Epilepsy and EEG Abnormalities in Children with Autism Spectrum Disorders

Dipolar EEG Spikes Are More Benign

PURPOSE

Rolandic epileptiform discharges with tangential dipole (T-dipole) configurations are associated with favorable prognosis. Whether the same is true for T-dipole epileptiform discharges in other brain regions is less established and is the objective of this study.

METHODS

Over 20 years, patients with epileptiform discharges were identified as follows: frontal (F = 176), temporal (T = 196), central (C = 201), parietal (P = 120), and occipital (O = 205). T-dipoles were documented. Clinical features of children with and without T-dipole were compared both regardless of brain region and separately for each brain region.

RESULTS

The prevalence of T-dipoles was 232/898 (25.8%) overall and within different regions as follows: T = 104 (53.1%), O = 51 (24.9%), P = 23 (19.2%), C = 35 (17.4%), and F = 19 (10.8%). Most had epilepsy (T-dipole: 193 [83.2%] and nondipole: 532 [79.9%]). Regardless of region, T-dipole was associated with less drug-resistant epilepsy (11 [4.7%] vs. 202 [30.3%], P < 0.001), developmental delay (57 [24.6%] vs. 436 [51.0%], P < 0.001), school performance difficulties (SPD) (101 [43.5%] vs. 410 [61.6%], P < 0.001), autism (30 [12.9%] vs. 127 [19.1%], P = 0.037), and abnormal examination (28 [12.1%] vs. 257 [38.6%], P < 0.001]). Within different brain regions, on logistic regression, T-dipole was associated with lower odds of drug-resistant epilepsy (F, T, C, P, and O), developmental delay (F, T, C, and P), SPD (F, T, and C), autism (F and T), abnormal examination (F, T, C, and O), and abnormal neuroimaging (T, C, P, and O).

CONCLUSIONS

On routine EEG analysis, focal epileptiform discharges with T-dipoles, regardless of brain region, are associated with a more favorable clinical course.

Electroencephalography in Autism Spectrum Disorder

Background/Objectives: Electroencephalography (EEG) has been widely used to differentiate individuals with autism spectrum disorder (ASD) and co-occurring conditions, particularly epilepsy. However, the relationship between EEG abnormalities and core features of ASD remains unclear. This study reviews the potential impact of EEG findings on the development, behavior, sleep, and seizure occurrence in ASD patients. Additionally, it evaluates whether routine EEG testing is warranted for all ASD patients, particularly in the absence of clinical seizures. Methods: A systematic review was conducted that covered literature published between 2014 and 2024. The review focused on EEG abnormalities, both epileptiform and non-epileptiform, in individuals with ASD. Studies were selected based on predefined inclusion criteria, emphasizing the prevalence, type, and clinical relevance of EEG findings. The analysis also included a critical assessment of whether EEG abnormalities correlate with specific ASD symptoms, such as cognitive impairment, speech delay, or behavioral issues. Results: EEG abnormalities were reported in 23-80% of ASD patients, indicating a broad range of findings. Despite their frequent occurrence, the evidence linking these abnormalities to specific clinical symptoms remains inconclusive. Some studies suggest an association between epileptiform patterns and more severe ASD traits, while others do not confirm this. Furthermore, the effectiveness of anticonvulsant treatment in children with EEG abnormalities and no seizures remains uncertain, with limited supporting data. Conclusions: Given the uncertain relationship between EEG findings and ASD symptoms, routine EEG testing for all children with ASD appears unnecessary. EEG should be considered primarily when epilepsy is clinically suspected.

