Synchrony 2022: Epilepsy and Seizures in Autism Spectrum Disorder Roundtable.

The BRAIN Foundation (Pleasanton, CA, USA) hosted Synchrony 2022, a translational medicine conference focused on research into treatments for individuals with neurodevelopmental disorders (NDD), including those with autism spectrum disorders (ASD) [...].

Transcranial Direct Current Stimulation Modulates EEG Microstates in Low-Functioning Autism: A Pilot Study.

Autism spectrum disorder (ASD) is a heterogeneous disorder that affects several behavioral domains of neurodevelopment. Transcranial direct current stimulation (tDCS) is a new method that modulates motor and cognitive function and may have potential applications in ASD treatment. To identify its potential effects on ASD, differences in electroencephalogram (EEG) microstates were compared between children with typical development (n = 26) and those with ASD (n = 26). Furthermore, children with ASD were divided into a tDCS (experimental) and sham stimulation (control) group, and EEG microstates and Autism Behavior Checklist (ABC) scores before and after tDCS were compared. Microstates A, B, and D differed significantly between children with TD and those with ASD. In the experimental group, the scores of microstates A and C and ABC before tDCS differed from those after tDCS. Conversely, in the control group, neither the EEG microstates nor the ABC scores before the treatment period (sham stimulation) differed from those after the treatment period. This study indicates that tDCS may become a viable treatment for ASD.

Abnormalities of EEG Functional Connectivity and Effective Connectivity in Children with Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder that interferes with normal brain development. Brain connectivity may serve as a biomarker for ASD in this respect. This study enrolled a total of 179 children aged 3-10 years (90 typically developed (TD) and 89 with ASD). We used a weighted phase lag index and a directed transfer function to investigate the functional and effective connectivity in children with ASD and TD. Our findings indicated that patients with ASD had local hyper-connectivity of brain regions in functional connectivity and simultaneous significant decrease in effective connectivity across hemispheres. These connectivity abnormalities may help to find biomarkers of ASD.

Development of EEG connectivity from preschool to school-age children.

Introduction: Many studies have collected normative developmental EEG data to better understand brain function in early life and associated changes during both aging and pathology. Higher cognitive functions of the brain do not normally stem from the workings of a single brain region that works but, rather, on the interaction between different brain regions. In this regard studying the connectivity between brain regions is of great importance towards understanding higher cognitive functions and its underlying mechanisms. Methods: In this study, EEG data of children (N = 253; 3-10 years old; 113 females, 140 males) from pre-school to schoolage was collected, and the weighted phase delay index and directed transfer function method was used to find the electrophysiological indicators of both functional connectivity and effective connectivity. A general linear model was built between the indicators and age, and the change trend of electrophysiological indicators analyzed for age. Results: The results showed an age trend for the functional and effective connectivity of the brain of children. Discussion: The results are of importance in understanding normative brain development and in defining those conditions that deviate from typical growth trajectories.

Impact of repetitive transcranial magnetic stimulation on the directed connectivity of autism EEG signals: a pilot study.

To compare the differences in directed connectivity between typically developing (TD) and autism spectrum disorder (ASD) children and identify the potential effects of repetitive transcranial magnetic stimulation (rTMS) on brain connectivity and behavior of children with ASD; 26 TD children (18 males/8 females; the average age was 6.34 ± 0.45) and 30 ASD children (21 males/9 females; the average age was 6.42 ± 0.17) participated in the experiment. ASD children were divided randomly into an experimental group and a control group. The experimental group received 18 rTMS sessions (twice a week for nine weeks), whereas the control group received the same procedures with sham stimulation. Directed transfer function (DTF) was used to calculate the effective connectivity as a way of investigating differences between ASD and TD children while simultaneously evaluating the effectiveness of rTMS for ASD. The results illustrate that the DTF of TD children in the frontal lobe (Fp1, Fp2, F7, F8) and temporal lobe (T7, T8) is higher than that of ASD children in all frequency bands; however, the DTF of ASD children is higher than TD in the midline (Fz, Cz), central lobe (C3, C4), and parietal lobe (P3, P4). In the experimental group of ASD children, the effective connectivity decreased from O1 to T7 and from P7 to Fp1 in the alpha band and from Pz to T8 in the gamma band after stimulation. Significant changes in Autism Behavior Checklist (ABC) scores were also found in social behaviors. Effective connectivity derived from DTF distinguishes ASD from TD children. rTMS provides changes in connectivity and behavior, suggesting its potential use as a viable treatment option for ASD individuals.

