A novel electroencephalography‐based tool for objective assessment of network dynamics activated by nociceptive stimuli

Abstract

Background: Pain perception is typically assessed using subjective measures; an objective measure of the response to pain would be valuable. In this study, Brain Network Activation (BNA), a novel multivariate pattern analysis and scoring algorithm, was applied to event-related potentials (ERPs) elicited by cortical responses to brief heat stimuli. Objectives of this study were to evaluate the utility of BNA as a quantitative and qualitative measure of cortical response to pain. Methods: Contact Heat Evoked Potentials (CHEPs) data were collected from 17 healthy, right-handed volunteers (10 M, 7F) using 5 different temperatures (35, 41, 46, 49 and 52°C). A set of spatio-temporal activity patterns common to all the subjects in the group (Reference Brain Network Model; RBNM) was generated using the BNA algorithm, based on evoked responses at 52°C. Results: Frame by frame 'unfolding' of the brain network across time showed qualitative differences between responses to painful and non-painful stimuli. Brain network activation scores were shown to be a better indicator of the individual's sensitivity to pain when compared to subjective pain ratings. Additionally, BNA scores correlated significantly with temperature, demonstrated good testretest reliability, as well as a high degree of sensitivity, specificity and accuracy in correctly categorizing subjects who reported stimuli as painful. Conclusions: These results may provide evidence that the multivariate analysis performed with BNA may be useful as a quantitative, temporally sensitive tool for assessment of pain perception.

Clinically Effective Treatment of Fibromyalgia Pain With High-Definition Transcranial Direct Current Stimulation: Phase II Open-Label Dose Optimization

“…The RBNM was characterized with central theta-delta activations and represented the response to pain of healthy individuals (Fig 4, top left). This network has been validated in a previous study 36 in which we showed a similar central theta-delta network for CHEPs at 52°C. The dynamics of the network activity can be revealed in a frame-by-frame presentation (Fig 4, bottom), with a heat probe applied, activating pain-related network activity (Fig 4, top right).…”

“…In addition, we assessed biomarkers of response, including an electroencephalography (EEG)/ event-related potential (ERP) analysis of brain reorganization, known as brain network activation (BNA). 33,36,39 The exploratory aims were to test screening procedures to predict response and individualize treatment.…”

Skin denervation does not alter cortical potentials to surface concentric electrode stimulation: A comparison with laser evoked potentials and contact heat evoked potentials

“…According to the guidelines issued by the International Federation of Clinical Neurophysiology, and the Neuropathic Pain Special Interest Group of the IASP, laser evoked potentials (LEPs) related to Aδ‐fibre activation are the easiest and most reliable neurophysiological technique for assessing nociceptive system function (Cruccu et al., ; Haanpää et al., ). Among nociceptive evoked potentials, contact‐heat‐evoked potentials (CHEPs) are also commonly used for investigation of patients with neuropathic pain, and several studies have indicated that CHEPs are mediated by Aδ‐fibre activation (Granovsky et al., ; Reches et al., ). Pain related evoked potentials by concentric electrode stimulation (PREPs) have also been introduced to assess nociceptive system.…”

Brain Network Activation as a Novel Biomarker for the Return-to-Play Pathway Following Sport-Related Brain Injury

“…A recent approach that examines ERPs via a brain network activation (BNA) analysis may provide the next step in the evolution of EEG as an accepted tool for diagnosis and recovery assessment. A detailed description of the BNA algorithm is provided elsewhere ( 23 – 27 ); thus, only a brief summary of the method is given here. BNA analysis is a new tool for evaluating the network dynamics associated with brain responses (i.e., ERPs).…”

“…Specifically, the BNA algorithm extracts the interparticipant sequential temporal co-occurrence of pairs of ERP peaks (event pairs) extracted from signals that were band-pass filtered into different frequency ranges and that emerged in different spatial locations. Next, BNA integrates group-common event pairs of specific temporal relations, spatial locations frequencies, and amplitudes into a unified functional network, which is the BNA group network ( 25 – 27 ). This stage must be completed only once as it becomes the normative group for comparison for future clinical comparisons.…”