EEG Abnormalities and Phenotypic Correlates in Preschoolers with Autism Spectrum Disorder: A Single-Center Study

Background: The literature suggests the existence of an association between autism spectrum disorders (ASDs) and subclinical electroencephalographic abnormalities (SEAs), which show a heterogeneous prevalence rate (12.5-60.7%) within the pediatric ASD population. The aim of this study was to investigate the EEG findings in a cohort of ASD preschoolers and their correlation with the phenotypic characteristics. Methods: We retrospectively reviewed data on 141 ASD preschoolers evaluated in a tertiary care university hospital over the period 2008-2018. All participants underwent at least one standard polygraphic electroencephalogram (EEG) and a clinical multidisciplinary assessment with standardized instruments. Results: 77 patients (55%) showed SEAs, which were mainly represented by epileptiform discharges (p < 0.00001), especially focal and multifocal (p = 0.010). Abnormal EEG (p = 0.035) and epileptiform discharges (p = 0.014) were associated with seizure onset and were predominant in sleep (p < 0.00001). Patients with abnormal tracing (p = 0.031) and slow abnormalities (p < 0.001) were significantly younger. ASD severity was not found to be correlated with EEG results, which showed a potential, albeit non-significant, association with some psychometric parameters. Very similar results were found when patients were divided according to sex. Conclusions: EEG abnormalities appear to correlate more with ASD internalizing, externalizing and emotional comorbidities, rather than with ASD core symptoms; larger samples are needed to further investigate this association.

Identification of autism spectrum disorder using electroencephalography and machine learning: a review

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by communication barriers, societal disengagement, and monotonous actions. Traditional diagnostic methods for ASD rely on clinical observations and behavioural assessments, which are time-consuming. In recent years, researchers have focused mainly on the early diagnosis of ASD due to the unavailability of recognised causes and the lack of permanent curative solutions. Electroencephalography (EEG) research in ASD offers insight into the neural dynamics of affected individuals. This comprehensive review examines the unique integration of EEG, machine learning, and statistical analysis for ASD identification, highlighting the promise of an interdisciplinary approach for enhancing diagnostic precision. The comparative analysis of publicly available EEG datasets for ASD, along with local data acquisition methods and their technicalities, is presented in this paper. This study also compares preprocessing techniques, and feature extraction methods, followed by classification models and statistical analysis which are discussed in detail. In addition, it briefly touches upon comparisons with other modalities to contextualize the extensiveness of ASD research. Moreover, by outlining research gaps and future directions, this work aims to catalyse further exploration in the field, with the main goal of facilitating more efficient and effective early identification methods that may be helpful to the lives of ASD individuals.

Case report: Assessment of linguistic, cognitive, and sensory profile competencies in a child with ASD and epilepsy

Introduction

Autism Spectrum Disorder (ASD) and epilepsy pose significant challenges for early diagnosis during childhood. Current scientific literature does not reflect robust action protocols that allow for a detailed screening of difficulties in this population, especially in areas such as language, cognition, and sensory profile. Additionally, detecting epilepsy before the age of 4 is established as a major current public health challenge in our society.

Objective

The aim was to evaluate a patient exhibiting symptoms compatible with both ASD and epilepsy, determining the linguistic, cognitive, and sensory profile through a clinical assessment protocol. Furthermore, the objective included establishing a diagnosis of ASD.

Method

This single-case study (N = 1) presents the evaluation of a 7-year-old patient with suspected ASD, experiencing a decline in linguistic and cognitive competencies following a documented epileptic episode. Evaluation was conducted using instruments such as CELF-5, PROLEC-R, WISC-V, ENFEN, PS-2, ADI-R, and ADOS-2.

Results

Following assessment of language, cognition, sensory aspects, and behaviors associated with ASD, the diagnosis of ASD was confirmed in the patient, along with impairments in expressive and receptive language, executive functioning, and alterations in the sensory profile.

Conclusion

Diagnosing ASD and epilepsy, as well as their evaluation, is a complex process requiring interdisciplinary assessment involving a detailed exploration of all functional competencies in individuals with this comorbidity. Future studies should focus on creating and improving existing protocols to develop optimal and effective evaluation strategies for assessing this population during childhood.

