]
  12. Y. Zhang, D. H. Brooks and D. A. Boas, "A haemodynamic response function model in spatio-temporal diffuse optical tomography," Phys. Med. Biol. 50, 4625-44, (2005).
    [CrossRef] [PubMed]
  13. Y. Meyer, Wavelets: Algorithms and Applications, (SIAM, Philadelphia, 1993).
  14. Recordings done in D. A. Boas laboratory, MGH (http://www.nmr.mgh.harvard.edu/PMI/).
  15. D. A. Boas, A. M. Dale and M. A. Franceschini, "Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution and accuracy," NeuroImage 23, S275-S288 (2004).
    [CrossRef] [PubMed]
  16. A. T. Smith, A. L. Williams and K. D. Singh, "Negative BOLD in the visual cortex: evidence against blood stealing," Human Brain Mapping 21, 213-220, (2004).
    [CrossRef] [PubMed]
  17. A. Shmuel, E. Yacoub, J. Pfeuffer, P.F. Van de Moortele, G. Adriany, X. Hu and K. Ugurbil, "Sustained negative BOLD, blood flow and oxygen consumption response and Its coupling to the positive response in the human brain," Neuron 36, 1195-1210, (2002).
    [CrossRef] [PubMed]
  18. F. G. Meyer, "Wavelet-based estimation of a semiparametric generalized linear model of fMRI time-series," IEEE Trans. Med. Imaging 22, 315-322 (2003).
    [CrossRef] [PubMed]
  19. S. Mallat, A Wavelet Tour of Signal Processing, (Academic Press, 1998).
  20. B. Torresani, Analyse continue par ondelettes, (CNRS Editions, 1995).
  21. I. Daubechies, Ten lectures on wavelets, (SIAM Philadelphia, 1992).
    [CrossRef]
  22. H. Obrig, M. Neufang, R. Wenzel, M. Kohl, J. Steinbrink, K. Einhaupl and A. Villringer, "Spontaneous low frequency oscillations of cerebral hemodynamics and metabolism in human adults," NeuroImage 12, 623-639 (2000).
    [CrossRef] [PubMed]
  23. C. Julien, "The enigma of Mayer waves: facts and model," Cardiovasc. Res. 70, 12-21 (2006).
    [CrossRef]
  24. S. Bayard, N. Gosselin, M. Robert, M. Lassonde, "Inter- and Intra-hemispheric Processing of visual event related potentials in the absence of the corpus callosum," J. Cognitive Neuroscience 16, 1-14 (2004).
    [CrossRef]
  25. M. Dehaes, L. Gagnon, M. Desjardins, R. M. Comeau and F. Lesage, "Positive responses in diffuse optical imaging and their relation to the negative BOLD effect," in preparation, (2007).
  26. G. W. Wornell, A karhunen-loeve-like expansion for 1/f process via wavelets. IEEE Trans. Inf. Theory 36, 859- 861 (1990).
    [CrossRef]
  27. G. W. Wornell, Signal Processing with Fractals: A wavelet-based approach, (Prentice Hall, 1996).
  28. P. Flandrin, "Wavelet analysis and synthesis of fractional brownian motion," IEEE Trans. Inf. Theory 38, 910-917 (1992)
    [CrossRef]
  29. A. H. Tewfik and M. Kim, "Correlation structure of the discrete wavelet coefficients of fractional Brownian motion," IEEE Trans. Inf. Theory 38, 904-909 (1992).
    [CrossRef]
  30. M. J. Fadili and E. T. Bullmore, "Wavelet-Generalized Least Squares: A New BLU Estimator of Linear Regression Models with 1/f Errors," Neuroimage 15, 217-232 (2002).
    [CrossRef] [PubMed]

2007 (1)

J. Cohen-Adad, S. Chapuisat, J. Doyon, J.M. Lina, H. Benali and F. Lesage, "Application of the general linear model to response estimation in optical imaging," Medical Imaging Analysis 11, 616-629 (2007).
[CrossRef]

2006 (3)

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, 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, 054007 (2006).
[CrossRef] [PubMed]

C. Julien, "The enigma of Mayer waves: facts and model," Cardiovasc. Res. 70, 12-21 (2006).
[CrossRef]

2005 (2)

2004 (3)

D. A. Boas, A. M. Dale and M. A. Franceschini, "Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution and accuracy," NeuroImage 23, S275-S288 (2004).
[CrossRef] [PubMed]

A. T. Smith, A. L. Williams and K. D. Singh, "Negative BOLD in the visual cortex: evidence against blood stealing," Human Brain Mapping 21, 213-220, (2004).
[CrossRef] [PubMed]

S. Bayard, N. Gosselin, M. Robert, M. Lassonde, "Inter- and Intra-hemispheric Processing of visual event related potentials in the absence of the corpus callosum," J. Cognitive Neuroscience 16, 1-14 (2004).
[CrossRef]

2003 (4)

F. G. Meyer, "Wavelet-based estimation of a semiparametric generalized linear model of fMRI time-series," IEEE Trans. Med. Imaging 22, 315-322 (2003).
[CrossRef] [PubMed]

S. Prince, V. Kolehmainen, J. P. Kaipio, M. A. Franceschini, D. Boas and S. R. Arridge, "Time-series estimation of biological factors in optical diffusion tomography," Phys. Med. Biol. 48, 1491-504 (2003).
[CrossRef] [PubMed]

