Biology subjects

Alexander, A. L.

Publications and source records attributed to Alexander, A. L..

6 recordsLinked to original sources

bioRxiv2025

Diffusion MRI Processing in the HEALthy Brain and Child Development Study: Innovations and Applications

The landmark ongoing HEALthy Brain and Cognitive Development (HBCD) study will longitudinally chart brain development in a large sample (projected n=7,200) of infants through age 10 years with multimodal neuroimaging that includes an advanced diffusion MRI (dMRI) acquisition. Here, we detail advances in dMRI image processing developed for HBCD, incorporated into the widely used QSIPrep pipeline. Major changes to preprocessing include improvements in infant brain extraction, distortion correction, and normalization to infant-specific templates. Additionally, we describe a new software package - QSIRecon - that yields rich derived data including diverse maps of tissue microstructure as well as person-specific white matter bundles. Using dMRI data from a subset of the HBCD 1.0 release where age information was available (n=529 sessions across two time points), we observe critical improvements in data quality with preprocessing and see expected developmental patterns. Moving forward, the publicly-available data from HBCD will rapidly grow to become the largest study of brain development in infancy and early childhood using dMRI. QSIPrep and QSIRecon are openly available and can be applied to other infant and pediatric dMRI datasets.

neuroscience↗

bioRxiv2023

Reduced Lateralization of Multiple Functional Brain Networks in Autistic Males

BackgroundAutism spectrum disorder has been linked to a variety of organizational and developmental deviations in the brain. One such organizational difference involves hemispheric lateralization, which may be localized to language-relevant regions of the brain or distributed more broadly. MethodsIn the present study, we estimated brain hemispheric lateralization in autism based on each participants unique functional neuroanatomy rather than relying on group-averaged data. Additionally, we explored potential relationships between the lateralization of the language network and behavioral phenotypes including verbal ability, language delay, and autism symptom severity. We hypothesized that differences in hemispheric asymmetries in autism would be limited to the language network, with the alternative hypothesis of pervasive differences in lateralization. We tested this and other hypotheses by employing a cross-sectional dataset of 118 individuals (48 autistic, 70 neurotypical). Using resting-state fMRI, we generated individual network parcellations and estimated network asymmetries using a surface area-based approach. A series of multiple regressions were then used to compare network asymmetries for eight significantly lateralized networks between groups. ResultsWe found significant group differences in lateralization for the left-lateralized Language (d = -0.89), right-lateralized Salience/Ventral Attention-A (d = 0.55), and right-lateralized Control-B (d = 0.51) networks, with the direction of these group differences indicating less asymmetry in autistic individuals. These differences were robust across different datasets from the same participants. Furthermore, we found that language delay stratified language lateralization, with the greatest group differences in language lateralization occurring between autistic individuals with language delay and neurotypical individuals. LimitationsThe generalizability of our findings is restricted due to the male-only sample and greater representation of individuals with high verbal and cognitive performance. ConclusionsThese findings evidence a complex pattern of functional lateralization differences in autism, extending beyond the Language network to the Salience/Ventral Attention-A and Control-B networks, yet not encompassing all networks, indicating a selective divergence rather than a pervasive one. Furthermore, a differential relationship was identified between Language network lateralization and specific symptom profiles (namely, language delay) of autism.

neuroscience↗

bioRxiv2023

Developmental Characterization of Neuronal Migration Anomalies and Axon Proliferation in mTOR pathway-associated Malformations of Cortical Development

Drug-resistant epilepsy (DRE) is a prevalent problem in children that can lead to abnormal development and various psychiatric comorbidities. Malformations of cortical development (MCD) include focal cortical dysplasia, tuberous sclerosis complex and hemimegalencephaly, which are the most common pathologies among children who undergo surgical resection for treatment of DRE. These disorders share many histopathological features, including dyslamination of the cerebral cortex and enlarged neuronal somata. Recently, genetic mutations in the mammalian target of rapamycin (mTOR) signaling cascade have been shown to underpin most MCDs. Rodent models, including the RhebCA model, recapitulate histologic and physiologic aspects of human DRE. However, there have been few studies characterizing the developmental time point of the histological changes seen in MCDs. In this study, we use in utero electroporation to upregulate the Rheb protein (directly upstream of mTOR) in a focal area of the neocortex. We demonstrate that mTOR dysregulation leads to focal dyslamination and increased neuronal size that is histologically similar to MCD, which correlates to spontaneous recurrent seizures. We used immunohistochemistry to investigate neuronal lamination at several time points during development between E18 and P21 and show early differences in lamination that persisted through development. Furthermore, the increased axonal length associated with mTOR upregulation occurs early in development. Our study provides a time frame for the initial development of abnormal neuronal migration and cellular growth that occurs in MCDs, and our data supports that these anatomical changes may contribute to the formation of epileptic networks.

