Biology subjects

Cabral, L.

Publications and source records attributed to Cabral, L..

5 recordsLinked to original sources

bioRxiv2023

Multivariate and Regional Age-Related Change in Basal Ganglia Iron in Neonates

In the perinatal period, reward and cognitive systems begin trajectories, influencing later psychiatric risk. The basal ganglia is important for reward and cognitive processing but early development has not been fully characterized. To assess age-related development, we used a measure of basal ganglia physiology, specifically brain tissue iron, obtained from nT2* signal in rsfMRI, associated with dopaminergic processing. We used data from the Developing Human Connectome Project (N=464) to assess how moving from the prenatal to the postnatal environment affects rsfMRI nT2*, modeling gestational and postnatal age separately for basal ganglia subregions in linear models. We did not find associations with tissue iron and gestational age [Range: 24.29-42.29] but found positive associations with postnatal age [Range:0-17.14] in the pallidum and putamen, but not the caudate. We tested if there was an interaction between preterm birth and postnatal age, finding early preterm infants (GA<35 weeks) had higher iron levels and changed less over time. To assess multivariate change, we used support vector regression to predict age from voxel-wise-nT2* maps. We could predict postnatal but not gestational age when maps were residualized for the other age term. This provides evidence subregions differentially change with postnatal experience and preterm birth may disrupt trajectories.

neuroscience↗

bioRxiv2023

Gestational and postnatal age associations for striatal tissue iron deposition in early infancy

Striatal development is crucial for later motor, cognitive, and reward behavior, but age-related change in striatal physiology during the neonatal period remains understudied. An MRI-based measure of tissue iron deposition, T2*, is a non-invasive way to probe striatal physiology neonatally, linked to dopaminergic processing and cognition in children and adults. Striatal subregions have distinct functions that may come online at different time periods in early life. To identify if there are critical periods before or after birth, we measured if striatal iron accrued with gestational age at birth [range=34.57-41.85 weeks] or postnatal age at scan [range=5-64 days], using MRI to probe the T2* signal in N=83 neonates in three striatal subregions. We found iron increased with postnatal age in the pallidum and putamen but not the caudate. No significant relationship between iron and gestational age was observed. Using a subset of infants scanned at preschool age (N=26), we show distributions of iron shift between timepoints. In infants, the pallidum had the least iron of the three regions but had the most by preschool age. Together, this provides evidence of distinct change for striatal subregions, a possible differentiation between motor and cognitive systems, identifying a mechanism that may impact future trajectories. HighlightsO_LINeonatal striatal tissue iron can be measured using the T2* signal from rsfMRI C_LIO_LInT2* changed with postnatal age in the pallidum and putamen but not in the caudate C_LIO_LInT2* did not change with gestational age in any of the three regions C_LIO_LIPatterns of iron deposition (nT2*) among regions shift from infancy to preschool C_LI

neuroscience↗

bioRxiv2022

Building bridges from genome to physiology using machine learning and Drosophila experimental evolution

Drosophila experimental evolution, with its well-defined selection protocols, has long supplied useful genetic material for the analysis of functional physiology. While there is a long tradition of interpreting the effects of large-effect mutants physiologically, in the genomic era identifying and interpreting gene-to-phenotype relationships has been challenging, with many labs not resolving how physiological traits are affected by multiple genes throughout the genome. Drosophila experimental evolution has demonstrated that multiple phenotypes change due to the evolution of many loci across the genome, creating the scientific challenge of sifting out differentiated but noncausal loci for individual characters. The fused lasso additive model method (FLAM) allows us to infer some of the differentiated loci that have relatively greater causal effects on the differentiation of specific phenotypes. The experimental material used in the present study comes from 50 populations that have been selected for different life-histories and levels of stress resistance. Differentiation of cardiac robustness, starvation resistance, desiccation resistance, lipid content, glycogen content, water content, and body masses was assayed among 40 to 50 of these experimentally-evolved populations. Through FLAM, we combined physiological analysis from eight parameters with whole-body pooled-seq genomic data to identify potentially causally linked genomic regions. We have identified approximately 1,900 significantly differentiated 50 kb genomic windows among our 50 populations, with 161 of those identified genomic regions highly likely to have a causal effect connecting specific genome sites to specific physiological characters.

physiology↗

bioRxiv2020

QSIPrep: An integrative platform for preprocessing and reconstructing diffusion MRI

Diffusion-weighted magnetic resonance imaging (dMRI) has become the primary method for non-invasively studying the organization of white matter in the human brain. While many dMRI acquisition sequences have been developed, they all sample q-space in order to characterize water diffusion. Numerous software platforms have been developed for processing dMRI data, but most work on only a subset of sampling schemes or implement only parts of the processing workflow. Reproducible research and comparisons across dMRI methods are hindered by incompatible software, diverse file formats, and inconsistent naming conventions. Here we introduce QSIPrep, an integrative software platform for the processing of diffusion images that is compatible with nearly all dMRI sampling schemes. Drawing upon a diverse set of software suites to capitalize upon their complementary strengths, QSIPrep automatically applies best practices for dMRI preprocessing, including denoising, distortion correction, head motion correction, coregistration, and spatial normalization. Throughout, QSIPrep provides both visual and quantitative measures of data quality as well as "glass-box" methods reporting. Taken together, these features facilitate easy implementation of best practices for processing of diffusion images while simultaneously ensuring reproducibility.

bioinformatics↗

bioRxiv2019

Category-Selective Visual Regions Have Distinctive Signatures of Connectivity in Early Infancy

The development of the ventral visual stream is shaped both by an innate proto-organization and by experience. The fusiform face area (FFA), for example, has stronger connectivity to early visual regions representing the fovea and lower spatial frequencies. In adults, category-selective regions in the ventral stream (e.g. the FFA) also have distinct signatures of connectivity to widely distributed brain regions, which are thought to encode rich cross-modal, motoric, and affective associations (e.g., tool regions to the motor cortex). It is unclear whether this long-range connectivity is also innate, or if it develops with experience. We used MRI diffusion-weighted imaging with tractography to characterize the connectivity of face, place, and tool category-selective regions in neonates (N=445), 1-9 month old infants (N=11), and adults (N=14). Using a set of linear-discriminant classifiers, category-selective connectivity was found to be both innate and shaped by experience. Connectivity for faces was the most developed, with no evidence of significant change in the time period studied. Place and tool networks were present at birth but also demonstrated evidence of development with experience, with tool connectivity developing over a more protracted period (9 months). Taken together, the results support an extended proto-organizon to include long-range connectivity that could provide additional constraints on experience dependent development.

neuroscience↗