Search Results (3,369)

The Activity-Dependent Neuroprotective Protein (ADNP) is an important regulator of early brain development, especially during cortical neurogenesis and neurite formation. De novo point mutations or haploinsufficiency of the ADNP gene result in ADNP syndrome, which is also known as Helsmoortel-Van der Aa syndrome, a complex neurodevelopmental disorder recognized as a leading single-gene cause of syndromic autism spectrum disorder (ASD) and intellectual disability. ADNP works as both a transcription factor and a microtubule (MT) regulator. As a transcription factor, ADNP is a key component of chromatin remodeling complexes such as ChAHP (CHD4 (Chromodomain Helicase DNA-binding Protein 4)-ADNP-HP1 (Heterochromatin Protein 1)) and SWI/SNF (Switch/Sucrose Non-Fermentable), and it tightly regulates the expression of numerous essential developmental genes. ADNP also modulates the Wnt/β-catenin signaling pathway. During neural differentiation, ADNP is redistributed from the nucleus to the cytoplasm, and this redistribution is regulated by binding to 14-3-3 proteins, which are phosphorylated by protein Kinase C (PKC). After relocating to the cytoplasm, ADNP functions as an MT regulator by binding to microtubule end-binding proteins (EB1 and EB3) and Tau to control neurite formation. Previous studies have focused on NAP (also known as Davunetide, a peptide derived from ADNP) in MT regulation and its therapeutic potential for autism spectrum disorder (ASD) and neurodegenerative diseases, such as Alzheimer’s disease. This review highlights the functions of full-length ADNP and NAP in early brain development, particularly in neurogenesis and neurite formation during cortical development. We will also discuss the potential of NAP as a therapeutic medication for neurodevelopmental disorders, especially ASD and ADNP syndrome. Full article

Transsynaptic bridges are molecular complexes spanning the synaptic cleft that physically couple presynaptic release machinery to postsynaptic receptor fields. That this architecture is the direct target of autoimmune attack in myasthenia gravis and a primary locus of genetic risk in autism spectrum disorder and schizophrenia underscores that transsynaptic bridges are not only important during synapse development but are continuously required organizers of neural function. This review traces the evolution of structural, molecular, and functional evidence that shaped our understanding of the synapse as a single integrated trans-cellular unit. Several defining properties of a synapse emerge as a consequence of transsynaptic bridges—for example, the nanoscale alignment they impose between vesicle fusion sites and receptor nanodomains determines transmission efficacy, the bidirectional communication they coordinate across the cleft drives signaling specificity, and they undergo activity-dependent remodeling, thereby physically encoding synaptic history. Full article

Parental involvement in applied behavior analysis (ABA) interventions for children with autism spectrum disorder (ASD) is essential for treatment success, yet caregiver engagement remains inconsistent across clinical contexts. This qualitative study employs reflexive thematic analysis to explore the lived experiences of eight mothers receiving ABA services through a single South Florida provider. We identified barriers (time constraints, insufficient family support, communication gaps) and facilitators (observed child progress, economic support, intrinsic motivation) to parental involvement. Interpreted through a family systems lens, findings suggest that parental engagement is better understood as a dynamic, context-dependent process shaped by systemic and relational factors rather than as a matter of individual motivation alone. This modest, single-site account contributes contextually to understanding how service-design factors shape caregiver participation within one ABA program and aligns with existing literature on barriers to service engagement among underserved families. Clinical implications point to concrete service adaptations including flexible scheduling, enhanced communication protocols, family-centered psychoeducation, and evaluation of caregiver-recommended practices such as relaxation techniques and family therapy. While this study cannot generalize broadly, its findings offer specific recommendations for improving practice in community-based ABA settings serving diverse populations. Full article

Social problem-solving (SPS) difficulties may affect social, communicative, and adaptive functioning among individuals with autism. This study conducted a three-level meta-analysis of SPS interventions in single-case experimental design (SCED) research. Twenty-one SCED studies published between 2002 and 2025 met the inclusion criteria, yielding 114 dependent-variable-level effect sizes nested within 59 participant clusters. The unconditional three-level model showed a positive and statistically significant pooled effect, 1.741 (SE = 0.087, 95% CI [1.570, 1.911], p < 0.001), with low approximate total heterogeneity (I² = 24.48%). Moderator analyses did not identify clear statistically significant predictors of effect-size variability across SPS centrality, intervention setting, intervention type, implementer type, participant characteristics, or methodological quality. Sensitivity and study-level publication-bias analyses provided no clear indication that the findings were driven by a single influential study or by obvious small-study effects. Overall, targeted outcomes improved from baseline to intervention phases in studies of SPS-related intervention packages. Because many studies used multi-component intervention packages, the observed effects reflect the combined impact of interventions in which SPS-related components were embedded, and it is not possible to isolate the independent contribution of SPS components based on the available SCED evidence. Full article

Background: Autism spectrum disorder (ASD) is characterized by widespread aberrations in brain scalp-level synchronization. Phase-amplitude coupling (PAC), which reflects cross-frequency neuronal oscillatory interactions, serves as a crucial metric for assessing functional brain integration. However, the specific patterns of PAC at both intra-region and inter-region scalp levels in young children with ASD, as well as their precise associations with clinical symptoms, remain unclear. Methods: This study enrolled 237 children with ASD aged 3–9 years and 201 age-matched typically developing (TD) children. Resting-state electroencephalography (EEG) data were acquired from all participants. The analysis systematically examined low-frequency oscillation phase (δ, θ, α) modulation of high-frequency oscillation amplitude (β and low γ) from both intra-region and inter-region dimensions. The PAC strength was quantified using the modulation index (MI). Multiple comparisons were corrected using the Bonferroni method. Finally, correlations between PAC metrics and Autism Behavior Checklist (ABC) scores were analyzed. Results: Compared to the control group, children with ASD exhibited significant frequency-specific PAC abnormalities: (1) Multi-regional γ hyper-coupling: There was a significant enhancement in the modulation of γ amplitude by δ/θ/α phase across the measured scalp regions, suggesting abnormal high-frequency synchronization. (2) Dissociated β modulation patterns: The ASD group showed increased δ–β coupling (predominantly in frontal, temporal, and occipital lobes) alongside significantly reduced α–β coupling (localized to frontal and central regions). This reflects both an abnormal locking of slow-wave activity to the β band and a diminished regulatory role of α oscillations. (3) Clinical correlation: Notably, abnormally elevated PAC strength (particularly in the δ/θ/α–γ bands) showed a negative correlation with clinical symptom severity—that is, stronger coupling was associated with lower scores on the ABC. Conclusions: Leveraging a large-sample dataset, this study characterizes the landscape of aberrant cross-frequency interactions in young children with ASD. Our findings indicate that the neuroelectrical activity in ASD goes beyond mere connectivity anomalies by demonstrating altered PAC strength at both the intra-region and inter-region levels. Notably, the strength of this aberrant intra-region PAC is correlated with clinical symptoms. Full article

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition, and objective identification based on neuroimaging remains challenging due to inter-subject variability, multi-site heterogeneity, and the complex topology of brain functional networks. Resting-state functional magnetic resonance imaging (rs-fMRI) provides a non-invasive way to characterize intrinsic brain activity, but existing functional-connectivity-based methods often rely on single-scale static representations and insufficiently capture high-order topology, temporal evolution, and phenotypic heterogeneity. This study aims to develop a mathematical and AI-based brain-network modeling framework for ASD identification from rs-fMRI. The proposed method integrates low-order functional connectivity, high-order functional connectivity, phenotypic information, dynamic graph sequences, Transformer-based temporal attention, and static–dynamic gated fusion. Experiments were conducted on the ABIDE-I dataset, including 1112 subjects from 17 acquisition sites, with 539 ASD subjects and 573 typical controls. The proposed static multi-channel model achieved an accuracy of 75.8%, while the dynamic extension achieved a mean accuracy of 78.5% ± 0.7% and an AUC of 0.84 ± 0.01 over repeated runs. The results suggest that jointly modeling multi-scale static topology and dynamic temporal evolution may improve rs-fMRI-based ASD identification and offer a computationally interpretable framework for AI-assisted neuroimaging analysis. Full article

