Resting state EEG abnormalities in autism spectrum disorders

Chemiluminescence analysis of saliva for the assessment of emotional stress in autistic children undergoing a medical examination

Purpose

An electroencephalography (EEG) examination may cause psychological stress in children with autism that can interfere with the examination results. The objective information on the presence or absence of psycho-emotional stress in patients can help interpret electroencephalograms. This paper aimed to demonstrate the potential of noninvasive objective diagnostics of emotional stress in autistic children undergoing an EEG examination based on analysis of saliva.

Design/methodology/approach

This study involved 19 children with autism spectrum disorder (ASD) (ICD-10 F84.0); the mean age was seven years. During EEG examination of the children, behavioral parameters were assessed. The activity of cytochrome P450 reductase (CYPOR) in saliva was measured before and after the EEG procedure using lucigenin-enhanced nicotinamide adenine dinucleotide phosphate-stimulated chemiluminescence assay.

Findings

Significant differences in CYPOR activity were found between the children who were distressed during an EEG examination and the children without behavioral disturbances (Mann–Whitney test, p = 0.002). Thus, the EEG examination resulted in an increase in CYPOR activity in saliva cells, which may prove the stressful effect of this procedure on autistic children.

Originality/value

The chemiluminescent indices reflecting the activity of microsomal CYPOR in cells presenting in saliva correlate with the absence or presence of psychological stress in children; this phenomenon can be explained by an increased metabolism of the stress hormone, cortisol, by the cytochrome P450 microsomal system. Furthermore, the proposed method is completely safe, noninvasive, rapid (recording time is 20 min), inexpensive and promising for an objective assessment of psycho-emotional stress in autistic children undergoing medical examinations.

The Directionality of Fronto-Posterior Brain Connectivity Is Associated with the Degree of Individual Autistic Traits

Altered patterns of brain connectivity have been found in autism spectrum disorder (ASD) and associated with specific symptoms and behavioral features. Growing evidence suggests that the autistic peculiarities are not confined to the clinical population but extend along a continuum between healthy and maladaptive conditions. The aim of this study was to investigate whether a differentiated connectivity pattern could also be tracked along the continuum of autistic traits in a non-clinical population. A Granger causality analysis conducted on a resting-state EEG recording showed that connectivity along the posterior-frontal gradient is sensitive to the magnitude of individual autistic traits and mostly conveyed through fast oscillatory activity. Specifically, participants with higher autistic traits were characterized by a prevalence of ascending connections starting from posterior regions ramping the cortical hierarchy. These findings point to the presence of a tendency within the neural mapping of individuals with higher autistic features in conveying proportionally more bottom-up information. This pattern of findings mimics those found in clinical forms of autism, supporting the idea of a neurobiological continuum between autistic traits and ASD.

Increased 2-arachidonoyl-sn-glycerol levels normalize cortical responses to sound and improve behaviors in Fmr1 KO mice

Background

Individuals with Fragile X syndrome (FXS) and autism spectrum disorder (ASD) exhibit an array of symptoms, including sociability deficits, increased anxiety, hyperactivity, and sensory hyperexcitability. It is unclear how endocannabinoid (eCB) modulation can be targeted to alleviate neurophysiological abnormalities in FXS as behavioral research reveals benefits to inhibiting cannabinoid (CB) receptor activation and increasing endocannabinoid ligand levels. Here, we hypothesize that enhancement of 2-arachidonoyl-sn-glycerol (2-AG) in Fragile X mental retardation 1 gene knock-out (Fmr1 KO) mice may reduce cortical hyperexcitability and behavioral abnormalities observed in FXS.

Methods

To test whether an increase in 2-AG levels normalized cortical responses in a mouse model of FXS, animals were subjected to electroencephalography (EEG) recording and behavioral assessment following treatment with JZL-184, an irreversible inhibitor of monoacylglycerol lipase (MAGL). Assessment of 2-AG was performed using lipidomic analysis in conjunction with various doses and time points post-administration of JZL-184. Baseline electrocortical activity and evoked responses to sound stimuli were measured using a 30-channel multielectrode array (MEA) in adult male mice before, 4 h, and 1 day post-intraperitoneal injection of JZL-184 or vehicle. Behavior assessment was done using the open field and elevated plus maze 4 h post-treatment.

Results

Lipidomic analysis showed that 8 mg/kg JZL-184 significantly increased the levels of 2-AG in the auditory cortex of both Fmr1 KO and WT mice 4 h post-treatment compared to vehicle controls. EEG recordings revealed a reduction in the abnormally enhanced baseline gamma-band power in Fmr1 KO mice and significantly improved evoked synchronization to auditory stimuli in the gamma-band range post-JZL-184 treatment. JZL-184 treatment also ameliorated anxiety-like and hyperactivity phenotypes in Fmr1 KO mice.

Conclusions

Overall, these results indicate that increasing 2-AG levels may serve as a potential therapeutic approach to normalize cortical responses and improve behavioral outcomes in FXS and possibly other ASDs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s11689-021-09394-x.

Signal complexity indicators of health status in clinical EEG

Brain signal variability changes across the lifespan in both health and disease, likely reflecting changes in information processing capacity related to development, aging and neurological disorders. While signal complexity, and multiscale entropy (MSE) in particular, has been proposed as a biomarker for neurological disorders, most observations of altered signal complexity have come from studies comparing patients with few to no comorbidities against healthy controls. In this study, we examined whether MSE of brain signals was distinguishable across patient groups in a large and heterogeneous set of clinical-EEG data. Using a multivariate analysis, we found unique timescale-dependent differences in MSE across various neurological disorders. We also found MSE to differentiate individuals with non-brain comorbidities, suggesting that MSE is sensitive to brain signal changes brought about by metabolic and other non-brain disorders. Such changes were not detectable in the spectral power density of brain signals. Our findings suggest that brain signal complexity may offer complementary information to spectral power about an individual's health status and is a promising avenue for clinical biomarker development.

Neural Correlates of Auditory Hypersensitivity in Fragile X Syndrome

The mechanisms underlying the common association between autism spectrum disorders (ASD) and sensory processing disorders (SPD) are unclear, and treatment options to reduce atypical sensory processing are limited. Fragile X Syndrome (FXS) is a leading genetic cause of intellectual disability and ASD behaviors. As in most children with ASD, atypical sensory processing is a common symptom in FXS, frequently manifesting as sensory hypersensitivity. Auditory hypersensitivity is a highly debilitating condition in FXS that may lead to language delays, social anxiety and ritualized repetitive behaviors. Animal models of FXS, including Fmr1 knock out (KO) mouse, also show auditory hypersensitivity, providing a translation relevant platform to study underlying pathophysiological mechanisms. The focus of this review is to summarize recent studies in the Fmr1 KO mouse that identified neural correlates of auditory hypersensitivity. We review results of electroencephalography (EEG) recordings in the Fmr1 KO mice and highlight EEG phenotypes that are remarkably similar to EEG findings in humans with FXS. The EEG phenotypes associated with the loss of FMRP include enhanced resting EEG gamma band power, reduced cross frequency coupling, reduced sound-evoked synchrony of neural responses at gamma band frequencies, increased event-related potential amplitudes, reduced habituation of neural responses and increased non-phase locked power. In addition, we highlight the postnatal period when the EEG phenotypes develop and show a strong association of the phenotypes with enhanced matrix-metalloproteinase-9 (MMP-9) activity, abnormal development of parvalbumin (PV)-expressing inhibitory interneurons and reduced formation of specialized extracellular matrix structures called perineuronal nets (PNNs). Finally, we discuss how dysfunctions of inhibitory PV interneurons may contribute to cortical hyperexcitability and EEG abnormalities observed in FXS. Taken together, the studies reviewed here indicate that EEG recordings can be utilized in both pre-clinical studies and clinical trials, while at the same time, used to identify cellular and circuit mechanisms of dysfunction in FXS. New therapeutic approaches that reduce MMP-9 activity and restore functions of PV interneurons may succeed in reducing FXS sensory symptoms. Future studies should examine long-lasting benefits of developmental vs. adult interventions on sensory phenotypes.

