Open AccessIdentification of traits and functional connectivity-based neurotraits of chronic pain
Author(s) -
Étienne Vachon-Presseau,
Sara Berger,
Taha Abdullah,
James W. Griffith,
Thomas J. Schnitzer,
A. Vania Apkarian
Publication year - 2019
Publication title -
plos biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.127
H-Index - 271
eISSN - 1545-7885
pISSN - 1544-9173
DOI - 10.1371/journal.pbio.3000349
Subject(s) - chronic pain , trait , big five personality traits , personality , functional magnetic resonance imaging , socioeconomic status , biology , neurophysiology , clinical psychology , neuroscience , psychology , medicine , population , computer science , social psychology , environmental health , programming language
Psychological and personality factors, socioeconomic status, and brain properties all contribute to chronic pain but have essentially been studied independently. Here, we administered a broad battery of questionnaires to patients with chronic back pain (CBP) and collected repeated sessions of resting-state functional magnetic resonance imaging (fMRI) brain scans. Clustering and network analyses applied on the questionnaire data revealed four orthogonal dimensions accounting for 56% of the variance and defining chronic pain traits. Two of these traits—Pain-trait and Emote-trait—were associated with back pain characteristics and could be related to distinct distributed functional networks in a cross-validation procedure, identifying neurotraits. These neurotraits showed good reliability across four fMRI sessions acquired over five weeks. Further, traits and neurotraits all related to the income, emphasizing the importance of socioeconomic status within the personality space of chronic pain. Our approach is a first step in providing metrics aimed at unifying the psychology and the neurophysiology of chronic pain applicable across diverse clinical conditions.