Approximation to pain‐signaling network in humans by means of migraine

• Published in: Human brain mapping Vol. 42; no. 3; pp. 766 - 779
• Main Authors: Hosp, Jonas Aurel, Reisert, Marco, Kageneck, Charlotte, Rijntjes, Michel, Weiller, Cornelius
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 15.02.2021
• Subjects: Adult; Bayesian analysis; Brain; Cerebral Cortex - diagnostic imaging; Cerebral Cortex - pathology; Cortex (insular); Diffusion Tensor Imaging - methods; Female; global tractography; Headache; Humans; Integrity; Learning algorithms; Machine learning; Magnetic resonance imaging; Male; Migraine; Migraine Disorders - diagnostic imaging; Migraine Disorders - pathology; Nerve Net - diagnostic imaging; Nerve Net - pathology; Neuroimaging; Pain; Pain - diagnostic imaging; Pain - pathology; pain matrix; Pain perception; Sensory integration; Signal processing; Signal transduction; Signaling; Substantia alba; Substantia grisea; Supervised Machine Learning; Tensors; Young Adult; pain matrix; global tractography; migraine; humans
• ISSN: 1065-9471; 1097-0193; 1097-0193
• DOI: 10.1002/hbm.25261

Nociceptive signals are processed within a pain‐related network of the brain. Migraine is a rather specific model to gain insight into this system. Brain networks may be described by white matter tracts interconnecting functionally defined gray matter regions. Here, we present an overview of the migraine‐related pain network revealed by this strategy. Based on diffusion tensor imaging data from subjects in the Human Connectome Project (HCP) database, we used a global tractography approach to reconstruct white matter tracts connecting brain regions that are known to be involved in migraine‐related pain signaling. This network includes an ascending nociceptive pathway, a descending modulatory pathway, a cortical processing system, and a connection between pain‐processing and modulatory areas. The insular cortex emerged as the central interface of this network. Direct connections to visual and auditory cortical association fields suggest a potential neural basis of phono‐ or photophobia and aura phenomena. The intra‐axonal volume (Vintra) as a measure of fiber integrity based on diffusion microstructure was extracted using an innovative supervised machine learning approach in form of a Bayesian estimator. Self‐reported pain levels of HCP subjects were positively correlated with tract integrity in subcortical tracts. No correlation with pain was found for the cortical processing systems. Brain networks may be described by white matter tracts interconnecting functionally defined grey matter regions. Here, we present an overview of the migraine‐related pain network revealed by this strategy. Based on diffusion tensor imaging data from subjects in the Human Connectome Project database, we used a global tractography approach to reconstruct white matter tracts connecting brain regions that are known to be involved in migraine‐related pain signaling.