Children with Autism Spectrum Disorder and Abnormalities of Clinical EEG: A Qualitative Review

Over the last decade, the comorbidity between Autism Spectrum Disorder (ASD) and epilepsy has been widely demonstrated, and many hypotheses regarding the common neurobiological bases of these disorders have been put forward. A variable, but significant, prevalence of abnormalities on electroencephalogram (EEG) has been documented in non-epileptic children with ASD; therefore, several scientific studies have recently tried to demonstrate the role of these abnormalities as a possible biomarker of altered neural connectivity in ASD individuals. This narrative review intends to summarize the main findings of the recent scientific literature regarding abnormalities detected with standard EEG in children/adolescents with idiopathic ASD. Research using three different databases (PubMed, Scopus and Google Scholar) was conducted, resulting in the selection of 10 original articles. Despite an important lack of studies on preschoolers and a deep heterogeneity in results, some authors speculated on a possible association between EEG abnormalities and ASD characteristics, in particular, the severity of symptoms. Although this correlation needs to be more strongly elucidated, these findings may encourage future studies aimed at demonstrating the role of electrical brain abnormalities as an early biomarker of neural circuit alterations in ASD, highlighting the potential diagnostic, prognostic and therapeutic value of EEG in this field.

Clinical and Demographic Characteristics of Families Attending the Epilepsy, Neuromuscular, and Child Wellbeing Clinics

Background Neurological diseases entail a broad spectrum of disorders. Among such ailments are epilepsy and neuromuscular disorders which impose a substantial burden on children and their families. Ensuring adequate access to outpatient services is crucial for these children regardless of the subclinical specialty, and clinicians can better comprehend the caregivers' perspectives by being aware of their backgrounds which can be aided using epidemiological studies. Methods In June 2023, a cross-sectional study was carried out in pediatric neurology clinics at a tertiary care center. The study included all families with a child or more (14 years and younger) diagnosed with neurological disorders. The study adopted a three-section survey delivered to participants recruited using a non-probability sampling technique to achieve a 95% confidence interval with a 5% margin of error. Results A total of 821 families participated in this study. The mean age of respondents was 40.46±8.72 years. Of the affected children, there were 600 (73.08%) children following up with the general neurology and epilepsy clinics, 164 (19.98%) were following up with the neuromuscular disorders clinics, and 57 (6.94%) were following up with the neurogenetic clinics. Familial status had no association with the type of clinic the patient was following up with p=0.0054. Single respondents had a significantly higher prevalence of children with epilepsy (p<0.0001). Parents with a high school level of education or lower had a significantly greater prevalence of epilepsy clinic follow-ups (p=0.0048). Conclusion The findings of this study contribute to the assessment of prevalent neurological disorders in children and shed light on the family dynamics surrounding these conditions. Through statistical analysis, the study establishes connections between certain demographic and clinical traits and specific neurological disorders among pediatric patients and their families. The study emphasizes the importance of socio-economic and socio-clinical support in promoting child health in such cases. Similar research would offer a more accurate portrayal of the challenges faced by families in these circumstances.

The Predictive Relationship Between Sensory Reactivity and Depressive Symptoms in Young Autistic Children with Few to No Words

Depression and sensory reactivity are both common in autism. However, there is little understanding of the predictive relationship between these factors, or the nature of this relationship in autistic children who speak few to no words. This study set out to explore the longitudinal relationship between sensory reactivity and depressive symptoms in 33 young autistic children who speak few to no words. We found positive correlations between depressive symptoms and hyper-reactivity and sensory seeking at both timepoints, and across timepoints. We further found a bidirectional predictive relationship between depressive symptoms and sensory seeking. These results implicate sensory seeking in the development of depressive symptoms in young autistic children who use few to no words. Our findings have important implications for preventative mental health interventions, especially for those with a developmental language delay.

