Person:

Vangel, Mark

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 (ASL) 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 anti-correlated with pain. Finally, baseline DMN connectivity predicted maneuver-induced changes in both pain and DMN-rINS connectivity. Our results support the use of ASL to evaluate clinical pain, and the use of resting DMN connectivity as a potential neuroimaging biomarker for chronic pain perception.

Pain stimuli evoke widespread responses in the brain. However, our understanding of the physiological significance underlying heterogeneous response within different pain-activated and -deactivated regions is still limited. Using functional MRI, we evaluated brain responses to a wide range of stimulus intensity levels (1 innocuous, 7 painful) in order to estimate region-specific stimulus-response functions, which we hypothesized could illuminate that region’s functional relationship to pain. Linear and nonlinear brain responses to pain were estimated through independent Legendre polynomial transformations of pain ratings within a general linear model. This approach identified at least five different, regionally-specific activity profiles in the brain. Linearly increasing (e.g., primary somatosensory/motor cortex, insulae) and intensity-independent (e.g., secondary somatosensory cortex) activation was noted in traditional pain processing areas, potentially reflecting sensory encoding and all-or-none salience responses, respectively. Multiple activity profiles were seen in areas of the default mode network (DMN): intensity-independent deactivation (e.g., posterior cingulate cortex), linearly decreasing (e.g., contralateral inferior parietal lobule), and quadratic (U-shaped; e.g., medial prefrontal cortex). The latter observation suggests that: 1) different DMN subregions exhibit functional heterogeneity and 2) some DMN subregions respond in a percept-related manner to pain, suggesting closer linkage between the DMN and pain processing than previously thought. Future studies should apply a similar approach using innocuous stimuli of multiple intensities in order to evaluate whether the response profiles reported here can also be generalized to nonpainful somatosensory processing.