Genomics-informed neuropsychiatric care for neurodevelopmental disorders: Results from a multidisciplinary clinic.

Purpose: Patients with neurodevelopmental disorders (NDDs) have high rates of neuropsychiatric comorbidities. Genomic medicine may help guide care because pathogenic variants are identified in up to 50% of patients with NDDs. We evaluate the impact of a genomics-informed, multidisciplinary, neuropsychiatric specialty clinic on the diagnosis and management of patients with NDDs.

Functional Mixed Membership Models.

Mixed membership models, or partial membership models, are a flexible unsupervised learning method that allows each observation to belong to multiple clusters. In this paper, we propose a Bayesian mixed membership model for functional data. By using the multivariate Karhunen-Loève theorem, we are able to derive a scalable representation of Gaussian processes that maintains data-driven learning of the covariance structure.

Flexible Regularized Estimation in High-Dimensional Mixed Membership Models.

Mixed membership models are an extension of finite mixture models, where each observation can partially belong to more than one mixture component. A probabilistic framework for mixed membership models of high-dimensional continuous data is proposed with a focus on scalability and interpretability. The novel probabilistic representation of mixed membership is based on convex combinations of dependent multivariate Gaussian random vectors.

Central Posterior Envelopes for Bayesian Functional Principal Component Analysis.

Bayesian methods provide direct inference in functional data analysis applications without reliance on bootstrap techniques. A major tool in functional data applications is the functional principal component analysis which decomposes the data around a common mean function and identifies leading directions of variation. Bayesian functional principal components analysis (BFPCA) provides uncertainty quantification on the estimated functional model components via the posterior samples obtained.

Concomitant medication use in children with autism spectrum disorder: Data from the Autism Biomarkers Consortium for Clinical Trials.

Children with autism spectrum disorder are prescribed a variety of medications that affect the central nervous system (psychotropic medications) to address behavior and mood. In clinical trials, individuals taking concomitant psychotropic medications often are excluded to maintain homogeneity of the sample and prevent contamination of biomarkers or clinical endpoints. However, this choice may significantly diminish the clinical representativeness of the sample.

Covariate-adjusted hybrid principal components analysis for region-referenced functional EEG data.

Electroencephalography (EEG) studies produce region-referenced functional data via EEG signals recorded across scalp electrodes. The high-dimensional data can be used to contrast neurodevelopmental trajectories between diagnostic groups, for example between typically developing (TD) children and children with autism spectrum disorder (ASD). Valid inference requires characterization of the complex EEG dependency structure as well as covariate-dependent heteroscedasticity, such as changes in variation over developmental age.

Multilevel hybrid principal components analysis for region-referenced functional electroencephalography data.

Electroencephalography experiments produce region-referenced functional data representing brain signals in the time or the frequency domain collected across the scalp. The data typically also have a multilevel structure with high-dimensional observations collected across multiple experimental conditions or visits. Common analysis approaches reduce the data complexity by collapsing the functional and regional dimensions, where event-related potential (ERP) features or band power are targeted in a pre-specified scalp region.

The diagnostic journey of genetically defined neurodevelopmental disorders.

Background: The development of advanced genetic technologies has resulted in rapid identification of genetic etiologies of neurodevelopmental disorders (NDDs) and has transformed the classification and diagnosis of various NDDs. However, diagnostic genetics has far outpaced our ability to provide timely medical counseling, guidance, and care for patients with genetically defined NDDs. These patients and their caregivers present with an unmet need for care coordination across multiple domains including medical, developmental, and psychiatric care and for educational resources and guidance from care professionals.

Measurement of Sleep Behaviors in Chromosome 15q11.2-13.1 Duplication (Dup15q Syndrome).

Duplication of chromosome 15q11.2-q13.1 (dup15q syndrome) results in hypotonia, intellectual disability (ID), and autism symptomatology.

REGION-REFERENCED SPECTRAL POWER DYNAMICS OF EEG SIGNALS: A HIERARCHICAL MODELING APPROACH.

Functional brain imaging through electroencephalography (EEG) relies upon the analysis and interpretation of high-dimensional, spatially organized time series. We propose to represent time-localized frequency domain characterizations of EEG data as region-referenced functional data. This representation is coupled with a hierarchical regression modeling approach to multivariate functional observations.

Comprehensive Assessment of Individuals With Significant Levels of Intellectual Disability: Challenges, Strategies, and Future Directions.

