Work

Attentional bias alignment for pain: A neurophysiological approach

Year: 2025

Type: article

Abstract: Attentional bias (AB) toward pain-related information has been implicated in the development and maintenance of pain problems. Recent theoretical frameworks propose that AB is not a fixed trait but rather a dynamic process that aligns with contextual and goal-related factors. A Virtual Reality (VR) paradigm-PainFlex-was recently developed to assess AB alignment. In this study, the PainFlex paradigm was combined with neurophysiological indices of somatosensory attention to obtain a measure of AB uncontaminated by task instructions. Participants were approached by dynamic stimuli directed at a hand either threatened by pain or not and were exposed to a CS+ (i.e., a pen previously paired with pain) or a CS- (i.e., a pen never paired with pain). Tactile stimuli were delivered to either the threatened or the safe hand to elicit somatosensory evoked potentials (SEPs). Results showed that N120 amplitudes were significantly higher at the threat location compared to the safe location, indicating AB. Additionally, P200 amplitudes were reduced at the safe location, but only when the nopain side was approached, suggesting a dynamic and context-dependent response. Contrary to the hypothesis, no interaction with CS type emerged for either component, indicating that AB did not align with changes in the presence of threat as was expected. In conclusion, these findings provide only partial support for the context-sensitivity of AB, highlighting the complexity of attentional processes in pain-related contexts. PERSPECTIVE: This study integrates EEG with a VR paradigm to examine attentional bias in pain. Findings show enhanced somatosensory responses to threat but limited alignment with contextual cues, underscoring the complexity of attentional processes in pain.

Source: Journal of Pain

DOI: 10.1016/j.jpain.2025.105641

Authors: Eleana A. Pinto, Justine Mac Goris, Stefaan Van Damme, Richard Benning, Dimitri ML Van Ryckeghem

Institutions: Ghent University, University of Luxembourg, Maastricht University

Language: English

Topic: Pain Mechanisms and Treatments

Subfield: Physiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $4,180