Parsing evoked and induced gamma response differences in Autism: A visual evoked potential study.

OBJECTIVE: Electroencephalography (EEG) measures of visual evoked potentials (VEPs) provide a targeted approach for investigating neural circuit dynamics. This study separately analyses phase-locked (evoked) and non-phase-locked (induced) gamma responses within the VEP to comprehensively investigate circuit differences in autism. METHODS: We analyzed VEP data from 237 autistic and 114 typically developing (TD) children aged 6-11, collected through the Autism Biomarkers Consortium for Clinical Trials (ABC-CT). Evoked and induced gamma (30-90 Hz) responses were separately quantified using a wavelet-based time-frequency analysis, and group differences were evaluated using a permutation-based clustering procedure. RESULTS: Autistic children exhibited reduced evoked gamma power but increased induced gamma power compared to TD peers. Group differences in induced responses showed the most prominent effect size and remained statistically significant after excluding outliers. CONCLUSIONS: Our study corroborates recent research indicating diminished evoked gamma responses in children with autism. Additionally, we observed a pronounced increase in induced power. Building upon existing ABC-CT findings, these results highlight the potential to detect variations in gamma-related neural activity, despite the absence of significant group differences in time-domain VEP components. SIGNIFICANCE: The contrasting patterns of decreased evoked and increased induced gamma activity in autistic children suggest that a combination of different EEG metrics may provide a clearer characterization of autism-related circuitry than individual markers alone.

Resting state EEG in young children with Tuberous Sclerosis Complex.

Background: Tuberous Sclerosis Complex (TSC) manifests behaviorally with features of autism, epilepsy, and intellectual disability. Resting state electroencephalography (EEG) offers a window into neural oscillatory activity and may serve as an intermediate biomarker between gene expression and behavioral manifestations. Such a biomarker could be useful in clinical trials as an endpoint or predictor of treatment response. However, seizures and antiepileptic medications also affect resting neural oscillatory activity and could undermine the utility of resting state EEG features as biomarkers in neurodevelopmental disorders such as TSC. Methods: This paper compares resting state EEG features in a cross-sectional cohort of young children with TSC (n=49, ages 12-37 months) to 49 age- and sex-matched typically developing controls. Within children with TSC, associations were examined between resting state EEG features, seizure severity composite score, and use of GABA agonists. Results: Compared to matched typically developing controls, children with TSC showed significantly greater alpha and beta power in permutation cluster analyses iterated across a broad frequency range (2-50Hz). Children with TSC also showed significantly greater aperiodic offset after power spectra were parameterized using SpecParam into aperiodic and periodic components. Within children with TSC, greater seizure severity was significantly related to increased periodic peak beta power. Use of GABA agonists was also independently and significantly associated with increased periodic peak beta power; the interaction between seizure severity and GABA agonist use had no significant effect on peak beta power. Conclusions: The elevated peak beta power observed in children with TSC compared to matched typically developing controls may be driven by both seizures and GABA agonist use. It is recommended to collect seizure and mediation data alongside EEG data for clinical trials. These results highlight the challenge of using resting state EEG features as biomarkers in trials with neurodevelopmental disabilities when epilepsy and anti-epileptic medication are common.

Sleep EEG signatures in mouse models of 15q11.2-13.1 duplication (Dup15q) syndrome.

