Abnormal white matter structural networks characterize heroin-dependent individuals: a network analysis.

Area of Science:

• Neuroscience
• Addiction Research
• Medical Imaging

Background:

• Drug addiction is associated with abnormal brain functional connectivity.
• Alterations in white matter (WM) connectivity in addictive drug users are not well understood.
• Few studies have examined WM connectivity changes in heroin-dependent individuals (HDIs).

Purpose of the Study:

• To investigate whole-brain white matter structural network alterations in heroin-dependent individuals.
• To compare brain network topology between HDIs and healthy controls.
• To identify specific regions and connections affected by heroin dependence.

Main Methods:

• Diffusion Tensor Imaging (DTI) was used to acquire brain data.
• Deterministic fiber tracking constructed whole-brain WM structural networks.
• Graph theoretical analysis and Network-based statistic (NBS) assessed network differences.

Main Results:

• HDIs showed significantly increased global efficiency and network strength, with decreased characteristic path length.
• Nodal efficiency was elevated in the left prefrontal cortex, bilateral orbital frontal cortices, and left anterior cingulate gyrus in HDIs.
• NBS analysis identified increased WM connections in paralimbic, orbitofrontal, prefrontal, and temporal regions in HDIs.

Conclusions:

• Heroin dependence is associated with significant disruptions in whole-brain white matter structural networks.
• Altered brain network topology may underlie the neuromechanisms of heroin addiction.
• Mapping WM structural networks offers a potential avenue for understanding heroin addiction.