Structural differences in adolescent brains can predict alcohol misuse

Structural differences in adolescent brains can predict alcohol misuse

Alcohol misuse during adolescence (AAM) has been associated with disruptive development of adolescent brains. In this longitudinal machine learning (ML) study, we could predict AAM significantly from brain structure (T1-weighted imaging and DTI) with accuracies of 73 -78% in the IMAGEN dataset (n∼11...

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Main Authors: Roshan Prakash Rane, Evert Ferdinand de Man, JiHoon Kim, Kai Görgen, Mira Tschorn, Michael A Rapp, Tobias Banaschewski, Arun LW Bokde, Sylvane Desrivieres, Herta Flor, Antoine Grigis, Hugh Garavan, Penny A Gowland, Rüdiger Brühl, Jean-Luc Martinot, Marie-Laure Paillere Martinot, Eric Artiges, Frauke Nees, Dimitri Papadopoulos Orfanos, Herve Lemaitre, Tomas Paus, Luise Poustka, Juliane Fröhner, Lauren Robinson, Michael N Smolka, Jeanne Winterer, Robert Whelan, Gunter Schumann, Henrik Walter, Andreas Heinz, Kerstin Ritter, IMAGEN consortium
Format: Article
Language:English
Published: eLife Sciences Publications Ltd 2022-05-01
Series:eLife
Subjects:
adolescence alcohol misuse
machine learning
data science for psychiatry
alcohol use disorder
magnetic resonance imaging
confound control
Online Access:https://elifesciences.org/articles/77545

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