BACKGROUND: Sleep disturbances are a prevalent and complex comorbidity in neurodevelopmental disorders (NDDs). Dup15q syndrome (duplications of 15q11.2-13.1) is a genetic disorder highly penetrant for NDDs such as autism and intellectual disability and it is frequently accompanied by significant disruptions in sleep patterns. The 15q critical region harbors genes crucial for brain development, notably UBE3A and a cluster of gamma-aminobutyric acid type A receptor (GABAAR) genes. We previously described an electrophysiological biomarker of the syndrome, marked by heightened beta oscillations (12-30 Hz) in individuals with Dup15q syndrome, akin to electroencephalogram (EEG) alterations induced by allosteric modulation of GABAARs. Those with Dup15q syndrome exhibited increased beta oscillations during the awake resting state and during sleep, and they showed profoundly abnormal NREM sleep. This study aims to assess the translational validity of these EEG signatures and to delve into their neurobiological underpinnings by quantifying sleep physiology in chromosome-engineered mice with maternal (matDp/ + mice) or paternal (patDp/ + mice) inheritance of the full 15q11.2-13.1-equivalent duplication, and mice with duplication of just the UBE3A gene (Ube3a overexpression mice; Ube3a OE mice) and comparing the sleep metrics with their respective wildtype (WT) littermate controls. METHODS: We collected 48-h EEG/EMG recordings from 35 (23 male, 12 female) 12-24-week-old matDp/ + , patDp/ + , Ube3a OE mice, and their WT littermate controls. We quantified baseline sleep, sleep fragmentation, spectral power dynamics during sleep states, and recovery following sleep deprivation. Within each group, distinctions between Dup15q mutant mice and WT littermate controls were evaluated using analysis of variance (ANOVA) and student's t-test. The impact of genotype and time was discerned through repeated measures ANOVA, and significance was established at p < 0.05. RESULTS: Our study revealed that across brain states, matDp/ + mice mirrored the elevated beta oscillation phenotype observed in clinical EEGs from individuals with Dup15q syndrome. Time to sleep onset after light onset was significantly reduced in matDp/ + and Ube3a OE mice. However, NREM sleep between Dup15q mutant and WT littermate mice remained unaltered, suggesting a divergence from the clinical presentation in humans. Additionally, while increased beta oscillations persisted in matDp/ + mice after 6-h of sleep deprivation, recovery NREM sleep remained unaltered in all groups, thus suggesting that these mice exhibit resilience in the fundamental processes governing sleep-wake regulation. CONCLUSIONS: Quantification of mechanistic and translatable EEG biomarkers is essential for advancing our understanding of NDDs and their underlying pathophysiology. Our study of sleep physiology in the Dup15q mice underscores that the beta EEG biomarker has strong translational validity, thus opening the door for pre-clinical studies of putative drug targets, using the biomarker as a translational measure of drug-target engagement. The unaltered NREM sleep may be due to inherent differences in neurobiology between mice and humans. These nuanced distinctions highlight the complexity of sleep disruptions in Dup15q syndrome and emphasize the need for a comprehensive understanding that encompasses both shared and distinct features between murine models and clinical populations.

Modeling intra-individual inter-trial EEG response variability in autism.

Autism spectrum disorder (autism) is a prevalent neurodevelopmental condition characterized by early emerging impairments in social behavior and communication. EEG represents a powerful and non-invasive tool for examining functional brain differences in autism. Recent EEG evidence suggests that greater intra-individual trial-to-trial variability across EEG responses in stimulus-related tasks may characterize brain differences in autism. Traditional analysis of EEG data largely focuses on mean trends of the trial-averaged data, where trial-level analysis is rarely performed due to low neural signal to noise ratio. We propose to use nonlinear (shape-invariant) mixed effects (NLME) models to study intra-individual inter-trial EEG response variability using trial-level EEG data. By providing more precise metrics of response variability, this approach could enrich our understanding of neural disparities in autism and potentially aid the identification of objective markers. The proposed multilevel NLME models quantify variability in the signal's interpretable and widely recognized features (e.g., latency and amplitude) while also regularizing estimation based on noisy trial-level data. Even though NLME models have been studied for more than three decades, existing methods cannot scale up to large data sets. We propose computationally feasible estimation and inference methods via the use of a novel minorization-maximization (MM) algorithm. Extensive simulations are conducted to show the efficacy of the proposed procedures. Applications to data from a large national consortium find that children with autism have larger intra-individual inter-trial variability in P1 latency in a visual evoked potential (VEP) task, compared to their neurotypical peers.

Patterns of spontaneous neural activity associated with social communication abilities among infants and toddlers showing signs of autism.