Resting state EEG in youth with ASD: age, sex, and relation to phenotype

BACKGROUND

Identification of ASD biomarkers is a key priority for understanding etiology, facilitating early diagnosis, monitoring developmental trajectories, and targeting treatment efforts. Efforts have included exploration of resting state encephalography (EEG), which has a variety of relevant neurodevelopmental correlates and can be collected with minimal burden. However, EEG biomarkers may not be equally valid across the autism spectrum, as ASD is strikingly heterogeneous and individual differences may moderate EEG-behavior associations. Biological sex is a particularly important potential moderator, as females with ASD appear to differ from males with ASD in important ways that may influence biomarker accuracy.

METHODS

We examined effects of biological sex, age, and ASD diagnosis on resting state EEG among a large, sex-balanced sample of youth with (N = 142, 43% female) and without (N = 138, 49% female) ASD collected across four research sites. Absolute power was extracted across five frequency bands and nine brain regions, and effects of sex, age, and diagnosis were analyzed using mixed-effects linear regression models. Exploratory partial correlations were computed to examine EEG-behavior associations in ASD, with emphasis on possible sex differences in associations.

RESULTS

Decreased EEG power across multiple frequencies was associated with female sex and older age. Youth with ASD displayed decreased alpha power relative to peers without ASD, suggesting increased neural activation during rest. Associations between EEG and behavior varied by sex. Whereas power across various frequencies correlated with social skills, nonverbal IQ, and repetitive behavior for males with ASD, no such associations were observed for females with ASD.

CONCLUSIONS

Research using EEG as a possible ASD biomarker must consider individual differences among participants, as these features influence baseline EEG measures and moderate associations between EEG and important behavioral outcomes. Failure to consider factors such as biological sex in such research risks defining biomarkers that misrepresent females with ASD, hindering understanding of the neurobiology, development, and intervention response of this important population.

Repeated Sessions of Transcranial Direct Current Stimulation on Adolescents With Autism Spectrum Disorder: Study Protocol for a Randomized, Double-Blind, and Sham-Controlled Clinical Trial

Background: Social-emotional difficulties are a core symptom of autism spectrum disorder (ASD). Accordingly, individuals with ASD have problems with social cognition such as recognizing emotions from other peoples' faces. Various results from functional magnetic resonance imaging and electroencephalography studies as well as eye-tracking data reveal a neurophysiological basis of these deficits by linking them to abnormal brain activity. Thus, an intervention targeting the neural origin of ASD impairments seems warranted. A safe method able to influence neural activity is transcranial direct current stimulation (tDCS). This non-invasive brain stimulation method has already demonstrated promising results in several neuropsychiatric disorders in adults and children. The aim of this project is to investigate the effects of tDCS on ASD symptoms and their neural correlates in children and adolescents with ASD. Method: This study is designed as a double-blind, randomized, and sham-controlled trial with a target sample size of 20 male participants (aged 12-17 years) diagnosed with ASD. Before randomization, the participants will be stratified into comorbid depression, comorbid ADHS/conduct disorder, or no-comorbidity groups. The intervention phase comprises 10 sessions of anodal or sham tDCS applied over the left prefrontal cortex within 2 consecutive weeks. To engage the targeted brain regions, participants will perform a social cognition training during the stimulation. TDCS-induced effects on ASD symptoms and involved neural circuits will be investigated through psychological, neurophysiological, imaging, and behavioral data at pre- and post-measurements. Tolerability will be evaluated using a standardized questionnaire. Follow-up assessments 1 and 6 months after the intervention will examine long-lasting effects. Discussion: The results of this study will provide insights into the changeability of social impairments in ASD by investigating social and emotional abilities on different modalities following repeated sessions of anodal tDCS with an intra-simulation training. Furthermore, this trial will elucidate the tolerability and the potential of tDCS as a new treatment approach for ASD in adolescents. Clinical Trial Registration: The study is ongoing and has been registered in the German Registry of Clinical Trials (DRKS00017505) on 02/07/2019.

Excitatory synapses and gap junctions cooperate to improve Pv neuronal burst firing and cortical social cognition in Shank2-mutant mice

NMDA receptor (NMDAR) and GABA neuronal dysfunctions are observed in animal models of autism spectrum disorders, but how these dysfunctions impair social cognition and behavior remains unclear. We report here that NMDARs in cortical parvalbumin (Pv)-positive interneurons cooperate with gap junctions to promote high-frequency (>80 Hz) Pv neuronal burst firing and social cognition. Shank2^–/– mice, displaying improved sociability upon NMDAR activation, show impaired cortical social representation and inhibitory neuronal burst firing. Cortical Shank2^–/– Pv neurons show decreased NMDAR activity, which suppresses the cooperation between NMDARs and gap junctions (GJs) for normal burst firing. Shank2^–/– Pv neurons show compensatory increases in GJ activity that are not sufficient for social rescue. However, optogenetic boosting of Pv neuronal bursts, requiring GJs, rescues cortical social cognition in Shank2^–/– mice, similar to the NMDAR-dependent social rescue. Therefore, NMDARs and gap junctions cooperate to promote cortical Pv neuronal bursts and social cognition.

How NMDAR and GABA neuronal dysfunctions result in impaired social behaviour is unclear. Here, the authors show that NMDARs and gap junctions in cortical PV interneurons modulate burst firing, affecting social behaviour.

Choosing Strategies to Deal with Artifactual EEG Data in Children with Cognitive Impairment

Rett syndrome is a disease that involves acute cognitive impairment and, consequently, a complex and varied symptomatology. This study evaluates the EEG signals of twenty-nine patients and classify them according to the level of movement artifact. The main goal is to achieve an artifact rejection strategy that performs well in all signals, regardless of the artifact level. Two different methods have been studied: one based on the data distribution and the other based on the energy function, with entropy as its main component. The method based on the data distribution shows poor performance with signals containing high amplitude outliers. On the contrary, the method based on the energy function is more robust to outliers. As it does not depend on the data distribution, it is not affected by artifactual events. A double rejection strategy has been chosen, first on a motion signal (accelerometer or EEG low-pass filtered between 1 and 10 Hz) and then on the EEG signal. The results showed a higher performance when working combining both artifact rejection methods. The energy-based method, to isolate motion artifacts, and the data-distribution-based method, to eliminate the remaining lower amplitude artifacts were used. In conclusion, a new method that proves to be robust for all types of signals is designed.

Association between spectral electroencephalography power and autism risk and diagnosis in early development

Autism spectrum disorder (ASD) has its origins in the atypical development of brain networks. Infants who are at high familial risk for, and later diagnosed with ASD, show atypical activity in multiple electroencephalography (EEG) oscillatory measures. However, infant-sibling studies are often constrained by small sample sizes. We used the International Infant EEG Data Integration Platform, a multi-site dataset with 432 participants, including 222 at high-risk for ASD, from whom repeated measurements of EEG were collected between the ages of 3-36 months. We applied a latent growth curve model to test whether familial risk status predicts developmental trajectories of spectral power across the first 3 years of life, and whether these trajectories predict ASD outcome. Change in spectral EEG power in all frequency bands occurred during the first 3 years of life. Familial risk, but not a later diagnosis of ASD, was associated with reduced power at 3 months, and a steeper developmental change between 3 and 36 months in nearly all absolute power bands. ASD outcome was not associated with absolute power intercept or slope. No associations were found between risk or outcome and relative power. This study applied an analytic approach not used in previous prospective biomarker studies of ASD, which was modeled to reflect the temporal relationship between genetic susceptibility, brain development, and ASD diagnosis. Trajectories of spectral power appear to be predicted by familial risk; however, spectral power does not predict diagnostic outcome above and beyond familial risk status. Discrepancies between current results and previous studies are discussed. LAY SUMMARY: Infants with an older sibling who is diagnosed with ASD are at increased risk of developing ASD themselves. This article tested whether EEG spectral power in the first year of life can predict whether these infants did or did not develop ASD.

