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: 2014
• 资助国家: 加拿大
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=544195
• 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.

拟建研究项目的主要目标是：1)建立宏观和微观计算机模型，阐明正常和病理状态（如癫痫）下脑电节律活动的性质。特别是，在现有的模型中，包括神经可塑性和细胞外钾清除（由胶质细胞执行）的机制，以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产生模型（由我们的实验室团队提出）来描述脑电节律方面的“系统”行为，微观模型将使用随机霍奇金-赫胥黎模型来描述细胞模型中的离子传输机制，这些模型在静息电位中表现出类似噪音的活动，正如我们的实验室团队从超极化海马神经元中记录的那样。2)开发人工神经网络，从大脑的生物神经网络学习大脑的各种状态及其状态转换。3)在上述模型的基础上，开发生物启发的反应性神经调节剂，以消除自发性癫痫样事件的发生。4)开发生物启发的反应性神经调节剂的原型电子硬件实现，最初适用于动物模型，最终适用于人类受试者的深部脑刺激（DBS）。