G. Gratton, M. Fabiani, T. Elbert and B. Rockstroh, "Seeing right through you: applications of optical imaging to the study of the human brain," Psychophysiology 40, 487-491 (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, 876-889 (2003).
[CrossRef]

2002 (4)

M. J. Fadili and E. T. Bullmore, "Wavelet-Generalized Least Squares: A New BLU Estimator of Linear Regression Models with 1/f Errors," Neuroimage 15, 217-232 (2002).
[CrossRef] [PubMed]

A. A. Baird, J. Kagan, T. Gaudette, K. A. Walz, N. Hershlag and D. A. Boas, "Frontal lobe activation during object permanence: data from near-infrared spectroscopy," NeuroImage. 16, 1120-1126 (2002).
[CrossRef] [PubMed]

H. Kato, M. Izumiyama, H. Koizumi, A. Takahashi and Y. Itoyama, "Near-infrared spectroscopic topography as a tool to monitor motor reorganization after hemiparetic stroke: a comparison with functional MRI," Stroke 33, 2032-2036 (2002).
[CrossRef] [PubMed]

A. Shmuel, E. Yacoub, J. Pfeuffer, P.F. Van de Moortele, G. Adriany, X. Hu and K. Ugurbil, "Sustained negative BOLD, blood flow and oxygen consumption response and Its coupling to the positive response in the human brain," Neuron 36, 1195-1210, (2002).
[CrossRef] [PubMed]

2000 (1)

H. Obrig, M. Neufang, R. Wenzel, M. Kohl, J. Steinbrink, K. Einhaupl and A. Villringer, "Spontaneous low frequency oscillations of cerebral hemodynamics and metabolism in human adults," NeuroImage 12, 623-639 (2000).
[CrossRef] [PubMed]

1995 (1)

A. Yodh and B. Chance, "Spectroscopy and imaging with diffusing light," Phys. Today 48, 34-40 (1995).
[CrossRef]

1992 (2)

P. Flandrin, "Wavelet analysis and synthesis of fractional brownian motion," IEEE Trans. Inf. Theory 38, 910-917 (1992)
[CrossRef]

A. H. Tewfik and M. Kim, "Correlation structure of the discrete wavelet coefficients of fractional Brownian motion," IEEE Trans. Inf. Theory 38, 904-909 (1992).
[CrossRef]

1990 (1)

G. W. Wornell, A karhunen-loeve-like expansion for 1/f process via wavelets. IEEE Trans. Inf. Theory 36, 859- 861 (1990).
[CrossRef]

1977 (1)

F. Jobsis, "Noninvasive infrared monitoring of cerebral and myocardial sufficiency and circulatory parameters," Science 198, 1264-1267 (1977).
[CrossRef] [PubMed]

Adriany, G.

A. Shmuel, E. Yacoub, J. Pfeuffer, P.F. Van de Moortele, G. Adriany, X. Hu and K. Ugurbil, "Sustained negative BOLD, blood flow and oxygen consumption response and Its coupling to the positive response in the human brain," Neuron 36, 1195-1210, (2002).
[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, 88-101 (2006).
[CrossRef]

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, 876-889 (2003).
[CrossRef]

S. Prince, V. Kolehmainen, J. P. Kaipio, M. A. Franceschini, D. Boas and S. R. Arridge, "Time-series estimation of biological factors in optical diffusion tomography," Phys. Med. Biol. 48, 1491-504 (2003).
[CrossRef] [PubMed]

Baird, A. A.

A. A. Baird, J. Kagan, T. Gaudette, K. A. Walz, N. Hershlag and D. A. Boas, "Frontal lobe activation during object permanence: data from near-infrared spectroscopy," NeuroImage. 16, 1120-1126 (2002).
[CrossRef] [PubMed]

Bayard, S.

S. Bayard, N. Gosselin, M. Robert, M. Lassonde, "Inter- and Intra-hemispheric Processing of visual event related potentials in the absence of the corpus callosum," J. Cognitive Neuroscience 16, 1-14 (2004).
[CrossRef]

Benali, H.

J. Cohen-Adad, S. Chapuisat, J. Doyon, J.M. Lina, H. Benali and F. Lesage, "Application of the general linear model to response estimation in optical imaging," Medical Imaging Analysis 11, 616-629 (2007).
[CrossRef]

Boas, D.

S. Prince, V. Kolehmainen, J. P. Kaipio, M. A. Franceschini, D. Boas and S. R. Arridge, "Time-series estimation of biological factors in optical diffusion tomography," Phys. Med. Biol. 48, 1491-504 (2003).
[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, 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, 054007 (2006).
[CrossRef] [PubMed]

Y. Zhang, D. H. Brooks and D. A. Boas, "A haemodynamic response function model in spatio-temporal diffuse optical tomography," Phys. Med. Biol. 50, 4625-44, (2005).
[CrossRef] [PubMed]

A. Li, G. Boverman, Y. H. Zhang, D. Brooks, E. L. Miller, M. E. Kilmer, Q. Zhang, E. M. C. Hillman and D. A. Boas, "Optimal linear inverse solution with multiple priors in diffuse optical tomography," Appl. Opt. 44, 1948-1956 (2005).
[CrossRef] [PubMed]

D. A. Boas, A. M. Dale and M. A. Franceschini, "Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution and accuracy," NeuroImage 23, S275-S288 (2004).
[CrossRef] [PubMed]

A. A. Baird, J. Kagan, T. Gaudette, K. A. Walz, N. Hershlag and D. A. Boas, "Frontal lobe activation during object permanence: data from near-infrared spectroscopy," NeuroImage. 16, 1120-1126 (2002).
[CrossRef] [PubMed]

Boverman, G.

