Biology subjects

Luna-Munguia, H.

Publications and source records attributed to Luna-Munguia, H..

3 recordsLinked to original sources

bioRxiv2024

Longitudinal Multi-Tensor Analysis of Neocortical Microstructure in an Animal Model of Cortical Dysplasia

The neocortex is a highly organized structure, with region-specific spatial patterns of cells and fibers constituting cyto- and myelo-architecture, respectively. These architectural features are modulated during neurodevelopment, aging, and disease. While invasive techniques have contributed significantly to our understanding of cortical patterning, the task remains challenging through non-invasive methods. Structural magnetic resonance imaging (MRI) has advanced to improve sensitivity in identifying cortical features, yet most methods focus on capturing macrostructural characteristics, often overlooking critical microscale components. Diffusion-weighted MRI (dMRI) offers an opportunity to extract quantitative information reflecting microstructural changes. Here we investigate how different dMRI modalities contribute to the detection of microstructural characteristics and whether per-bundle approaches can disentangle characteristics related to the orientational organization of the myelo- and cyto-architecture in an animal model of cortical dysplasia, a malformation of cortical development. We scanned 32 animals (n=16 experimental; n=16 control) at four different time points (30, 60, 120, and 150 post-natal days) using both structural and multi-shell diffusion-weighted MRI. All dMRI metrics were sampled using a 2D curvilinear system of coordinates as a common anatomical descriptor across animals. Per-bundle metrics were labeled according to their orientation with respect to the cortical surface, and analyzed separately. Experimental animals showed diffusion abnormalities of the tangential and radial fiber components in deeper cortical areas, consistent with histological findings of neuronal and fiber disorganization. The ability of dMRI to detect abnormalities in an animal model of cortical dysplasia is indicative of the clinical potential of advanced dMRI methods to study cortical microstructure in neurological disorders.

neuroscience↗

bioRxiv2023

Selective medial septum lesions in healthy rats induce longitudinal changes in microstructure of limbic regions, behavioral alterations, and increased susceptibility to status epilepticus

Septo-hippocampal pathway is crucial for physiological functions and is involved in epilepsy. Its clinical monitoring during epileptogenesis is complicated. We aim to evaluate tissue changes after lesioning the medial septum of normal rats and assess how the depletion of specific neuronal populations alters the animals behavior and susceptibility to establishing a pilocarpine-induced status epilepticus. A total of 64 young-adult male Sprague-Dawley rats were injected into the medial septum with vehicle or saporins (GAT1 or 192-IgG for GABAergic or cholinergic depletion, respectively; n=16 per group). Thirty-two animals were used for diffusion tensor imaging (DTI); they were scanned before surgery and 14 and 49 days post-injection. Fractional anisotropy and apparent diffusion coefficient were evaluated in the fimbria, dorsal hippocampus, ventral hippocampus, dorso-medial thalamus and amygdala. Between scans 2 and 3, animals were submitted to the elevated plus-maze, open-field test, rotarod test, Y-maze and water-maze. Timm, toluidine and Nissl staining were used to analyze tissue alterations. Twenty-four different animals received pilocarpine to evaluate the latency and severity of the status epilepticus two weeks after surgery. Eight animals were only used to evaluate the extent of neuronal damage inflicted on the medial septum one week after the molecular surgery. Progressive changes in DTI parameters in both the white and gray matter structures of the four evaluated groups were observed. Behaviorally, the GAT1-saporin injection impacted spatial memory formation, while 192-IgG-saporin triggered anxiety-like behaviors. Histologically, the GABAergic toxin also induced aberrant mossy fiber sprouting, tissue damage and neuronal death. Regarding the pilocarpine-induced status epilepticus, this agent provoked an increased mortality rate. Selective septo-hippocampal modulation impacts the integrity of limbic regions crucial for certain behavioral skills and could represent a precursor for epilepsy development. Significance statementThe medial septum is believed to be involved in epilepsy. However, whether and how defects in the integrity of each neuronal subpopulation conforming this structure affect gray and white matter structures remains unclear. Here we examine whether the injection of vehicle or partially-selective saporins into medial septum of normal rats play a role in the integrity of specific brain regions relevant to memory formation, anxiety-like behaviors, and susceptibility to status epilepticus induction and survival. We find that lesioning the medial septum GABAergic or cholinergic neurons can represent a precursor for behavioral deficits or epilepsy development. Therefore, these results strongly support the idea that modulation of medial septum can be a potential target to improve cognition or reduce seizure frequency.

neuroscience↗

bioRxiv2023

Differentiation of white matter histopathology using b-tensor encoding and machine learning

Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) is a non-invasive technique that is sensitive to microstructural geometry in neural tissue and is useful for the detection of neuropathology in research and clinical settings. Tensor valued diffusion encoding schemes (b-tensor) have been developed to enrich the microstructural data that can be obtained through DW-MRI. These advanced methods have proven to be more specific to microstructural properties than conventional DW-MRI acquisitions. Additionally, machine learning methods are particularly useful for the study of multidimensional data sets. In this work, we have tested the reach of b-tensor encoding data analyses with machine learning in different histopathological scenarios. We achieved this in three steps: 1) We induced different forms of white matter damage in rodent optic nerves. 2) We obtained ex-vivo DW-MRI with b-tensor encoding schemes and calculated quantitative metrics using Q-space Trajectory Imaging. 3) We used a machine learning model to identify the main contributing features and built a voxel-wise probabilistic classification map of histological damage. Our results show that this model is sensitive to characteristics of microstructural damage. In conclusion, b-tensor encoded DW-MRI analyzed with machine learning methods, have the potential to be further developed for the detection of histopathology and neurodegeneration.

neuroscience↗