Von Economo neurons: Cellular specialization of human limbic cortices?

Von Economo neurons (VENs) have been mentioned in the medical literature since the second half of the 19th century; however, it was not until the second decade of the 20th century that their cytomorphology was described in detail. To date, VENs have been found in limbic sectors of the frontal, temporal and insular lobes. In humans, their density seems to decrease in the caudo-rostral and ventro-dorsal direction; that is, from the anterior regions of the cingulate and insular cortices towards the frontal pole and the superior frontal gyrus. Several studies have provided similar descriptions of the shape of the VEN soma, but the size of the soma varies from one cortical region to another. There is consensus among different authors about the selective vulnerability of VENs in certain pathologies, in which a deterioration of the capacities involved in social behaviour is observed. In this review, we propose that the restriction of VENs towards the sectors linked to limbic information processing in Homo sapiens gives them a possible functional role in relation to the structures in which they are located. However, given the divergence in characteristics such as location, density, size and biochemical profile among VENs of different cortical sectors, the activities in which they participate could allow them to partake in a wide spectrum of neurological functions, including autonomic responses and executive functions.

Effects of 1Hz repetitive transcranial magnetic stimulation on autism with intellectual disability: A pilot study.

OBJECTIVE: To explore whether 1 Hz repetitive transcranial magnetic stimulation (rTMS) has positive effects on brain activity and behavior of autistic children with intellectual disability. METHODS: 32 autistic children with intellectual disability (26 boys and 6 girls) were recruited to participate in this feasibility study. The autistic children were divided randomly and equally into an experimental group and a control group. 16 children (three girls and 13 boys; mean ± SD age: 7.8 ± 2.1 years) who received rTMS treatment twice a week were served as the experimental group, while 16 children (three girls and 13 boys; mean ± SD age: 7.2 ± 1.6 years) with sham stimulation were considered as the control group. Recurrence quantification analysis (RQA) was employed to quantify the nonlinear features of electroencephalogram (EEG) signals recorded during the resting state. Three RQA measures, including recursive rate (RR), deterministic (DET) and mean diagonal length (L) were extracted from the EEG signals to characterize the deterministic features of cortical activity. RESULTS: Significant differences in RR and DET were observed between the experimental group and the control group. We also found discernible discrepancies in the Autism Behavior Checklist (ABC) score pre- and post-rTMS for the experimental group. CONCLUSIONS: 1 Hz repetitive transcranial magnetic stimulation (rTMS) could positively influence brain activity and behavior of autistic children with intellectual disability.

Ringing Decay of Gamma Oscillations and Transcranial Magnetic Stimulation Therapy in Autism Spectrum Disorder.

Research suggest that in autism spectrum disorder (ASD) a disturbance in the coordinated interactions of neurons within local networks gives rise to abnormal patterns of brainwave activity in the gamma bandwidth. Low frequency transcranial magnetic stimulation (TMS) over the dorsolateral prefrontal cortex (DLPFC) has been proven to normalize gamma oscillation abnormalities, executive functions, and repetitive behaviors in high functioning ASD individuals. In this study, gamma frequency oscillations in response to a visual classification task (Kanizsa figures) were analyzed and compared in 19 ASD (ADI-R diagnosed, 14.2 ± 3.61 years old, 5 girls) and 19 (14.8 ± 3.67 years old, 5 girls) age/gender matched neurotypical individuals. The ASD group was treated with low frequency TMS (1.0 Hz, 90% motor threshold, 18 weekly sessions) targeting the DLPFC. In autistic subjects, as compared to neurotypicals, significant differences in event-related gamma oscillations were evident in amplitude (higher) pre-TMS. In addition, recordings after TMS treatment in our autistic subjects revealed a significant reduction in the time period to reach peak amplitude and an increase in the decay phase (settling time). The use of a novel metric for gamma oscillations. i.e., envelope analysis, and measurements of its ringing decay allowed us to characterize the impedance of the originating neuronal circuit. The ringing decay or dampening of gamma oscillations is dependent on the inhibitory tone generated by networks of interneurons. The results suggest that the ringing decay of gamma oscillations may provide a biomarker reflective of the excitatory/inhibitory balance of the cortex and a putative outcome measure for interventions in autism.