Brooks, D.

Brooks, D. H.

Y. Zhang, D. H. Brooks and D. A. Boas, "A haemodynamic response function model in spatio-temporal diffuse optical tomography," Phys. Med. Biol. 50, 4625-44, (2005).
[CrossRef] [PubMed]

Bullmore, E. T.

M. J. Fadili and E. T. Bullmore, "Wavelet-Generalized Least Squares: A New BLU Estimator of Linear Regression Models with 1/f Errors," Neuroimage 15, 217-232 (2002).
[CrossRef] [PubMed]

Chance, B.

A. Yodh and B. Chance, "Spectroscopy and imaging with diffusing light," Phys. Today 48, 34-40 (1995).
[CrossRef]

Chapuisat, S.

J. Cohen-Adad, S. Chapuisat, J. Doyon, J.M. Lina, H. Benali and F. Lesage, "Application of the general linear model to response estimation in optical imaging," Medical Imaging Analysis 11, 616-629 (2007).
[CrossRef]

Cohen-Adad, J.

J. Cohen-Adad, S. Chapuisat, J. Doyon, J.M. Lina, H. Benali and F. Lesage, "Application of the general linear model to response estimation in optical imaging," Medical Imaging Analysis 11, 616-629 (2007).
[CrossRef]

Dale, A. M.

D. A. Boas, A. M. Dale and M. A. Franceschini, "Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution and accuracy," NeuroImage 23, S275-S288 (2004).
[CrossRef] [PubMed]

Diamond,

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, 88-101 (2006).
[CrossRef]

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, 054007 (2006).
[CrossRef] [PubMed]

Doyon, J.

J. Cohen-Adad, S. Chapuisat, J. Doyon, J.M. Lina, H. Benali and F. Lesage, "Application of the general linear model to response estimation in optical imaging," Medical Imaging Analysis 11, 616-629 (2007).
[CrossRef]

Einhaupl, K.

H. Obrig, M. Neufang, R. Wenzel, M. Kohl, J. Steinbrink, K. Einhaupl and A. Villringer, "Spontaneous low frequency oscillations of cerebral hemodynamics and metabolism in human adults," NeuroImage 12, 623-639 (2000).
[CrossRef] [PubMed]

Elbert, T.

G. Gratton, M. Fabiani, T. Elbert and B. Rockstroh, "Seeing right through you: applications of optical imaging to the study of the human brain," Psychophysiology 40, 487-491 (2003).
[CrossRef] [PubMed]

Fabiani, M.

G. Gratton, M. Fabiani, T. Elbert and B. Rockstroh, "Seeing right through you: applications of optical imaging to the study of the human brain," Psychophysiology 40, 487-491 (2003).
[CrossRef] [PubMed]

Fadili, M. J.

M. J. Fadili and E. T. Bullmore, "Wavelet-Generalized Least Squares: A New BLU Estimator of Linear Regression Models with 1/f Errors," Neuroimage 15, 217-232 (2002).
[CrossRef] [PubMed]

Flandrin, P.

P. Flandrin, "Wavelet analysis and synthesis of fractional brownian motion," IEEE Trans. Inf. Theory 38, 910-917 (1992)
[CrossRef]

Franceschini,

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, 054007 (2006).
[CrossRef] [PubMed]

Franceschini, M. 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, 88-101 (2006).
[CrossRef]

D. A. Boas, A. M. Dale and M. A. Franceschini, "Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution and accuracy," NeuroImage 23, S275-S288 (2004).
[CrossRef] [PubMed]

S. Prince, V. Kolehmainen, J. P. Kaipio, M. A. Franceschini, D. Boas and S. R. Arridge, "Time-series estimation of biological factors in optical diffusion tomography," Phys. Med. Biol. 48, 1491-504 (2003).
[CrossRef] [PubMed]

Gaudette, T.

A. A. Baird, J. Kagan, T. Gaudette, K. A. Walz, N. Hershlag and D. A. Boas, "Frontal lobe activation during object permanence: data from near-infrared spectroscopy," NeuroImage. 16, 1120-1126 (2002).
[CrossRef] [PubMed]

Gosselin, N.

S. Bayard, N. Gosselin, M. Robert, M. Lassonde, "Inter- and Intra-hemispheric Processing of visual event related potentials in the absence of the corpus callosum," J. Cognitive Neuroscience 16, 1-14 (2004).
[CrossRef]

Gratton, G.

G. Gratton, M. Fabiani, T. Elbert and B. Rockstroh, "Seeing right through you: applications of optical imaging to the study of the human brain," Psychophysiology 40, 487-491 (2003).
[CrossRef] [PubMed]

Hershlag, N.

A. A. Baird, J. Kagan, T. Gaudette, K. A. Walz, N. Hershlag and D. A. Boas, "Frontal lobe activation during object permanence: data from near-infrared spectroscopy," NeuroImage. 16, 1120-1126 (2002).
[CrossRef] [PubMed]

Hillman, E. M. C.

