The findings suggest that social orienting variability within ASD is associated with heterogeneous neurodynamic modes that become most visible under naturalistic social input and are more strongly associated with phase synchronization.
Abstract
Background
Social deficit in autism spectrum disorder (ASD) varies substantially across individuals, yet the neural mechanisms underlying this variability remain poorly understood. Resting state electrophysiological measures may under-engage social information processing and may be less sensitive to ASD-related neural differences. Here we combined EEG with eye tracking during a low demand viewing paradigm to probe neural dynamics and to identify data-driven neurodynamic modes associated with variability in social orienting.
Methods
We recruited 88 autistic and 71 typically developing (TD) participants for eyes-open resting-state EEG. A subset of these participants, including 58 autistic and 61 TD participants, additionally completed a Social vs. Geometric paradigm with simultaneous EEG and eye tracking. Alpha-band resting-state and task-state EEG were segmented into five microstate (MS) classes (A-E). We compared MS temporal and complexity features between conditions and used support vector machine classification to test whether resting-state or task-state MS features better differentiated ASD from TD participants. For the more discriminative condition, MS-based alpha activity was further characterized by amplitude and phase-locking value (PLV). Participant-level MS-based PLV features were then used for k-means clustering, and moderation models examined whether PLV shaped the association between autistic traits and social orienting.
Results
Task-state MS features differentiated ASD from TD more accurately than resting-state features. Group differences were primarily expressed in MS-based alpha PLV across the five MS classes, whereas alpha amplitude showed no significant group differences. Clustering identified two PLV-based synchronization modes that were present in both ASD and TD participants. Within ASD, these modes differed in social orienting, and MS A PLV moderated the association between autistic traits and social scene preference ratio.
Limitations
Given the cross-sectional design, tracing the developmental trajectories of these distinct neurodynamic modes will require future multi-center, longitudinal tracking.
Conclusions
These findings suggest that social orienting variability within ASD is associated with heterogeneous neurodynamic modes that become most visible under naturalistic social input and are more strongly associated with phase synchronization.
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.
N. Taiga, Yumi Shikauchi, T. Itahashi et al.· bioRxiv· 0 citations
Introduction Developmental language disorder (DLD) has been associated with atypical neural processing, but it remains unclear whether preschool children with DLD show altered EEG microstate organization across cognitive states. Most microstate studies in clinical populations have focused on resting-state activity, and much less is known about how microstate profiles vary across task contexts in young children. Methods EEG was recorded from preschool children with DLD (n = 12) and typically developing (TD) children (n = 22) during three consecutive paradigms: a video-based rest-like viewing condition (Rest), semantic picture–sound matching (Match), and passive auditory oddball listening (Oddball). Within-condition template extraction and cross-condition alignment were used to quantify conventional microstate features, including mean duration, time coverage, occurrence rate, and global explained variance (GEV). Directed transition probabilities and condition-difference Δ-transition indices were additionally summarized as exploratory descriptors of microstate switching organization. Conventional microstate features were analyzed using mixed-design repeated-measures ANOVA. Results Multiple conventional microstate features differed across Rest, Match, and Oddball, indicating that EEG microstate profiles varied across task contexts under the condition-specific template framework. In contrast, Group main effects and Group × Condition interactions did not provide robust evidence of DLD-TD differences in conventional microstate features. Full transition matrices also showed descriptive condition-related variation in switching organization, whereas group-related deviations in transition probabilities were generally small. Among the representative exploratory Δ-transition pathways, one Oddball-Match pathway showed a nominal uncorrected group difference, but this effect did not survive full-family false discovery rate correction. Discussion EEG microstate profiles in preschool children appear sensitive to task context, whereas evidence for DLD-specific microstate alterations was limited in the present sample. Because templates were extracted separately within each condition and aligned post hoc, the condition-related findings should be interpreted as descriptive evidence of task-context-related microstate organization rather than as a strict common-template test of condition effects. Larger, better-characterized samples and common-template approaches are needed to clarify whether reproducible DLD-related alterations in EEG microstate organization are present across cognitive contexts.
Ai-Min Liang, Hanxiao Wang, Yang Shi et al.· Frontiers in Neuroscience· 0 citations
Frequency-specific resting-state features, particularly local synchronization in the slow-4 band, capture developmental-stage-related variation within ASD, highlighting the potential of frequency-specific rs-fMRI metrics as candidate markers for characterizing neurodevelopmental stages in ASD.