neuroscience↗

bioRxiv2022

Characterizing the diversity of L2/3 human neocortical neurons in epilepsy

In the current study, we performed whole-cell current clamp recordings from human cortical neurons in layer 2/3 of the human neocortex in order to characterize the diversity of L2/3 human neocortical neurons in epileptic foci with various etiologies in order to begin to elucidate the underlying mechanisms of hyperexcitability which are still mostly unknown. We differentiated neuronal subtypes based on their firing patterns and AHP kinetics or epilepsy subtype (malformation of cortical development (MCD) vs. other (non-MCD)). We found that L2/3 pyramidal neurons have diverse firing properties and action potential kinetics, with some neurons looking remarkably similar to LTS interneurons. We also saw that L2/3 pyramidal neurons could be split into those with fast AHPs and those without, medium AHPs (mAHPs). Based on these parameters, we were unable to significantly differentiate neurons based on firing properties indicating that AHP component kinetics alone do not dictate L2/3 pyramidal neuron firing in human epileptic cortical slices. We also report significant differences in intrinsic properties between MCD and non-MCD and control L2/3 pyramidal neurons and are the first to characterize that wash on of the proconvulsant drug, 4-aminopyridine (4-AP), leads to increased AP duration, less firing rate (FR) accommodation, and slowed down AHPs. Overall, the present study is the first to characterize the large variability of L2/3 human neocortical pyramidal neurons, to compare between L2/3 pyramidal neurons within the epileptic foci between MCD and non-MCD cases, to use control tissue from tumor patients without incidence of seizure, and to determine the influence of 4-AP on L2/3 pyramidal neuron intrinsic properties.

neuroscience↗

bioRxiv2019

Optimizing the intrinsic parallel diffusivity in NODDI: an extensive empirical evaluation

PurposeNODDI is widely used in parameterizing microstructural brain properties. The model includes three signal compartments: intracellular, extracellular, and free water. The neurite compartment intrinsic parallel diffusivity (d||) is set to 1.7 {micro}m2*ms-1, though the effects of this assumption have not been extensively explored. This work seeks to optimize d|| by minimizing the model residuals.\n\nMethodsThe model residuals were evaluated in function of d|| over the range from 0.5 to 3.0 {micro}m2*ms-1. This was done with respect to tissue type (i.e., white matter versus gray matter), sex, age (infancy to late adulthood), and diffusion-weighting protocol (maximum b-value). Variation in the estimated parameters with respect to d|| was also explored.\n\nResultsResults show the optimum d|| is significantly lower for gray matter relative to 1.7 {micro}m2*ms-1 and to white matter. Infants showed significantly decreased optimum d|| in gray and white matter. Minor optimum d|| differences were observed versus diffusion protocol. No significant sex effects were observed. Additionally, changes in d|| resulted in significant changes to the estimated NODDI parameters.\n\nConclusionFuture implementations of NODDI would benefit from d|| optimization, particularly when investigating young populations and/or gray matter.

biophysics↗

bioRxiv2017

Integrative Structural Brain Network Analysis In Diffusion Tensor Imaging

In diffusion tensor imaging, structural connectivity between brain regions is often measured by the number of white matter fiber tracts connecting them. Other features such as the length of tracts or fractional anisotropy (FA) are also used in measuring the strength of connectivity. In this study, we investigated the effects of incorporating the number of tracts, the tract length and FA-values into the connectivity model. Using various node-degree based graph theory features, the three connectivity models are compared. The methods are applied in characterizing structural networks between normal controls and maltreated children, who experienced maltreatment while living in post-institutional settings before being adopted by families in the US.

neuroscience↗