Background and aims: The inclusion of gaming disorder as a new diagnosis in the 11th revision of the International Statistical Classification of Diseases (ICD-11) has caused ongoing debate. This review aimed to summarise the potential neural mechanisms of gaming disorder and provide additional evidence for this debate.Methods: We conducted a comprehensive literature review of gaming disorder, focusing on studies that investigated its clinical characteristics and neurobiological mechanisms. Based on this evidence, we further discuss gaming disorder as a psychiatric disorder.Results: The present review demonstrated that the brain regions involved in gaming disorder are related to executive functioning (e.g., anterior cingulate cortex and dorsolateral prefrontal cortex), reward systems (e.g., striatum and orbitofrontal cortex), and emotional regulation (e.g., insula and amygdala). Despite the inclusion of gaming disorder in the ICD-11, the debate remains on the benefits and harms of classifying it as a mental health disorder. Opponents argue that the current manifestations that support gaming disorder as a psychiatric disorder remain inadequate, it could cause moral panic among healthy gamers, and that the label of gaming disorder is stigmatising.Discussion: Evidence suggests that gaming disorder shares similar neurobiological alterations with other types of behavioural and substance-related addictions, which further supports gaming disorder as a behavioural addiction. Ongoing debates on whether gaming disorder is a psychiatric disorder push for further exploring the nature of gaming disorder and resolving this dilemma in the field.

Toludesvenlafaxine hydrochloride sustained‐release tablets, as China’s first independently developed chemical Class 1 innovative drug with independent intellectual property rights for the treatment of depression and a new molecular entity, represent a novel triple reuptake inhibitor (TRI) with specific target selectivity for serotonin (5‐HT), norepinephrine (NE), and dopamine (DA). This single‐arm, multicenter clinical study aimed to evaluate the efficacy and safety of toludesvenlafaxine in alleviating anhedonia symptoms in patients with major depressive disorder (MDD). A total of 123 patients aged 18–65 years were enrolled between April 2023 and April 2024 and received an 8‐week treatment with toludesvenlafaxine sustained‐release tablets (80–160 mg/day). The primary efficacy endpoint was the change in the total score of the Dimensional Anhedonia Rating Scale (DARS) at weeks 2, 4, and 8. Significant improvements in DARS scores were observed, with mean changes from baseline of 8.4 (95% CI [6.4, 10.4], p < 0.0001), 14.1 (95% CI [12.0, 16.2], p < 0.0001), and 20.4 (95% CI [18.0, 22.9], p < 0.0001), respectively. Additionally, after 8 weeks of treatment, plasma levels of neurotrophic factors, including mature brain‐derived neurotrophic factor (mBDNF) ( t = 28.78, p < 0.0001), pro‐BDNF ( t = 27.71, p < 0.0001), and vascular endothelial growth factor (VEGF) ( t = 31.07, p < 0.0001), were significantly increased, and the plasma level of IGF‐1 was not significantly changed ( t = 0.35, p = 0.7269). No association was found between the percentage of changes in neurotrophic factors and the percentage of symptom improvements. Toludesvenlafaxine was generally well‐tolerated, with treatment‐emergent adverse events (AEs) (TEAEs) reported in 83.7% of participants and treatment‐related AEs (TRAEs) in 76.4%. These findings indicate that toludesvenlafaxine hydrochloride sustained‐release tablets are safe, well‐tolerated, and effective in alleviating anhedonia symptoms in patients with depression. Trial Registration: http://www.chictr.org.cn (No.: ChiCTR2300070331).

Understanding the alterations in brain function across different episodes of bipolar disorder (BD), including manic (BipM), depressive (BipD), and remission states (rBD), poses a significant challenge. In our cross-sectional study, we collected resting-state functional magnetic resonance imaging data from 117 BD patients (BipM: 38, BipD: 42, rBD: 37) and 35 healthy controls. Our aim was to delineate functional connections associated with episode dynamics, delineate common and specific patterns, validate them as biomarkers, and elucidate their biological underpinnings. Initially, we identified a common altered pattern within the sub-regions of the ventral-attention network, alongside specific patterns observed in the default mode network for BipM, the prefrontal network for BipD, and the limbic network for rBD. Using large-sample data from the Human Connectome Project, we further identified that these connectivity patterns exhibit relatively high reliability and heritability. Also, these distinct patterns accurately characterized the diverse episodes of BD and effectively predicted the cor responding clinical symptoms linked with each episode type. Importantly, using out of sample data to decode possible neurobiological mechanisms underlying these patterns, we found that regions of particular interest were enriched in multiple receptors, including MOR, NMDA, and H3 for specific alterations, and A4B2, 5HTT, and 5HT1a for common alterations. Moreover, both episode-specific and common patterns demonstrated a high enrichment for cell types such as L5ET, Micro/PVM,oligodendrites and Chandelier. Our study offers novel insights concerning episode dynamics in BD, paving the way for personalized medicine approaches tailored to address the various episodes.

The prevalence of sleep disorders has been rising over recent decades. Sleep disorders are frequently associated with disruptions in resting-state functional brain networks. Despite these associations, the direction and genetic basis of the relationships between brain functional networks and sleep disorders remain unclear. Utilizing bidirectional two-sample Mendelian randomization (MR), we examined bidirectional associations between 191 resting-state functional magnetic resonance imaging (rsfMRI) phenotypes (n = 34,691 individuals) and 8 sleep disorder phenotypes (N = 307,843–410,385 individuals). Forward MR identified 14 rsfMRI traits that showed significant associations with sleep disorder phenotypes. Notably, the inverse variance-weighted method showed that increased amplitude in the precuneus or occipital regions within the default mode or central executive network was associated with 13.2% higher odds of sleep disorders (combined; odds ratio = 1.132, 95% confidence interval: 1.064–1.204, P = 8.30 × 10 ⁻⁵ ). In addition, reverse MR identified 6 sleep disorder phenotypes with significant associations involving 18 rsfMRI traits. For example, higher genetic liability to sleep disorders (combined) was associated with a 14.2% lower strength of functional connectivity between precentral, frontal, or supplementary motor and frontal networks (odds ratio = 0.858, 95% confidence interval: 0.795–0.927, P = 9.62 × 10 ⁻⁵ ). This study identified 32 bidirectional MR associations between sleep disorders and brain functional networks, providing candidate neural circuits for future mechanistic and interventional studies of sleep disorders.