Literature DB >> 28925006

Evidence-based source modeling of nociceptive cortical responses: A direct comparison of scalp and intracranial activity in humans.

Claire Bradley1, Hélène Bastuji1, Luis Garcia-Larrea1.   

Abstract

BACKGROUND: Source modeling of EEG traditionally relies on interplay between physiological hypotheses and mathematical estimates. We propose to optimize the process by using evidence gathered from brain imaging and intracortical recordings.
METHODS: We recorded laser-evoked potentials in 18 healthy participants, using high-density EEG. Brain sources were modeled during the first second poststimulus, constraining their initial position to regions where nociceptive-related activity has been ascertained by intracranial EEG. These comprised the two posterior operculo-insular regions, primary sensorimotor, posterior parietal, anterior cingulate/supplementary motor (ACC/SMA), bilateral frontal/anterior insular, and posterior cingulate (PCC) cortices.
RESULTS: The model yielded an average goodness of fit of 91% for individual and 95.8% for grand-average data. When compared with intracranial recordings from 27 human subjects, no significant difference in peak latencies was observed between modeled and intracranial data for 5 of the 6 assessable regions. Morphological match was excellent for operculo-insular, frontal, ACC/SMA and PCC regions (cross-correlation > 0.7) and fair for sensori-motor and posterior parietal cortex (c-c ∼ 0.5).
CONCLUSIONS: Multiple overlapping activities evoked by nociceptive input can be disentangled from high-density scalp EEG guided by intracranial data. Modeled sources accurately described the timing and morphology of most activities recorded with intracranial electrodes, including those coinciding with the emergence of stimulus awareness. Hum Brain Mapp 38:6083-6095, 2017.
© 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Entities:  

Keywords:  insula; laser-evoked potentials; pain; sEEG; source modeling

Mesh:

Year:  2017        PMID: 28925006      PMCID: PMC6866722          DOI: 10.1002/hbm.23812

Source DB:  PubMed          Journal:  Hum Brain Mapp        ISSN: 1065-9471            Impact factor:   5.038


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