ArticleJournal of neurophysiology2017
Automated classification of pain perception using high-density electroencephalography data.
Article in Journal of neurophysiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.
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Who cites it
31 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Potential applications of artificial intelligence in pain management: a scoping review.Frontiers in pain research (Lausanne, Switzerland) · 2026Pooled it
- Empathy for pain persists across live two-way video interactions and viewing of prerecorded videos.Cognitive, affective & behavioral neuroscience · 2026Article
- Preoperative Beta and Gamma EEG Spectral Power as Independent Predictors of Acute Postoperative Pain in Spinal Surgery: A Prospective Observational Cohort Study.Journal of pain research · 2026Article
- Objective monitoring of acute pain and nociception in anaesthesia and intensive care: evidence and applications.Anaesthesiology intensive therapy · 2025Review
- Physiological Sensor Modality Sensitivity Test for Pain Intensity Classification in Quantitative Sensory Testing.Sensors (Basel, Switzerland) · 2025Article
- Physiological framework for non-invasive detection and objective nociception activity in communicative patients: a pilot case study.Frontiers in physiology · 2025Article
- The Role of the Mu Opioid Receptors of the Medial Prefrontal Cortex in the Modulation of Analgesia Induced by Acute Restraint Stress in Male Mice.International journal of molecular sciences · 2024Article
- A systematic review of neurophysiological sensing for the assessment of acute pain.NPJ digital medicine · 2023Review
- External validation of binary machine learning models for pain intensity perception classification from EEG in healthy individuals.Scientific reports · 2023Article
- PainVision-based evaluation of brain potentials: a novel approach for quantitative pain assessment.Frontiers in bioengineering and biotechnology · 2023Article
- Artificial Intelligence for Automatic Pain Assessment: Research Methods and Perspectives.Pain research & management · 2023Review
- In search of a composite biomarker for chronic pain by way of EEG and machine learning: where do we currently stand?Frontiers in neuroscience · 2023Review
- Changes in alpha, theta, and gamma oscillations in distinct cortical areas are associated with altered acute pain responses in chronic low back pain patients.Frontiers in neuroscience · 2023Article
- Electroencephalography functional connectivity-A biomarker for painful polyneuropathy.European journal of neurology · 2023Article
- Premature infants display discriminable behavioral, physiological, and brain responses to noxious and nonnoxious stimuli.Cerebral cortex (New York, N.Y. : 1991) · 2022Article
- Distinct spatio-temporal and spectral brain patterns for different thermal stimuli perception.Scientific reports · 2022Article
- Elevated and Slowed EEG Oscillations in Patients with Post-Concussive Syndrome and Chronic Pain Following a Motor Vehicle Collision.Brain sciences · 2021Article
- The Prediction of Acute Postoperative Pain Based on Neural Oscillations Measured before the Surgery.Neural plasticity · 2021Article
- Pain phenotypes classified by machine learning using electroencephalography features.NeuroImage · 2020Article
- Metabolite activity in the anterior cingulate cortex during a painful stimulus using functional MRS.Scientific reports · 2020Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The translation of brief, millisecond-long pain-eliciting stimuli to the subjective perception of pain is associated with changes in theta, alpha, beta, and gamma oscillations over sensorimotor cortex. However, when a pain-eliciting stimulus continues for minutes, regions beyond the sensorimotor cortex, such as the prefrontal cortex, are also engaged. Abnormalities in prefrontal cortex have been associated with chronic pain states, but conventional, millisecond-long EEG paradigms do not engage prefrontal regions. In the current study, we collected high-density EEG data during an experimental paradigm in which subjects experienced a 4-s, low- or high-intensity pain-eliciting stimulus. EEG data were analyzed using independent component analyses, EEG source localization analyses, and measure projection analyses. We report three novel findings. First, an increase in pain perception was associated with an increase in gamma and theta power in a cortical region that included medial prefrontal cortex. Second, a decrease in lower beta power was associated with an increase in pain perception in a cortical region that included the contralateral sensorimotor cortex. Third, we used machine learning for automated classification of EEG data into low- and high-pain classes. Theta and gamma power in the medial prefrontal region and lower beta power in the contralateral sensorimotor region served as features for classification. We found a leave-one-out cross-validation accuracy of 89.58%. The development of biological markers for pain states continues to gain traction in the literature, and our findings provide new information that advances this body of work.
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