Executive Impairment in Alcohol Use Disorder Reflects Structural Changes in Large-Scale Brain Networks: A Joint Independent Component Analysis on Gray-Matter and White-Matter Features

Frontiers in Psychology

article

Chiara Crespi¹  Caterina Galandra²  Marina Manera³  Gianpaolo Basso⁴  Paolo Poggi⁵  Nicola Canessa¹ 

[1] NEtS Center, Scuola Universitaria Superiore Istituto Universitario di Studi Superiori Pavia;Cognitive Neuroscience Laboratory, Istituti Clinici Scientifici Maugeri IRCCS;Psychology Unit, Istituti Clinici Scientifici Maugeri IRCCS;University of Milano-Bicocca;Radiology Unit, Istituti Clinici Scientifici Maugeri IRCCS

关键词: alcohol use disorder;    alcohol chronic consumption;    voxel-based morphometry;    diffusion tensor MRI;    joint independent component analysis;    large-scale brain network;    rehabilitative applications;   

DOI  :  10.3389/fpsyg.2019.02479

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

Alcohol Use Disorder (AUD) entails chronic effects on brain structure. Neurodegeneration due to alcohol toxicity is a neural signature of executive impairment typically observed in AUD, previously related to both gray-matter volume/density and white-matter abnormalities. Recent studies highlighted the role of meso-cortico-limbic structures supporting the salience and executive networks, in which the extent of neurostructural damage is significantly related to patients’ executive performance. Here we aim to integrate multimodal information on gray-matter and white-matter features with a multivariate data-driven approach (joint Independent Component Analysis, jICA), and to assess the relationship between the extent of damage in the resulting neurostructural superordinate components and executive profile in AUD. Twenty-two AUD patients and 18 matched healthy controls (HC) underwent a Magnetic Resonance Imaging (MRI) protocol, alongside clinical and neuropsychological examinations. We ran jICA on five neurostructural features, including gray-matter density and different diffusion tensor imaging metrics. We extracted 12 Independent Components (ICs) and compared the resulting mixing coefficients in patients vs. HC. Finally, we correlated significant ICs with executive and clinical variables. One out of 12 ICs (IC11) discriminated patients from healthy controls and correlated positively both with executive performance in all subjects, and with lifetime duration of alcohol abuse in patients. In line with previous related evidence, this component involved widespread gray-matter and white-matter patterns including key nodes and fiber tracts of salience, default-mode and central executive networks. These findings highlighted the role of multivariate data integration as a valuable approach revealing superordinate hallmarks of neural changes related to cognition in neurological and psychiatric populations.

【 授权许可】

CC BY