Hu, X.

A. Shmuel, E. Yacoub, J. Pfeuffer, P.F. Van de Moortele, G. Adriany, X. Hu and K. Ugurbil, "Sustained negative BOLD, blood flow and oxygen consumption response and Its coupling to the positive response in the human brain," Neuron 36, 1195-1210, (2002).
[CrossRef] [PubMed]

Huppert, T. J.

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, 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, 054007 (2006).
[CrossRef] [PubMed]

Itoyama, Y.

H. Kato, M. Izumiyama, H. Koizumi, A. Takahashi and Y. Itoyama, "Near-infrared spectroscopic topography as a tool to monitor motor reorganization after hemiparetic stroke: a comparison with functional MRI," Stroke 33, 2032-2036 (2002).
[CrossRef] [PubMed]

Izumiyama, M.

H. Kato, M. Izumiyama, H. Koizumi, A. Takahashi and Y. Itoyama, "Near-infrared spectroscopic topography as a tool to monitor motor reorganization after hemiparetic stroke: a comparison with functional MRI," Stroke 33, 2032-2036 (2002).
[CrossRef] [PubMed]

Jobsis, F.

F. Jobsis, "Noninvasive infrared monitoring of cerebral and myocardial sufficiency and circulatory parameters," Science 198, 1264-1267 (1977).
[CrossRef] [PubMed]

Joseph, D. K.

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

Julien, C.

C. Julien, "The enigma of Mayer waves: facts and model," Cardiovasc. Res. 70, 12-21 (2006).
[CrossRef]

Kagan, J.

A. A. Baird, J. Kagan, T. Gaudette, K. A. Walz, N. Hershlag and D. A. Boas, "Frontal lobe activation during object permanence: data from near-infrared spectroscopy," NeuroImage. 16, 1120-1126 (2002).
[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, 88-101 (2006).
[CrossRef]

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, 876-889 (2003).
[CrossRef]

S. Prince, V. Kolehmainen, J. P. Kaipio, M. A. Franceschini, D. Boas and S. R. Arridge, "Time-series estimation of biological factors in optical diffusion tomography," Phys. Med. Biol. 48, 1491-504 (2003).
[CrossRef] [PubMed]

Kato, H.

H. Kato, M. Izumiyama, H. Koizumi, A. Takahashi and Y. Itoyama, "Near-infrared spectroscopic topography as a tool to monitor motor reorganization after hemiparetic stroke: a comparison with functional MRI," Stroke 33, 2032-2036 (2002).
[CrossRef] [PubMed]

Kilmer, M. E.

Kim, M.

A. H. Tewfik and M. Kim, "Correlation structure of the discrete wavelet coefficients of fractional Brownian motion," IEEE Trans. Inf. Theory 38, 904-909 (1992).
[CrossRef]

Kohl, M.

H. Obrig, M. Neufang, R. Wenzel, M. Kohl, J. Steinbrink, K. Einhaupl and A. Villringer, "Spontaneous low frequency oscillations of cerebral hemodynamics and metabolism in human adults," NeuroImage 12, 623-639 (2000).
[CrossRef] [PubMed]

Koizumi, H.

H. Kato, M. Izumiyama, H. Koizumi, A. Takahashi and Y. Itoyama, "Near-infrared spectroscopic topography as a tool to monitor motor reorganization after hemiparetic stroke: a comparison with functional MRI," Stroke 33, 2032-2036 (2002).
[CrossRef] [PubMed]

Kolehmainen,

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, 88-101 (2006).
[CrossRef]

S. Prince, V. Kolehmainen, J. P. Kaipio, M. A. Franceschini, D. Boas and S. R. Arridge, "Time-series estimation of biological factors in optical diffusion tomography," Phys. Med. Biol. 48, 1491-504 (2003).
[CrossRef] [PubMed]

Lassonde, M.

S. Bayard, N. Gosselin, M. Robert, M. Lassonde, "Inter- and Intra-hemispheric Processing of visual event related potentials in the absence of the corpus callosum," J. Cognitive Neuroscience 16, 1-14 (2004).
[CrossRef]

Lesage, F.

J. Cohen-Adad, S. Chapuisat, J. Doyon, J.M. Lina, H. Benali and F. Lesage, "Application of the general linear model to response estimation in optical imaging," Medical Imaging Analysis 11, 616-629 (2007).
[CrossRef]

Li,

Lina, J.M.

J. Cohen-Adad, S. Chapuisat, J. Doyon, J.M. Lina, H. Benali and F. Lesage, "Application of the general linear model to response estimation in optical imaging," Medical Imaging Analysis 11, 616-629 (2007).
[CrossRef]

Meyer, F. G.

F. G. Meyer, "Wavelet-based estimation of a semiparametric generalized linear model of fMRI time-series," IEEE Trans. Med. Imaging 22, 315-322 (2003).
[CrossRef] [PubMed]

Miller, E. L.

Neufang, M.

H. Obrig, M. Neufang, R. Wenzel, M. Kohl, J. Steinbrink, K. Einhaupl and A. Villringer, "Spontaneous low frequency oscillations of cerebral hemodynamics and metabolism in human adults," NeuroImage 12, 623-639 (2000).
[CrossRef] [PubMed]

Obrig, H.

