Computer models of the electrical activities in hippocampal neurons

海马神经元电活动的计算机模型

• 批准号: 4486-2012
• 负责人: Bardakjian, Berj
• 金额: $ 1.82万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2012
• 资助国家: 加拿大
• 起止时间: 2012-01-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=509512
• 关键词: Computer; models; electrical; activities; hippocampal

The main objectives of the proposed research program are: 1) Develop macroscopic and microscopic computer models to elucidate the nature of the brain's electrical rhythmic activity under normal and pathological states (such as epilepsy). In particular, include mechanisms of neuroplasticity and extracellular potassium clearance (as performed by glial cells), in the existing models, to investigate their effects on system state transitions. Macroscopic models will characterize the "system" behaviour in terms of electrical brain rhythms using cognitive rhythm generator models (proposed by our lab team), and microscopic models will characterize ionic transport mechanisms in cellular models using stochastic Hodgkin-Huxley type models - that exhibit the noise-like activity in their resting potentials, as recorded (by our lab team) from hyperpolarized hippocampal neurons. 2) Develop artificial neural networks that learn the various brain states and their state transitions, from the biological neural networks of the brain. 3) Develop biologically-inspired responsive neuromodulators, based on the above models, to abolish the onset of spontaneous seizure-like events. 4) Develop proto-type electronic hardware implementations of the biologiocally-inspired responsive neuromodulators, appropriate for use initially in animal models, and eventually for deep brain stimulation (DBS) in human subjects.

该研究计划的主要目标是：1）开发宏观和微观计算机模型，以阐明正常和病理状态（如癫痫）下大脑电节律活动的本质。特别是，包括神经可塑性和细胞外钾清除机制（如神经胶质细胞），在现有的模型中，研究它们对系统状态转换的影响。宏观模型将使用认知节律发生器模型（由我们的实验室团队提出）根据脑电节律来表征“系统”行为，微观模型将使用随机Hodgkin-Huxley型模型来表征细胞模型中的离子转运机制-这些模型在其静息电位中表现出类似噪声的活动，如（由我们的实验室团队）从超极化海马神经元记录的那样。2)开发人工神经网络，从大脑的生物神经网络中学习各种大脑状态及其状态转换。3)基于上述模型，开发生物激发的响应性神经调节剂，以消除自发性神经元样事件的发作。4)开发生物启发的响应神经调制器的原型电子硬件实现，适用于最初在动物模型中使用，并最终用于人类受试者的深部脑刺激（DBS）。