The autism spectrum disorder-associated SCN2A, ANK2, and SHANK-family genes encode molecularly distinct proteins that converge functionally on dendritic integration. Recent work established that ankyrin-B, encoded by ANK2, acts as an obligate dendritic scaffold for NaV1.2, encoded by SCN2A, in neocortical pyramidal neurons. Loss of this module mislocalizes dendritic NaV1.2, reduces dendritic Na⁺ influx, weakens backpropagating action potentials, and impairs synaptic maturation and long-term potentiation. SHANK proteins organize a complementary postsynaptic receptor scaffold within dendritic spines, coupling N-methyl-D-aspartate (NMDA), α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA), and metabotropic glutamate receptor (e.g., mGluR5) signaling to the actin cytoskeleton through layered PSD-95/GKAP/Homer interactions. Disruption of this scaffold can destabilize excitatory transmission, spine morphology, and plasticity. We propose that these dendritic shaft and spine-associated modules jointly regulate dendritic input–output gain and that their disruption may contribute to autism spectrum disorder by destabilizing, rather than uniformly shifting, excitatory integration across cortico-subcortical circuits relevant to sensory reactivity, behavioral flexibility, and social-valence processing. Here, we review the cortical evidence for this layered dendritic convergence and evaluate its potential relevance beyond the cortex. We assess the striatum, thalamus, and amygdala as subcortical sites where related dendritic scaffolding mechanisms may operate. The striatum provides the strongest current test case, with established roles for both NaV1.2 and SHANK3 in medium spiny neuron physiology and corticostriatal connectivity. Thalamic and amygdalar extensions are supported mainly by SHANK-related circuit and channelopathy data but lack direct evidence for ANK2–SCN2A involvement. The framework is experimentally testable: conditional Ank2 deletion in striatal, thalamic, and amygdalar cell types; dendritic Na⁺/Ca²⁺ imaging across Scn2a, Ank2, and Shank3 models; adult rescue experiments; and genetic-interaction designs would determine whether ankyrin-B supports dendritic excitability beyond the cortex and whether these genes converge on, rather than merely parallel, dendritic input–output gain. Validation in human subcortical tissue would then establish whether this dendritic scaffolding logic represents a shared point of convergence through which genetically distinct autism spectrum disorder-risk variants alter circuit function. Full article

Neurodevelopmental disorders (NDDs) are associated with impairments in communication, behavior, and social interaction, making accurate diagnosis clinically challenging. Autism Spectrum Disorder (ASD), a major NDD, often exhibits atypical speech patterns characterized by altered prosody and reduced emotional expressiveness. The study proposes a hybrid dual-path framework for ASD detection from emotional speech using two strategies: PCA–GMM-based acoustic modeling and a CNN–BiLSTM–Attention architecture for spectral–temporal feature learning. The proposed framework captures probabilistic, spectral, and temporal speech characteristics for robust ASD classification. Acoustic analysis demonstrated clear separability between ASD and non-ASD speech, while the deep learning framework achieved stable and reliable performance across multiple emotional conditions. Experimental evaluation achieved 98.3% accuracy, AUC values ranging from 0.9699 to 0.9864, and F1-scores up to 0.9891. The findings highlight the potential of AI-driven speech analysis as a scalable and non-invasive tool for early ASD screening and predictive healthcare applications. Full article

Background/Objectives: Children with chronic neurological and neurodevelopmental disorders (CNDD) constitute a medically vulnerable population in whom routine childhood immunization may be interrupted because of clinical complexity and parental concerns. This study aimed to evaluate immunization patterns, timing of vaccination interruption, and associated clinical and sociodemographic factors in children with CNDDs followed at a tertiary pediatric neurology center. Methods: This prospective cross-sectional study included 545 children aged 1–18 years with chronic neurological and neurodevelopmental disorders evaluated between September and November 2025. Immunization status according to the Turkish National Immunization Program was classified as fully vaccinated, partially vaccinated, or not vaccinated. Information regarding non-NIP vaccines, timing of vaccination interruption, parental characteristics, and motor impairment severity assessed using the Gross Motor Function Classification System (GMFCS) was collected. Associations between vaccination status and clinical variables were evaluated using chi-square tests and logistic regression analysis. Results: Overall, 72.1% of children were fully vaccinated, 25.0% were partially vaccinated, and 2.9% had never received routine childhood vaccines. Immunization status differed significantly across diagnostic groups (p < 0.001). Partial vaccination was more common than complete vaccine refusal across most diagnostic categories. Lower full vaccination rates were observed in autism spectrum disorder and cerebral palsy, whereas higher coverage was observed in Down syndrome. Among partially vaccinated children, interruption of routine immunization after 48 months was the most frequent pattern. In multivariable analysis, only maternal age remained significantly associated with incomplete or no vaccination. Conclusions: Incomplete immunization in children with CNDDs was more commonly characterized by partial vaccination than complete vaccine refusal and followed diagnosis-specific patterns. Evaluating vaccination continuity during pediatric neurology follow-up may help support diagnosis-sensitive immunization counseling. Full article

