Key result
Electroencephalographic features, particularly gamma band activity and contact-heat-evoked potentials, were identified as predominant predictors of acute thermal pain across 26 reviewed studies.
Why the study?
No practical system reliably decodes and predicts pain clinically, creating a need for objective pain assessment tools for patients unable to verbally express pain.
Can electroencephalographic features predict acute experimental pain?
Can electroencephalographic features predict acute experimental pain?
EEG features, particularly gamma band activity, show potential as objective biomarkers for predicting acute thermal pain, which could aid in assessing pain in non-verbal patients.
Nowadays, no practical system has successfully been able to decode and predict pain in clinical settings. The inability of some patients to verbally express their pain creates the need for a tool that could objectively assess pain in these individuals. Neuroimaging techniques combined with machine learning are seen as possible candidates for the identification of pain biomarkers. This review aimed to address the potential use of electroencephalographic features as predictors of acute experimental pain. Twenty-six studies using only thermal stimulations were identified using a PubMed and Scopus search. Combinations of the following terms were used: "EEG," "Electroencephalography," "Acute," "Pain," "Tonic," "Noxious," "Thermal," "Stimulation," "Brain," "Activity," "Cold," "Subjective," and "Perception." Results revealed that contact-heat-evoked potentials have been widely recorded over central areas during noxious heat stimulations. Furthermore, a decrease in alpha power over central regions was revealed, as well as increased theta and gamma powers over frontal areas. Gamma and theta rhythms were associated with connectivity between sensory and affective regions involved in pain processing. A machine learning analysis revealed that the gamma band is a predominant predictor of acute thermal pain. This review also addressed the need of supplementing current spectral features with techniques that allow the investigation of network dynamics.
No takes yet. Share an insight, caveat, or question.
Savignac et al. (2021) conducted a review in Acute thermal pain. Electroencephalography (EEG) was evaluated on Predictors of acute experimental pain. Electroencephalographic features, particularly gamma band activity and contact-heat-evoked potentials, were identified as predominant predictors of acute thermal pain across 26 reviewed studies.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: