Biology subjects

Barkovich, A. J.

Publications and source records attributed to Barkovich, A. J..

4 recordsLinked to original sources

bioRxiv2021

Brain age predicted using graph convolutional neural network explains developmental trajectory in preterm neonates

Dramatic alterations in brain morphology, such as cortical thickness and sulcal folding, occur during the 3rd trimester of gestation which overlaps with the period of premature births. Here, we investigated the ability of the graph convolutional network (GCN) to predict brain age for preterm neonates by accounting for morphometrics measured on the cortical surface and the surface mesh topology as a sparse graph. Our findings demonstrate that GCN-based age prediction of preterm neonates (n=170; mean absolute error [MAE]: 1.06 weeks) outperformed conventional machine learning algorithms and deep learning methods that did not use topological information. We further evaluated how predicted brain age (PBA) emerges as a biologically meaningful index that characterizes the current status of brain development at the time of imaging. We hypothesized that the relative brain age (RBA; PBA minus chronological age) at scan reflects a combination of perinatal clinical factors, including preterm birth, birthweight, perinatal brain injuries, exposure to postnatal steroids, etc. We also hypothesized that RBA of neonatal scans may be associated with brain functional development in the future. To validate these hypotheses, we used general linear models. Furthermore, we established structural equation models (SEM) to determine the structural relationship between preterm birth (as a latent variable of birthweight and birth age), perinatal injuries (as a latent variable of three leading brain injuries), postnatal factors (as a latent variable of six clinical conditions), RBA at scan, and neurodevelopmental scores at 30 months. Our results suggest that low birthweight, chronic lung disease, and exposure to postnatal steroids impair cortical growth, as low RBA was significantly associated with these risks. Furthermore, RBA was associated with cognitive and language scores at 30 months. SEM analysis indicated that RBA mediated the influences of preterm birth and postnatal clinical factors, but not perinatal brain injuries, toward brain functional development at 30 months. The left middle cingulate cortex showed the most accurate prediction of brain age (MAE: 1.19 weeks), followed by left posterior and right middle cingulate cortices (1.21 weeks). These cingulate regions presented faster growth than others. RBAs of several frontal cortices significantly correlated with cognitive abilities at 30 months of age (n=50). Whereas, RBA of left Brocas area, which is important for language production and comprehension, was associated with language functional scores. Overall, our results demonstrate the potential of the GCN in both predicting brain age and localizing regional growth that relates to postnatal factors and future neurodevelopmental outcome.

neuroscience↗

bioRxiv2021

Cyto/myeloarchitectural changes of cortical gray matter and superficial white matter in early neurodevelopment: Multimodal MRI study of preterm neonates

The developing cerebral cortex undergoes rapid microstructural and morphological changes throughout the third trimester. Recently, increased attention has been focused on the identification of imaging features that represent the underlying cortical cyto/myeloarchitecture driving intracortical myelination and the maturation of cortical gray matter (GM) and its adjacent superficial white matter (sWM). However, the characterization and spatiotemporal pattern of complex cyto/myeloarchitectural changes in this critical time period remain incompletely understood. Using 92 MRI scans from 78 preterm neonates (baseline: n{square}={square}78, postmenstrual age=33.1{+/-}1.8 weeks; follow-up: n=14, 37.3{+/-}1.3), the current study leveraged combined T1/T2 intensity ratio and diffusion tensor imaging (DTI) measurements, including fractional anisotropy (FA) and mean diffusivity (MD), to characterize the cyto/myeloarchitectural architecture of cortical GM and its adjacent sWM in preterm neonates. DTI metrics during these weeks showed an overall linear developmental trajectory: FA decreased along with time in GM but increased in sWM; MD decreased in both GM and sWM. In contrast, T1/T2 measurements showed a distinctive parabolic developmental trajectory, revealing additional cyto/myeloarchitectural signature inferred. Furthermore, the spatiotemporal courses of T1/T2 ratio and DTI parameters were found to be regionally heterogeneous across the cerebral cortex, suggesting these imaging features specific relationship to regional cyto/myeloarchitectural maturation: faster T1/T2 ratio changes were found in the central, ventral, and temporal regions of GM and sWM, faster FA increases in anterior sWM areas, and faster MD decreases in GM and sWM central and cingulate areas. Taken together, our results may offer an explanation of the novel pattern of cyto/myeloarchitectural processes observed throughout the third trimester, including dendritic arborization, synaptogenesis, glial proliferation, as well as radial glial cell organization and apoptosis. Finally, T1/T2 ratio and DTI measurements were significantly associated with 1 year outcome scores of language and cognitive performance as well as perinatal clinical conditions, including intraventricular hemorrhage and chronic lung disease, demonstrating their potential as imaging biomarkers characterizing microstructural deviation in atypical neurodevelopment. Ultimately, with combined properties of cortical T1/T2 and DTI measurements, this study provides unique insights into the cellular processes and associated developmental mechanisms during the critical development of the third trimester.

