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Graph Theoretical Analysis of Brain Structural Connectivity in Patients with Alcohol Dependence
Hyunjung Lee1, Joon Hyung Jung1,2, Seungwon Chung1,3
1Department of Psychiatry, Chungbuk National University Hospital, Cheongju 28644, Korea.
Experimental Neurobiology
|November 6, 2023
Summary
Alcohol dependence impacts brain network stability, leading to reduced local and global efficiency in key brain networks. This structural connectivity difference suggests impaired information processing in individuals with alcohol use disorder.
Area of Science:
- Neuroscience
- Brain Imaging
- Graph Theory
Background:
- Alcohol dependence is a chronic relapsing brain disorder.
- Understanding its effects on brain structural connectivity is crucial.
- Graph theory provides a framework for analyzing complex brain networks.
Purpose of the Study:
- To compare brain structural connectivity using graph theory between alcohol-dependent patients and social drinkers.
- To investigate alterations in network efficiency and transitivity associated with alcohol dependence.
Main Methods:
- 3T magnetic resonance imaging (MRI) was used to acquire brain data.
- Whole-brain tractography was performed using DSI Studio.
- Graph analysis was conducted using the igraph R package on structural connectivity matrices derived from 400 cortical regions of interest (ROIs).
Main Results:
- The alcohol group exhibited significantly lower local efficiency in the whole-brain, somato-motor, and default mode networks.
- Lower global efficiency was observed in the control network for the alcohol group.
- The alcohol group showed higher transitivity in the dorsal attention network compared to controls.
Conclusions:
- Structural stability of the whole-brain network is compromised in alcohol dependence.
- These network alterations may result in ineffective information processing.
- Findings highlight the neurobiological impact of alcohol dependence on brain network organization.
