Predicting the Risk of Driving Under the Influence of Alcohol Using EEG-Based Machine Learning.

Driving under the influence of alcohol (DUIA) is closely associated with alcohol use disorder (AUD). Our previous study on machine learning (ML) algorithms revealed a very high accuracy of decision trees with neuropsychological features in predicting the risk of DUIA despite limited data availability. Thus, this study aimed at comparing six well-known ML algorithms based on electroencephalographic (EEG) signals to differentiate adults with AUD and DUIA (AUD-DD) from those with AUD without DUIA (AUD-NDD) and controls.

A systematic review and meta-analysis of the relationship between heavy smoking and probability discounting.

Background And Objectives: Probability discounting (PD), which refers to the process of adjusting the value of future probabilities when making decisions, is a method of measuring impulsive decision-making; however, the relationship between PD and nicotine remains unclear. The current study aimed at investigating the significance of PD in individuals who smoke.

Methods: According to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we searched the PubMed, Embase, PsycINFO, and Web of Science databases for articles comparing individuals who smoke and their tobacco-naïve controls using PD task as outcome measure from inception to May 2023.

Meta-analysis reveals a reduced surface area of the amygdala in individuals with attention deficit/hyperactivity disorder.

Despite the reported lack of structural alterations in the amygdala of individuals with attention deficit/hyperactivity disorder (ADHD) in previous meta-analyses, subsequent observational studies produced conflicting results. Through incorporating the updated data from observational studies on structural features of the amygdala in ADHD, the primary goal of this study was to examine the anatomical differences in amygdala between subjects with ADHD and their neurotypical controls. Using the appropriate keyword strings, we searched the PubMed, Embase, and Web of Science databases for English articles from inception to February 2022.

Structural and Functional Neural Correlates in Individuals with Excessive Smartphone Use: A Systematic Review and Meta-Analysis.

Background: Despite known association of internet addiction with a reduced brain volume and abnormal connectivity, the impact of excessive smartphone use remains unclear. Methods: PubMed, Embase, ClinicalTrial.gov, and Web of Science databases were systematically searched from inception to July 2022 using appropriate keywords for observational studies comparing differences in brain volumes and activations between excessive smartphone users and individuals with regular use by magnetic resonance imaging.