Early disruptions to social communication development, including delays in joint attention and language, are among the earliest markers of autism spectrum disorder (autism, henceforth). Although social communication differences are a core feature of autism, there is marked heterogeneity in social communication-related development among infants and toddlers exhibiting autism symptoms. Neural markers of individual differences in joint attention and language abilities may provide important insight into heterogeneity in autism symptom expression during infancy and toddlerhood. This study examined patterns of spontaneous electroencephalography (EEG) activity associated with joint attention and language skills in 70 community-referred 12- to 23-month-olds with autism symptoms and elevated scores on an autism diagnostic instrument. Data-driven cluster-based permutation analyses revealed significant positive associations between relative alpha power (6-9 Hz) and concurrent response to joint attention skills, receptive language, and expressive language abilities. Exploratory analyses also revealed significant negative associations between relative alpha power and measures of core autism features (i.e., social communication difficulties and restricted/repetitive behaviors). These findings shed light on the neural mechanisms underlying typical and atypical social communication development in emerging autism and provide a foundation for future work examining neural predictors of social communication growth and markers of intervention response.

The relationship between gamma-band neural oscillations and language skills in youth with Autism Spectrum Disorder and their first-degree relatives.

BACKGROUND: Most children with Autism Spectrum Disorder (ASD) have co-occurring language impairments and some of these autism-specific language difficulties are also present in their non-autistic first-degree relatives. One of the possible neural mechanisms associated with variability in language functioning is alterations in cortical gamma-band oscillations, hypothesized to be related to neural excitation and inhibition balance. METHODS: We used a high-density 128-channel electroencephalography (EEG) to register brain response to speech stimuli in a large sex-balanced sample of participants: 125 youth with ASD, 121 typically developing (TD) youth, and 40 unaffected siblings (US) of youth with ASD. Language skills were assessed with Clinical Evaluation of Language Fundamentals. RESULTS: First, during speech processing, we identified significantly elevated gamma power in ASD participants compared to TD controls. Second, across all youth, higher gamma power was associated with lower language skills. Finally, the US group demonstrated an intermediate profile in both language and gamma power, with nonverbal IQ mediating the relationship between gamma power and language skills. LIMITATIONS: We only focused on one of the possible neural contributors to variability in language functioning. Also, the US group consisted of a smaller number of participants in comparison to the ASD or TD groups. Finally, due to the timing issue in EEG system we have provided only non-phase-locked analysis. CONCLUSIONS: Autistic youth showed elevated gamma power, suggesting higher excitation in the brain in response to speech stimuli and elevated gamma power was related to lower language skills. The US group showed an intermediate pattern of gamma activity, suggesting that the broader autism phenotype extends to neural profiles.

Salience network connectivity is altered in 6-week-old infants at heightened likelihood for developing autism.

Converging evidence implicates disrupted brain connectivity in autism spectrum disorder (ASD); however, the mechanisms linking altered connectivity early in development to the emergence of ASD symptomatology remain poorly understood. Here we examined whether atypicalities in the Salience Network - an early-emerging neural network involved in orienting attention to the most salient aspects of one's internal and external environment - may predict the development of ASD symptoms such as reduced social attention and atypical sensory processing. Six-week-old infants at high likelihood of developing ASD based on family history exhibited stronger Salience Network connectivity with sensorimotor regions; infants at typical likelihood of developing ASD demonstrated stronger Salience Network connectivity with prefrontal regions involved in social attention. Infants with higher connectivity with sensorimotor regions had lower connectivity with prefrontal regions, suggesting a direct tradeoff between attention to basic sensory versus socially-relevant information. Early alterations in Salience Network connectivity predicted subsequent ASD symptomatology, providing a plausible mechanistic account for the unfolding of atypical developmental trajectories associated with vulnerability to ASD.

Measurement of Developmental and Behavioral Concerns in Toddlers With Tuberous Sclerosis Complex.

