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.

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.

Jenny Saffran, PhD – Slide of the Week

 Eye-gaze methods offer numerous advantages for studying cognitive processes in children with autism spectrum disorder (ASD), but data loss may threaten the validity and generalizability of results. Some eye-gaze systems may be more vulnerable to data loss than others, but to our knowledge, this issue has not been empirically investigated. In the current study, we asked whether automatic eye-tracking and manual gaze coding produce different rates of data loss or different results in a group of 51 toddlers with ASD.

Ari Rosenberg, PhD – Slide of the Week

Reconstructing three-dimensional (3D) scenes from two-dimensional (2D) retinal images is an ill-posed problem. Despite this, 3D perception of the world based on 2D retinal images is seemingly accurate and precise. The integration of distinct visual cues is essential for robust 3D perception in humans, but it is unclear whether this is true for non-human primates (NHPs).