Default mode network connectivity encodes clinical pain: An arterial spin labeling study
Marco L. Loggia, Jieun Kim, Randy L. Gollub, Mark Vangel, Irving Kirsch, Jian Kong, Ajay D. Wasan, Vitaly Napadow
Pain October 29, 2012 DOI: 10.1016/j.pain.2012.07.029 via OpenAlex
Summary
AI-generated from the abstractPatients with chronic low back pain show stronger resting connectivity between the default mode network and the right insula, pregenual anterior cingulate cortex, and left inferior parietal lobule compared to healthy controls. Baseline clinical pain correlates positively with default mode network–right insula connectivity. Physical maneuvers that exacerbate pain produce parallel changes in default mode network–right insula connectivity and disrupt default mode network–pregenual anterior cingulate cortex connectivity, which at baseline was anticorrelated with pain. Baseline default mode network connectivity also predicts maneuver-induced changes in both pain and default mode network–right insula connectivity. These findings support resting default mode network connectivity as a potential neuroimaging biomarker for chronic pain perception.
Study at a glance
| Characteristics | Observational cohort Cross-sectional Peer reviewed |
|---|---|
| Population | Patients with chronic low back pain and healthy controls |
| Intervention | calibrated physical maneuvers |
| Topics | Default mode network |
| Keywords | Insula Resting State FMRI Chronic pain Neuroscience |
| Citations | 319 |
| Key finding | Resting default mode network connectivity to the right insula correlates with clinical pain and tracks pain exacerbation in chronic low back pain patients. |
Abstract
Neuroimaging studies have suggested the presence of alterations in the anatomo-functional properties of the brain of patients with chronic pain. However, investigation of the brain circuitry supporting the perception of clinical pain presents significant challenges, particularly when using traditional neuroimaging approaches. While potential neuroimaging markers for clinical pain have included resting brain connectivity, these cross-sectional studies have not examined sensitivity to within-subject exacerbation of pain. We used the dual regression probabilistic Independent Component Analysis approach to investigate resting-state connectivity on arterial spin labeling data. Brain connectivity was compared between patients with chronic low back pain (cLBP) and healthy controls, before and after the performance of maneuvers aimed at exacerbating clinical pain levels in the patients. Our analyses identified multiple resting state networks, including the default mode network (DMN). At baseline, patients demonstrated stronger DMN connectivity to the pregenual anterior cingulate cortex (pgACC), left inferior parietal lobule, and right insula (rINS). Patients' baseline clinical pain correlated positively with connectivity strength between the DMN and right insula (DMN-rINS). The performance of calibrated physical maneuvers induced changes in pain, which were paralleled by changes in DMN-rINS connectivity. Maneuvers also disrupted the DMN-pgACC connectivity, which at baseline was anticorrelated with pain. Finally, baseline DMN connectivity predicted maneuver-induced changes in both pain and DMN-rINS connectivity. Our results support the use of arterial spin labeling to evaluate clinical pain, and the use of resting DMN connectivity as a potential neuroimaging biomarker for chronic pain perception.