H. Obrig, M. Neufang, R. Wenzel, M. Kohl, J. Steinbrink, K. Einhaupl and A. Villringer, "Spontaneous low frequency oscillations of cerebral hemodynamics and metabolism in human adults," NeuroImage 12, 623-639 (2000).
[CrossRef] [PubMed]

Pfeuffer, J.

A. Shmuel, E. Yacoub, J. Pfeuffer, P.F. Van de Moortele, G. Adriany, X. Hu and K. Ugurbil, "Sustained negative BOLD, blood flow and oxygen consumption response and Its coupling to the positive response in the human brain," Neuron 36, 1195-1210, (2002).
[CrossRef] [PubMed]

Prince,

S. Prince, V. Kolehmainen, J. P. Kaipio, M. A. Franceschini, D. Boas and S. R. Arridge, "Time-series estimation of biological factors in optical diffusion tomography," Phys. Med. Biol. 48, 1491-504 (2003).
[CrossRef] [PubMed]

Prince, S.

Robert, M.

S. Bayard, N. Gosselin, M. Robert, M. Lassonde, "Inter- and Intra-hemispheric Processing of visual event related potentials in the absence of the corpus callosum," J. Cognitive Neuroscience 16, 1-14 (2004).
[CrossRef]

Rockstroh, B.

G. Gratton, M. Fabiani, T. Elbert and B. Rockstroh, "Seeing right through you: applications of optical imaging to the study of the human brain," Psychophysiology 40, 487-491 (2003).
[CrossRef] [PubMed]

Shmuel, A.

A. Shmuel, E. Yacoub, J. Pfeuffer, P.F. Van de Moortele, G. Adriany, X. Hu and K. Ugurbil, "Sustained negative BOLD, blood flow and oxygen consumption response and Its coupling to the positive response in the human brain," Neuron 36, 1195-1210, (2002).
[CrossRef] [PubMed]

Singh, K. D.

A. T. Smith, A. L. Williams and K. D. Singh, "Negative BOLD in the visual cortex: evidence against blood stealing," Human Brain Mapping 21, 213-220, (2004).
[CrossRef] [PubMed]

Smith, A. T.

A. T. Smith, A. L. Williams and K. D. Singh, "Negative BOLD in the visual cortex: evidence against blood stealing," Human Brain Mapping 21, 213-220, (2004).
[CrossRef] [PubMed]

Steinbrink, J.

H. Obrig, M. Neufang, R. Wenzel, M. Kohl, J. Steinbrink, K. Einhaupl and A. Villringer, "Spontaneous low frequency oscillations of cerebral hemodynamics and metabolism in human adults," NeuroImage 12, 623-639 (2000).
[CrossRef] [PubMed]

Takahashi, A.

H. Kato, M. Izumiyama, H. Koizumi, A. Takahashi and Y. Itoyama, "Near-infrared spectroscopic topography as a tool to monitor motor reorganization after hemiparetic stroke: a comparison with functional MRI," Stroke 33, 2032-2036 (2002).
[CrossRef] [PubMed]

Tewfik, A. H.

A. H. Tewfik and M. Kim, "Correlation structure of the discrete wavelet coefficients of fractional Brownian motion," IEEE Trans. Inf. Theory 38, 904-909 (1992).
[CrossRef]

Ugurbil, K.

A. Shmuel, E. Yacoub, J. Pfeuffer, P.F. Van de Moortele, G. Adriany, X. Hu and K. Ugurbil, "Sustained negative BOLD, blood flow and oxygen consumption response and Its coupling to the positive response in the human brain," Neuron 36, 1195-1210, (2002).
[CrossRef] [PubMed]

Van de Moortele, P. F.

A. Shmuel, E. Yacoub, J. Pfeuffer, P.F. Van de Moortele, G. Adriany, X. Hu and K. Ugurbil, "Sustained negative BOLD, blood flow and oxygen consumption response and Its coupling to the positive response in the human brain," Neuron 36, 1195-1210, (2002).
[CrossRef] [PubMed]

Villringer, A.

H. Obrig, M. Neufang, R. Wenzel, M. Kohl, J. Steinbrink, K. Einhaupl and A. Villringer, "Spontaneous low frequency oscillations of cerebral hemodynamics and metabolism in human adults," NeuroImage 12, 623-639 (2000).
[CrossRef] [PubMed]

Walz, K. A.

A. A. Baird, J. Kagan, T. Gaudette, K. A. Walz, N. Hershlag and D. A. Boas, "Frontal lobe activation during object permanence: data from near-infrared spectroscopy," NeuroImage. 16, 1120-1126 (2002).
[CrossRef] [PubMed]

Wenzel, R.

H. Obrig, M. Neufang, R. Wenzel, M. Kohl, J. Steinbrink, K. Einhaupl and A. Villringer, "Spontaneous low frequency oscillations of cerebral hemodynamics and metabolism in human adults," NeuroImage 12, 623-639 (2000).
[CrossRef] [PubMed]

Williams, A. L.

A. T. Smith, A. L. Williams and K. D. Singh, "Negative BOLD in the visual cortex: evidence against blood stealing," Human Brain Mapping 21, 213-220, (2004).
[CrossRef] [PubMed]

Wornell,

G. W. Wornell, A karhunen-loeve-like expansion for 1/f process via wavelets. IEEE Trans. Inf. Theory 36, 859- 861 (1990).
[CrossRef]

Yacoub, E.

