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A multi-ingredient brain function model predicting chronic pain in youth: a window into future well-being

CORDIS · observation · Publication date unknown

ogy to predict who will develop chronic pain. I will use a longitudinal design involving adolescents undergoing major surgeries, coupled with an experimental neuroimaging approach, precision fMRI and machine learning methods to: (i) test the directionality of the association between risk factors, brain physiology and future onset of chronic pain (WP1); (ii) identify a neurophysiological multi-ingredient model that predicts, before surgery, who will (and via what mechanisms) develop chronic postsurgical pain (WP2); and, in a subset of pre-selected patients, (iii) test whether target neurophysiological pathways track pain along subacute and chronic pain phases and after treatment (WP3). I hypothesize that target brain pathways during pain, multisensory unpleasantness and self-evaluation in an affective context will: (i) synergistically predict future onset of pain at the individual adolescent level; (ii) be associated with major risk sources, (iii) exacerbate with chronic pain and attenuate after effective treatment. The results will lay foundational tools that can be used prospective

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recordType

award

status

SIGNED

region

EU

value

1998081

unit

EUR