The variety and extent of impairments in individuals with severe-profound levels of intellectual disability (ID) impact their ability to complete valid behavioral assessments. Although standardized assessment is crucial for objectively evaluating patients, many individuals with severe-profound levels of ID perform at the floor of most assessments designed for their chronological age. Additionally, the presence of language and motor impairments may influence the individual's ability to perform a task, even when that task is meant to measure an unrelated construct leading to an underestimation of their true ability.

The Neurodevelopmental and Motor Phenotype of SCA21 (ATX-TMEM240).

Spinocerebellar ataxia type 21 (SCA21/ATX-TMEM240) is a rare form of cerebellar ataxia that commonly presents with motor, cognitive, and behavioral impairments. Although these features have been identified as part of the clinical manifestations of SCA21, the neurodevelopmental disorders associated with SCA21 have not been well studied or described. Here we present extensive phenotypic data for 3 subjects from an SCA21 family in the United States.

Principle ERP reduction and analysis: Estimating and using principle ERP waveforms underlying ERPs across tasks, subjects and electrodes.

Event-related potentials (ERP) waveforms are the summation of many overlapping signals. Changes in the peak or mean amplitude of a waveform over a given time period, therefore, cannot reliably be attributed to a particular ERP component of ex ante interest, as is the standard approach to ERP analysis. Though this problem is widely recognized, it is not well addressed in practice.

Correction to: Mechanisms underlying the EEG biomarker in Dup15q syndrome.

[This corrects the article DOI: 10.1186/s13229-019-0280-6.].

Covariate-adjusted region-referenced generalized functional linear model for EEG data.

Electroencephalography (EEG) studies produce region-referenced functional data in the form of EEG signals recorded across electrodes on the scalp. It is of clinical interest to relate the highly structured EEG data to scalar outcomes such as diagnostic status. In our motivating study, resting-state EEG is collected on both typically developing (TD) children and children with autism spectrum disorder (ASD) aged 2 to 12 years old.

Behavioral characterization of dup15q syndrome: Toward meaningful endpoints for clinical trials.

Duplication of 15q11.2-q13.1 (dup15q syndrome) is one of the most common copy number variations associated with autism spectrum disorders (ASD) and intellectual disability (ID).

Mechanisms underlying the EEG biomarker in Dup15q syndrome.

Background: Duplications of 15q11.2-q13.1 (Dup15q syndrome), including the paternally imprinted gene and three nonimprinted gamma-aminobutyric acid type-A (GABA) receptor genes, are highly penetrant for neurodevelopmental disorders such as autism spectrum disorder (ASD).

EEG Data Collection in Children with ASD: The Role of State in Data Quality and Spectral Power.

Background: Electroencephalography can elucidate neurobiological mechanisms underlying heterogeneity in ASD. Studying the full range of children with ASD introduces methodological challenges stemming from participants' difficulties tolerating the data collection process, leading to diminished EEGdataretentionandincreasedvariabilityin participant 'state' during the recording. Quantifying state will improve data collection methods and aide in interpreting results.

ERP evidence of semantic processing in children with ASD.

25% of children with autism spectrum disorder (ASD) remain minimally verbal (MV), despite intervention. Electroencephalography can reveal neural mechanisms underlying language impairment in ASD, potentially improving our ability to predict language outcomes and target interventions. Verbal (V) and MV children with ASD, along with an age-matched typically developing (TD) group participated in a semantic congruence ERP paradigm, during which pictures were displayed followed by the expected or unexpected word.

Inferring Brain Signals Synchronicity from a Sample of EEG Readings.

Inferring patterns of synchronous brain activity from a heterogeneous sample of electroencephalograms (EEG) is scientifically and methodologically challenging. While it is intuitively and statistically appealing to rely on readings from more than one individual in order to highlight recurrent patterns of brain activation, pooling information across subjects presents non-trivial methodological problems. We discuss some of the scientific issues associated with the understanding of synchronized neuronal activity and propose a methodological framework for statistical inference from a sample of EEG readings.

Hybrid principal components analysis for region-referenced longitudinal functional EEG data.

Electroencephalography (EEG) data possess a complex structure that includes regional, functional, and longitudinal dimensions. Our motivating example is a word segmentation paradigm in which typically developing (TD) children, and children with autism spectrum disorder (ASD) were exposed to a continuous speech stream. For each subject, continuous EEG signals recorded at each electrode were divided into one-second segments and projected into the frequency domain via fast Fourier transform.