School counselors working in preschool special education institutions undertake multidimensional responsibilities involving support for children with developmental disabilities, family guidance, interdisciplinary collaboration, and participation in individualized education program (IEP) processes. Despite the complexity of these responsibilities, limited research has specifically examined the professional development needs of counselors employed in early childhood special education settings. This study aimed to determine the professional development needs of school counselors working in preschool special education institutions and to explore the professional challenges they experience in practice. The study was conducted using a qualitative research design. Participants consisted of 19 school counselors working in preschool special education institutions across different regions of Türkiye. Data were collected through semi-structured interviews and analyzed using thematic analysis. The findings indicated that school counselors experienced substantial professional development needs related to autism spectrum disorder, behavioral intervention strategies, family counseling, crisis intervention, interdisciplinary teamwork, assessment procedures, and individualized education planning. School counselors also emphasized inadequacies in preservice education and reported a strong need for applied, field-specific in-service training opportunities. Furthermore, role ambiguity, institutional limitations, and insufficient supervision emerged as significant factors negatively influencing professional competence perceptions. The findings suggest that counselor education curricula and professional development policies should be restructured to address the unique demands of preschool special education settings more effectively. This study contributes to the literature by highlighting the necessity of specialized professional preparation for school counselors supporting young children with special needs and their families. Full article

Background: Sensory processing differences are highly prevalent in children with autism spectrum disorder (ASD) and may shape how they interact with their environment and acquire new knowledge. The present study investigated developmental changes in learning potential and cognitive functioning in preschool children with ASD presenting a sensory seeking profile with typical sensitivity. In addition, the study examined which components of early learning potential predicted intellectual functioning two years later. Methods: A longitudinal design was employed with 44 preschool boys with ASD assessed at ages four and six. The potential for learning through dynamic assessment, intelligence and sensory processing patterns was assessed. Paired sample t-tests were conducted to examine developmental changes, and hierarchical regression analyses were used to identify predictors of intellectual functioning at age six. Results: Significant improvements were observed in general cognitive ability, classification ability, and perspective-taking skills across the two-year period. Regression analyses revealed that visual memory, sequential pattern completion, classification ability, and perspective taking significantly predicted intellectual functioning at age six, jointly explaining 51% of the variance in IQ scores. Conclusions: The findings suggest that visuospatial processing and pattern-based reasoning may play a central role in cognitive development among preschool children with ASD who exhibit active sensory engagement. Full article

Applied Behavior Analysis (ABA) is recognized as among the most empirically supported interventions for autism spectrum disorder (ASD) and related neurodevelopmental conditions. This clinical perspective examines the gap between controlled research efficacy and community-based implementation by integrating insights from developmental psychology, family systems theory, and implementation science. The paper argues that several limitations sometimes observed in long-term functional outcomes are better understood as challenges of community-level implementation rather than deficiencies of behavioral principles themselves. Furthermore, dimensions occasionally described as “missing” from behavioral practice—including attention to covert behavior, family systems, emotional regulation, and lifespan adaptation—already fall within contemporary best practice, though they may be applied inconsistently across diverse service contexts. Rather than positioning these dimensions as external to behavior analysis, this paper proposes an explicitly interdisciplinary, family-centered, and lifespan-oriented framework in which behavioral science is embedded within structured caregiver preparation, clear referral pathways, and neurodiversity-affirming goals. Key recommendations include flexible service delivery models aligned with family realities; integrated family stress screening and mental-health referral pathways; workforce training in developmental psychology and emotional regulation; and lifespan-oriented outcome measurement beyond behavior reduction. The paper concludes that ABA’s contributions to autism intervention are profound and not in dispute; rather, the field benefits from expanding implementation contexts to address the full scope of neurodevelopmental care and family support. This perspective is intended to generate empirical investigation of proposed service-design innovations and to inform clinical practice in community-based ABA settings serving diverse, underserved populations. Full article