Qi Huang, Sisi Jiang, Cheng Luo et al.· Frontiers in Neuroscience· 0 citations
Objective. Sensory processing dysfunction (SPD) not only affects most individuals with autism spectrum disorder (ASD), but at least 5% of children without ASD also experience SPD. Our understanding of the relationship between sensory dysfunction and resting state brain activity is still emerging. The objective of this study was to examine group differences and behavioral associations with resting state alpha and beta oscillatory activity in ASD, SPD, and typically developing control (TDC) groups. Approach. This study compared long-range resting state functional connectivity of neural oscillatory behavior in 60 male children aged 8–12 years with (ASD; N = 18), those with (SPD; N = 18) who did not meet ASD criteria, and typically developing control participants (TDC; N = 24) using magnetoencephalography. Functional connectivity analyses were performed in the alpha and beta frequency bands, which are known to be implicated in sensory information processing. Group differences in functional connectivity and associations between sensory abilities and functional connectivity were examined. Main results. Distinct patterns of functional connectivity differences between ASD and SPD groups were found only in the beta band, but not in the alpha band. In both alpha and beta bands, ASD and SPD cohorts differed from the TDC cohort. Distinct patterns of associations between imaginary coherence and performance-based measures of sensory processing and verbal abilities were identified across groups. Significance. These findings demonstrate distinct long-range alpha and beta band phase-lagged neural synchrony alterations in SPD and ASD that are associated with sensory processing abilities in male children. These measures could serve as potential candidate neurophysiological markers for ASD and SPD at the group level, and may provide mechanistic insights relevant to biomarker development.
C. Demopoulos, Xuan Jesson, Molly Gerdes et al.· Journal of Neural Engineerin...· 0 citations
Autism spectrum disorder (ASD) is a neurodevelopmental condition with core diagnostic domains of social communication impairments, restricted interests and repetitive behaviors. Idiosyncratic brain organization is a potential hallmark of ASD. Previous transcranial direct current stimulation (tDCS) studies often targeted dorsolateral prefrontal cortex, with changes oin brain dynamics averaged across the cohort. We utilized a magnetoencephalographic (MEG) array to characterize individual differences in brain dynamics induced by cortico-cerebellar tDCS across nodes of a social cognition network. A randomized, sham-controlled, double-blind, within-subject clinical trial was conducted in a cohort of 24 young adults with ASD or high autistic traits. Two separate sessions of computerized social learning activities were combined with verum/sham tDCS, with anodal electrode over right temporoparietal junction (TPJ) and cathode on right deltoid. Following stimulation, theta- and alpha-band activity were evaluated within nodes of a social cognition network: bilateral TPJ, fusiform, medial prefrontal cortex and Crus I/II of cerebellum. Idiosyncratic participant-specific up- and down-regulation of theta- and alpha-band activity occurred across the network. Activity in right Crus I/II, a region inundated by the stimulation current, strongly correlated with the change of activity summed across all cerebral cortical nodes in theta- but not alpha-band. Intrinsic theta-band activity is believed to mediate input/output relationships in cerebellar cortex and to drive synaptic plasticity. These results suggest that theta-band stimulation of cerebellar cortex might be an effective therapy for individuals on the autism spectrum who present with cerebellar hyperactivity.
BACKGROUND
Multiple object tracking (MOT) tasks are widely used to examine attention impairments in autism spectrum disorder (ASD); however, existing research has predominantly relied on behavioral measures and has barely incorporated physiological data, such as electroencephalography (EEG). Additionally, how cognition and emotion interact in individuals with ASD during MOT tasks remains unclear.
METHODS
In this study we addressed these gaps using a publicly available dataset containing EEG recordings and clinical measurement from 28 children with ASD and 28 typically developing (TD) individuals. Participants listened to speech recordings reflecting prosodic happiness and sadness while completing three attention-level tasks: neutral image viewing (low-attention), one-target four-disc MOT-4 (intermediate-attention), and one-target eight-disc MOT-8 (high-attention). For each participant's EEG data, we calculated the theta-beta ratio (TBR) for each channel and then extracted five EEG features: averaged TBR for all channels (allTBR), averaged TBR for channels in the frontal brain region (fTBR), averaged TBR for channels in the temporal brain region (tTBR), averaged TBR for channels in the central brain region (cTBR), and averaged TBR for channels in the parietal brain region (pTBR). Correlation analysis was also conducted to explore the association between EEG features and clinical measures.
RESULTS
Findings showed that: (1) the interaction effect between attentional level and emotion was significant for allTBR and tTBR; (2) Significant main effects of group were observed for all five TBR metrics (allTBR, fTBR, tTBR, cTBR, and pTBR), with the ASD group showing higher values than the TD group; (3) only tTBR showed a significant difference between happiness and sadness stimuli during the MOT-8 task after Bonferroni correction; (4) during the MOT-4 task, the TD group had higher correlations between five EEG features and clinical measures than the ASD group; and (5) the tTBR finding during the MOT-8 task suggests that emotional valence may modulate neural processing in the temporal region under high cognitive load.
CONCLUSIONS
These findings could provide new insights into attentional impairments and cognition-emotion interactions in ASD, offering potential implications for the development of clinical intervention strategies.
Muhammad Zakir Ullah, Hon-Gan Wang, Na Ta et al.· Journal of Integrative Neuro...· 0 citations
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