Neural encoding of pain is robust within but unstable between individuals

Area of Science:

• Neuroscience
• Pain Perception
• Psychophysics

Background:

• Pain perception exhibits significant intra- and inter-individual variability, even with constant sensory input.
• Understanding the neural encoding of these variations is crucial for pain mechanisms and brain-based clinical markers.
• Previous research on neural correlates of pain variability has yielded inconsistent findings regarding robustness.

Purpose of the Study:

• To investigate the neural patterns underlying intra- and inter-individual variations in pain perception.
• To assess the temporal stability and cross-cohort replicability of these neural patterns.
• To determine the suitability of brain-based markers for clinical applications in pain assessment.

Main Methods:

• Electroencephalography (EEG) was employed in 161 healthy participants.
• Bayesian multivariate multi-model regression analyzed the relationship between pain ratings and EEG responses.
• The study design included a 4-week re-test and replication in an independent cohort (n=111).

Main Results:

• Neural patterns for inter-individual pain differences were repeatable over time but not across cohorts.
• Neural patterns for intra-individual pain fluctuations demonstrated robustness over time and across cohorts.
• Distinct neural patterns underlie within-person and between-person pain variability, differing in robustness.

Conclusions:

• Intra-individual pain variability is encoded by robust neural patterns, making brain markers suitable for tracking fluctuations.
• Inter-individual pain variability is less robustly encoded by neural patterns across different populations.
• Within-person analyses are vital for advancing pain mechanisms and developing clinically relevant pain biomarkers.