Neurocognitive mechanisms of co‐occurring math difficulties in dyslexia: Differences in executive function and visuospatial processing

Children with dyslexia frequently also struggle with math. However, studies of reading disability (RD) rarely assess math skill, and the neurocognitive mechanisms underlying co-occurring reading and math disability (RD+MD) are not clear. The current study aimed to identify behavioral and neurocognitive factors associated with co-occurring MD among 86 children with RD. Within this sample, 43% had co-occurring RD+MD and 22% demonstrated a possible vulnerability in math, while 35% had no math difficulties (RD-Only). We investigated whether RD-Only and RD+MD students differed behaviorally in their phonological awareness, reading skills, or executive functions, as well as in the brain mechanisms underlying word reading and visuospatial working memory using functional magnetic resonance imaging (fMRI). The RD+MD group did not differ from RD-Only on behavioral or brain measures of phonological awareness related to speech or print. However, the RD+MD group demonstrated significantly worse working memory and processing speed performance than the RD-Only group. The RD+MD group also exhibited reduced brain activations for visuospatial working memory relative to RD-Only. Exploratory brain-behavior correlations along a broad spectrum of math ability revealed that stronger math skills were associated with greater activation in bilateral visual cortex. These converging neuro-behavioral findings suggest that poor executive functions in general, including differences in visuospatial working memory, are specifically associated with co-occurring MD in the context of RD

The past, present, and future of the Brain Imaging Data Structure (BIDS)

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS

A large-scale investigation of white matter microstructural associations with reading ability

Reading involves the functioning of a widely distributed brain network, and white matter tracts are responsible for transmitting information between constituent network nodes. Several studies have analyzed fiber bundle microstructural properties to shed insights into the neural basis of reading abilities and disabilities. Findings have been inconsistent, potentially due to small sample sizes and varying methodology. To address this, we analyzed a large data set of 686 children ages 5-18 using state-of-the-art neuroimaging acquisitions and processing techniques. We searched for associations between fractional anisotropy (FA) and single-word and single-nonword reading skills in children with diverse reading abilities across multiple tracts previously thought to contribute to reading. We also looked for group differences in tract FA between typically reading children and children with reading disabilities. FA of the white matter increased with age across all participants. There were no significant correlations between overall reading abilities and tract FAs across all children, and no significant group differences in tract FA between children with and without reading disabilities. There were associations between FA and nonword reading ability in older children (ages 9 and above). Higher FA in the right superior longitudinal fasciculus (SLF) and left inferior cerebellar peduncle (ICP) correlated with better nonword reading skills. These results suggest that letter-sound correspondence skills, as measured by nonword reading, are associated with greater white matter coherence among older children in these two tracts, as indexed by higher FA

A practical guide for combining functional regions of interest and white matter bundles

Diffusion-weighted imaging (DWI) is the primary method to investigate macro- and microstructure of neural white matter in vivo. DWI can be used to identify and characterize individual-specific white matter bundles, enabling precise analyses on hypothesis-driven connections in the brain and bridging the relationships between brain structure, function, and behavior. However, cortical endpoints of bundles may span larger areas than what a researcher is interested in, challenging presumptions that bundles are specifically tied to certain brain functions. Functional MRI (fMRI) can be integrated to further refine bundles such that they are restricted to functionally-defined cortical regions. Analyzing properties of these Functional Sub-Bundles (FSuB) increases precision and interpretability of results when studying neural connections supporting specific tasks. Several parameters of DWI and fMRI analyses, ranging from data acquisition to processing, can impact the efficacy of integrating functional and diffusion MRI. Here, we discuss the applications of the FSuB approach, suggest best practices for acquiring and processing neuroimaging data towards this end, and introduce the FSuB-Extractor, a flexible open-source software for creating FSuBs. We demonstrate our processing code and the FSuB-Extractor on an openly-available dataset, the Natural Scenes Dataset

Neurocognitive risk factors for co-occurring math difficulties in dyslexia: Differences in executive function and visuospatial processing

What makes math difficulties so common in children with dyslexia? The current study aimed to identify behavioral and neurocognitive factors associated with co-occurring reading disability (RD) and math disability (MD). We tested reading, math, and cognitive skills in a sample of 86 children in 3rd–7th grade (ages 9-13) with RD. Within this sample, 35% of children had RD only with no weakness in math, 43% had co-occurring RD+MD, and over 20% demonstrated a possible vulnerability in math. We investigated whether RD-Only and RD+MD students differed behaviorally in their phonological awareness, reading skills, or executive function, as well as in the brain mechanisms underlying word reading and visuospatial working memory using fMRI. We found that the additional difficulty with math in children with RD was unrelated to differences in behavioral or brain measures of phonological awareness related to speech or print. However, the RD+MD group performed significantly worse than the RD-Only group on multiple measures of executive function, including working memory and processing speed. The RD+MD group also exhibited reduced brain activations for visuospatial working memory relative to the RD-Only group. Continuous analyses along a spectrum of math ability revealed that greater math difficulties were associated with reduced activation in the visual cortex. These converging neuro-behavioral findings suggest that poor executive function in general, and differences in visuospatial working memory in particular, are associated with co-occurring MD among children with RD

Differential excitatory vs inhibitory SCN expression at single cell level regulates brain sodium channel function in neurodevelopmental disorders

The four voltage-gated sodium channels SCN1/2/3/8A have been associated with heterogeneous types of developmental disorders, each presenting with disease specific temporal and cell type specific gene expression. Using single-cell RNA sequencing transcriptomic data from humans and mice, we observe that SCNIA is predominantly expressed in inhibitory neurons. In contrast, SCN2/3/8A are profoundly expressed in excitatory neurons with SCN2/3A starting prenatally, followed by SCN1/8A neonatally. In contrast to previous observations from low resolution RNA screens, we observe that all four genes are expressed in both excitatory and inhibitory neurons, however, exhibit differential expression strength. These findings provide molecular evidence, at single-cell resolution, to support the hypothesis that the excitatory/inhibitory (E/I) neuronal expression ratios of sodium channels are important regulatory mechanisms underlying brain homeostasis and neurological diseases. Modulating the Ell expression balance within cell types of sodium channels could serve as a potential strategy to develop targeted treatment for Nay-associated neuronal developmental disorders. (C) 2019 Published by Elsevier Ltd on behalf of European Paediatric Neurology Society

ModelArray: An R package for statistical analysis of fixel-wise data

ABSTRACT: Diffusion MRI is the dominant non-invasive imaging method used to characterize white matter organization in health and disease. Increasingly, fiber-specific properties within a voxel are analyzed using fixels. While tools for conducting statistical analyses of fixel-wise data exist, currently available tools support only a limited number of statistical models. Here we introduce ModelArray, an R package for mass-univariate statistical analysis of fixel-wise data. At present, ModelArray supports linear models as well as generalized additive models (GAMs), which are particularly useful for studying nonlinear effects in lifespan data. In addition, ModelArray also aims for scalable analysis. With only several lines of code, even large fixel-wise datasets can be analyzed using a standard personal computer. Detailed memory profiling revealed that ModelArray required only limited memory even for large datasets. As an example, we applied ModelArray to fixel-wise data derived from diffusion images acquired as part of the Philadelphia Neurodevelopmental Cohort (n = 938). ModelArray revealed anticipated nonlinear developmental effects in white matter. Moving forward, ModelArray is supported by an open-source software development model that can incorporate additional statistical models and other imaging data types. Taken together, ModelArray provides a flexible and efficient platform for statistical analysis of fixel-wise data