Clustering Electrophysiological Predisposition to Binge Drinking: An Unsupervised Machine Learning Analysis.

ABSTRACT:

Background

The demand for fresh strategies to analyze intricate multidimensional data in neuroscience is increasingly evident. One of the most complex events during our neurodevelopment is adolescence, where our nervous system suffers constant changes, not only in neuroanatomical traits but also in neurophysiological components. One of the most impactful factors we deal with during this time is our environment, especially when encountering external factors such as social behaviors or substance consumption. Binge drinking (BD) has emerged as an extended pattern of alcohol consumption in teenagers, not only affecting their future lifestyle but also changing their neurodevelopment. Recent studies have changed their scope into finding predisposition factors that may lead adolescents in

SUBMITTER: Uceta M 

PROVIDER: S-EPMC11583822 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature