Skip to main content
SpringerLink
Log in
Book cover

XIV Mediterranean Conference on Medical and Biological Engineering and Computing 2016 pp 179–183Cite as

Analysis of MEG Signals for Selective Arithmetic Tasks

  • Conference paper
  • First Online:

Part of the book series: IFMBE Proceedings ((IFMBE,volume 57))

Abstract

In this study, magnetoencephalography (MEG) data were recorded as subjects carried out a basic numerical task: deciding whether a number is even or odd. Signal processing techniques were applied to the MEG data so as to characterise the spatial and temporal dynamics of the brain during the decision-making process. Event-related fields (ERFs) were found by averaging all the trials in the time domain. Induced potentials or oscillatory rhythms were found by averaging the time-frequency representations (TFRs) for all the trials. The TFRs were found using the Wavelet transform. The results show that typical ERF components are present just after the onset of the stimulus. N100, P200 and N200 waveforms indicate that the brain carries out higher-order perceptual processing modulated by attention, and that memory may play a critical role in parity selection. TFRs show beta-band synchronisation as the individual concentrates on the mental task, followed by desynchronisation as the motor response is carried out. Activity is pronounced in the left general interpretive area (Wernicke’s area) with a latency of around 610 ms.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   259.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Hansen PC, Kringelbach, Salmelin R (2010) MEG an introduction to methods. Oxford University Press, New York

    Google Scholar 

  2. Dinse HR, Krüger K, Akhavan AC, et al. (1997) Low-frequency oscillations of visual, auditory and somatosensory cortical neurons evoked by sensory stimulation. Int J Psychophysiol Off J Int Organ Psychophysiol 26:205–227.

    Google Scholar 

  3. Miniussi C, Marzi CA, Nobre AC (2005) Modulation of brain activity by selective task sets observed using event-related potentials. Neuropsychologia 43:1514–1528. doi: 10.1016/j.neuropsychologia.2004.12.014

    Google Scholar 

  4. Kou H, Iwaki S (2007) Modulation of neural activities by the complexity of mental arithmetic: An MEG study. Int Congr Ser 1300:539–542. doi: 10.1016/j.ics.2006.12.076

    Google Scholar 

  5. Martini FH (2003) Fundamentals of Anatomy & Physiology, Sixth Edition, 6 edition. Benjamin Cummings

    Google Scholar 

  6. Pfurtscheller G, Lopes da Silva FH (1999) Event-related EEG/MEG synchronization and desynchronization: basic principles. Clin Neurophysiol Off J Int Fed Clin Neurophysiol 110:1842–1857.

    Google Scholar 

  7. Gross J, Baillet S, Barnes GR, et al. (2013) Good practice for conducting and reporting MEG research. NeuroImage 65:349–363. doi: 10.1016/j.neuroimage.2012.10.001

    Google Scholar 

  8. Mitra PP, Pesaran B (1999) Analysis of dynamic brain imaging data. Biophys J 76:691–708. doi: 10.1016/S0006-3495(99)77236-X

    Google Scholar 

  9. Bruns A (2004) Fourier-, Hilbert- and wavelet-based signal analysis: are they really different approaches? J Neurosci Methods 137:321–332. doi: 10.1016/j.jneumeth.2004.03.002

    Google Scholar 

  10. Tallon-Baudry, Bertrand (1999) Oscillatory gamma activity in humans and its role in object representation. Trends Cogn Sci 3:151–162.

    Google Scholar 

  11. Semmlow JL (2008) Biosignal and biomedical image processing: MATLAB-based applications. CRC ; Taylor & Francis [distributor], Boca Raton, Fla.; London

    Google Scholar 

  12. Ropella KM (2007) Introduction to Statistics for Biomedical Engineers. Morgan & Claypool Publishers

    Google Scholar 

  13. Park H, Kim JS, Chung CK (2013) Differential Beta-Band Event-Related Desynchronization during Categorical Action Sequence Planning. PLoS ONE 8:e59544. doi: 10.1371/journal.pone.0059544

    Google Scholar 

  14. Folstein JR, Van Petten C (2008) Influence of cognitive control and mismatch on the N2 component of the ERP: a review. Psychophysiology 45:152–170. doi: 10.1111/j.1469-8986.2007.00602.x

    Google Scholar 

  15. Sur S, Sinha VK (2009) Event-related potential: An overview. Ind Psychiatry J 18:70–73. doi: 10.4103/0972-6748.57865

    Google Scholar 

  16. Libet B, Gleason CA, Wright EW, Pearl DK (1983) Time of conscious intention to act in relation to onset of cerebral activity (readiness-potential). The unconscious initiation of a freely voluntary act. Brain J Neurol 106 (Pt 3):623–642.