Rethinking Stereotypies in Autism

Stereotyped movements ("stereotypies") are semi-voluntary repetitive movements that are a prominent clinical feature of autism spectrum disorder. They are described in first-person accounts by people with autism as relaxing and that they help focus the mind and cope in overwhelming sensory environments. Therefore, we generally recommend against techniques that aim to suppress stereotypies in individuals with autism. Further, we hypothesize that understanding the neurobiology of stereotypies could guide development of treatments to produce the benefits of stereotypies without the need to generate repetitive motor movements. Here, we link first-person reports and clinical findings with basic neuroanatomy and physiology to produce a testable model of stereotypies. We hypothesize that stereotypies improve sensory processing and attention by regulating brain rhythms, either directly from the rhythmic motor command, or via rhythmic sensory feedback generated by the movements.

Drug development for Autism Spectrum Disorder (ASD): Progress, challenges, and future directions

In 2017, facing lack of progress and failures encountered in targeted drug development for Autism Spectrum Disorder (ASD) and related neurodevelopmental disorders, the ISCTM with the ECNP created the ASD Working Group charged to identify barriers to progress and recommending research strategies for the field to gain traction. Working Group international academic, regulatory and industry representatives held multiple in-person meetings, teleconferences, and subgroup communications to gather a wide range of perspectives on lessons learned from extant studies, current challenges, and paths for fundamental advances in ASD therapeutics. This overview delineates the barriers identified, and outlines major goals for next generation biomedical intervention development in ASD. Current challenges for ASD research are many: heterogeneity, lack of validated biomarkers, need for improved endpoints, prioritizing molecular targets, comorbidities, and more. The Working Group emphasized cautious but unwavering optimism for therapeutic progress for ASD core features given advances in the basic neuroscience of ASD and related disorders. Leveraging genetic data, intermediate phenotypes, digital phenotyping, big database discovery, refined endpoints, and earlier intervention, the prospects for breakthrough treatments are substantial. Recommendations include new priorities for expanded research funding to overcome challenges in translational clinical ASD therapeutic research.

Electrophysiological Biomarkers in Genetic Epilepsies

Precision treatments for epilepsy targeting the underlying genetic diagnoses are becoming a reality. Historically, the goal of epilepsy treatments was to reduce seizure frequency. In the era of precision medicine, however, outcomes such as prevention of epilepsy progression or even improvements in cognitive functions are both aspirational targets for any intervention. Developing methods, both in clinical trial design and in novel endpoints, will be necessary for measuring, not only seizures, but also the other neurodevelopmental outcomes that are predicted to be targeted by precision treatments. Biomarkers that quantitatively measure disease progression or network level changes are needed to allow for unbiased measurements of the effects of any gene-level treatments. Here, we discuss some of the promising electrophysiological biomarkers that may be of use in clinical trials of precision therapies, as well as the difficulties in implementing them.

An mtDNA mutant mouse demonstrates that mitochondrial deficiency can result in autism endophenotypes

Autism spectrum disorders (ASDs) have increasingly been associated with mitochondrial dysfunction, corroborated by mitochondrial DNA (mtDNA) germline and somatic variants being found in ASD patients. If mitochondrial defects can generate ASD, then specific mtDNA mutations should induce ASD endophenotypes in mice. We tested this prediction by introduction of an mtDNA ND6 gene missense mutation (ND6^P25L) into the mouse germline and found ASD endophenotypes. The ND6^P25L mice exhibit impaired social interaction, compulsive behavior, and increased anxiety. They have reduced electroencephalographic delta and theta wave power, increased predilection to seizures, but without diminution of hippocampal interneurons. These endophenotypes correlate with impaired cortical and hippocampal mitochondrial respiration and increased reactive oxygen species production. Thus, mitochondrial defects can be sufficient to produce ASD phenotypes.

Autism spectrum disorders (ASDs) are characterized by a deficit in social communication, pathologic repetitive behaviors, restricted interests, and electroencephalogram (EEG) aberrations. While exhaustive analysis of nuclear DNA (nDNA) variation has revealed hundreds of copy number variants (CNVs) and loss-of-function (LOF) mutations, no unifying hypothesis as to the pathophysiology of ASD has yet emerged. Based on biochemical and physiological analyses, it has been hypothesized that ASD may be the result of a systemic mitochondrial deficiency with brain-specific manifestations. This proposal has been supported by recent mitochondrial DNA (mtDNA) analyses identifying both germline and somatic mtDNA variants in ASD. If mitochondrial defects do predispose to ASD, then mice with certain mtDNA mutations should present with autism endophenotypes. To test this prediction, we examined a mouse strain harboring an mtDNA ND6 gene missense mutation (P25L). This mouse manifests impaired social interactions, increased repetitive behaviors and anxiety, EEG alterations, and a decreased seizure threshold, in the absence of reduced hippocampal interneuron numbers. EEG aberrations were most pronounced in the cortex followed by the hippocampus. Aberrations in mitochondrial respiratory function and reactive oxygen species (ROS) levels were also most pronounced in the cortex followed by the hippocampus, but absent in the olfactory bulb. These data demonstrate that mild systemic mitochondrial defects can result in ASD without apparent neuroanatomical defects and that systemic mitochondrial mutations can cause tissue-specific brain defects accompanied by regional neurophysiological alterations.

Accurate assessment of low-function autistic children based on EEG feature fusion

Autism spectrum disorder (ASD) is a very serious neurodevelopmental disorder and diagnosis mainly depends on the clinical scale, which has a certain degree of subjectivity. It is necessary to make accurate evaluation by objective indicators. In this study, we enrolled 96 children aged from 3 to 6 years: 48 low-function autistic children (38 males and 10 females; mean±SD age: 4.9±1.1 years) and 48 typically developing (TD) children (38 males and 10 females; mean±SD age: 4.9 ± 1.2 years) to participate in our experiment. We investigated to fuse multi-features (entropy, relative power, coherence and bicoherence) to distinguish low-function autistic children and TD children accurately. Minimum redundancy maximum correlation algorithm was used to choose the features and support vector machine was used for classification. Ten-fold cross validation was used to test the accuracy of the model. Better classification result was obtained. We tried to provide a reliable basis for clinical evaluation and diagnosis for ASD.

Personality in Autism Spectrum Disorder: Associations With Face Memory Deficit and Theory of Mind

OBJECTIVE

To examine the personality profiles of adults with autism spectrum disorder (ASD) using a standard personality assessment and to investigate the association between personality, ASD-related face memory deficit (FMD), and theory of mind (ToM). In a broader context, to examine whether there are distinct clinical phenotypes in the ASD population that have implications for personality development and treatment.

METHOD

Fifty-five adults with ASD and 22 neurotypical (NT) adults underwent a battery of neuropsychological tests, including measures of personality, face memory, and ToM. We compared ASD and NT groups in terms of their Personality Assessment Inventory (PAI) profiles. Additional analyses focused on the association between specific PAI scales and FMD. Performance on the Eyes Test was compared across groups and was examined in relation to FMD.

RESULTS

Adults with ASD demonstrated significant elevations on several PAI scales compared with NT adults. The presence of FMD was associated with differing PAI profiles among the ASD adults. The ASD adults with FMD scored significantly higher on scales that are sensitive to positive impression management and treatment rejection and significantly lower on scales that are sensitive to borderline personality, anxiety, depression, schizophrenia, and stress. There was a significant association between performance on the Eyes Test and FMD in the ASD group.

CONCLUSION

Adults with ASD have a unique personality profile. Further, ASD adults with FMD have reduced insight into their difficulties with emotional processing and may not be as sensitive as ASD adults without FMD to the emotions of others.

Sex differences in resting EEG power in Fragile X Syndrome

Electrophysiological alterations may represent a neural substrate of impaired neurocognitive processes and other phenotypic features in Fragile X Syndrome (FXS). However, the role of biological sex in electroencephalography (EEG) patterns that differentiate FXS from typical development has not been determined. This limits use of EEG in both the search for biomarkers of impairment in FXS as well as application of those markers to enhance our understanding of underlying neural mechanisms to speed treatment discovery. We investigated topographical relative EEG power in participants at rest in a sample of males and females with FXS and in age- and sex-matched typically developing controls (TDC) using a cluster-based analysis. While alterations in theta and low beta power were similar across males and females in FXS, relative power varied by sex in the alpha, upper beta, gamma, and epsilon frequency bands. Follow up analyses showed that Individual Alpha Peak Frequency (IAPF), a continuous variable that may capture atypicalities across the theta and alpha ranges in neurodevelopmental disorders, also varied by sex. Finally, performance on an auditory filtering task correlated with theta power in males, but not females with FXS. The impact of biological sex on resting state EEG power differences in FXS is discussed as it relates to potential GABAergic and glutamatergic etiologies of neurocognitive deficits in FXS.