neuroscience↗

bioRxiv2021

Robust T1 MRI cortical surface pipeline for neonatal brain and systematic evaluation using multi-site MRI datasets

The human brain grows the most dramatically during the perinatal and early postnatal periods, during which preterm birth or perinatal injury that may alter brain structure and lead to developmental anomalies. Thus, characterizing cortical thickness of developing brains remains an important goal. However, this task is often complicated by inaccurate cortical surface extraction due to small-size brains. Here, we propose a novel complex framework for the reconstruction of neonatal WM and pial surfaces, accounting for large partial volumes due to small-size brains. The proposed approach relies only on T1-weighted images unlike previous T2-weighted image-based approaches while only T1-weighted images are sometimes available under the different clinical/research setting. Deep neural networks are first introduced to the neonatal MRI pipeline to address the mis-segmentation of brain tissues. Furthermore, this pipeline enhances cortical boundary delineation using combined models of the CSF/GM boundary detection with edge gradient information and a new skeletonization of sulcal folding where no CSF voxels are seen due to the limited resolution. We also proposed a systematic evaluation using three independent datasets comprising 736 preterm and 97 term neonates. Qualitative assessment for reconstructed cortical surfaces shows that 86.9% are rated as accurate across the three site datasets. In addition, our landmark-based evaluation shows that the mean displacement of the cortical surfaces from the true boundaries was less than a voxel size (0.532{+/-}0.035mm). Evaluating the proposed pipeline (namely NEOCIVET 2.0) shows the robustness and reproducibility across different sites and different age-groups. The mean cortical thickness measured positively correlated with postmenstrual age (PMA) at scan (p<0.0001); Cingulate cortical areas grew the most rapidly whereas the inferior temporal cortex grew the least rapidly. The range of the cortical thickness measured was biologically congruent (1.3mm at 28 weeks of PMA to 1.8mm at term equivalent). Cortical thickness measured on T1 MRI using NEOCIVET 2.0 was compared with that on T2 using the established dHCP pipeline. It was difficult to conclude that either T1 or T2 imaging is more ideal to construct cortical surfaces. NEOCIVET 2.0 has been open to the public through CBRAIN (https://mcin-cnim.ca/technology/cbrain/), a web-based platform for processing brain imaging data.

bioinformatics↗

bioRxiv2020

Role for the Na+/K+ ATPase α 3 subunit in folding and lamination of the human neocortex

Osmotic equilibrium and membrane potential in animal cells depend on concentration gradients of sodium (Na+) and potassium (K+) ions across the plasma membrane, a function that is catalyzed by the Na,K-ATPase alpha subunit. In vertebrates, four paralogous genes, ATP1A1-4, encode distinct alpha subunit isoforms (a1-a4), three of which (a1, a2, a3) are expressed in the brain, and two (a1, a3) predominantly in neurons. The a3 isoform, encoded by ATP1A3, is critical to neuronal physiology, and a growing spectrum of neurological diseases are associated with ATP1A3 pathogenic variants, with ages of onset ranging from early childhood to adulthood. Here, we describe ATP1A3 variants encoding dysfunctional a3 subunits in children affected by polymicrogyria, a developmental malformation of the cerebral cortex characterized by abnormal folding and laminar organization. To gain cell-biological insights into the spatiotemporal dynamics of prenatal ATP1A3 expression, we established a transcriptional atlas of ATP1A3 expression during cortical development using mRNA in situ hybridization and transcriptomic profiling of ~125,000 individual cells with single-cell RNA sequencing (Drop-Seq) from various areas of the midgestational human neocortex. We find that fetal expression of ATP1A3 is restricted to a subset of excitatory neurons carrying transcriptional signatures of neuronal activity and maturation characteristic of the developing subplate. Furthermore, by performing Drop-Seq on ~52,000 nuclei from four different areas of an infant human neocortex, we show that ATP1A3 expression persists throughout early postnatal development, not only within excitatory neurons across all cortical layers, but also and more predominantly in inhibitory neurons, with specific enrichment in fast-spiking basket cells. In addition, we show that ATP1A3 expression, both in fetal and postnatal neurons, tends to be higher in frontal cortical areas than in occipital areas, in a pattern consistent with the rostro-caudal maturation gradient of the human neocortex. Finally, we discover distinct co-expression patterns linking catalytic subunit isoforms (ATP1A1,2,3) and auxiliary isoforms (ATP1B1,2,3), suggesting the ATPase pump may form non-redundant, cell-type specific -{beta} combinations. Together, the importance of the developmental phenotypes and dynamic expression patterns of ATP1A3 point to a key role for a3 in the development and function of human cortex.

neuroscience↗