Download PDF
Methods Inf Med 2007; 46(02): 164-168
DOI: 10.1055/s-0038-1625400
Original Article
Schattauer GmbH

Cross-correlation Analysis of the Correspondence between Magnetoencephalographic and Near-infrared Cortical Signals

T. H. Sander
1   Physikalisch-Technische Bundesanstalt, Division of Medical Physics, Berlin, Germany
,
A. Liebert
2   Institute of Biocybernetics and Biomedical Engineering, Warsaw, Poland
,
M. Burghoff
1   Physikalisch-Technische Bundesanstalt, Division of Medical Physics, Berlin, Germany
,
H. Wabnitz
1   Physikalisch-Technische Bundesanstalt, Division of Medical Physics, Berlin, Germany
,
R. Macdonald
1   Physikalisch-Technische Bundesanstalt, Division of Medical Physics, Berlin, Germany
,
L. Trahms
1   Physikalisch-Technische Bundesanstalt, Division of Medical Physics, Berlin, Germany
› Author Affiliations
Further Information

Publication History

Publication Date:
11 January 2018 (online)

    Permissions and Reprints

Summary

Objectives : The study of neurovascular coupling greatly benefits from combined measurements of neuronal and vascular signals. Two-step signal processing is developed to extract parameters describing the coupling.

Methods : Using a magnetometer in an extremely well shielded room a broadband magnetoencephalogram was simultaneously measured with time-resolved nearinfrared spectroscopy during a motor activity paradigm. The raw MEG and NIRS data were denoised separately using independent component analysis.

Results : After averaging the resulting signals showed motor activity-related changes. The temporal correspondence between MEG and NIRS was assessed plotting a combined trajectory and calculating a crosscorrelation. Compared to the MEG signal, at movement onset the NIRS signal showed an onsetdelay in the range of seconds.

Conclusions : Multi-variate signal pre-processing followed by temporal delay estimates demonstrated the extraction of neurovascular coupling parameters.

Keywords

Direct current magnetoencephalography - near-infrared spectroscopy - independent component analysis - cross-correlation - neurovascular coupling
 

  • References

  • 1. Arthurs OJ, Boniface S. How well do we understand the neural origins of the fMRI BOLD signal?. Trends Neurosc 2002; 25: 27-31.
    CrossrefPubMedSearch in Google Scholar
  • 2. Obrig H, Hirth C, Junge-Hulsing JG, Döge C, Wolf T, Dirnagl U, Villringer A. Cerebral oxygenation changes in response to motor stimulation. J Appl Physiol 1996; 81: 1174-1183.
    CrossrefPubMedSearch in Google Scholar
  • 3. Steinbrink J, Wabnitz H, Obrig H, Villringer A, Rinneberg H. Determining changes in NIR absorption using a layered model of the human head. Phys Med Biol 2001; 46: 879-896.
    CrossrefPubMedSearch in Google Scholar
  • 4. Franceschini MA, Fantini S, Thompson JH, Culver JP, Boas DA. Hemodynamic evoked response of the sensorimotor cortex measured non-invasively with near-infrared optical imaging. Psychophys 2003; 40: 548-560.
    CrossrefPubMedSearch in Google Scholar
  • 5. Wolf M, Wolf U, Toronov V, Michalo A, Paunescu LA, Choi JH, Gratton E. Different time evolution of oxy- and deoxyhemoglobin concentration changes in the visual and motor cortices during functional stimulation: a near-infrared spectroscopy study. Neuroimage 2002; 16: 704-712.
    CrossrefPubMedSearch in Google Scholar
  • 6. Wübbeler G, Ziehe A, Mackert BM, Müller KR, Trahms L, Curio G. Independent component analysis of non-invasively recorded cortical magnetic DC-fields in humans. IEEE Trans Biomed Eng 2000; 47: 594-599.
    CrossrefPubMedSearch in Google Scholar
  • 7. Mackert BM, Wübbeler G, Leistner S, Uludag K, Obrig H, Villringer A, Trahms L, Curio G. Neurovascular coupling analyzed non-invasively in the human brain. NeuroReport 2004; 15: 63-66.
    CrossrefPubMedSearch in Google Scholar
  • 8. Sander TH, Liebert A, Wabnitz H, Burghoff M, Macdonald R, Trahms L, Leistner S, Curio G, Mackert BM. Concurrent DC-magnetoencepha-lography and near-infrared spectroscopy for the study of slow brain activity. In: Halgren A et al. (eds). Proc of BIOMAG 2004. Boston 2005: 75-76.
    PubMedSearch in Google Scholar
  • 9. Burghoff M, Sander TH, Schnabel A, Drung D, Trahms L, Curio G, Mackert BM. DC-Magnetoencephalography: direct measurement in a magnetically extremely well shielded room. Appl Phys Lett 2004; 85: 6278-6280.
    CrossrefPubMedSearch in Google Scholar
  • 10. Liebert A, Wabnitz H, Steinbrink J, Obrig H, Moller M, Macdonald R, Villringer A, Rinneberg H. Time-resolved multi-distance NIR spectroscopy of the adult head: intra- and extra-cerebral absorption changes from moments of distributions of time of flight of photons. Appl Optics 2004; 43: 3037-3047.
    CrossrefPubMedSearch in Google Scholar
  • 11. Hyvärinen A, Karhunen J, Oja E. Independent component analysis. New York: John Wiley and Sons; 2001
    PubMedSearch in Google Scholar
  • 12. Cichocki A, Amari SI. Adaptive blind signal and image processing. New York: John Wiley and Sons; 2002
    PubMedSearch in Google Scholar
  • 13. Belouchrani A, Abed-Meraim K, Cardoso JF, Moulines E. A blind source separation technique based on second-order statistics. IEEE Trans Sig Proc 1997; 45: 434-444.
    CrossrefPubMedSearch in Google Scholar
  • 14. Ziehe A, Müller KR. TDSEP - an efficient algorithm for blind separation using time structure. In: Niklasson L et al. (eds). Proc of the 8th ICANN. Berlin: Springer Verlag; 1988: 675-680.
    PubMedSearch in Google Scholar
  • 15. Ziehe A, Nolte G, Curio G, Müller KR. OFI: Optimal filtering algorithms for source separation. In: Oja E et al. (eds). Proc of the 2nd Intern Workshop on ICA and BSS. Helsinki; 2000: 127-132.
    PubMedSearch in Google Scholar