Brain network correlates of tonic and chronic pain

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Pain is a complex and highly subjective experience, which subserves vital protective functions. However, in chronic pain states, ongoing pain no longer subserves protective functions but represents a pathological condition with devastating effects on quality of life. Recent evidence indicates that the brain is actively involved in the development and maintenance of chronic pain. However, the cerebral mechanisms of chronic pain are not fully understood. In the preceding project, we have therefore started to investigate the cerebral correlates of long-lasting experimental and clinical pain using electroencepahlography (EEG). The proposed project renewal builds upon the paradigms and analyses of the previous project and extends our approach from the assessment of pain-related brain activity to the comprehensive investigation of brain connectivity, i.e., how communication in the human brain relates to ongoing pain. In 100 patients suffering from chronic back pain and 100 healthy human subjects, we will assess neuronal communication using recent brain connectivity measures, which overcome field spread and volume conduction limitations of traditional EEG analyses. Based on these connectivity measures we will perform timely graph theory-based network analyses of brain connectivity during ongoing tonic and chronic pain. A thorough clinical and psychological assessment will allow for relating network measures of brain connectivity to the individual clinical and psychological characteristics. Based on our previous findings, we hypothesize that the current intensity of ongoing experimental and clinical pain is reflected by local gamma oscillations in medial prefrontal cortex, which represents an important node in a brain network connecting at beta and/or theta frequencies. We further hypothesize that chronic pain is associated with additional global changes of brain connectivity, e.g., a reduction in small-worldness. We expect that these global network changes reflect long-term pain-related disability rather than the current pain intensity and are therefore not observed in healthy controls. In a further step, we will use multivariate pattern analysis to test whether patterns of brain connectivity can be used to decode ongoing pain. This approach could help to establish neuronal markers of chronic pain, which might support the diagnosis and classification of chronic pain and the monitoring and optimization of pain therapy. The proposed project renewal, thus, promises novel insights into the brain mechanisms of pain with possible implications for the diagnosis and treatment of chronic pain.