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Functional characterisation of sensory ERPs using probabilistic ICA: Effect of stimulus modality and stimulus location

  • M. Liang
  • , A. Mouraux
  • , V. Chan
  • , C. Blakemore
  • , G.D. Iannetti*
  • *Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

Abstract

Objective: To decompose sensory event-related brain potentials (ERPs) into a set of independent components according to the modality and the spatial location of the eliciting sensory stimulus, and thus provide a quantitative analysis of their underlying components.
Methods: Auditory, somatosensory and visual ERPs were recorded from 124 electrodes in thirteen healthy participants. Probabilistic Independent Component Analysis (P-ICA) was used to decompose these sensory ERPs into a set of independent components according to the modality (auditory, somatosensory, visual or multimodal) and the spatial location (left or right side) of the eliciting stimulus. 
Results: Middle-latency sensory ERPs were explained by a large contribution of multimodal neural activities, and a smaller contribution of unimodal neural activities. While a significant fraction of unimodal neural activities were dependent on the location of the eliciting stimulus, virtually all multimodal neural activities were not (i.e. their scalp distributions and time courses were not different when stimuli were presented on the left and right sides). 
Conclusion: These findings show that P-ICA can be used to dissect effectively sensory ERPs into physiologically meaningful components, and indicate a new approach for exploring the effect of various experimental modulations of sensory ERPs. 
Significance: This approach offers a better understanding of the functional significance of sensory ERPs. © 2009 International Federation of Clinical Neurophysiology.
Original languageEnglish
Pages (from-to)577-587
JournalClinical Neurophysiology
Volume121
Issue number4
Online published27 Jan 2010
DOIs
Publication statusPublished - Apr 2010
Externally publishedYes

Research Keywords

  • Auditory
  • Blind source separation
  • Event-related potentials (ERPs)
  • Probabilistic Independent Component Analysis (ICA)
  • Somatosensory
  • Visual

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