An EEG investigation of alpha and beta activity during resting states in adults with Williams syndrome

Background

Williams syndrome (WS) is neurodevelopmental disorder characterised by executive deficits of attention and inhibitory processing. The current study examined the neural mechanisms during resting states in adults with WS in order to investigate how this subserves the attention and inhibitory deficits associated with the syndrome.

Method

Adopting electroencephalography (EEG) methodology, cortical electrical activity was recorded from eleven adults with WS aged 35 + years during Eyes Closed (EC) and Eyes Open (EO) resting states, and compared to that of thirteen typically developing adults matched for chronological age (CA) and ten typically developing children matched for verbal mental ability (MA). Using mixed-design analyses of variance (ANOVA), analyses focused on the full alpha (8–12.5 Hz), low-alpha (8–10 Hz), upper-alpha (10–12.5 Hz), and beta (13–29.5 Hz) bands, as these are thought to have functional significance with attentional and inhibitory processes.

Results

No significant difference in alpha power were found between the WS and CA groups across all analyses, however a trend for numerically lower alpha power was observed in the WS group, consistent with other developmental disorders characterised by attentional/inhibitory deficits such as Attention Deficit Hyperactivity Disorder (ADHD). In contrast, comparable beta power between the WS and CA groups during both EC/EO conditions suggests that their baseline EEG signature is commensurate with successful attentional processing, though this needs to be interpreted with caution due to the small sample size. Analyses also revealed an unusual trend for low variability in the EEG signature of the WS group, which contradicts the heterogeneity typically observed behaviourally.

Conclusions

This novel finding of low variability in the EEG spectra in the WS group has been previously associated with poor behavioural performance in ADHD and is highly informative, highlighting future research needs to also consider how the role of low variability in the EEG profile of WS manifests in relation to their behavioural and cognitive profiles.

Shifted phase of EEG cross-frequency coupling in individuals with Phelan-McDermid syndrome

BACKGROUND

Phelan-McDermid Syndrome (PMS) is a rare condition caused by deletion or mutation of the SHANK3 gene. Individuals with PMS frequently present with intellectual disability, autism spectrum disorder, and other neurodevelopmental challenges. Electroencephalography (EEG) can provide a window into network-level function in PMS.

METHODS

Here, we analyze EEG data collected across multiple sites in individuals with PMS (n = 26) and typically developing individuals (n = 15). We quantify oscillatory power, alpha-gamma phase-amplitude coupling strength, and phase bias, a measure of the phase of cross frequency coupling thought to reflect the balance of feedforward (bottom-up) and feedback (top-down) activity.

RESULTS

We find individuals with PMS display increased alpha-gamma phase bias (U = 3.841, p < 0.0005), predominantly over posterior electrodes. Most individuals with PMS demonstrate positive overall phase bias while most typically developing individuals demonstrate negative overall phase bias. Among individuals with PMS, strength of alpha-gamma phase-amplitude coupling was associated with Sameness, Ritualistic, and Compulsive behaviors as measured by the Repetitive Behavior Scales-Revised (Beta = 0.545, p = 0.011).

CONCLUSIONS

Increased phase bias suggests potential circuit-level mechanisms underlying phenotype in PMS, offering opportunities for back-translation of findings into animal models and targeting in clinical trials.

Diagnosis of Alzheimer's Disease by Time-Dependent Power Spectrum Descriptors and Convolutional Neural Network Using EEG Signal

Using strategies that obtain biomarkers where early symptoms coincide, the early detection of Alzheimer's disease and its complications is essential. Electroencephalogram is a technology that allows thousands of neurons with equal spatial orientation of the duration of cerebral cortex electrical activity to be registered by postsynaptic potential. Therefore, in this paper, the time-dependent power spectrum descriptors are used to diagnose the electroencephalogram signal function from three groups: mild cognitive impairment, Alzheimer's disease, and healthy control test samples. The final feature used in three modes of traditional classification methods is recorded: k-nearest neighbors, support vector machine, linear discriminant analysis approaches, and documented results. Finally, for Alzheimer's disease patient classification, the convolutional neural network architecture is presented. The results are indicated using output assessment. For the convolutional neural network approach, the accurate meaning of accuracy is 82.3%. 85% of mild cognitive impairment cases are accurately detected in-depth, but 89.1% of the Alzheimer's disease and 75% of the healthy population are correctly diagnosed. The presented convolutional neural network outperforms other approaches because performance and the k-nearest neighbors' approach is the next target. The linear discriminant analysis and support vector machine were at the low area under the curve values.

Spontaneous neural activity relates to psychiatric traits in 16p11.2 CNV carriers: An analysis of EEG spectral power and multiscale entropy

Copy number variations (CNV) at the 16p11.2 chromosomal region are rare high-risk CNVs associated with various clinical features and psychiatric disorders including intellectual disability, developmental delays, and autism spectrum disorder. No study to date has investigated whether spontaneous neural activity is altered for 16p11.2 CNV carriers and whether this relates to psychiatric traits. The aim of this study is to examine the impact of 16p11.2 deletions (del) and duplications (dup) on spontaneous neural activity and its relationship to psychiatric problems. EEG was previously collected as part of the Simons Searchlight initiative. Using spectral power (delta, theta, alpha, and beta frequency bands), complexity index (CI), and multiscale entropy analysis techniques, we analyzed frontal resting-state EEG data collected from 22 16p11.2 del carriers, 14 dup carriers, and 13 controls. We then examined associations between neural activity and psychiatric traits, measured with the Child Behavior Checklist. Results indicated that EEG entropy was higher for del and dup compared to controls, respectively, at all timescales. CI was also higher for del and dup compared to controls. Theta power of 16p11.2 dup carriers was higher than controls. A strong association was found between entropy at higher timescales and anxiety problems. In addition, a strong correlation was found between theta power and pervasive developmental problems. Atypical spontaneous neural activity is implicated in 16p11.2 CNVs. With higher entropy or theta power, psychiatric traits increase in severity. Our findings provide evidence of the link between genotype, neural activity, and phenotypes in 16p11.2 CNVs.

Improvement of brain functional connectivity in autism spectrum disorder: an exploratory study on the potential use of virtual reality

Patients with Autism Spectrum Disorder (ASD) need to be provided with behavioral, psychological, educational, or skill-building interventions as early as possible. Cognitive Behavior Therapy has proven useful to manage such problems. There is also growing evidence on the usefulness of Virtual Reality Therapy (VRT) in treating various functional deficits in ASD. This exploratory study is aimed at assessing the changes in cognitive functions in children with ASD, and the putative subtending neurophysiological mechanisms, following the provision of rehab training using an innovative VRT system. Twenty patients with ASD, aged 6-15 years, were provided with 24 sessions of VRT by using the pediatric module of the BTS NIRVANA System. Neuropsychological and EEG evaluations were carried out before and at the end of the training. After VRT, all patients showed a significant improvement in their cognitive-behavioral problems concerning attention processes, visuospatial cognition, and anxiety. These findings were paralleled by an evident reshape of frontoparietal connectivity in the alpha and theta frequency range. Our study suggests that VRT could be a useful and promising tool to improve ASD neurorehabilitation outcomes. This improvement is likely to occur through changes in frontoparietal network connectivity following VRT.