A robust DWT-CNN-based CAD system for early diagnosis of autism using task-based fMRI.

PURPOSE: Task-based fMRI (TfMRI) is a diagnostic imaging modality for observing the effects of a disease or other condition on the functional activity of the brain. Autism spectrum disorder (ASD) is a pervasive developmental disorder associated with impairments in social and linguistic abilities. Machine learning algorithms have been widely utilized for brain imaging aiming for objective ASD diagnostics. Recently, deep learning methods have been gaining more attention for fMRI classification. The goal of this paper is to develop a convolutional neural network (CNN)-based framework to help in global diagnosis of ASD using TfMRI data that are collected from a response to speech experiment. METHODS: To achieve this goal, the proposed framework adopts a novel imaging marker integrating both spatial and temporal information that are related to the functional activity of the brain. The developed pipeline consists of three main components. In the first step, the collected TfMRI data are preprocessed and parcellated using the Harvard-Oxford probabilistic atlas included with the fMRIB Software Library (FSL). Second, a group analysis using FSL is performed between ASD and typically developing (TD) children to identify significantly activated brain areas in response to the speech task. In order to reduce brain spatial dimensionality, a K-means clustering technique is performed on such significant brain areas. Informative blood oxygen level-dependent (BOLD) signals are extracted from each cluster. A compression step for each extracted BOLD signal using discrete wavelet transform (DWT) has been proposed. The adopted wavelets are similar to the expected hemodynamic response which enables DWT to compress the BOLD signal while highlighting its activation information. Finally, a deep learning 2D CNN network is used to classify the patients as ASD or TD based on extracted features from the previous step. RESULTS: Preliminary results on 100 TfMRI dataset (50 ASD, 50 TD) obtain 80% correct global classification using tenfold cross validation (with sensitivity = 84%, specificity = 76%). CONCLUSION: The experimental results show the high accuracy of the proposed framework and hold promise for the presented framework as a helpful adjunct to currently used ASD diagnostic tools.

The Relationship between Autism and Ehlers-Danlos Syndromes/Hypermobility Spectrum Disorders.

Considerable interest has arisen concerning the relationship between hereditary connective tissue disorders such as the Ehlers-Danlos syndromes (EDS)/hypermobility spectrum disorders (HSD) and autism, both in terms of their comorbidity as well as co-occurrence within the same families. This paper reviews our current state of knowledge, as well as highlighting unanswered questions concerning this remarkable patient group, which we hope will attract further scientific interest in coming years. In particular, patients themselves are demanding more research into this growing area of interest, although science has been slow to answer that call. Here, we address the overlap between these two spectrum conditions, including neurobehavioral, psychiatric, and neurological commonalities, shared peripheral neuropathies and neuropathologies, and similar autonomic and immune dysregulation. Together, these data highlight the potential relatedness of these two conditions and suggest that EDS/HSD may represent a subtype of autism.

Transcranial Magnetic Stimulation in Autism Spectrum Disorders: Neuropathological Underpinnings and Clinical Correlations.

Despite growing knowledge about autism spectrum disorder (ASD), research findings have not been translated into curative treatment. At present, most therapeutic interventions provide for symptomatic treatment. Outcomes of interventions are judged by subjective endpoints (eg, behavioral assessments) which alongside the highly heterogeneous nature of ASD account for wide variability in the effectiveness of treatments. Transcranial magnetic stimulation (TMS) is one of the first treatments that targets a putative core pathologic feature of autism, specifically the cortical inhibitory imbalance that alters gamma frequency synchronization. Studies show that low frequency TMS over the dorsolateral prefrontal cortex of individuals with ASD decreases the power of gamma activity and increases the difference between gamma responses to target and nontarget stimuli. TMS improves executive function skills related to self-monitoring behaviors and the ability to apply corrective actions. These improvements manifest themselves as a reduction of stimulus bound behaviors and diminished sympathetic arousal. Results become more significant with increasing number of sessions and bear synergism when used along with neurofeedback. When applied at low frequencies in individuals with ASD, TMS appears to be safe and to improve multiple patient-oriented outcomes. Future studies should be conducted in large populations to establish predictors of outcomes (eg, genetic profiling), length of persistence of benefits, and utility of booster sessions.

