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False Positives In Functional Nearinfrared Topography

  • Ilias Tachtsidis
  • Terence S. Leung
  • Anchal Chopra
  • Peck H. Koh
  • Caroline B. Reid
  • Clare E. Elwell
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 645)

Abstract

Functional cranial near-infrared spectroscopy (NIRS) has been widely used to investigate the haemodynamic changes which occur in response to functional activation. The technique exploits the different absorption spectra of oxy- and deoxy-haemoglobin ([HbO2] [HHb]) in the near-infrared region to measure the changes in oxygenation and haemodynamics in the cortical tissue. The aim of this study was to use an optical topography system to produce topographic maps of the haemodynamic response of both frontal cortex (FC) and motor cortex (MC) during anagram solving while simultaneously monitoring the systemic physiology (mean blood pressure, heart rate, scalp flux). A total of 22 young healthy dults were studied. The activation paradigm comprised of 4-, 6- and 8- letter anagrams. 12 channels of the optical topography system were positioned ver the FC and 12 channels over the MC. During the task 12 subjects demonstrated a significant change in at least one systemic variable (p≤0.05). Statistical analysis of task-related changes in [HbO2] and [HHb], based on a Student’s t-test was insufficient to distinguish between cortical haemodynamic activation and systemic interference. This lead to false positive haemodynamic maps of activation. It is therefore necessary to use statistical testing that incorporates the systemic changes that occur during brain activation.

Keywords

Frontal Cortex Motor Cortex Statistical Parametric Mapping Haemodynamic Change Haemodynamic Response 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    I. Tachtsidis, T.S. Leung, L. Devoto, D.T. Delpy, and C.E. Elwell, Measurement of frontal lobe functional activation and related systemic effects: a near-infrared spectroscopy investigation, Adv. Exp. Med. Biol.In Press (2008).Google Scholar
  2. 2.
    I. Tachtsidis, T.S. Leung, M.M. Tisdall, D. Presheena, M. Smith, D.T. Delpy, and C.E. Elwell, Investigation of frontal cortex, motor cortex and systemic haemodynamic changes during anagram solving, Adv. Exp. Med. Biol.In Press (2008).Google Scholar
  3. 3.
    Y. Hoshi, B. H. Tsou, V. A. Billock, M. Tanosaki, Y. Iguchi, M. Shimada, T. Shinba, Y. Yamada, and I. Oda, Spatiotemporal characteristics of hemodynamic changes in the human lateral prefrontal cortex during working memory tasks, NeuroImage 20(3), 1493-1504 (2003).PubMedCrossRefGoogle Scholar
  4. 4.
    B. Chance, S. Nioka, S. Sadi, and C. Li, Oxygenation and blood concentration changes in human subject prefrontal activation by anagram solutions, Adv. Exp. Med. Biol. 510, 397-401 (2003).PubMedGoogle Scholar
  5. 5.
    R.P. Kennan, D. Kim, A. Maki, H. Koizumi, and R.T. Constable, Non-invasive assessment of language lateralization by transcranial near infrared optical topography and functional MRI, Hum. Brain Mapp. 16(3), 183-189 (2002).PubMedCrossRefGoogle Scholar
  6. 6.
    P.H. Koh, D.E. Glaser, G. Flandin, S. Kiebel, B. Butterworth, A. Maki, D.T. Delpy, and C.E. Elwell, Functional optical signal analysis (fOSA): a software tool for NIRS data processing incorporating statistical parametric mapping (SPM), JBOIn Press (2007).Google Scholar
  7. 7.
    X. Zhang, V. Toronov, and A. Webb, Simultaneous integrated diffuse optical tomography and functional magnetic resonance imaging of the human brain, Opt. Express 13(14), 5513-5521 (2005).CrossRefPubMedGoogle Scholar
  8. 8.
    I. Schiessl, M. Stetter, J.E.W. Mayhew, N. McLoughlin, J.S. Lund, and K. Obermayer, Blind signal separation from optical imaging recordings with extended spatial decorrelation, IEEE Transactions on Biomedical Engineering, 47(5), 573-577 (2000).CrossRefGoogle Scholar
  9. 9.
    K.J. Friston, A.P. Holmes, J.B. Poline, P.J. Grasby, S.C. Williams, R.S. Frackowiak, and R. Turner, Analysis of fMRI time-series revisited, NeuroImage 2(1), 45-53 (1995).PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Ilias Tachtsidis
    • 1
  • Terence S. Leung
    • 1
  • Anchal Chopra
    • 1
  • Peck H. Koh
    • 1
  • Caroline B. Reid
    • 1
  • Clare E. Elwell
    • 1
  1. 1.Department of Medical Physics and BioengineeringMalet Place Engineering Building, University CollegeLondonUK

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