Pain in the default mode network: a voxel-based morphometry study on thermal pain sensitivity

Area of Science:

• Neuroscience
• Pain Research
• Brain Imaging

Background:

• The 'pain matrix' traditionally linked to pain processing is not exclusively activated by pain.
• Deactivated regions, particularly the default mode network (DMN), are increasingly recognized for their functional role in pain perception.
• Understanding structural correlates of pain sensitivity is crucial for advancing pain research.

Purpose of the Study:

• To identify pain-specific structural brain correlates in young adults.
• To investigate the relationship between grey matter volume and thermal pain sensitivity.
• To compare structural differences in the pain matrix and DMN.

Main Methods:

• Utilized voxel-based morphometry (VBM) to analyze grey matter volume.
• Focused analysis on regions within the pain matrix and the default mode network (DMN).
• Controlled for confounding factors like thermal detection/tolerance thresholds and psychological traits.

Main Results:

• Found that reduced grey matter volume (GMV) in the precuneus (a DMN region) predicts lower thermal pain thresholds (higher sensitivity).
• This association between precuneus GMV and pain sensitivity was not observed in the pain matrix regions.
• Demonstrated a dissociation between the precuneus and the pain matrix in relation to pain sensitivity.

Conclusions:

• The precuneus, part of the DMN, is structurally linked to pain sensitivity, independent of the pain matrix.
• Suggests the precuneus's role in pain processing is significant and warrants further investigation.
• Proposes a model of pain as a salience detection system rather than solely a nociceptive-specific system.