(1) Background: ASD diagnostic and screening instruments were historically developed on predominantly male samples, raising concerns about their differential validity across sexes. (2) Objective: This meta-analysis quantified the magnitude of gender bias in ASD diagnostic and screening tools and examined its consistency across instruments, age groups, and clinical contexts. (3) Method: A systematic search was conducted in APA PsycINFO, ERIC, Dialnet, and PsicoDoc (2015–2025) following PRISMA 2020 guidelines. Fourteen empirical studies were included (N = 55 to ~3,000,000). Effect sizes were computed as Fisher r-to-z transformed coefficients and pooled using a random-effects model. Heterogeneity was assessed via Cochran’s Q and I²; methodological quality was assessed via the CRF-QS. (4) Results: The pooled effect size was $\hat{\mathrm{\mu }}$ = 0.29 (95% CI: 0.11–0.47, z = 3.11, p = 0.001), indicating systematic bias favoring detection of externalizing, prototypically male profiles. Substantial heterogeneity was observed (I² = 99.93%, Q(13) = 11,417.61, p < 0.001, τ² = 0.11), with a prediction interval of −0.40 to 0.97. Funnel plot asymmetry suggested possible publication bias (p = 0.01). (5) Conclusions: ASD diagnostic instruments systematically underperform in identifying female presentations of autism. Bias operates across screening and formal evaluation stages, is not corrected by specialist assessment, and is associated with diagnostic delay and increased psychopathological burden. Revision of diagnostic tools and clinical training is urgently warranted. Full article

Autism spectrum disorder (ASD) is a neurodevelopmental condition where early detection is crucial for improving outcomes. Electroencephalography (EEG) offers a non-invasive approach for identifying potential biomarkers. In this study, we investigate hemispheric asymmetry using the Lateralisation Index (LI) derived from EEG signals and evaluate its effectiveness for ASD classification. Using a small dataset of children with and without ASD, we applied several machine learning models, including Logistic Regression, Support Vector Machines and Random Forest. Particular attention was given to evaluation strategies to avoid overfitting and data leakage. While initial results suggested moderate classification performance, repeated validation indicated unstable generalisation. Our findings highlight both the potential and limitations of LI-based features in small-sample settings and emphasise the importance of robust evaluation in EEG-based machine learning studies. Full article

Background/Objective: Emotion regulation (ER) is closely linked to decision-making (DM). Although executive functions (EF) are often suggested as a key mechanism underlying this relationship, evidence from different clinical conditions remains fragmented. This scoping review aims to map the literature on the relationship between ER and DM in clinical populations, with a specific focus on the interaction between EF and ER in shaping adaptive DM processes, particularly in populations characterised by cognitive impairment and emotional dysregulation. Methods: A search of electronic databases was conducted to identify empirical studies examining ER, EF and DM in clinical populations. Sixteen studies involving patients with dementia, traumatic brain injury, autism spectrum disorder, substance and behavioural addictions were included. Results: Difficulties in ER were associated with altered DM. EF, particularly inhibitory control, working memory, and cognitive flexibility, were found to be key processes linking emotional states to decision outcomes. Clinical groups consistently showed a tendency to prefer immediate rewards despite potential long-term negative consequences and experienced difficulties integrating emotional and cognitive information. Conclusions: This scoping review emphasises the importance of moving beyond reductionist explanations of DM and to adopt an integrative approach. ER and EF should be conceptualised as interacting components of a broader self-regulatory system shaping decision behaviour. Developing this framework will be crucial to enable targeted clinical and neurorehabilitation interventions for individuals experiencing impaired DM. Full article