Although epilepsy commonly presents with autism in children, it is currently unknown whether established estimates represent the prevalence and incidence of epilepsy in autistic adults. Our objective was to use population-level Medicaid data to determine prevalence, incidence, and antiepileptic drug use associated with epilepsy in a unique population of autistic adults aged 21+ with (N=2,738) and without (N=4,775) intellectual disability and to compare results to adults with intellectual disability alone (N=18,429).
Slide of the Week
Barbara Bendlin, PhD – Slide of the Week
In Alzheimer’s disease (AD), neurodegenerative processes are ongoing for years prior to the time that cortical atrophy can be reliably detected using conventional neuroimaging techniques. Recent advances in diffusion-weighted imaging have provided new techniques to study neural microstructure, which may provide additional information regarding neurodegeneration.
Karla Ausderau, PhD – Slide of the Week
Examine healthcare usage, pharmacy prescriptions and healthcare cost among people with Intellectual Disability in Wisconsin who participate in Special Olympics compared to people with Intellectual Disability who do not participate in Special Olympics. In addition, a sub-analysis was completed to compare Special Olympics athletes who participated in the Healthy Athlete program to those who had not.
UCEDD – Slide of the Week
Title: Pre- to post-training change in childcare provider belief that developmental monitoring is important and ability to identify appropriate referrals to make when there is a developmental concern Legend: Training in developmental monitoring significantly increases …
Andrew Alexander, PhD – Slide of the Week
Demonstration of the ability of MPnRAGE to correct for severe motion artifacts in a 7 year old girl. Retrospective motion correction greatly reduced motion-induced blurring in both structural T1-weighted images and quantitative T1 maps. The correction greatly improves the reliability of brain imaging measurements in children. The plots indicate the estimated amount of head motions that were corrected.
Donna Werling, PhD – Slide of the Week
Gene expression levels vary across developmental stage, cell type, and region in the brain. Genomic variants also contribute to the variation in expression, and some neuropsychiatric disorder loci may exert their effects through this mechanism. To investigate these relationships, we present BrainVar, a unique resource of paired whole-genome and bulk tissue RNA sequencing from the dorsolateral prefrontal cortex of 176 individuals across prenatal and post- natal development.
Xinyu Zhao, PhD – Slide of the Week
Title: Identification of FMR1-regulated molecular networks in human neurodevelopment Legend: Generation of FMR1-FLAG hPSCs using one-step seamless genome editing using CRISPR-Cas9, Neural differentiation of hPSCs into forebrain dorsal NPCs (dNPC) and ventral MGE-like NPCs (vNPC), …
Daifeng Wang, PhD – Slide of the Week
The molecular mechanisms and functions in complex biological systems currently remain elusive. Recent high-throughput techniques, such as next-generation sequencing, have generated a wide variety of multiomics datasets that enable the identification of biological functions and mechanisms via multiple facets. However, integrating these large-scale multiomics data and discovering functional insights are, nevertheless, challenging tasks.
Houri K. Vorperian, PhD – Slide of the Week
We present a unified heat kernel smoothing framework for modeling 3D anatomical surface data extracted from medical images. Due to image acquisition and preprocessing noises, it is expected the medical imaging data is noisy. The surface data of the anatomical structures is regressed using the weighted linear combination of Laplace-Beltrami (LB) eigenfunctions to smooth out noisy data and perform statistical analysis.
Brittany Travers, PhD – Slide of the Week
Motor challenges are commonly reported in autism spectrum disorder (ASD). Yet, there is substantial heterogeneity in motor ability within ASD, and it is unknown what behavioral characteristics best explain individual differences in motor ability in ASD and related conditions.