A randomized double-blind controlled trial of everolimus in individuals with PTEN mutations: Study design and statistical considerations

This randomized, double-blind controlled trial of everolimus in individuals with germline phosphatase and tensin homolog mutations (PTEN) was designed to evaluate the safety of everolimus compared with placebo and to evaluate the efficacy of everolimus on neurocognition and behavior compared to placebo as measured by standardized neurocognitive and motor measures as well as behavioral questionnaires. The safety profile of everolimus is characterized by manageable adverse events that are generally reversible and non-cumulative. The primary safety endpoint of this study was drop-out rate due to side effects, comparing everolimus versus placebo. We also sought to determine the frequency of adverse events by type and severity. The main efficacy endpoint was a neurocognitive composite computed in two ways: 1) an average for working memory, processing speed, and fine motor subtests; and 2) the same average as above except weighted 2/3, and an additional average based on all other available neurocognitive testing measures assessing the additional domains of nonverbal ability, visuomotor skills, verbal learning, and receptive and expressive language, weighted 1/3. Secondary efficacy endpoints examined the effect of everolimus on overall global clinical improvement, autism symptoms, behavioral problems, and adaptive abilities as measured by validated, standardized instruments. We predicted that the rate of adverse events would be no more than 10% higher in the everolimus group compared to placebo, and overall severity of side effects would be minimal. We also expected that individuals receiving everolimus would show more improvement, relative to those taking placebo, on the composite neurocognitive index.

Standardization and Personalized Medicine Using Quantitative EEG in Clinical Settings

Two major trends have been dominant in health care in recent years. First, there is a growing consensus that standardization of health care procedures and methods can result in improved effectiveness and safety of treatments. Second, there is increased interest in "personalized medicine," which refers to the tailoring of treatments to individual patients. Here I discuss how these trends apply to the field of quantitative EEG (qEEG), where de-artifacted resting state EEGs of individuals are compared with a normative database in order to assess clinically meaningful deviations, which can be used for diagnostic procedures, to guide personalized treatment protocols, and to assess treatment effectiveness. Standardized and automated de-artifacting procedures are increasingly being used in scientific research and in clinical practice. The advantages of these procedures over manual de-artifacting will be discussed. The results of a systematic comparison between 2 commonly used qEEG databases show that these databases produce very comparable results, illustrating not only the validity and reliability of both databases but also the opportunity to move forward to a standardized use of qEEG in clinical practice. Finally, the standardization of qEEG interpretation as both a diagnostic and treatment selection tool provides an example of how qEEG can merge both personalized medicine and standardization in the treatment of psychological disorders.

Is autonomic function during resting-state atypical in Autism: A systematic review of evidence

BACKGROUND

Theories of differences in resting-state arousal in autistic individuals are influential. Differences in arousal during resting-state would impact engagement and adaptation to the environment, having a cascading effect on development of attentional and social skills.

OBJECTIVES

We systematically evaluated the evidence for differences in measures of autonomic arousal (heart rate, pupillometry or electrodermal activity) during resting-state in autistic individuals; to understand whether certain contextual or methodological factors impact reports of such differences.

DATA SOURCES

We searched PsycInfo, MEDLINE and EMBASE databases for papers published until 16th May 2019. Of 1207 titles initially identified, 60 met inclusion criteria.

RESULTS AND CONCLUSIONS

Of the 51 studies that investigated group differences between neurotypical and autistic participants, 60.8 % found evidence of group differences. While findings of hyperarousal were more common, particularly using indices of parasympathetic function, findings of hypo-arousal and autonomic dysregulation were also consistently present. Importantly, experimental context played a role in revealing such differences. The evidence is discussed with regard to important methodological factors and implications for future research are described.

Cerebellar oscillations driven by synaptic pruning deficits of cerebellar climbing fibers contribute to tremor pathophysiology

Essential tremor (ET) is one of the most common movement disorders and the prototypical disorder for abnormal rhythmic movements. However, the pathophysiology of tremor generation in ET remains unclear. Here, we used autoptic cerebral tissue from patients with ET, clinical data, and mouse models to report that synaptic pruning deficits of climbing fiber (CF)-to-Purkinje cell (PC) synapses, which are related to glutamate receptor delta 2 (GluRδ2) protein insufficiency, cause excessive cerebellar oscillations and might be responsible for tremor. The CF-PC synaptic pruning deficits were correlated with the reduction in GluRδ2 expression in the postmortem ET cerebellum. Mice with GluRδ2 insufficiency and CF-PC synaptic pruning deficits develop ET-like tremor that can be suppressed with viral rescue of GluRδ2 protein. Step-by-step optogenetic or pharmacological inhibition of neuronal firing, axonal activity, or synaptic vesicle release confirmed that the activity of the excessive CF-to-PC synapses is required for tremor generation. In vivo electrophysiology in mice showed that excessive cerebellar oscillatory activity is CF dependent and necessary for tremor and optogenetic-driven PC synchronization was sufficient to generate tremor in wild-type animals. Human validation by cerebellar electroencephalography confirmed that excessive cerebellar oscillations also exist in patients with ET. Our findings identify a pathophysiologic contribution to tremor at molecular (GluRδ2), structural (CF-to-PC synapses), physiological (cerebellar oscillations), and behavioral levels (kinetic tremor) that might have clinical applications for treating ET.

Autism Spectrum Disorder from the Womb to Adulthood: Suggestions for a Paradigm Shift

The wide spectrum of unique needs and strengths of Autism Spectrum Disorders (ASD) is a challenge for the worldwide healthcare system. With the plethora of information from research, a common thread is required to conceptualize an exhaustive pathogenetic paradigm. The epidemiological and clinical findings in ASD cannot be explained by the traditional linear genetic model, hence the need to move towards a more fluid conception, integrating genetics, environment, and epigenetics as a whole. The embryo-fetal period and the first two years of life (the so-called 'First 1000 Days') are the crucial time window for neurodevelopment. In particular, the interplay and the vicious loop between immune activation, gut dysbiosis, and mitochondrial impairment/oxidative stress significantly affects neurodevelopment during pregnancy and undermines the health of ASD people throughout life. Consequently, the most effective intervention in ASD is expected by primary prevention aimed at pregnancy and at early control of the main effector molecular pathways. We will reason here on a comprehensive and exhaustive pathogenetic paradigm in ASD, viewed not just as a theoretical issue, but as a tool to provide suggestions for effective preventive strategies and personalized, dynamic (from womb to adulthood), systemic, and interdisciplinary healthcare approach.

Volitional modification of brain activity in adolescents with Autism Spectrum Disorder: A Bayesian analysis of Slow Cortical Potential neurofeedback

Autism spectrum disorder is (ASD) characterized by a persisting triad of impairments of social interaction, language as well as inflexible, stereotyped and ritualistic behaviors. Increasingly, scientific evidence suggests a neurobiological basis of these emotional, social and cognitive deficits in individuals with ASD. The aim of this randomized controlled brain self-regulation intervention study was to investigate whether the core symptomatology of ASD could be reduced via an electroencephalography (EEG) based brain self-regulation training of Slow Cortical Potentials (SCP). 41 male adolescents with ASD were recruited and allocated to a) an experimental group undergoing 24 sessions of EEG-based brain training (n1 = 21), or to b) an active control group undergoing conventional treatment (n2 = 20), that is, clinical counseling during a 3-months intervention period. We employed real-time neurofeedback training recorded from a fronto-central electrode intended to enable participants to volitionally regulate their brain activity. Core autistic symptomatology was measured at six time points during the intervention and analyzed with Bayesian multilevel approach to characterize changes in core symptomatology. Additional Bayesian models were formulated to describe the neural dynamics of the training process as indexed by SCP (time-domain) and power density (PSD, frequency-domain) measures. The analysis revealed a substantial improvement in the core symptomatology of ASD in the experimental group (reduction of 21.38 points on the Social Responsiveness Scale, SD = 5.29), which was slightly superior to that observed in the control group (evidence Ratio = 5.79). Changes in SCP manifested themselves as different trajectories depending on the different feedback conditions and tasks. Further, the model of PSD revealed a continuous decrease in delta power, parallel to an increase in alpha power. Most notably, a non-linear (quadratic) model turned out to be better at predicting the data than a linear model across all analyses. Taken together, our analyses suggest that behavioral and neural processes of change related to neurofeedback training are complex and non-linear. Moreover, they have implications for the design of future trials and training protocols.