    Google Scholar 

  17. Schafer EWP, Marcus MM (1973) Self-Stimulation Alters Human Sensory Brain Responses. Science 181:175–177. doi: 10.1126/science.181.4095.175

    Google Scholar 

  18. Freunberger R, Klimesch W, Doppelmayr M, Höller Y (2007) Visual P2 component is related to theta phase-locking. Neurosci Lett 426:181–186. doi: 10.1016/j.neulet.2007.08.062

    Google Scholar 

  19. Cohen Kadosh R, Walsh V (2009) Numerical representation in the parietal lobes: abstract or not abstract? Behav Brain Sci 32:313–328; discussion 328–373. doi: 10.1017/S0140525X09990938

    Google Scholar 

  20. Harmony T, Fernández T, Gersenowies J, et al. (2004) Specific EEG frequencies signal general common cognitive processes as well as specific task processes in man. Int J Psychophysiol 53:207–216. doi: 10.1016/j.ijpsycho.2004.04.006

    Google Scholar 

  21. Ansari D, Karmiloff-Smith A (2002) Atypical trajectories of number development: a neuroconstructivist perspective. Trends Cogn Sci 6:511–516.

    Google Scholar 

  22. Wang Y, Wang Y (2002) Cognitive models of the brain. In: First IEEE Int. Conf. Cogn. Inform. 2002 Proc. pp 259–269

    Google Scholar 

  23. Berch DB, Foley EJ, Hill RJ, Ryan PM (1999) Extracting parity and magnitude from Arabic numerals: developmental changes in number processing and mental representation. J Exp Child Psychol 74:286–308. doi: 10.1006/jecp.1999.2518

    Google Scholar 

  24. Breedlove SM, Watson NV, Rosenzweig MR (2010) Biological psychology: an introduction to behavioral, cognitive, and clinical neuroscience. Sinauer Associates, Inc. Publishers, Sunderland, MA

    Google Scholar 

  25. Fell J, Röschke J, Grözinger M, et al. (2000) Alterations of continuous MEG measures during mental activities. Neuropsychobiology 42:99–106. doi: 26679

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Biomedical Engineering Research Group, School of Electrical and Information Engineering, University of the Witwatersrand, Chamber of Mines Building, 1 Jan Smuts Avenue, Braamfontein, Johannesburg, South Africa

    Graham Peyton, David M. Rubin & Adam Pantanowitz

  2. Gonda Brain Research Center, Bar-Ilan University, 52900, Ramat-Gan, Israel

    Amir Kleks

  3. Department of Mathematics, Bar-Ilan University, 52900, Ramat-Gan, Israel

    Mina Teicher

Authors
  1. Graham Peyton
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. David M. Rubin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Adam Pantanowitz
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Amir Kleks
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mina Teicher
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Graham Peyton .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Frederick University, Nicosia, Cyprus

    Efthyvoulos Kyriacou

  2. Biomedical Research Foundation, Nicosia, Cyprus

    Stelios Christofides

  3. Department of Computer Science, University of Cyprus, Nicosia, Cyprus

    Constantinos S. Pattichis

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Peyton, G., Rubin, D.M., Pantanowitz, A., Kleks, A., Teicher, M. (2016). Analysis of MEG Signals for Selective Arithmetic Tasks. In: Kyriacou, E., Christofides, S., Pattichis, C. (eds) XIV Mediterranean Conference on Medical and Biological Engineering and Computing 2016. IFMBE Proceedings, vol 57. Springer, Cham. https://doi.org/10.1007/978-3-319-32703-7_37

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-32703-7_37

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32701-3

  • Online ISBN: 978-3-319-32703-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation