Biology subjects

Gholipour, A.

Publications and source records attributed to Gholipour, A..

3 recordsLinked to original sources

bioRxiv2023

A computational framework for characterizing normative development of structural brain connectivity in the perinatal stage

Quantitative assessment of the brains structural connectivity in the perinatal stage is useful for studying normal and abnormal neurodevelopment. However, estimation of the structural connectome from diffusion MRI data involves a series of complex and ill-posed computations. For the perinatal period, this analysis is further challenged by the rapid brain development and difficulties of imaging subjects at this stage. These factors, along with high inter-subject variability, have made it difficult to chart the normative development of the structural connectome. Hence, there is a lack of baseline trends in connectivity metrics that can be used as reliable references for assessing normal and abnormal brain development at this critical stage. In this paper we propose a computational framework, based on spatio-temporal atlases, for determining such baselines. We apply the framework on data from 169 subjects between 33 and 45 postmenstrual weeks. We show that this framework can unveil clear and strong trends in the development of structural connectivity in the perinatal stage. Some of our interesting findings include that connection weighting based on neurite density produces more consistent trends and that the trends in global efficiency, local efficiency, and characteristic path length are more consistent than in other metrics.

bioengineering↗

bioRxiv2022

Heterogeneous migration of neuronal progenitors to the insula shapes the human brain

The human cerebrum consists of a precise and stereotyped arrangement of lobes, gyri, and connectivity that underlies human cognition. The development of this arrangement is less clear. Current models of radial glial cell migration explain individual gyral formation but fail to explain the global configuration of the cerebral lobes. Moreover, the insula, buried in the depths of the Sylvian fissure, belies conventional models. Here, we show that the insula has unique morphology in adults, that insular morphology and slow volumetric growth emerge during fetal development, and that a novel theory of curved migration is required to explain these findings. We calculated morphologic data in the insula and other lobes in adults (N=107) and in an in utero fetal brain atlas (N=81 healthy fetuses). In utero, the insula grows an order of magnitude slower than the other lobes and demonstrates shallower sulci, less curvature, and less surface complexity both in adults and progressively throughout fetal development. Novel spherical projection analysis demonstrates that the lenticular nuclei obstruct 60-70% of radial pathways from the ventricular zone (VZ) to the insula, forcing a curved migration path to the insula in contrast to a direct radial pathway. Using fetal diffusion tractography, we identify streams of putative progenitor cells that originate from the VZ and migrate tangentially around the lenticular nuclei to form the insula. These results challenge existing models of radial migration to the cortex, provide an alternative model for insular and cerebral development, and lay the groundwork to understand cerebral malformations, insular functional connectivity, and insular pathologies.

developmental biology↗

bioRxiv2021

Insights from the IronTract challenge: optimal methods for mapping brain pathways from multi-shell diffusion MRI

Limitations in the accuracy of brain pathways reconstructed by diffusion MRI (dMRI) tractography have received considerable attention. While the technical advances spearheaded by the Human Connectome Project (HCP) led to significant improvements in dMRI data quality, it remains unclear how these data should be analyzed to maximize tractography accuracy. Over a period of two years, we have engaged the dMRI community in the IronTract Challenge, which aims to answer this question by leveraging a unique dataset. Macaque brains that have received both tracer injections and ex vivo dMRI at high spatial and angular resolution allow a comprehensive, quantitative assessment of tractography accuracy on state-of-the-art dMRI acquisition schemes. We find that, when analysis methods are carefully optimized, the HCP scheme can achieve similar accuracy as a more time-consuming, Cartesian-grid scheme. Importantly, we show that simple pre- and post-processing strategies can improve the accuracy and robustness of many tractography methods. Finally, we find that fiber configurations that go beyond crossing (e.g., fanning, branching) are the most challenging for tractography. The IronTract Challenge remains open and we hope that it can serve as a valuable validation tool for both users and developers of dMRI analysis methods.

neuroscience↗