A. Shmuel, E. Yacoub, J. Pfeuffer, P.F. Van de Moortele, G. Adriany, X. Hu and K. Ugurbil, "Sustained negative BOLD, blood flow and oxygen consumption response and Its coupling to the positive response in the human brain," Neuron 36, 1195-1210, (2002).
[CrossRef] [PubMed]

Yodh, A.

A. Yodh and B. Chance, "Spectroscopy and imaging with diffusing light," Phys. Today 48, 34-40 (1995).
[CrossRef]

Zhang,

Y. Zhang, D. H. Brooks and D. A. Boas, "A haemodynamic response function model in spatio-temporal diffuse optical tomography," Phys. Med. Biol. 50, 4625-44, (2005).
[CrossRef] [PubMed]

Zhang, Q.

Zhang, Y. H.

Appl. Opt. (1)

Cardiovasc. Res. (1)

C. Julien, "The enigma of Mayer waves: facts and model," Cardiovasc. Res. 70, 12-21 (2006).
[CrossRef]

Human Brain Mapping (1)

A. T. Smith, A. L. Williams and K. D. Singh, "Negative BOLD in the visual cortex: evidence against blood stealing," Human Brain Mapping 21, 213-220, (2004).
[CrossRef] [PubMed]

IEEE Trans. Inf. Theory (3)

G. W. Wornell, A karhunen-loeve-like expansion for 1/f process via wavelets. IEEE Trans. Inf. Theory 36, 859- 861 (1990).
[CrossRef]

P. Flandrin, "Wavelet analysis and synthesis of fractional brownian motion," IEEE Trans. Inf. Theory 38, 910-917 (1992)
[CrossRef]

A. H. Tewfik and M. Kim, "Correlation structure of the discrete wavelet coefficients of fractional Brownian motion," IEEE Trans. Inf. Theory 38, 904-909 (1992).
[CrossRef]

IEEE Trans. Med. Imaging (1)

F. G. Meyer, "Wavelet-based estimation of a semiparametric generalized linear model of fMRI time-series," IEEE Trans. Med. Imaging 22, 315-322 (2003).
[CrossRef] [PubMed]

J. Biomed. Opt. (1)

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, 054007 (2006).
[CrossRef] [PubMed]

J. Cognitive Neuroscience (1)

S. Bayard, N. Gosselin, M. Robert, M. Lassonde, "Inter- and Intra-hemispheric Processing of visual event related potentials in the absence of the corpus callosum," J. Cognitive Neuroscience 16, 1-14 (2004).
[CrossRef]

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

Medical Imaging Analysis (1)

J. Cohen-Adad, S. Chapuisat, J. Doyon, J.M. Lina, H. Benali and F. Lesage, "Application of the general linear model to response estimation in optical imaging," Medical Imaging Analysis 11, 616-629 (2007).
[CrossRef]

NeuroImage (3)

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, 88-101 (2006).
[CrossRef]

M. J. Fadili and E. T. Bullmore, "Wavelet-Generalized Least Squares: A New BLU Estimator of Linear Regression Models with 1/f Errors," Neuroimage 15, 217-232 (2002).
[CrossRef] [PubMed]

D. A. Boas, A. M. Dale and M. A. Franceschini, "Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution and accuracy," NeuroImage 23, S275-S288 (2004).
[CrossRef] [PubMed]

H. Obrig, M. Neufang, R. Wenzel, M. Kohl, J. Steinbrink, K. Einhaupl and A. Villringer, "Spontaneous low frequency oscillations of cerebral hemodynamics and metabolism in human adults," NeuroImage 12, 623-639 (2000).
[CrossRef] [PubMed]

NeuroImage. (1)

A. A. Baird, J. Kagan, T. Gaudette, K. A. Walz, N. Hershlag and D. A. Boas, "Frontal lobe activation during object permanence: data from near-infrared spectroscopy," NeuroImage. 16, 1120-1126 (2002).
[CrossRef] [PubMed]

Neuron (1)

A. Shmuel, E. Yacoub, J. Pfeuffer, P.F. Van de Moortele, G. Adriany, X. Hu and K. Ugurbil, "Sustained negative BOLD, blood flow and oxygen consumption response and Its coupling to the positive response in the human brain," Neuron 36, 1195-1210, (2002).
[CrossRef] [PubMed]

Phys. Med. Biol. (2)

S. Prince, V. Kolehmainen, J. P. Kaipio, M. A. Franceschini, D. Boas and S. R. Arridge, "Time-series estimation of biological factors in optical diffusion tomography," Phys. Med. Biol. 48, 1491-504 (2003).
[CrossRef] [PubMed]

Y. Zhang, D. H. Brooks and D. A. Boas, "A haemodynamic response function model in spatio-temporal diffuse optical tomography," Phys. Med. Biol. 50, 4625-44, (2005).
[CrossRef] [PubMed]

Phys. Today (1)

A. Yodh and B. Chance, "Spectroscopy and imaging with diffusing light," Phys. Today 48, 34-40 (1995).
[CrossRef]

Psychophysiology (1)

