Response inhibition as a critical executive function in differentiating attention-deficit/hyperactivity disorder from autism spectrum disorder: a comprehensive attention test study.

Background: Autism Spectrum Disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD) are both associated with impairment in executive function, particularly in complex attention. Although previous studies using clinical assessments have attempted to delineate differences between these disorders, the findings have been inconclusive. Our study aims to elucidate the differences of endophenotype between ASD, ADHD, and their co-occurring condition utilizing a uniform computerized test.

Neural correlates of model-based behavior in internet gaming disorder and alcohol use disorder.

Background: An imbalance between model-based and model-free decision-making systems is a common feature in addictive disorders. However, little is known about whether similar decision-making deficits appear in internet gaming disorder (IGD). This study compared neurocognitive features associated with model-based and model-free systems in IGD and alcohol use disorder (AUD).

Pharmacological and non-pharmacological interventions for irritability in autism spectrum disorder: a systematic review and meta-analysis with the GRADE assessment.

Background: Numerous interventions for irritability in autism spectrum disorder (ASD) have been investigated. We aimed to appraise the magnitude of pharmacological and non-pharmacological interventions for irritability in ASD without any restrictions in terms of eligible interventions.

Methods: We systematically searched PubMed/MEDLINE, Scopus, and Web of Science until April 15, 2023.

Development of Deep Ensembles to Screen for Autism and Symptom Severity Using Retinal Photographs.

Importance: Screening for autism spectrum disorder (ASD) is constrained by limited resources, particularly trained professionals to conduct evaluations. Individuals with ASD have structural retinal changes that potentially reflect brain alterations, including visual pathway abnormalities through embryonic and anatomic connections. Whether deep learning algorithms can aid in objective screening for ASD and symptom severity using retinal photographs is unknown.

Identifying major predictors for parenting stress in a caregiver of autism spectrum disorder using machine learning models.

Introduction: Previous studies have investigated predictive factors for parenting stress in caregivers of autism spectrum disorder (ASD) patients using traditional statistical approaches, but their study settings and results were inconsistent. Herein, this study aimed to identify major predictors for parenting stress in this population by developing explainable machine learning models.

Methods: Study participants were collected from the Department of Child and Adolescent Psychiatry, Severance Hospital, Yonsei University College of Medicine, Seoul, the Republic of Korea between March 2016 and October 2020.