Effects of Transcranial Magnetic Stimulation Therapy on Evoked and Induced Gamma Oscillations in Children with Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a behaviorally diagnosed neurodevelopmental condition of unknown pathology. Research suggests that abnormalities of elecltroencephalogram (EEG) gamma oscillations may provide a biomarker of the condition. In this study, envelope analysis of demodulated waveforms for evoked and induced gamma oscillations in response to Kanizsa figures in an oddball task were analyzed and compared in 19 ASD and 19 age/gender-matched neurotypical children. The ASD group was treated with low frequency transcranial magnetic stimulation (TMS), (1.0 Hz, 90% motor threshold, 18 weekly sessions) targeting the dorsolateral prefrontal cortex. In ASD subjects, as compared to neurotypicals, significant differences in evoked and induced gamma oscillations were evident in higher magnitude of gamma oscillations pre-TMS, especially in response to non-target cues. Recordings post-TMS treatment in ASD revealed a significant reduction of gamma responses to task-irrelevant stimuli. Participants committed fewer errors post-TMS. Behavioral questionnaires showed a decrease in irritability, hyperactivity, and repetitive behavior scores. The use of a novel metric for gamma oscillations. i.e., envelope analysis using wavelet transformation allowed for characterization of the impedance of the originating neuronal circuit. The results suggest that gamma oscillations may provide a biomarker reflective of the excitatory/inhibitory balance of the cortex and a putative outcome measure for interventions in autism.

A Comprehensive Framework for Differentiating Autism Spectrum Disorder From Neurotypicals by Fusing Structural MRI and Resting State Functional MRI.

Autism spectrum disorder is a neurodevelopmental disorder characterized by impaired social abilities and communication difficulties. The golden standard for autism diagnosis in research rely on behavioral features, for example, the autism diagnosis observation schedule, the Autism Diagnostic Interview-Revised. In this study we introduce a computer-aided diagnosis system that uses features from structural MRI (sMRI) and resting state functional MRI (fMRI) to help predict an autism diagnosis by clinicians. The proposed system is capable of parcellating brain regions to show which areas are most likely affected by autism related abnormalities and thus help in targeting potential therapeutic interventions. When tested on 18 data sets (n = 1060) from the ABIDE consortium, our system was able to achieve high accuracy (sMRI 0.75-1.00; fMRI 0.79-1.00), sensitivity (sMRI 0.73-1.00; fMRI 0.78-1.00), and specificity (sMRI 0.78-1.00; fMRI 0.79-1.00). The proposed system could be considered an important step toward helping physicians interpret results of neuroimaging studies and personalize treatment options. To the best of our knowledge, this work is the first to combine features from structural and functional MRI, use them for personalized diagnosis and achieve high accuracies on a relatively large population.

Translational Neuroscience in Autism: From Neuropathology to Transcranial Magnetic Stimulation Therapies.

The presence of heterotopias, increased regional density of neurons at the gray-white matter junction, and focal cortical dysplasias all suggest an abnormality of neuronal migration in autism spectrum disorder (ASD). The abnormality is borne from a dissonance in timing between radial and tangentially migrating neuroblasts to the developing cortical plate. The uncoupling of excitatory and inhibitory cortical cells disturbs the coordinated interactions of neurons within local networks, thus providing abnormal patterns of brainwave activity in the gamma bandwidth. In ASD, gamma oscillation abnormalities and autonomic markers offer measures of therapeutic progress and help in the identification of subgroups.

A Personalized Autism Diagnosis CAD System Using a Fusion of Structural MRI and Resting-State Functional MRI Data.

