Description
- Abstract:
- Numerous neural imaging and electrophysiological markers have been identified as correlates of pain, however, none have provided for the reliable, quantitative measurement of a human’s perceptual experience. In order to construct a more principled understanding of the cortical signals indicative of acute and chronic pain, this study takes two approaches, respectively. Part 1 elucidates where, when, and how noxious sensory input translates into magneto- and electroencephalography (M/EEG) evoked responses in primary somatosensory cortex (S1). Specifically, Part 1 uses a biophysically-principled model of a cortical column, Human Neocortical Neurosolver (HNN), to simulate the circuit mechanisms underlying the early-latency laser-evoked potential (LEP) versus median nerve stimulation-evoked potential (MNEP). The HNN model demonstrates that the early-latency LEP (i.e., the Aδ-N1 complex) emerges from S1 as the unique result of a phase-locked burst of proximal drive (from lemniscal thalamus to S1 layer 4) and distal drive (from high-order cortex or non-lemniscal thalamus to S1 layer 2/3). Furthermore, the inter-spike interval of pre-synaptic inputs occur at a theta period (125 ms) and gamma period (25 ms), respectively. Part 2 examines the transient nature of spectral EEG activity in humans with resting-state chronic pain (i.e., lumbar radiculopathy). Motivated by the understanding that governing mechanisms of ``rhythmic" neural activity begin and end in finite time, Part 2 compares four features of spectral events (i.e., count/epoch, power, duration, and frequency span) between the chronic pain and healthy control populations in empirically-determined frequency bands. Centered around 40 Hz, spectral event analysis revealed that three of the four features (count/epoch, peak power, and frequency span) were significantly different between the two populations for the eyes open condition and two of the four features (count/epoch and frequency span) where significantly different between the two populations for the eyes closed condition. Overall, the results of this study predict that specific bursts of rhythmic events facilitate transfer of pain-related information and call for a more targeted investigation for their use as both biomarkers and underlying circuit mechanisms.
- Notes:
- Thesis (Sc. M.)--Brown University, 2019
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Citation
Thorpe, Ryan V.,
"Characterizing M/EEG measures of pain through biophysically-principled neuromodeling and spectral event analysis"
(2019).
Biomedical Engineering Theses and Dissertations.
Brown Digital Repository. Brown University Library.
https://doi.org/10.26300/f7ba-n221
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Biomedical Engineering Theses and Dissertations
Theses and Dissertations for the Biomedical Engineering department....