Early Life Neurodevelopmental Disorder

Attention-deficit/hyperactivity disorder (ADHD), the most common neurodevelopmental condition affecting around 5% of children and adolescents world-wide. ADHD is characterized by its significant clinical heterogeneity, including different symptom courses, such as persistent, remitting, and emergent trajectories during adolescence and adulthood, which may be affected by pharmacological treatments. More importantly, the neurodevelopmental mechanisms underlying heterogeneity in ADHD-symptom trajectories remain unclear, mainly due to the scarcity of longitudinal neuroimaging studies of adolescent brain development. Therefore, a critical question remains unanswered: Do current medications influence symptom trajectories and their underlying neurodevelopmental processes toward sustained remission? A deeper understanding of these neurodevelopmental processes could facilitate the prediction of future symptom development, and inform novel intervention strategies that may alter symptom courses and promote sustained remission. 

Over six million children have been diagnosed with Attention-Deficit/Hyperactivity Disorder (ADHD) in the U.S., making it the most prevalent neurodevelopmental disorder.^1,2 Pharmacologic management of ADHD is the first-line treatment approach, aimed at mitigating behavioral symptoms, and is hypothesized to "normalize" brain structure.^3,4 However, research on the potential impacts of ADHD medications on brain phenotypes has been limited by small, homogeneous samples, leading to inconsistent and often null findings regarding affected brain regions.⁴ 

Autism Spectrum Disorder (ASD) is typically diagnosed through behavioral assessments at ages 2 to 3 or later. However, Hazlett et al. demonstrated the feasibility of early diagnosis by identifying significant brain overgrowth between 6 and 24 months, which can serve as an early indicator of ASD (Hazlett, 2017). While neuroimaging studies offer promising insights, rapid structural changes during the first two years and the heterogeneous neurological abnormalities in ASD hinder stable and consistent diagnosis. To address these issues, we propose NeuroExplainer, a novel surface-based analysis approach for more precise and interpretable early ASD diagnoses. 

Autism is a neurodevelopmental condition characterized by impaired social communication and interaction, restricted interests, stereotyped behaviors, and altered sensory responses to external stimuli (American Psychiatric Association, 2013). Many autistic individuals without intellectual impairment perform well in controlled tasks, such as recognizing emotional facial expressions (Keating et al., 2023), but their performance often declines in naturalistic settings requiring implicit social processing (Van de Cruys et al., 2014). Functional magnetic resonance imaging (fMRI), during naturalistic stimuli, such as movies, has proven effective for examining social brain activity (Finn et al., 2020). Inter-subject functional connectivity (ISFC) measures the interregional connectivity across individuals, by separating the shared and stimulus-driven component of fMRI responses from intrinsic brain activity and noise (Simony et al., 2016). Previous findings suggest idiosyncratic inter-subject functional connectivity patterns in autistic individuals (Bolton et al., 2018), but the precise regional differences remain unclear and may vary across movie segments. Addressing the reproducibility crisis in neuroimaging (Kelly & Hoptman, 2022), cross-center experiment design can validate the generalizability of findings. This study aimed to investigate the difference of inter-subject functional connectivity between autistic individuals and neurotypical controls and to evaluate replication across datasets. 

Typical brain development is shaped by genetic programming, environmental influences, and learning. For humans and nonhuman primates, there is a complex, protracted sequence of developmental events, including axon formation, synaptic refinement, and myelination that can extend well into adulthood. Structural maturation is reflected in the emergence of brain and behavioral functions, with touch recognized as the earliest sensory milestone achieved in utero [1].

Neurotropic infections, like Zika virus, can invade the brain with outcomes heavily influenced by developmental timing. First trimester infections have been linked to fetal loss and microcephaly, as seen in Congenital Zika Syndrome. In contrast, infections occurring in the mid-to-late trimesters often result in infants with normal appearing head sizes but an elevated risk of developmental delay [2].

The long-term consequences of disruptions during fetal brain development, particularly in primates, remain poorly understood. This study examines the effects of mid-term neurotropic infection within the context of normative structural and functional development using a macaque monkey model of fetal Zika virus infection (fZIKV). 

Attention-Deficit/Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder characterized by considerable clinical heterogeneity across inattentive and hyperactive/impulsive symptom domains. Understanding the heterogeneous neural mechanisms underlying ADHD could enhance opportunities for individualized management. To this end, normative modeling offers an effective method for identifying individual deviations from typical development. While previous normative modeling studies on ADHD primarily focused on regional morphological alterations, how these alterations are coupled between regions is unclear. This study investigates whether a hub-oriented fusion framework-which integrates multimodal topological deviations in morphometric similarity networks based on normative modeling-can provide robust neuromarkers for ADHD subtyping.