Associations between sensory processing and electrophysiological and neurochemical measures in children with ASD: an EEG-MRS study

Background

Autism spectrum disorder (ASD) is associated with hyper- and/or hypo-sensitivity to sensory input. Spontaneous alpha power, which plays an important role in shaping responsivity to sensory information, is reduced across the lifespan in individuals with ASD. Furthermore, an excitatory/inhibitory imbalance has also been linked to sensory dysfunction in ASD and has been hypothesized to underlie atypical patterns of spontaneous brain activity. The present study examined whether resting-state alpha power differed in children with ASD as compared to TD children, and investigated the relationships between alpha levels, concentrations of excitatory and inhibitory neurotransmitters, and atypical sensory processing in ASD.

Methods

Participants included thirty-one children and adolescents with ASD and thirty-one age- and IQ-matched typically developing (TD) participants. Resting-state electroencephalography (EEG) was used to obtain measures of alpha power. A subset of participants (ASD = 16; TD = 16) also completed a magnetic resonance spectroscopy (MRS) protocol in order to measure concentrations of excitatory (glutamate + glutamine; Glx) and inhibitory (GABA) neurotransmitters.

Results

Children with ASD evidenced significantly decreased resting alpha power compared to their TD peers. MRS estimates of GABA and Glx did not differ between groups with the exception of Glx in the temporal-parietal junction. Inter-individual differences in alpha power within the ASD group were not associated with region-specific concentrations of GABA or Glx, nor were they associated with sensory processing differences. However, atypically decreased Glx was associated with increased sensory impairment in children with ASD.

Conclusions

Although we replicated prior reports of decreased alpha power in ASD, atypically reduced alpha was not related to neurochemical differences or sensory symptoms in ASD. Instead, reduced Glx in the temporal-parietal cortex was associated with greater hyper-sensitivity in ASD. Together, these findings may provide insight into the neural underpinnings of sensory processing differences present in ASD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s11689-020-09351-0.

Changes in Electroencephalogram Coherence in Adolescents With Autism Spectrum Disorder After a Social Skills Intervention

Autism spectrum disorder (ASD) is a developmental condition that affects social communication and behavior. There is consensus that neurological differences are present in ASD. Further, theories emphasize the mixture of hypo- and hyper-connectivity as a neuropathologies in ASD [O'Reilly, Lewis, & Elsabbagh, 2017]; however, there is a paucity of studies specifically testing neurological underpinnings as predictors of success on social skills interventions. This study examined functional neural connectivity (electroencephalogram [EEG], coherence) of adolescents with ASD before and after the Program for the Education and Enrichment of Relational Skills (PEERS®) intervention, using a randomized controlled trial of two groups: an Experimental ASD (EXP) Group and a Waitlist Control ASD (WL) Group. The study had two purposes. First, the study aimed to determine whether changes in EEG coherence differed for adolescents that received PEERS® versus those that did not receive PEERS®. Results revealed a significant increase in connectivity in the occipital left to temporal left pair for the EXP group after intervention. Second, the study aimed to determine if changes in EEG coherence related to changes in behavior, friendships, and social skills measured by questionnaires. At post-intervention, results indicated: (a) positive change in frontal right to parietal right coherence was linked to an increase in social skills scores; and (b) positive changes in occipital right to temporal right coherence and occipital left to parietal left coherence were linked to an increase in the total number of get-togethers. Results of this study support utilizing neurobehavioral domains as indicators of treatment outcome. Lay Summary: This study examined how well various areas of the brain communicate in adolescents with ASD before and after a social skills intervention. Results revealed increased connectivity in the adolescents that received the intervention. Secondly, the study aimed to determine if changes in connectivity of brain areas related to changes in behavior, friendships, and social skills. Results indicated that changes in connectivity were also linked to increased social skills. Autism Res 2021, 14: 787-803. © 2021 International Society for Autism Research and Wiley Periodicals LLC.

Electroencephalography in Assessment of Autism Spectrum Disorders: A Review

Electroencephalography (EEG) can further out our understanding of autistic spectrum disorders (ASD) neurophysiology. Epilepsy and ASD comorbidity range between 5 and 46%, but its temporal relationship, causal mechanisms and interplay with intellectual disability are still unknown. Epileptiform discharges with or without seizures go as high as 60%, and associate with epileptic encephalopathies, conceptual term suggesting that epileptic activity can lead to cognitive and behavioral impairment beyond the underlying pathology. Seizures and ASD may be the result of similar mechanisms, such as abnormalities in GABAergic fibers or GABA receptor function. Epilepsy and ASD are caused by a number of genetic disorders and variations that induce such dysregulation. Similarly, initial epilepsy may influence synaptic plasticity and cortical connection, predisposing a growing brain to cognitive delays and behavioral abnormalities. The quantitative EEG techniques could be a useful tool in detecting and possibly measuring dysfunctions in specific brain regions and neuronal regulation in ASD. Power spectra analysis reveals a U-shaped pattern of power abnormalities, with excess power in the low and high frequency bands. These might be the consequence of a complicated network of neurochemical changes affecting the inhibitory GABAergic interneurons and their regulation of excitatory activity in pyramidal cells. EEG coherence studies of functional connectivity found general local over-connectivity and long-range under-connectivity between different brain areas. GABAergic interneuron growth and connections are presumably impaired in the prefrontal and temporal cortices in ASD, which is important for excitatory/inhibitory balance. Recent advances in quantitative EEG data analysis and well-known epilepsy ASD co-morbidity consistently indicate a role of aberrant GABAergic transmission that has consequences on neuronal organization and connectivity especially in the frontal cortex.

Music therapy as social skill intervention for children with comorbid ASD and ID: study protocol for a randomized controlled trial

BACKGROUND

Autism spectrum disorder (ASD) is a developmental impairment characterized by persistent deficits in social communication and interactions, and over half of children with ASD possess below average intellectual ability (IQ < 85). The social development and response to social skill interventions among children with ASD and comorbid intellectual disability (ID) is not well understood. Music therapy is a systematic process of intervention, wherein a therapist may help clients promote their social skills by using musical experience. The proposed study will address limited research evidence on music therapy as an intervention for social functioning in children with ASD with mild to borderline ID.

METHOD

A randomized controlled trial (RCT) with two parallel groups of 40 children each (1:1 allocation ratio) is planned. Participants will receive 45 min of music therapy or non-musical intervention targeting social skills once a week for 12 weeks. Primary outcome measures will be independent ratings on the Childhood Autism Rating Scale and parent ratings on the Social Responsiveness Scale-2. Linear mixed-effects models for these two outcome measures will be created for data collected at 2-week pre-intervention, 2-week post-intervention, and 4-month post-intervention sessions. In-session behaviors at the first and last intervention will be videotaped and coded offline and compared. Pretreatment neural response of quantitative electroencephalograms (qEEG) to social scenes will be used to predict the outcomes of musical and non-musical social skill interventions, whereas qEEG responses to music will be used to predict the effectiveness of musical social skill intervention.

DISCUSSION

If neural markers of social skill development are found, then the long-term goal is to develop individualized intervention based on pre-treatment markers to maximize treatment efficacy. The proposed study's results may also suggest directions to development and provision of music therapy services in Hong Kong.

TRIAL REGISTRATION

ClinicalTrials.gov ( NCT04557488 ). Registered September 21, 2020.

Resting state EEG-based diagnosis of Autism via elliptic area of continuous wavelet transform complex plot

Autism is a developmental disorder that influences social communication skills. It is currently diagnosed only by behavioral assessment. The assessment is susceptible to the experience of the examiner as well as to the descriptive scaling standard. This paper presents a computer aided approach to discrimination between neuro-typical and autistic children. A new method- based on the computing of the elliptic area of the Continuous Wavelet Transform complex plot of resting state EEG- is presented. First, the complex values of CWT, as a function of both time and frequency, are calculated for every EEG channel. Second, the CWT complex plot is obtained by plotting the real parts of the resulted CWT values versus the related imaginary components. Third, the 95% confidence value of the elliptic area of the complex plot is computed for every channel for both autistic and healthy subjects; and the obtained values are considered as the first set of features. Fourth, three additional features are computed for every channel: the average CWT, the maximum EEG amplitude, and the maximum real part of CWT. The classification of those features is realized through artificial neural network (ANN). The obtained accuracy, sensitivity and specificity values are: 95.9%, 96.7%, and 95.1% respectively.

