Biology subjects

Bezaire, M.

Publications and source records attributed to Bezaire, M..

3 recordsLinked to original sources

bioRxiv2021

Metabolic demand regulates selective cell death in Parkinson's Disease

Parkinsons Disease (PD) is a debilitating neurodegenerative condition that affects over 10 million people across the world, causing tremors and muscle weakness. Its mechanisms are unknown, but one key feature is selective cell death: neurons in the Substantia Nigra Pars Compacta (SNc) die, but their neighbors, the cells in the Ventral Tegmental Area (VTA), remain healthy. To study this phenomenon, we used an established single neuron model of the SNc, adapting its biophysical and bioenergetic properties to match that of the VTA. We discovered that reducing calcium influx correlates with higher ATP and lower ROS concentrations in the cell, suggesting in silico the importance of calcium influx in metabolic stress and selective vulnerability for Parkinsons Disease. Future efforts may target calcium channel inhibition as a therapeutic strategy, although caution is needed with potential metabolic side effects.

neuroscience↗

bioRxiv2016

Interneuronal mechanisms of hippocampal theta oscillation in a full-scale model of the rodent CA1 circuit

The hippocampal theta rhythm plays important roles in information processing; however, the mechanisms of its generation are not well understood. We developed a data-driven, supercomputer-based, full-scale (1:1) model of the CA1 area and studied its interneurons during theta oscillations. Theta rhythm with phase-locked gamma oscillations and phase-preferential discharges of distinct in terneuronal types spontaneously emerged from the isolated CA1 circuit without rhythmic inputs. Perturbation experiments identified parvalbumin-expressing interneurons and neurogliaform cells, as well as interneuronal diversity itself, as important factors in theta generation. These simulations reveal new insights into the spatiotemporal organization of the CA1 circuit during theta oscillations.

neuroscience↗

bioRxiv2016

SimTracker tool and code template to design, manage and analyze neural network model simulations in parallel NEURON

Advances in technical computing enable larger and more detailed neural models that can incorporate ever more of the rapidly expanding body of quantitative neuroscience data. In principle, such complex network models that are strongly constrained by experimental data could direct experimental research and provide novel insights into experimental observations. However, as network models grow in complexity and scale, the necessary tasks of development and organization become unwieldy. Further, the models risk becoming inaccessible to experimentalists and other modelers, and their results may then be seen as less relevant to experimental work. To address these obstacles, we developed a tool for managing simulations called SimTracker. It supports users at each step of the modeling process, including execution of large scale parallel models on supercomputers. SimTracker is suitable for users with a range of modeling experience. SimTracker can be a valuable modeling resource that promotes iterative progress between experiment and model.

neuroscience↗