Normative EC metrics supported accurate classification of ASD vs TD participants and suggest that normative EC values constitute robust and generalizable ASD biomarkers.
Abstract
Autism spectrum disorder (ASD) is one of the most common neurodevelopmental disorders. The absence of a clear aetiology strengthens the need to identify quantitative biomarkers capable of diagnosing the condition and assessing the severity of symptoms. We implemented a normative modelling framework based on EEG effective connectivity (EC), leveraging recordings collected in three centers, in typical development (TD) and ASD participants with age spanning from 5 to 19 years. Deviations from the normative evolution were tested as ASD biomarkers, compared with standard EC metrics. Normative EC metrics supported accurate classification of ASD vs TD participants (0.82 AUC), reaching 0.95 AUC when combined with behavioral subscales, significantly outperforming a classification based on behavioral data alone. In ASD participants, selected metrics in the Temporo-Parietal-Frontal network predicted social responsiveness scale (SRS) values with high significance (SRS Total R^2=0.42, p=0.0005). These results suggest that normative EC values constitute robust and generalizable ASD biomarkers.
Children and adolescents with ASD exhibited lower empathy capabilities than control subjects, which may be attributed to dysfunctions in the salience and social brain networks.
Yong-Lu Wang, Zhang-Liang Ma, Zhiyi Wang et al.· Frontiers in Psychiatry· 0 citations
RCCA revealed three distinct FC patterns in recurrent ASD-related networks, each contributing to predict individual differences in cognitive, social and sensory features, which may shed light on atypical brain network topology associated with specific phenotypic manifestations of ASD.
B. Rodríguez-Herreros, A. Mheich, J. A. Osório et al.· Autism Research· 0 citations
Background/Objectives: Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are frequently co-occurring neurodevelopmental conditions with partially overlapping neurophysiological profiles. Electroencephalography (EEG) provides non-invasive access to candidate biomarkers, yet the literature remains largely organized around single-diagnosis frameworks, limiting comparison across conditions and constraining translation into intervention selection. This review compares EEG signatures across ASD and ADHD from a transdiagnostic perspective and examines how such signatures might inform the selection of non-pharmacological interventions. Methods: A structured search of PubMed, Scopus, IEEE Xplore and Web of Science identified peer-reviewed studies published between 2010 and 2026 reporting EEG findings in ASD and/or ADHD, spanning resting-state, task-based, connectivity, event-related potential, machine learning and intervention studies. Sixty-eight sources were synthesized thematically. Given substantial heterogeneity in acquisition parameters and analytic pipelines, evidence was integrated interpretively rather than pooled quantitatively, and no formal risk-of-bias assessment was undertaken. Results: Shared features across both conditions frequently included low-frequency theta excess, reduced alpha modulation under cognitive load, and flattened aperiodic (1/f) slopes—a pattern compatible with, though not a direct measurement of, altered excitation/inhibition balance. While substantial heterogeneity exists, disorder-specific signatures often comprised the ASD “U-shaped” spectral profile alongside elevated epileptiform activity, and frontally pronounced theta/beta ratio elevation in subsets of individuals with ADHD. Machine-learning studies increasingly emphasize interpretable, multidomain feature sets over binary classification. Mindfulness-based and neurofeedback interventions converge on theta reduction and alpha enhancement, although reported effects are frequently conditional on responder status, task context, or outcome-rater blinding. Conclusions: Convergent EEG features support a transdiagnostic account of neurodevelopmental dysregulation. A biomarker-informed framework for intervention selection is proposed, which requires prospective validation before clinical application.
Akshay Bhuvaneswari Ramakrishnan, N. NavaneethaKrishnan, William Mahler et al.· Brain Science· 0 citations
Autism spectrum disorder (ASD) is highly heritable; however, the neural architecture underlying semantic processing and social functioning, and the extent to which it reflects familial liability, remains insufficiently understood. Unaffected siblings (SIB), who share substantial genetic liability with individuals with ASD, offer a critical framework for identifying intermediate neural phenotypes. We examined 36 individuals with ASD, 36 SIB, and 37 typically developing (TD) controls, matched for age, IQ, and handedness. Functional magnetic resonance imaging (fMRI) during a semantic judgment task was used to compare neural activation across groups and to assess whether associations with social functioning, measured by the Social Responsiveness Scale (SRS), reflected familial risk or dimensional continuity across the autism spectrum. Group comparisons revealed a graded endophenotypic pattern in inferior frontal gyrus (IFG) activation, with reduced activation in ASD and intermediate responses in SIB. The middle temporal gyrus (MTG) showed a similar but weaker gradient, with SIB not differing significantly from TD. Both ASD and SIB also demonstrated heightened cuneus activation, consistent with a heritable compensatory shift toward perceptual processing. Importantly, reduced MTG activation, along with a weaker marginal pattern in the IFG, was associated with higher SRS scores in both the familial and full samples, suggesting an association between semantic activation and social functioning. These findings clarify how familial liability and dimensional variation jointly shape the neural organization of semantic processing and social functioning in ASD.
Shu-Hui Lee, C. Liao, Tai-Li Chou et al.· Autism Research· 0 citations
An exploratory association between right precuneus GMV and ADOS social-domain scores suggests a possible link between localized structural variation and social symptom severity, although this finding requires replication in longitudinal and clinically richer datasets given their sensitivity to the harmonization strategy.
Gang Xiao, Xiaoshi Li, Yue Qin et al.· Frontiers in Neuroscience· 0 citations
Background Brain functions emerge from temporally organized neural dynamics, and an appropriate level of neural complexity may support flexible information processing. Electroencephalographic (EEG) studies using multiscale entropy (MSE), which quantifies signal complexity across multiple temporal scales, have reported reduced MSE at longer scales in individuals with autism spectrum disorder (ASD). However, most evidence comes from studies of infant and child samples, leaving adult data scarce, and the associations between reduced MSE, clinical symptoms, and social information processing are insufficiently understood. Methods We recorded and analyzed EEG data from adults with ASD (n = 47) and typically developing (TD) controls (n = 40) during eyes-closed rest and two movie viewing conditions: Inscapes, comprising dynamically changing abstract visual patterns, and Partly Cloudy, an emotionally engaging animated social narrative. Group and condition effects were assessed using cluster-based permutation tests, and associations between MSE and Social Affect (SA) scores from the Autism Diagnostic Observation Schedule, Second Edition (ADOS-2), as well as group differences in event-related MSE changes, were examined using linear mixed-effects models. Results Across conditions, adults with ASD showed lower MSE at longer scales (τ = 16–30), corresponding to effective sampling rates of 12.50–6.67 Hz in the coarse-grained time series, than TD adults. Longer-scale MSE within the ASD–TD difference cluster was negatively associated with ADOS-2 SA scores across diagnostic groups. The difference in event-related MSE change between Social and Non-Social conditions, comparing empathic-pain and mentalizing events in Partly Cloudy with temporally matched non-social windows in Inscapes, was smaller in ASD participants than in TD participants. No significant difference between Social and Non-Social windows was observed among ASD participants, whereas TD participants showed significantly greater MSE change during Social than Non-Social windows. Limitations This study used a modest sample without an independent replication cohort, and the short event windows limited the precision of the MSE estimation. Conclusions Reduced longer-scale MSE extends to adults with ASD and is associated with higher ADOS-2 SA scores across diagnostic groups. Event-related findings further suggest attenuated differentiation of longer-scale MSE between socially relevant and matched non-social windows in ASD.
Unknown authors· bioRxiv· 0 citations
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