Article Text
Abstract
Background and aims: Independent component analysis (ICA) of the electroencephalogram (EEG) overcomes many of the classical problems in EEG analysis. We used ICA to determine the brain responses to painful stimulation of the oesophagus.
Methods: Twelve subjects with a median age of 41 years were included. With a nasal endoscope, two series of 35 electrical stimuli at the pain threshold were given to the distal oesophagus and the EEG was subjected to ICA. The sessions were separated by 30 minutes. For each component head models, event related images, spectral perturbation, coherence analysis, and dipoles were extracted. The most valid components were found according to time/frequency information and reliability in both experiments.
Results: Reliable components with the most valid dipoles were found in the thalamus, insula, cingulate gyrus, and sensory cortex. Time locked activities were consistent with upstream activation of these areas, and cross coherence analysis of the sources demonstrated dynamic links in the β(14–25 Hz) and γ(25–50 Hz) bands between the suggested networks of neurones. The thalamic components were time and phase locked intermittently, starting around 50 ms. In the cingulate gyrus, the posterior areas were always firstly activated, followed by the middle and anterior regions. Components with dipoles in the sensory cortex were localised in several regions of the somatosensory area.
Conclusions: The method gives new information relating to the localisation and dynamics between neuronal networks in the brain to pain evoked from the human oesophagus, and should be used to increase our understanding of clinical pain.
- EEG, electroencephalography
- ERP, event related potentials
- ERSP, event related spectral perturbation
- ICA, independent component analysis
- ITC, inter-trial phase coherence
- fMRI, functional magnetic resonance imaging
- MEG, magnetoencephalography
- PDT, pain detection threshold
- PET, positron emission tomography
- oesophagus
- experimental pain
- electroencephalography
- signal analysis
- independent component analysis
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Footnotes
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Published online first 6 October 2005
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Conflict of interest: None declared.