Identifying brain nociceptive information transmission in patients with chronic somatic pain

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Abstract

Introduction:

Recent advances regarding mechanisms of chronic pain emphasize the role of corticolimbic circuitry in predicting risk for chronic pain, independently from the site of injury-related parameters. These results compel revisiting the role of peripheral nociceptive signaling in chronic pain. We address this issue by examining what information brain circuitry transmits regarding the intensity of chronic pain and how this information may be related to a common comorbidity, depression.

Objectives:

To identify what information brain circuitry transmits regarding intensity of chronic somatic pain.

Methods:

Resting-state functional magnetic resonance imaging was used in a large group of patients with chronic pain (n = 40 chronic back pain and n = 44 osteoarthritis patients), and in comparison with healthy subjects (n = 88). We used a graph theoretical measure, degree count, to investigate voxelwise information sharing/transmission in the brain. Degree count, a functional connectivity–based measure, identifies the number of voxels functionally connected to every given voxel. Subdividing the chronic pain cohort into discovery, replication, and also for the overall group, we show that only degree counts of diencephalic voxels centered in the ventral–lateral thalamus reflected intensity of chronic pain, independently of depression.

Results:

Pain intensity was reliably associated with degree count of the thalamus, which was correlated negatively with components of the default mode network and positively with the periaqueductal gray (in contrast to healthy controls). Depression scores were not reliably associated with regional degree count.

Conclusion:

Collectively, the results suggest that, across 2 types of chronic pain, nociceptive-specific information is relayed through the spinothalamic pathway to the lateral thalamus, potentiated by pronociceptive descending modulation, and interrupting cortical cognitive processes.

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