Autism spectrum disorder is a neuro-developmental disorder that affects the social abilities of the patients. Yet, the gold standard of autism diagnosis is the autism diagnostic observation schedule (ADOS). In this study, we are implementing a computer-aided diagnosis system that utilizes structural MRI (sMRI) and resting-state functional MRI (fMRI) to demonstrate that both anatomical abnormalities and functional connectivity abnormalities have high prediction ability of autism. The proposed system studies how the anatomical and functional connectivity metrics provide an overall diagnosis of whether the subject is autistic or not and are correlated with ADOS scores. The system provides a personalized report per subject to show what areas are more affected by autism-related impairment. Our system achieved accuracies of 75% when using fMRI data only, 79% when using sMRI data only, and 81% when fusing both together. Such a system achieves an important next step towards delineating the neurocircuits responsible for the autism diagnosis and hence may provide better options for physicians in devising personalized treatment plans.

Effects of repetitive transcranial magnetic stimulation on children with low-function autism.

BACKGROUND: Autism spectrum disorder (ASD) is a very complex neurodevelopmental disorder, characterized by social difficulties and stereotypical or repetitive behavior. Some previous studies using low-frequency repetitive transcranial magnetic stimulation (rTMS) have proven of benefit in ASD children. METHODS: In this study, 32 children (26 males and six females) with low-function autism were enrolled, 16 children (three females and 13 males; mean ± SD age: 7.8 ± 2.1 years) received rTMS treatment twice every week, while the remaining 16 children (three females and 13 males; mean ± SD age: 7.2 ± 1.6 years) served as waitlist group. This study investigated the effects of rTMS on brain activity and behavioral response in the autistic children. RESULTS: Peak alpha frequency (PAF) is an electroencephalographic measure of cognitive preparedness and might be a neural marker of cognitive function for the autism. Coherence is one way to assess the brain functional connectivity of ASD children, which has proven abnormal in previous studies. The results showed significant increases in the PAF at the frontal region, the left temporal region, the right temporal region and the occipital region and a significant increase of alpha coherence between the central region and the right temporal region. Autism Behavior Checklist (ABC) scores were also compared before and after receiving rTMS with positive effects shown on behavior. CONCLUSION: These findings supported our hypothesis by demonstration of positive effects of combined rTMS neurotherapy in active treatment group as compared to the waitlist group, as the rTMS group showed significant improvements in behavioral and functional outcomes as compared to the waitlist group.

Autism risk genes are evolutionarily ancient and maintain a unique feature landscape that echoes their function.

Previous research on autism risk (ASD), developmental regulatory (DevReg), and central nervous system (CNS) genes suggests they tend to be large in size, enriched in nested repeats, and mutation intolerant. The relevance of these genomic features is intriguing yet poorly understood. In this study, we investigated the feature landscape of these gene groups to discover structural themes useful in interpreting their function, developmental patterns, and evolutionary history. ASD, DevReg, CNS, housekeeping, and whole genome control (WGC) groups were compiled using various resources. Multiple gene features of interest were extracted from NCBI/UCSC Bioinformatics. Residual variation intolerance scores, Exome Aggregation Consortium pLI scores, and copy number variation data from Decipher were used to estimate variation intolerance. Gene age and protein-protein interactions (PPI) were estimated using Ensembl and EBI Intact databases, respectively. Compared to WGC: ASD, DevReg, and CNS genes are longer, produce larger proteins, maintain greater numbers/density of conserved noncoding elements and transposable elements, produce more transcript variants, and are comparatively variation intolerant. After controlling for gene size, mutation tolerance, and clinical association, ASD genes still retain many of these same features. In addition, we also found that ASD genes that are extremely mutation intolerant have larger PPI networks. These data support many of the recent findings within the field of autism genetics but also expand our understanding of the evolution of these broad gene groups, their potential regulatory complexity, and the extent to which they interact with the cellular network. Autism Res 2019, 12: 860-869. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Autism risk genes are more ancient compared to other genes in the genome. As such, they exhibit physical features related to their age, including long gene and protein size and regulatory sequences that help to control gene expression. They share many of these same features with other genes that are expressed in the brain and/or are associated with prenatal development.