BACKGROUND: The TAND (Tuberous Sclerosis Complex [TSC]-Associated Neuropsychiatric Disorders) Checklist was developed as a clinical screener for neurodevelopmental disorders in TSC. Most studies have described patterns in older children and adults. This study sought to better understand behavioral concerns as measured by the TAND Checklist in young children with TSC. METHODS: We examined patterns of caregiver responses to the TAND Checklist in 90 toddlers with TSC (12 to 23 months n = 60; 24 to 36 months n = 30) through data collected during baseline visits across two TSC early intervention studies. RESULTS: Over 90% of caregivers reported at least one behavioral concern related to TAND. The number of concerns increased with age. Delayed language was the most frequently reported concern across ages (12 to 23 months: 58.3%, 24 to 36 months: 86.7%). Questions related to behavioral concerns were largely relevant in this age range, but questions in other areas, such as neuropsychological or academic function, were not. CONCLUSIONS: TAND symptoms are very common in toddlers with TSC, and these symptoms may increase with age. The TAND Checklist is a useful tool for identifying behavioral concerns efficiently, but several items and sections are not suited to younger children. Results support the development of an abbreviated form of the TAND Checklist for toddlers.

Autism and Epilepsy.

Epilepsy is one of the most common comorbidities in individuals with autism spectrum disorders (ASDs). Risk factors include the presence of developmental delay/intellectual disability, female sex, age, and an underlying genetic condition. Due to higher prevalence of epilepsy in ASD, it is important to have a high index of suspicion for seizures and refer to a neurologist if there are concerns. Genetic testing is recommended for all children with ASD but it becomes more high yield in children with epilepsy and ASD.

Frontal EEG alpha asymmetry in youth with autism: Sex differences and social-emotional correlates.

In youth broadly, EEG frontal alpha asymmetry (FAA) associates with affective style and vulnerability to psychopathology, with relatively stronger right activity predicting risk for internalizing and externalizing behaviors. In autistic youth, FAA has been related to ASD diagnostic features and to internalizing symptoms. Among our large, rigorously characterized, sex-balanced participant group, we attempted to replicate findings suggestive of altered FAA in youth with an ASD diagnosis, examining group differences and impact of sex assigned at birth. Second, we examined relations between FAA and behavioral variables (ASD features, internalizing, and externalizing) within autistic youth, examining effects by sex. Third, we explored whether the relation between FAA, autism features, and mental health was informed by maternal depression history. In our sample, FAA did not differ by diagnosis, age, or sex. However, youth with ASD had lower total frontal alpha power than youth without ASD. For autistic females, FAA and bilateral frontal alpha power correlated with social communication features, but not with internalizing or externalizing symptoms. For autistic males, EEG markers correlated with social communication features, and with externalizing behaviors. Exploratory analyses by sex revealed further associations between youth FAA, behavioral indices, and maternal depression history. In summary, findings suggest that individual differences in FAA may correspond to social-emotional and mental health behaviors, with different patterns of association for females and males with ASD. Longitudinal consideration of individual differences across levels of analysis (e.g., biomarkers, family factors, and environmental influences) will be essential to parsing out models of risk and resilience among autistic youth.

The Selective Social Attention task in children with autism spectrum disorder: Results from the Autism Biomarkers Consortium for Clinical Trials (ABC-CT) feasibility study.

