Brain Topography

, Volume 31, Issue 2, pp 242–256 | Cite as

Neural Basis of Early Somatosensory Change Detection: A Magnetoencephalography Study

  • G. Naeije
  • T. Vaulet
  • V. Wens
  • B. Marty
  • S. Goldman
  • X. De Tiège
Original Paper

Abstract

The mismatch negativity (MMN) reflects the early detection of changes in sensory stimuli at the cortical level. The mechanisms underlying its genesis remain debated. This magnetoencephalography study investigates the spatio-temporal dynamics and the neural mechanisms of the magnetic somatosensory MMN. Somatosensory evoked magnetic fields elicited by tactile stimulation of the right fingertip (Single), tactile stimulation of the right middle phalanx and fingertip (Double) or omissions (Omitted) of tactile stimuli were studied in different paradigms: in oddballs where Double/Omitted followed a sequence of four Single, in sequences of two stimuli where Double occurred after one Single, and in random presentation of Double only. The predictability of Double occurrence in oddballs was also manipulated. Cortical sources of evoked responses were identified using equivalent current dipole modeling. Evoked responses elicited by Double were significantly different from those elicited by Single at the contralateral secondary somatosensory (cSII) cortex. Double elicited higher cSII cortex responses than Single when preceded by a sequence of four Single, compared to when they were preceded by one Single. Double elicited higher cSII cortex response when presented alone compared to when Double were preceded by one or a sequence of Single. Omitted elicited similar cSII cortex response than Single. Double in oddballs led to higher cSII cortex responses when less predictable. These data suggest that early tactile change detection involves mainly cSII cortex. The predictive coding framework probably accounts for the SII cortex response features observed in the different tactile paradigms.

Keywords

Change detection Mismatch negativity Somatosensory Adaptation Magnetoencephalography Predictive coding 

Notes

Acknowledgements

GN is supported by a research grant from the Fonds Erasme (http://www.fondserasme.org/, Brussels, Belgium). VW (Research logistic collaborator) and XDT (Post-doctorate Clinical Master Specialist) are supported by a research grant from the Fonds de la Recherche Scientifique (F.R.S.-FNRS, Belgium). This work is supported by a research grant from the Fondation ULB to Pr Serge Goldman (Université libre de Bruxelles, Belgium) (http://fondation.ulb.ac.be/fr/imagerie-fonctionnelle-cerveau-goldman/). The MEG project at the ULB-Hôpital Erasme is supported by the Fonds Erasme (http://www.fondserasme.org/, Brussels, Belgium). Gilles Naeije was funded by the Fonds Erasme (Brussels, Belgium; http://www.fondserasme.org/fonds-erasme-pour-la-recherche-medicale). Xavier De Tiège is Postdoctorate Clinical Master Specialist at the Fonds de la Recherche Scientifique (FRS-FNRS, Brussels, Belgium).

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflicts of interest.

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • G. Naeije
    • 1
    • 3
  • T. Vaulet
    • 1
  • V. Wens
    • 1
    • 2
  • B. Marty
    • 1
  • S. Goldman
    • 1
    • 2
  • X. De Tiège
    • 1
    • 2
  1. 1.Laboratoire de Cartographie fonctionnelle du Cerveau (LCFC), UNI – ULB Neuroscience InstituteUniversité libre de Bruxelles (ULB)BrusselsBelgium
  2. 2.Department of Functional Neuroimaging, Service of Nuclear Medicine, CUB Hôpital ErasmeUniversité libre de Bruxelles (ULB)BrusselsBelgium
  3. 3.Laboratoire de Cartographie fonctionnelle du Cerveau (LCFC)CUB Hôpital ErasmeBrusselsBelgium

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