Clinical features and drug-resistance in pediatric epilepsy with co-occurring autism: A retrospective comparative cohort study

OBJECTIVE

We conducted a retrospective comparative cohort study to determine the phenotypic and real-world management differences in children with epilepsy and co-occurring autism as compared to those without autism.

METHODS

Clinical variables, EEG, brain MRI, genetic results, medical and non-medical treatment were compared between 156 children with both epilepsy and autism, 156 randomly selected and 156 demographically matched children with epilepsy only. Logistic regression analyses were conducted to determine predictors of drug-resistant epilepsy (DRE).

RESULTS

As compared to the'matched' cohort, more patients with autism had generalized motor seizures although not statistically significant after Benjamini-Hochberg correction (54.5%, vs 42.3%, p = .0314); they had a lower rate of electroclinical syndromes (12.8%, vs 30.1%, p = .0002). There were more incidental MRI findings but less positive MRI findings to explain their epilepsy in children with autism (26.3%, vs 13.8% and 14.3%, vs 34.2%, respectively; p = .0003). In addition, LEV, LTG, and VPA were the most common ASMs prescribed to children with autism, as opposed to LEV, OXC, and LTG in children without autism. No difference in the major EEG abnormalities was observed. Although the rates of DRE were similar (24.8%, vs 26.6%, p = .7203), we identified two clinical and five electrographic correlates with DRE in children with both epilepsy and autism and a final prediction modeling of DRE that included EEG ictal findings, focal onset seizures, generalized motor seizures, abnormal EEG background, age of epilepsy onset, and history of SE, which were distinct from those in children without autism.

SIGNIFICANCE

Our study indicates that detailed seizure history and EEG findings are the most important evaluation and prediction tools for the development of DRE in children with epilepsy and co-occurring autism. Further studies of epilepsy in specific autism subgroups based on their etiology and clinical severity are warranted.

Early Diagnosis of Autism Spectrum Disorder: What the Pediatricians Should Know

Autism is a spectrum disorder marked by considerable heterogeneity and characterized by impairments in the social communication domain along with the presence of restricted and repetitive behaviors or interests. Comprehensive autism evaluation generally consists of assessments by a multidisciplinary team. Having multiple specialists in the evaluation team aids in diagnosis and in chalking out a comprehensive management plan. Diagnosis is generally based on detailed developmental history, clinical judgment, and the use of standardized diagnostic instruments. Differential diagnosis is complicated as many of the mental health and neurodevelopmental conditions that routinely coexist with autism also have some symptoms that overlap with autism. Several barriers are linked to delay in diagnosis including lack of comfort in diagnosing autism by primary care providers, delayed referrals, the inability of parents to raise critical developmental concerns, confusion of autism with other conditions, and health system that is not responsive to the needs of the underserved communities. The etiology of autism spectrum disorder (ASD) is complex and still not completely understood; it involves genetics, neurobiology, and environmental exposures, leading to a diverse presentation of behaviors and symptoms. There is an imperative need to start therapeutic interventions as soon as a diagnosis of autism is suspected rather than wait for a definitive diagnosis. Early diagnosis is vital as timely intervention can lead to better outcomes for children and their families.

Seizure susceptibility to various convulsant stimuli in the BTBR mouse model of autism spectrum disorders