The Selective Social Attention (SSA) task is a brief eye-tracking task involving experimental conditions varying along socio-communicative axes. Traditionally the SSA has been used to probe socially-specific attentional patterns in infants and toddlers who develop autism spectrum disorder (ASD). This current work extends these findings to preschool and school-age children. Children 4- to 12-years-old with ASD (N = 23) and a typically-developing comparison group (TD; N = 25) completed the SSA task as well as standardized clinical assessments. Linear mixed models examined group and condition effects on two outcome variables: percent of time spent looking at the scene relative to scene presentation time (%Valid), and percent of time looking at the face relative to time spent looking at the scene (%Face). Age and IQ were included as covariates. Outcome variables' relationships to clinical data were assessed via correlation analysis. The ASD group, compared to the TD group, looked less at the scene and focused less on the actress' face during the most socially-engaging experimental conditions. Additionally, within the ASD group, %Face negatively correlated with SRS total T-scores with a particularly strong negative correlation with the Autistic Mannerism subscale T-score. These results highlight the extensibility of the SSA to older children with ASD, including replication of between-group differences previously seen in infants and toddlers, as well as its ability to capture meaningful clinical variation within the autism spectrum across a wide developmental span inclusive of preschool and school-aged children. The properties suggest that the SSA may have broad potential as a biomarker for ASD.

Recognizing and Responding to the Needs of Future Child and Adult Neurology Care Through the Evolution of Residency Training.

Recent insights into the frequency of occurrence and the genetic and mechanistic basis of nervous system disease have demonstrated that neurologic disorders occur as a spectrum across all ages. To meet future needs of patients with neurologic disease of all ages and prepare for increasing implementaton of precision therapies, greater integration of child and adult neurology residency training is needed. ANN NEUROL 2023;94:1005-1007.

Development of webcam-collected and artificial-intelligence-derived social and cognitive performance measures for neurodevelopmental genetic syndromes.

This study focused on the development and initial psychometric evaluation of a set of online, webcam-collected, and artificial intelligence-derived patient performance measures for neurodevelopmental genetic syndromes (NDGS). Initial testing and qualitative input was used to develop four stimulus paradigms capturing social and cognitive processes, including social attention, receptive vocabulary, processing speed, and single-word reading. The paradigms were administered to a sample of 375 participants, including 163 with NDGS, 56 with idiopathic neurodevelopmental disability (NDD), and 156 neurotypical controls. Twelve measures were created from the four stimulus paradigms. Valid completion rates varied from 87 to 100% across measures, with lower but adequate completion rates in participants with intellectual disability. Adequate to excellent internal consistency reliability (α = 0.67 to 0.95) was observed across measures. Test-retest reproducibility at 1-month follow-up and stability at 4-month follow-up was fair to good (r = 0.40-0.73) for 8 of the 12 measures. All gaze-based measures showed evidence of convergent and discriminant validity with parent-report measures of other cognitive and behavioral constructs. Comparisons across NDGS groups revealed distinct patterns of social and cognitive functioning, including people with PTEN mutations showing a less impaired overall pattern and people with SYNGAP1 mutations showing more attentional, processing speed, and social processing difficulties relative to people with NFIX mutations. Webcam-collected performance measures appear to be a reliable and potentially useful method for objective characterization and monitoring of social and cognitive processes in NDGS and idiopathic NDD. Additional validation work, including more detailed convergent and discriminant validity analyses and examination of sensitivity to change, is needed to replicate and extend these observations.

Enabling endpoint development for interventional clinical trials in individuals with Angelman syndrome: a prospective, longitudinal, observational clinical study (FREESIAS).

