Effective Connectivity for Default Mode Network Analysis of Alcoholism
Danish M. Khan, Nidal Kamel, Mustapha Muzaimi, Timothy Hill
Brain Connectivity February 1, 2021 DOI: 10.1089/brain.2019.0721 (opens in new tab)
Summary
AI-generated from the abstractElectroencephalography (EEG), with its high temporal resolution, was used to estimate effective connectivity within the default mode network (DMN) in 20 subjects with alcoholism and 25 healthy controls. The resulting connectivity diagrams revealed unidirectional causal effects among DMN regions. Variations in these causal effects between controls and alcoholics correlated with symptoms commonly associated with alcoholism, such as cognitive and memory impairments, executive control deficits, and attention deficiency. The findings provide insight into how alcohol modulates cognitive and executive functions, potentially aiding treatment for alcohol use disorder.
Study at a glance
| Characteristics | Observational cohort Peer reviewed |
|---|---|
| Sample size | 45 |
| Population | Subjects with alcoholism and healthy controls |
| Key finding | Variations in effective connectivity within the default mode network between controls and alcoholics correlate with symptoms associated with alcoholism. |
Abstract
Introduction: With the recent technical advances in brain imaging modalities such as magnetic resonance imaging, positron emission tomography, and functional magnetic resonance imaging ( f MRI), researchers' interests have inclined over the years to study brain functions through the analysis of the variations in the statistical dependence among various brain regions. Through its wide use in studying brain connectivity, the low temporal resolution of the f MRI represented by the limited number of samples per second, in addition to its dependence on brain slow hemodynamic changes, makes it of limited capability in studying the fast underlying neural processes during information exchange between brain regions. Materials and Methods: In this article, the high temporal resolution of the electroencephalography (EEG) is utilized to estimate the effective connectivity within the default mode network (DMN). The EEG data are collected from 20 subjects with alcoholism and 25 healthy subjects (controls), and used to obtain the effective connectivity diagram of the DMN using the Partial Directed Coherence algorithm. Results: The resulting effective connectivity diagram within the DMN shows the unidirectional causal effect of each region on the other. The variations in the causal effects within the DMN between controls and alcoholics show clear correlation with the symptoms that are usually associated with alcoholism, such as cognitive and memory impairments, executive control, and attention deficiency. The correlation between the exchanged causal effects within the DMN and symptoms related to alcoholism is discussed and properly analyzed. Conclusion: The establishment of the causal differences between control and alcoholic subjects within the DMN regions provides valuable insight into the mechanism by which alcohol modulates our cognitive and executive functions and creates better possibility for effective treatment of alcohol use disorder.