Disentangling linear and nonlinear brain responses to evoked deep tissue pain

Marco L. Loggia, Robert R. Edwards, Jieun Kim, Mark G. Vangel, Ajay D. Wasan, Randy L. Gollub, Richard E. Harris, Kyungmo Park, Vitaly Napadow

Research output: Contribution to journalArticlepeer-review

43 Scopus citations

Abstract

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 magnetic resonance imaging, 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 5 different, regionally specific activity profiles in the brain. Linearly increasing (eg, primary somatosensory/motor cortex, insulae) and intensity-independent (eg, 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 (eg, posterior cingulate cortex), linearly decreasing (eg, contralateral inferior parietal lobule), and quadratic (U-shaped; eg, 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 to evaluate whether the response profiles reported here can also be generalized to nonpainful somatosensory processing.

Original languageEnglish (US)
Pages (from-to)2140-2151
Number of pages12
JournalPain
Volume153
Issue number10
DOIs
StatePublished - Oct 2012
Externally publishedYes

Keywords

  • BOLD fMRI
  • Cuff pain algometry
  • Default mode network
  • Human
  • Neuroimaging
  • Psychophysics

ASJC Scopus subject areas

  • Clinical Neurology
  • Anesthesiology and Pain Medicine
  • Neurology
  • Pharmacology

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