BACKGROUND: Angelman syndrome (AS) is a rare neurodevelopmental disorder characterized by the absence of a functional UBE3A gene, which causes developmental, behavioral, and medical challenges. While currently untreatable, comprehensive data could help identify appropriate endpoints assessing meaningful improvements in clinical trials. Herein are reported the results from the FREESIAS study assessing the feasibility and utility of in-clinic and at-home measures of key AS symptoms. METHODS: Fifty-five individuals with AS (aged < 5 years: n = 16, 5-12 years: n = 27, ≥ 18 years: n = 12; deletion genotype: n = 40, nondeletion genotype: n = 15) and 20 typically developing children (aged 1-12 years) were enrolled across six USA sites. Several clinical outcome assessments and digital health technologies were tested, together with overnight 19-lead electroencephalography (EEG) and additional polysomnography (PSG) sensors. Participants were assessed at baseline (Clinic Visit 1), 12 months later (Clinic Visit 2), and during intermittent home visits. RESULTS: The participants achieved high completion rates for the clinical outcome assessments (adherence: 89-100% [Clinic Visit 1]; 76-91% [Clinic Visit 2]) and varied feasibility of and adherence to digital health technologies. The coronavirus disease 2019 (COVID-19) pandemic impacted participants' uptake of and/or adherence to some measures. It also potentially impacted the at-home PSG/EEG recordings, which were otherwise feasible. Participants achieved Bayley-III results comparable to the available natural history data, showing similar scores between individuals aged ≥ 18 and 5-12 years. Also, participants without a deletion generally scored higher on most clinical outcome assessments than participants with a deletion. Furthermore, the observed AS EEG phenotype of excess delta-band power was consistent with prior reports. CONCLUSIONS: Although feasible clinical outcome assessments and digital health technologies are reported herein, further improved assessments of meaningful AS change are needed. Despite the COVID-19 pandemic, remote assessments facilitated high adherence levels and the results suggested that at-home PSG/EEG might be a feasible alternative to the in-clinic EEG assessments. Taken altogether, the combination of in-clinic/at-home clinical outcome assessments, digital health technologies, and PSG/EEG may improve protocol adherence, reduce patient burden, and optimize study outcomes in AS and other rare disease populations.

Development of informant-report neurobehavioral survey scales for PTEN hamartoma tumor syndrome and related neurodevelopmental genetic syndromes.

There are few well-validated measures that are appropriate for assessing the full range of neurobehavioral presentations in PTEN hamartoma tumor syndrome (PHTS) and other neurodevelopmental genetic syndromes (NDGS). As potential therapeutics are developed, having reliable, valid, free, and easily accessible measures to track a range of neurobehavioral domains will be crucial for future clinical trials. This study focused on the development and initial psychometric evaluation of a set of freely available informant-report survey scales for PHTS-the Neurobehavioral Evaluation Tool (NET). Concept elicitation, quantitative ratings, and cognitive interviewing processes were conducted with stakeholders and clinician-scientist experts, used to identify the most important neurobehavioral domains for this population, and to ensure items were appropriate for the full range of individuals with PHTS. Results of this process identified a PHTS neurobehavioral impact model with 11 domains. The final NET scales assessing these domains were administered to a sample of 384 participants (median completion time = 20.6 min), including 32 people with PHTS, 141 with other NDGS, 47 with idiopathic neurodevelopmental disorder (NDD), and 164 neurotypical controls. Initial psychometric results for the total scores of each scale indicated very good model (ω = 0.83-0.99) and internal consistency reliability (α = 0.82-0.98) as well as excellent test-retest reproducibility at 1-month follow-up (r = 0.78-0.98) and stability at 4-month follow-up (r = 0.76-0.96). Conditional reliability estimates indicated very strong measurement precision in key score ranges for assessing PHTS and other people with NDGS and/or idiopathic NDD. Comparisons across domains between PHTS and the other groups revealed specific patterns of symptoms and functioning, including lower levels of challenging behavior and more developed daily living and executive functioning skills relative to other NDGS. The NET appears to be a reliable and potentially useful tool for clinical characterization and monitoring of neurobehavioral symptoms in PHTS and may also have utility in the assessment of other NDGS and idiopathic NDD. Additional validation work, including convergent and discriminant validity analyses, are needed to replicate and extend these observations.

Associations between thalamocortical functional connectivity and sensory over-responsivity in infants at high likelihood for ASD.