Background: Autism spectrum disorders (ASDs) are one of the most severe chronic childhood disorders in terms of prevalence, morbidity, and impact on society. Interestingly, several systematic reviews and meta-analyses documented a bidirectional link between epilepsy and ASD, supporting the hypothesis that both disorders may have common neurobiological pathways. According to this hypothesis, an imbalance of the excitatory/inhibitory (E/I) ratio in several brain regions may represent a causal mechanism underpinning the co-occurrence of these neurological diseases. Methods: To investigate this bidirectional link, we first tested the seizure susceptibility to chemoconvulsants acting on GABAergic and glutamatergic systems in the BTBR mice, in which an imbalance between E/I has been previously demonstrated. Subsequently, we performed the PTZ kindling protocol to study the impact of seizures on autistic-like behavior and other neurological deficits in BTBR mice. Results: We found that BTBR mice have an increased susceptibility to seizures induced by chemoconvulsants impairing GABA_A neurotransmission in comparison to C57BL/6J control mice, whereas no significant difference in seizure susceptibility was observed after administration of AMPA, NMDA, and Kainate. This data suggests that deficits in GABAergic neurotransmission can increase seizure susceptibility in this strain of mice. Interestingly, BTBR mice showed a longer latency in the development of kindling compared to control mice. Furthermore, PTZ-kindling did not influence autistic-like behavior in BTBR mice, whereas it was able to significantly increase anxiety and worsen cognitive performance in this strain of mice. Interestingly, C57BL/6J displayed reduced sociability after PTZ injections, supporting the hypothesis that a tight connection exists between ASD and epilepsy. Conclusion: BTBR mice can be considered a good model to study epilepsy and ASD contemporarily. However, future studies should shed light on the mechanisms underpinning the co-occurrence of these neurological disorders in the BTBR model.

Access to Care for US Children with Co-Occurrence of Autism Spectrum Disorder and Epilepsy

Epilepsy is a common comorbidity among children with autism spectrum disorder (ASD). There is a lack of understanding of the inequality in access to care for children with co-occurring ASD and epilepsy (ASD-EP). The purpose of this study is to examine key indicators for access to care and care coordination for children with ASD-EP in the US National Survey of Children’s Health (NSCH). Data were collected from the 2017–2019 NSCH. Our analytic sample included children with ASD without epilepsy (N = 2150), children with both ASD and epilepsy (N = 143), and children with epilepsy without ASD (N = 711). The dependent variables included important access to care indicators such as having usual sources of care, having adequate coverage, being frustrated in efforts to get service, and receiving care coordination. The independent variables included ASD-EP status, child demographics, and an intellectual disability (ID) diagnosis. Our results show that demographic characteristics such as sex, race, income level, and insurance type affect access to care. Inadequate access to healthcare was significantly higher among female children, children from low-income families, and children with ID. The access barriers among children with ASD-EP were more likely due to the interplay of multiple clinical and individual factors.

Tauopathy and Epilepsy Comorbidities and Underlying Mechanisms

Tau is a microtubule-associated protein known to bind and promote assembly of microtubules in neurons under physiological conditions. However, under pathological conditions, aggregation of hyperphosphorylated tau causes neuronal toxicity, neurodegeneration, and resulting tauopathies like Alzheimer's disease (AD). Clinically, patients with tauopathies present with either dementia, movement disorders, or a combination of both. The deposition of hyperphosphorylated tau in the brain is also associated with epilepsy and network hyperexcitability in a variety of neurological diseases. Furthermore, pharmacological and genetic targeting of tau-based mechanisms can have anti-seizure effects. Suppressing tau phosphorylation decreases seizure activity in acquired epilepsy models while reducing or ablating tau attenuates network hyperexcitability in both Alzheimer's and epilepsy models. However, it remains unclear whether tauopathy and epilepsy comorbidities are mediated by convergent mechanisms occurring upstream of epileptogenesis and tau aggregation, by feedforward mechanisms between the two, or simply by coincident processes. In this review, we investigate the relationship between tauopathies and seizure disorders, including temporal lobe epilepsy (TLE), post-traumatic epilepsy (PTE), autism spectrum disorder (ASD), Dravet syndrome, Nodding syndrome, Niemann-Pick type C disease (NPC), Lafora disease, focal cortical dysplasia, and tuberous sclerosis complex. We also explore potential mechanisms implicating the role of tau kinases and phosphatases as well as the mammalian target of rapamycin (mTOR) in the promotion of co-pathology. Understanding the role of these co-pathologies could lead to new insights and therapies targeting both epileptogenic mechanisms and cognitive decline.