G. Gratton, M. Fabiani, T. Elbert and B. Rockstroh, "Seeing right through you: applications of optical imaging to the study of the human brain," Psychophysiology 40, 487-491 (2003).
[CrossRef] [PubMed]

Science (1)

F. Jobsis, "Noninvasive infrared monitoring of cerebral and myocardial sufficiency and circulatory parameters," Science 198, 1264-1267 (1977).
[CrossRef] [PubMed]

Stroke (1)

H. Kato, M. Izumiyama, H. Koizumi, A. Takahashi and Y. Itoyama, "Near-infrared spectroscopic topography as a tool to monitor motor reorganization after hemiparetic stroke: a comparison with functional MRI," Stroke 33, 2032-2036 (2002).
[CrossRef] [PubMed]

Other (7)

Y. Meyer, Wavelets: Algorithms and Applications, (SIAM, Philadelphia, 1993).

Recordings done in D. A. Boas laboratory, MGH (http://www.nmr.mgh.harvard.edu/PMI/).

S. Mallat, A Wavelet Tour of Signal Processing, (Academic Press, 1998).

B. Torresani, Analyse continue par ondelettes, (CNRS Editions, 1995).

I. Daubechies, Ten lectures on wavelets, (SIAM Philadelphia, 1992).
[CrossRef]

M. Dehaes, L. Gagnon, M. Desjardins, R. M. Comeau and F. Lesage, "Positive responses in diffuse optical imaging and their relation to the negative BOLD effect," in preparation, (2007).

G. W. Wornell, Signal Processing with Fractals: A wavelet-based approach, (Prentice Hall, 1996).

Cited By

OSA participates in CrossRef's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (17)

Fig. 1.
Fig. 1.

Lusin wavelet ψ7 in the time domain. (A): real part (solid line) and imaginary part (dashed line). (B): ψ7 in frequency. w0 denotes the central frequency of the wavelet.

Fig. 2.
Fig. 2.

Left column: Two modulated gaussians (A) at 0.12 Hz and 1.0 Hz and the corresponding scalogram (B) with ψ 7. Note that the wavelet transform provides both temporal and frequency localizations of the two constituents of the signal. The figure displays amplitudes of the coefficients and the cone of influence. The wavelet coefficients outside the cone (close to the boundaries of the signal) are tainted by artifacts due to edge discontinuities of the signal. Coefficients inside the cone are sufficiently far from the edge to be free of these artifacts. Right column: A wave train (C) given by equation (6) for some block paradigm B and its time-frequency representation (D).

Fig. 3.
Fig. 3.

Time-Frequency plane for HbO, HbR and four physiology signals at rest, group averaged wavelet power over 10 subjects. HbO and HbR signal power spectrum are averaged over 3 optode pairs. HbO channel exhibits theMayer waves around 0.1 Hz. A similar effect is seen in HbR channel but is in fact much smaller: the graphs are normalized individually and the HbR signal around 0.1 Hz is 20 times smaller than for HbO. We also observe a similar pattern in the time-frequency plane of the heart rate. The cardiac beats are visible in the HbO signal as well when compared to the heart beat. The respiratory signal does not show strongly in the optical data but its effect is expected to be smaller.

Fig. 4.
Fig. 4.

Motor task (finger-tapping) paradigm, single subject. (A): optodes configuration composed with 4 sources and 8 detectors. (B): scalogram of the stimuli convolved with the SPM2 canonical hemodynamic response (expected response in the data). The time axis has been truncated to eliminate the cone of influence. The six other panels show the normalized scalograms (the single colorbar applies to all graphs) of the wavelet transforms for HbO (left) and HbR (right) channels at 3 selected optode pairs (4,9 and 13). Notice the clear activation in the HbR channels of optode pair 4, in correspondence with the stimuli and the presence of Mayer waves in the HbO channels somewhat obscuring the presence of evoked activation. Optode pair 13 has no activation but still sees the Mayer waves.

Fig. 5.
Fig. 5.

Computation of the synchrony maps, i.e. ρi ,k(a,b), for si =HbR (or HbO) and sk one of the physiological signals. The top row shows the HbO correlations, the bottom row HbR (group averaged wavelet synchrony over 10 subjects, 3 optodes each).

Fig. 6.
Fig. 6.

Simulation of an optode pair signal on a single run. (A): block design stimulation (black) and the hemodynamic response (in red). The HbR signal (B) and HbO signal (C) with the respective simulated activation (in red) added. (D): Wavelet coefficients of the HRF (red line in (A)). (E) and (F): Norm of the wavelet coefficients of the HbR channel and HbO channel respectively. The HbO channel is dominated by physiology. In figure (E), there are high intensity norms at high frequencies which have support on very small areas which is why the color map is not as well distributed. Wavelet transforms are normalized.

Fig. 7.
Fig. 7.

Normalized wavelet power coefficients averaged over the blocks for HbO (A) and HbR (C) corresponding to the simulation of Fig. 6 on a single run. Corresponding phaselock maps: HbO (B) and HbR (D). In this case, the averaged power exhibits mostly the activation in the HbO channel whereas HbR channel only shows the evoked response through the phase-lock map.

Fig. 8.
Fig. 8.

(A): Cut-off function for keeping wavelet coefficients in terms of the synchrony index. (B): Estimation (and variance) of β in the HbO (red) and HbR (blue) channels in terms of the threshold λ in equation (16). λ=0 corresponds to the average in the time-frequency plane.