Despite growing evidence implicating thalamic functional connectivity atypicalities in autism spectrum disorder (ASD), it remains unclear how such alterations emerge early in human development. Because the thalamus plays a critical role in sensory processing and neocortical organization early in life, its connectivity with other cortical regions could be key for studying the early onset of core ASD symptoms. Here, we investigated emerging thalamocortical functional connectivity in infants at high (HL) and typical (TL) familial likelihood for ASD in early and late infancy. We report significant thalamo-limbic hyperconnectivity in 1.5-month-old HL infants, and thalamo-cortical hypoconnectivity in prefrontal and motor regions in 9-month-old HL infants. Importantly, early sensory over-responsivity (SOR) symptoms in HL infants predicted a direct trade-off in thalamic connectivity whereby stronger thalamic connectivity with primary sensory regions and basal ganglia was inversely related to connectivity with higher order cortices. This trade-off suggests that ASD may be characterized by early differences in thalamic gating. The patterns reported here could directly underlie atypical sensory processing and attention to social vs. nonsocial stimuli observed in ASD. These findings lend support to a theoretical framework of ASD whereby early disruptions in sensorimotor processing and attentional biases early in life may cascade into core ASD symptomatology.

Efficacy, safety, and tolerability of soticlestat as adjunctive therapy for the treatment of seizures in patients with Dup15q syndrome or CDKL5 deficiency disorder in an open-label signal-finding phase II study (ARCADE).

OBJECTIVE: Chromosome 15q duplication (Dup15q) syndrome and cyclin­dependent kinase-like 5 deficiency disorder (CDD) are rare neurodevelopmental disorders associated with epileptic encephalopathies, with a lack of specifically approved treatment options. ARCADE assessed the efficacy and safety of adjunctive soticlestat (TAK-935) for the treatment of seizures in patients with Dup15q syndrome or CDD (NCT03694275). METHODS: ARCADE was a phase II, open-label, pilot study of soticlestat (≤300 mg/day twice daily, weight-adjusted) in pediatric and adult patients 2-55 years of age with Dup15q syndrome or CDD who experienced ≥3 motor seizures per month in the 3 months before screening and at baseline. The 20-week treatment period consisted of a dose-optimization period and a 12-week maintenance period. Efficacy endpoints included the change from baseline in motor seizure frequency during the maintenance period and the proportion of treatment responders. Safety endpoints included the incidence of treatment-emergent adverse effects (TEAEs). RESULTS: The modified-intent-to-treat population included 20 participants who received ≥1 dose of soticlestat and had ≥1 efficacy assessment (Dup15q syndrome, n = 8; CDD, n = 12). Soticlestat administration during the maintenance period was associated with a median change from baseline in motor seizure frequency of +11.7% in the Dup15q syndrome group and -23.6% in the CDD group. Reductions in all seizure frequency of -23.4% and -30.5% were also observed during the maintenance period in the Dup15q syndrome group and the CDD group, respectively. Most TEAEs were of mild or moderate severity. Serious TEAEs were reported by three patients (15.0%); none were considered drug related. The most common TEAEs were constipation, rash, and seizure. No deaths were reported. CONCLUSIONS: Adjunctive soticlestat treatment was associated with a decrease in motor seizure frequency from baseline in patients with CDD and a decrease in all seizure frequency in both patient groups. Soticlestat treatment was associated with an increase in motor seizure frequency in patients with Dup15q syndrome.

A functional model for studying common trends across trial time in eye tracking experiments.

Eye tracking (ET) experiments commonly record the continuous trajectory of a subject's gaze on a two-dimensional screen throughout repeated presentations of stimuli (referred to as trials). Even though the continuous path of gaze is recorded during each trial, commonly derived outcomes for analysis collapse the data into simple summaries, such as looking times in regions of interest, latency to looking at stimuli, number of stimuli viewed, number of fixations or fixation length. In order to retain information in trial time, we utilize functional data analysis (FDA) for the first time in literature in the analysis of ET data. More specifically, novel functional outcomes for ET data, referred to as viewing profiles, are introduced that capture the common gazing trends across trial time which are lost in traditional data summaries. Mean and variation of the proposed functional outcomes across subjects are then modeled using functional principal components analysis. Applications to data from a visual exploration paradigm conducted by the Autism Biomarkers Consortium for Clinical Trials showcase the novel insights gained from the proposed FDA approach, including significant group differences between children diagnosed with autism and their typically developing peers in their consistency of looking at faces early on in trial time.