Online social activity time predicts ADHD problems in youth from late childhood to early adolescence in the ABCD study.

Online social interactions increase into adolescence. Although cross-sectional studies have positively associated online social activity (OSA) time and attention-deficit/hyperactivity disorder (ADHD) problems, the directionality remains unclear. Therefore, we examined longitudinal associations between OSA time and ADHD problems using data from the Adolescent Brain Cognitive Development (ABCD) study.

Hypercomplex Graph Neural Network: Towards Deep Intersection of Multi-modal Brain Networks.

The multi-modal neuroimage study has provided insights into understanding the heteromodal relationships between brain network organization and behavioral phenotypes. Integrating data from various modalities facilitates the characterization of the interplay among anatomical, functional, and physiological brain alterations or developments. Graph Neural Networks (GNNs) have recently become popular in analyzing and fusing multi-modal, graph-structured brain networks.

The dorsomedial prefrontal cortex represents subjective value across effort-based and risky decision-making.

Decisions that require taking effort costs into account are ubiquitous in real life. The neural common currency theory hypothesizes that a particular neural network integrates different costs (e.g.

Youth Screen Media Activity Patterns and Associations With Behavioral Developmental Measures and Resting-state Brain Functional Connectivity.

Objective: Screen media activity (SMA) consumes considerable time in youth's lives, raising concerns about the effects it may have on youth development. Disentangling mixed associations between SMA of youth and developmental measures should move beyond overall screen time and consider types and patterns of SMA. This study aimed to identify reliable and generalizable SMA patterns among youth and examine their associations with behavioral developmental measures and developing brain functional connectivity.

Subgroups of internet gaming disorder based on addiction-related resting-state functional connectivity.

Aims: To identify subgroups of people with internet gaming disorder (IGD) based on addiction-related resting-state functional connectivity and how these subgroups show different clinical correlates and responses to treatment.

Design: Secondary analysis of two functional magnetic resonance imaging (fMRI) data sets.

Setting: Zhejiang province and Beijing, China.

Emotional bias modification weakens game-related compulsivity and reshapes frontostriatal pathways.

Addiction is characterized by compulsive engagement despite adverse consequences. Psychobehavioural interventions targeting compulsivity in addictions are relatively rare, particularly for behavioural addictions like internet gaming disorder (IGD). Free from confounding drug-on-brain effects, IGD provides a promising model for understanding neuropsychological processes of addictions.

Gender-related differences in involvement of addiction brain networks in internet gaming disorder: Relationships with craving and emotional regulation.

Background: Abnormal interactions among addiction brain networks associated with intoxication, negative affect, and anticipation may have relevance for internet gaming disorder (IGD). Despite prior studies having identified gender-related differences in the neural correlates of IGD, gender-related differences in the involvement of brain networks remain unclear.

Methods: One-hundred-and-nine individuals with IGD (54 males) and 111 with recreational game use (RGU; 58 males) provided resting-state fMRI data.

Connectome-based prediction of marital quality in husbands' processing of spousal interactions.

Marital quality may decrease during the early years of marriage. Establishing models predicting individualized marital quality may help develop timely and effective interventions to maintain or improve marital quality. Given that marital interactions have an important impact on marital well-being cross-sectionally and prospectively, neural responses during marital interactions may provide insight into neural bases underlying marital well-being.

Efficient Brain Connectivity Reconfiguration Predicts Higher Marital Quality and Lower Depression.

Social-information processing is important for successful romantic relationships and protecting against depression, and depends on functional connectivity (FC) within and between large-scale networks. Functional architecture evident at rest is adaptively reconfigured during task and there were two possible associations between brain reconfiguration and behavioral performance during neurocognitive tasks (efficiency effect and distraction-based effect). This study examined relationships between brain reconfiguration during social-information processing and relationship-specific and more general social outcomes in marriage.

A review of psychological interventions for internet addiction.

Internet addiction (IA) may constitute a widespread and serious mental problem. Previous reviews have not fully considered potential factors that may contribute to therapeutic outcomes or predict behavioral changes. Such information is relevant to understand the active ingredients of interventions and to develop more efficacious treatments that target features of IA.

Neural classification of internet gaming disorder and prediction of treatment response using a cue-reactivity fMRI task in young men.

Background: Neural mechanisms underlying internet gaming disorder (IGD) are important for diagnostic considerations and treatment development. However, neurobiological underpinnings of IGD remain relatively poorly understood.

Methods: We employed multi-voxel pattern analysis (MVPA), a machine-learning approach, to examine the potential of neural features to statistically predict IGD status and treatment outcome (percentage change in weekly gaming time) for IGD.

Resting-state connectome-based support-vector-machine predictive modeling of internet gaming disorder.

Internet gaming disorder (IGD), a worldwide mental health issue, has been widely studied using neuroimaging techniques during the last decade. Although dysfunctions in resting-state functional connectivity have been reported in IGD, mapping relationships from abnormal connectivity patterns to behavioral measures have not been fully investigated. Connectome-based predictive modeling (CPM)-a recently developed machine-learning approach-has been used to examine potential neural mechanisms in addictions and other psychiatric disorders.

Impaired regulation of both addiction-related and primary rewards in individuals with internet gaming disorder.

Poor executive function (EF) has been implicated in addictions. Among "hot" EFs (i.e.