Resting-state EEG Dynamics Reveals Differences in Network Organization and its Fluctuation between Frequency Bands

Functional connectivity in EEG resting-state is not stable but fluctuates considerably. The aim of this study was to investigate how efficient information flows through a network, i.e. how resting-state EEG networks are organized and whether this organization it also subject to fluctuations. Differences of the network organization (small-worldness), degree of clustered connectivity, and path length as an indicator of how information is integrated into the network across time was compared between theta, alpha and beta bands. We show robust differences in network organization (small-worldness) between frequency bands. Fluctuations in network organization were larger in the theta, compared to the alpha and beta frequency. Variation in network organization and not the frequency of fluctuations differs between frequency bands. Furthermore, the degree of clustered connectivity and its modulation across time is the same across frequency bands, but the path length revealed the same modulatory pattern as the small-world metric. It is therefore the interplay of local processing efficiency and global information processing efficiency in the brain that fluctuates in a frequency-specific way. Properties of how information can be integrated is subject to fluctuations in a frequency-specific way in the resting-state. The possible relevance of these resting-state EEG properties is discussed including its clinical relevance.

A study on EEG feature extraction and classification in autistic children based on singular spectrum analysis method

INTRODUCTION

The clinical diagnosis of Autism spectrum disorder (ASD) depends on rating scale evaluation, which introduces subjectivity. Thus, objective indicators of ASD are of great interest to clinicians. In this study, we sought biomarkers from resting-state electroencephalography (EEG) data that could be used to accurately distinguish children with ASD and typically developing (TD) children.

METHODS

We recorded resting-state EEG from 46 children with ASD and 63 age-matched TD children aged 3 to 5 years. We applied singular spectrum analysis (SSA) to the EEG sequences to eliminate noise components and accurately extract the alpha rhythm.

RESULTS

When we used individualized alpha peak frequency (iAPF) and individualized alpha absolute power (iABP) as features for a linear support vector machine, ASD versus TD classification accuracy was 92.7%.

CONCLUSION

This study suggested that our methods have potential to assist in clinical diagnosis.

The Generalized Adaptation Account of Autism

The heterogeneous phenomenology of autism together with diverse patterns of comorbidities led in the past to formulation of manifold theories and hypotheses on different explanatory levels. We scrutinize most recent findings from genetics, neurobiology and physiology and derive testable hypotheses about possible physiological links between domains. With focus on altered sensory perception and neuronal processing in ASD, we assume two intertwined regulatory feedback circuits under the umbrella of genetics and environmental factors. Both regulatory circuits are highly variable between individuals in line with the heterogeneous spectrum of ASD. The circuits set off from altered pathways and connectivity in ASD, fueling HPA-axis activity and distress. In the first circuit altered tryptophan metabolism leads to higher neurotoxic substances and reinforces the excitation:inhibition imbalance in the brain. The second circuit focuses on the impact and interaction with the environment and its rhythms in ASD. With lower melatonin levels, as the pacemaker molecule of the circadian system, we assume misalignment to outer and inner states corroborated from the known comorbidities in ASD. Alterations of the microbiome composition in ASD are supposed to act as a regulatory linking factor for both circuits. Overall, we assume that altered internal balance on cellular and neurophysiological levels is one of the main reasons leading to a lower ability in ASD to adapt to the environment and own internal changing states, leading to the conceptualization of autism as a condition of generalized imbalance in adaptation. This comprehensive framework opens up new perspectives on possible intervention and prevention strategies.

Shifts in broadband power and alpha peak frequency observed during long-term isolation

Prolonged periods of social isolation and spatial confinement do not only represent an issue that needs to be faced by a few astronauts during space missions, but can affect all of us as recently shown during pandemic situations. The fundamental question, how the brain adapts to periods of sensory deprivation and re-adapts to normality, has only received little attention. Here, we use eyes closed and eyes open resting-state electroencephalographic (EEG) recordings to investigate how neural activity is altered during 120 days of isolation in a spatially confined, space-analogue environment. After disentangling oscillatory patterns from 1/f activity, we show that isolation leads to a reduction in broadband power and a flattening of the 1/f spectral slope. Beyond that, we observed a reduction in alpha peak frequency during isolation, but did not find strong evidence for isolation-induced changes that are of oscillatory nature. Critically, all effects reversed upon release from isolation. These findings suggest that isolation and concomitant sensory deprivation lead to an enhanced cortical deactivation which might be explained by a reduction in the mean neuronal population firing rate.

A Spectral Clustering Approach for the Classification of Waveform Anomalies in High-Dimensional Brain Signals

Transient electrophysiological anomalies in the human brain have been associated with neurological disorders such as epilepsy, may signal impending adverse events (e.g, seizurse), or may reflect the effects of a stressor, such as insufficient sleep. These, typically brief, high-frequency and heterogeneous signal anomalies remain poorly understood, particularly at long time scales, and their morphology and variability have not been systematically characterized. In continuous neural recordings, their inherent sparsity, short duration and low amplitude makes their detection and classification difficult. In turn, this limits their evaluation as potential biomarkers of abnormal neurodynamic processes (e.g., ictogenesis) and predictors of impending adverse events. A novel algorithm is presented that leverages the inherent sparsity of high-frequency abnormalities in neural signals recorded at the scalp and uses spectral clustering to classify them in very high-dimensional signals spanning several days. It is shown that estimated clusters vary dynamically with time and their distribution changes substantially both as a function of time and space.

Autism Spectrum Disorder and Medical Cannabis: Review and Clinical Experience

Autism spectrum disorder (ASD) is a multifactorial, pervasive neurodevelopmental disorder defined by the core symptoms of significant impairment in social interaction and communication as well as restricted, repetitive patterns of behavior. In addition to these core behaviors, persons with ASD frequently have associated noncore behavioral disturbance (ie, self-injury, aggression), as well as several medical comorbidities. Currently, no effective treatment exists for the core symptoms of ASD. This review reports the available preclinical and clinical data regarding the use of cannabis and cannabidiol in the treatment of core symptoms, noncore symptoms and comorbidities associated with ASD. Additionally, we describe our clinical experience working with children and young adults with ASD who have used cannabis or cannabidiol. At present, preclinical and clinical data suggest a potential for therapeutic benefit among some persons with ASD and that it is overall well tolerated. Further research is required to better identify patients who may benefit from treatment without adverse effects.

The Effect of Transcranial Pulsed Current Stimulation at 4 and 75 Hz on Electroencephalography Theta and High Gamma Band Power: A Pilot Study

Introduction: Transcranial pulsed current stimulation (tPCS) is an emerging noninvasive brain stimulation technique that has shown significant effects on cortical excitability. To date, electrophysiological measures of the efficiency of monophasic tPCS have not been reported. Objective: We aimed to explore the effects of monophasic anodal and cathodal-tPCS (a-tPCS/c-tPCS) at theta (4 Hz) and gamma (75 Hz) frequencies on theta and high gamma electroencephalography (EEG) oscillatory power. Methods: In a single-blind, randomized, sham-controlled crossover design, 15 healthy participants were randomly assigned into 5 experimental sessions in which they received a-PCS/c-tPCS at 4 and 75 Hz or sham stimulation over the left primary motor cortex (M1) for 15 min at an intensity of 1.5 mA. Changes in theta and high gamma oscillatory power were recorded at baseline, immediately after, and 30 min after stimulation using EEG at rest with eyes open. Results: a-tPCS at 4 Hz showed a significant increase in theta power compared with sham, whereas c-tPCS at 4 Hz had no significant effect on theta power. a-tPCS at 75 Hz produced no changes in high gamma power compared with sham. Importantly, c-tPCS at 75 Hz led to a significant reduction in high gamma power compared with baseline, as well as compared with c-tPCS at 4 Hz and sham stimulation. Conclusion: The results demonstrate the modulation of oscillatory brain activity by monophasic tPCS, and highlight the need for future studies on a larger scale to confirm these initial findings. Impact statement Transcranial pulsed current stimulation (tPCS) is a novel brain stimulation technique. Recently, tPCS has been introduced to directly modulate brain oscillations by applying pulsatile current over the target brain area. Using both anodal and cathodal monophasic tPCS at theta and gamma frequencies, we demonstrate the ability of the stimulation to modulate brain activity. The present findings are the first direct electroencephalography evidence of an interaction between tPCS and ongoing oscillatory activity in the human motor cortex. Our work recommends tPCS as a tool for investigating human brain oscillations and open more studies in this area.

