• Juergen Brinkmeyer, Arian Mobascher, Tracy Warbrick, Francesco Musso, Hans-Jörg Wittsack, Andreas Saleh, Alfons Schnitzler, and Georg Winterer.
• Neuropsychiatric Research Laboratory, Department of Psychiatry, Heinrich-Heine University Duesseldorf, Germany.
• Hum Brain Mapp. 2010 Nov 1;31(11):1702-12.

AbstractPrevious studies on the spatio-temporal dynamics of cortical pain processing using electroencephalography (EEG), magnetoencephalography (MEG), or intracranial recordings point towards a high degree of parallelism, e.g. parallel instead of sequential activation of primary and secondary somatosensory areas or simultaneous activation of somatosensory areas and the mid-cingulate cortex. However, because of the inverse problem, EEG and MEG provide only limited spatial resolution and certainty about the generators of cortical pain-induced electromagnetic activity, especially when multiple sources are simultaneously active. On the other hand, intracranial recordings are invasive and do not provide whole-brain coverage. In this study, we thought to investigate the spatio-temporal dynamics of cortical pain processing in 10 healthy subjects using simultaneous EEG/functional magnetic resonance imaging (fMRI). Voltages of 20 ms segments of the EEG root mean square (a global, largely reference-free measure of event-related EEG activity) in a time window 0-400 ms poststimulus were used to model trial-to-trial fluctuations in the fMRI blood oxygen level dependent (BOLD) signal. EEG-derived regressors explained additional variance in the BOLD signal from 140 ms poststimulus onward. According to this analysis, the contralateral parietal operculum was the first cortical area to become activated upon painful laser stimulation. The activation pattern in BOLD analyses informed by subsequent EEG-time windows suggests largely parallel signal processing in the bilateral operculo-insular and mid-cingulate cortices. In that regard, our data are in line with previous reports. However, the approach presented here is noninvasive and bypasses the inverse problem using only temporal information from the EEG.© 2010 Wiley-Liss, Inc.

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