Fig. 9.
Fig. 9.

Estimated values of the responses for HbO and HbR respectively for N=30. In each case, three methods are compared: the General linear model (GLM), the averaging technique (AVG) and the complex wavelet technique (CPLX). In parenthesis: Absolute value of the Z scores for the above estimations given that we measure the mean of the distribution.

Fig. 10.
Fig. 10.

Estimation of the hemodynamic response by wavelet shrinkage for a single case. HbR channel (A) and HbO channel (B). Block average (blue lines), synchrony based estimator (red lines) and true response (dot lines). The estimated β* are found equal to -0.9×10-6 and 3.1×10-6 for HbR and HbO respectively.

Fig. 11.
Fig. 11.

Estimation errors for HbO (red) and HbR (blue) responses for random stimuli. Two methods are compared: the General Linear Model (GLM) and the Complex Wavelet technique (CPLX). In each case, we indicate the t-score in parenthesis. For the complex cased, the error mean is closer to zero showing that the bias has been diminished. The t-score values reflects this.

Fig. 12.
Fig. 12.

Optodes configuration (left) registered over the cortex of the subject (middle) and visual stimulation (right).

Fig. 13.
Fig. 13.

Block averaged synchronization index per pair number for HbR (left column) and HbO (right column). Results from two experiments are shown in different colors.

Fig. 14.
Fig. 14.

Optodes configuration for the left side of the head.

Fig. 15.
Fig. 15.

Top:Map of the synchrony indices for all optode pairs for the HbR channel (Similar map for the HbO channels does not exhibit such a significative contrast between optode pairs). We indicate in bold face the most contrasted optode pairs, they are those located over the motor area of the brain’s subject.

Fig. 16.
Fig. 16.

Synchrony-based reconstructions of the HRF for the HbR channels over the motor area. The solid lines exhibit the dominant response in case of the Left (red) and Right (blue) stimulus.

Fig. 17.
Fig. 17.

Event related finger tapping experiment and the optode pairs setup (TOP). (a) The expected response, (b) the scalogram of the HbR channel for pair 6, (c,d) the estimated values for the (top,bottom) optode-pair rows, HbO in red, HbR in blue. (e,f) the correponding t-statistics for the same estimates.

Equations (25)

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

ψ a , b ( t ) = 1 a ψ n ( t b a ) , a > 0 , b
ψ n ( t ) = ( n 1 ) ! 2 π ( 1 + it ) 1 + n ( 1 + t 2 ) 1 + n ,
ψ ̂ n ( ω ) = { ω n e ω for ω 0 0                 for ω < 0 .
w ( s ) ( a , b ) = + s ( t ) ψ a , b ( t ) ¯ d t ,
γ a , b ( s ) = w ( s ) ( a , b ) w ( s ) ( a , b ) .
H ( t ) = B * h ( t ) .
s ( t ) = 1 k ψ [ 0 + w ( s ) ( a , t ) d a a 3 2 ] 1 k ψ [ j w s ( a j , t ) a j ]
Δ OD ( t , λ ) = ln ( Φ ( t , λ ) Φ 0 ( t , λ ) ) .
[ Δ C HbO ( t ) Δ C HbR ( t ) ] = [ ε HbO λ 1 ε HbR λ 1 ε HbO λ 2 ε HbR λ 2 ] 1 [ Δ OD ( t , λ 1 ) Δ OD ( t , λ 2 ) ]
ρ i , k = e j ( ϕ i ϕ k )
ρ i , k ( a , b ) = 1 N T b = b T 2 b + T 2 γ a , b s i γ a , b s k ¯ .
ρ i , HRF ( a , b ) = γ a , b s i γ a , b HRF ¯ ,
ρ s i ( a , b ) = 1 N e m γ a , b + m Δ s i γ a , b HRF ¯ = 1 N e m γ a , b + m Δ s i .
s * ( b ) = 1 k ψ [ j g ( ρ s ( a j , b ) ) w ( s ) ( a j , b ) a j ] .
s * ( t ) = 1 k ψ [ j j max g ( ρ s ( a j , t ) ) w ( s ) ( a j , t ) a j ] .
g ( ρ ) = [ 1 1 + e ρ λ σ 1 1 + e λ σ ] [ 1 1 + e 1 λ σ 1 1 + e λ σ ] 1 , with σ = 0.01 .
W s ( t ) = β W H ( t ) + W Θ ( t ) + W ε .
β * = argmin β t = 1 S w s ( a i * , b i * ) β w H ( a i * , b i * ) 2 .
β * = ( W H t W H ) 1 W H t W s .
t−score = β * β 0 * ¯ σ * 2 + σ 0 * 2
s c ( t ) = s rest ( t ) + β c H ( t ) ,
H ( t ) w ( H ) ( a , b ) H * ( t ) = 1 k ψ [ j w ( H ) ( a j , t ) a j ] = H ( t ) .
s * ( t ) = β * H ( t ) + δ ,
ρ s i ( C ) ( a , b ) = 1 N epoch epoch ( C ) γ a , b s i .
c s i ( a , b ) = ρ s i ( L 5 ) ( a , b ) ρ s i ( R 5 ) ( a , b ) .

Metrics