Electroencephalographic Abnormalities in Autism Spectrum Disorder: Characteristics and Therapeutic Implications

A large body of literature reports the higher prevalence of epilepsy in subjects with Autism Spectrum Disorder (ASD) compared to the general population. Similarly, several studies report an increased rate of Subclinical Electroencephalographic Abnormalities (SEAs) in seizure-free patients with ASD rather than healthy controls, although with varying percentages. SEAs include both several epileptiform discharges and different non-epileptiform electroencephalographic abnormalities. They are more frequently associated with lower intellectual functioning, more serious dysfunctional behaviors, and they are often sign of severer forms of autism. However, SEAs clinical implications remain controversial, and they could represent an epiphenomenon of the neurochemical alterations of autism etiology. This paper provides an overview of the major research findings with two main purposes: to better delineate the state-of-the-art about EEG abnormalities in ASD and to find evidence for or against appropriateness of SEAs pharmacological treatment in ASD.

EEG Biomarkers Related With the Functional State of Stroke Patients

Introduction

Recent studies explored promising new quantitative methods to analyze electroencephalography (EEG) signals. This paper analyzes the correlation of two EEG parameters, Brain Symmetry Index (BSI) and Laterality Coefficient (LC), with established functional scales for the stroke assessment.

Methods

Thirty-two healthy subjects and thirty-six stroke patients with upper extremity hemiparesis were recruited for this study. The stroke patients where subdivided in three groups according to the stroke location: Cortical, Subcortical, and Cortical + Subcortical. The participants performed assessment visits to record the EEG in the resting state and perform functional tests using rehabilitation scales. Then, stroke patients performed 25 sessions using a motor-imagery based Brain Computer Interface system (BCI). BSI was calculated with the EEG data in resting state and LC was calculated with the Event-Related Synchronization maps.

Results

The results of this study demonstrated significant differences in the BSI between the healthy group and Subcortical group (P = 0.001), and also between the healthy and Cortical+Subcortical group (P = 0.019). No significant differences were found between the healthy group and the Cortical group (P = 0.505). Furthermore, the BSI analysis in the healthy group based on gender showed statistical differences (P = 0.027). In the stroke group, the correlation between the BSI and the functional state of the upper extremity assessed by Fugl-Meyer Assessment (FMA) was also significant, ρ = −0.430 and P = 0.046. The correlation between the BSI and the FMA-Lower extremity was not significant (ρ = −0.063, P = 0.852). Similarly, the LC calculated in the alpha band has significative correlation with FMA of upper extremity (ρ = −0.623 and P < 0.001) and FMA of lower extremity (ρ = −0.509 and P = 0.026). Other important significant correlations between LC and functional scales were observed. In addition, the patients showed an improvement in the FMA-upper extremity after the BCI therapy (ΔFMA = 1 median [IQR: 0–8], P = 0.002).

Conclusion

The quantitative EEG tools used here may help support our understanding of stroke and how the brain changes during rehabilitation therapy. These tools can help identify changes in EEG biomarkers and parameters during therapy that might lead to improved therapy methods and functional prognoses.

Lesion of the Fastigial Nucleus in Juvenile Rats Deteriorates Rat Behavior in Adulthood, Accompanied by Altered Neuronal Activity in the Medial Prefrontal Cortex

The cerebellar cognitive affective syndrome may result from various cerebellar injuries. Although it is not exactly known which anatomical structures are involved, the fastigial nucleus has been thought to play a pivotal role according to recent studies. Here we investigate whether bilateral fastigial nucleus lesions in juvenile rats affect cognitive-associative and limbic related functions in adulthood. Furthermore, potential effects on the neuronal activity in the medial prefrontal cortex (mPFC) and local field coherence with the sensorimotor cortex (SMCtx) were evaluated. The fastigial nucleus was lesioned bilaterally by thermocoagulation via stereotaxically inserted electrodes in 23-day old male Sprague Dawley rats. Naïve and sham-lesioned rats (electrodes inserted above the nucleus and no electrical current applied) served as controls. As adults, all groups were tested for cognitive-associative function, social behavior, and anxiety. Thereafter, electrophysiological recordings were obtained under urethane anesthesia. Finally, lesions and recording sites were histologically verified. Spatial learning in a radial maze test and learning in an operant learning paradigm was disturbed in rats with fastigial lesions. Furthermore, in the elevated plus maze anxiety was enhanced, whereas social behavior was not affected. Electrophysiological recordings showed enhanced local field coherence between mPFC and SMCtx across all frequency bands. Impaired cognitive and affective functions together with enhanced coherence between mPFC and SMCtx after bilateral fastigial nucleus lesions indicate that the fastigial nucleus contribute to the development of the cerebellar cognitive affective syndrome and associated motor behavior.

A Phase II Randomized Clinical Trial of the Safety and Efficacy of Intravenous Umbilical Cord Blood Infusion for Treatment of Children with Autism Spectrum Disorder

OBJECTIVE

To evaluate whether umbilical cord blood (CB) infusion is safe and associated with improved social and communication abilities in children with autism spectrum disorder (ASD).

STUDY DESIGN

This prospective, randomized, placebo-controlled, double-blind study included 180 children with ASD, aged 2-7 years, who received a single intravenous autologous (n = 56) or allogeneic (n = 63) CB infusion vs placebo (n = 61) and were evaluated at 6 months postinfusion.

RESULTS

CB infusion was safe and well tolerated. Analysis of the entire sample showed no evidence that CB was associated with improvements in the primary outcome, social communication (Vineland Adaptive Behavior Scales-3 [VABS-3] Socialization Domain), or the secondary outcomes, autism symptoms (Pervasive Developmental Disorder Behavior Inventory) and vocabulary (Expressive One-Word Picture Vocabulary Test). There was also no overall evidence of differential effects by type of CB infused. In a subanalysis of children without intellectual disability (ID), allogeneic, but not autologous, CB was associated with improvement in a larger percentage of children on the clinician-rated Clinical Global Impression-Improvement scale, but the OR for improvement was not significant. Children without ID treated with CB showed significant improvements in communication skills (VABS-3 Communication Domain), and exploratory measures including attention to toys and sustained attention (eye-tracking) and increased alpha and beta electroencephalographic power.

CONCLUSIONS

Overall, a single infusion of CB was not associated with improved socialization skills or reduced autism symptoms. More research is warranted to determine whether CB infusion is an effective treatment for some children with ASD.

Aged heterozygous Cdkl5 mutant mice exhibit spontaneous epileptic spasms

CDKL5 deficiency disorder (CDD) is a devastating neurodevelopmental disorder characterized by early-onset epilepsy, severe intellectual disability, cortical visual impairment and motor disabilities. Epilepsy is a central feature of CDD, with most patients having intractable seizures, but seizure frequency and severity can vary. Clinical reports demonstrate a diversity in seizure semiology and electrographic features, with no pattern diagnostic of CDD. Although animal models of CDD have shown evidence of hyperexcitability, spontaneous seizures have not been previously reported. Here, we present the first systematic study of spontaneous seizures in mouse models of CDD. Epileptic spasms, the most frequent and persistent seizure type in CDD patients, were recapitulated in two mouse models of CDD carrying heterozygous mutations, Cdkl5^R59X and Cdkl5^KO. Spasm-like events were present in a significant proportion of aged heterozygous female mice carrying either of the two Cdkl5 mutations with significant variability in seizure burden. Electrographically, spasms were most frequently associated with generalized slow-wave activity and tended to occur in clusters during sleep. CDD mice also showed interictal and background abnormalities, characterized by high-amplitude spiking and altered power in multiple frequency bands. These data demonstrate that aged female heterozygous Cdkl5 mice recapitulate multiple features of epilepsy in CDD and can serve to complement existing models of epileptic spasms in future mechanistic and translational studies.