Computer models of the electrical rhythmic activities in hippocampal neurons

海马神经元电节律活动的计算机模型

• 批准号: RGPIN-2017-06431
• 负责人: Bardakjian, Berj
• 金额: $ 2.04万
• 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: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=682178
• 关键词: Computer; models; electrical; rhythmic; activities

Objectives: (a) Develop macro and micro level computer models of the electrical rhythmic activity in hippocampal neuro-glial networks under normal and pathological states exhibiting seizure-like events (SLEs). (i) Macro level models characterize system behaviour by populations of coupled cognitive rhythm generator (CRG) models (previously reported by our lab team). Each CRG consists of an input layer of neuronal modes (whose transfer functions are measured from Volterra series or alternately chosen from predetermined design functions) for sensing the input environment. The outputs of the neuronal modes layer are feed-forward to a Winfree type ring device whose variables are mapped by a static nonlinearity (representing the wave shape) into an observable output variable. The frequencies of the ring device are modulated by the outputs of the neuronal modes to provide “responsive adaptation” to changes in the input environment. Coupled CRGs are utilized to model pathological states and are used as testing platforms of neuromodulation strategies for abolishment of SLEs. (ii) Micro level models of traditional and "stochastic" Hodgkin-Huxley type models to characterize ionic transport mechanisms in "cellular" models of pyramidal, interneuron and glial cells. These models are used to investigate (1) the effects of astrocytes on hyper-excitability, and (2) the mechanisms of cross frequency coupling in the electrical rhythms of the neuro-glial networks characterizing their states.***(b) Develop neuromodulators using coupled CRGs as therapeutic network to abolish onset of spontaneous SLEs in computer models. With the long term objective of miniaturization as electronic hardware implementation to be used as brain implants and substitutes for damaged neurons in the hippocampus. Our preliminary results on computer models demonstrated the “proof of principle” (previously reported by our lab team).******Scientific Approach: The main hypothesis is that pathological brain states can be anticipated, detected and abolished by "cognitive devices" in feedback loop with the biological system. The main approach is to develop computer models of hippocampal neuro-glial networks, validated using reported biological data, which elucidate the physical basis for the phenomena of cross frequency coupling in their electrical rhythms.******Significance: (a) Develop novel cognitive devices as tools for (1) neurogenic disorder therapies, and (2) in information and communication technology.***(b) Provide insights into the (1) mechanisms of cross frequency coupling between low and high frequency rhythms of neuro-glial networks, (2) classification of brain states, (3) role of astrocytes in moderating neuronal firing in hyper-excitable networks underlying many neurogenic brain disorders.***(c) Provide computer model platform for “proof of principle” testing and comparison of various neuromodulation strategies.

目的：(a)建立正常和病理状态下海马神经胶质网络电节律活动的宏观和微观计算机模型。(i)宏观层面的模型通过耦合认知节律发生器（CRG）模型的群体来表征系统行为（之前由我们的实验室团队报道）。每个CRG由神经元模式的输入层组成（其传递函数由Volterra系列测量或交替从预定的设计函数中选择），用于感知输入环境。神经元模式层的输出前馈到Winfree型环形装置，其变量由静态非线性（表示波形）映射为可观察的输出变量。环形装置的频率由神经元模式的输出调制，以提供对输入环境变化的“响应适应”。耦合的crg被用来模拟病理状态，并被用作消除SLEs的神经调节策略的测试平台。（ii）传统和“随机”霍奇金-赫胥黎模型的微观水平模型，以表征锥体、中间神经元和胶质细胞的“细胞”模型中的离子转运机制。这些模型用于研究(1)星形胶质细胞对高兴奋性的影响，以及(2)表征其状态的神经胶质网络电节律中的交叉频率耦合机制。***(b)在计算机模型中利用偶联CRGs作为治疗网络开发神经调节剂，以消除自发性SLEs的发作。以微型化为长期目标，作为电子硬件实现，用于大脑植入物和海马中受损神经元的替代品。我们在计算机模型上的初步结果证明了“原理证明”（之前由我们的实验室团队报告）。******科学方法：主要假设是大脑的病理状态可以通过与生物系统的反馈回路中的“认知装置”来预测、检测和消除。主要方法是开发海马神经胶质网络的计算机模型，使用已报道的生物学数据进行验证，这阐明了其电节律中交叉频率耦合现象的物理基础。******意义：(a)开发新的认知设备作为(1)神经源性疾病治疗的工具，以及(2)信息和通信技术的工具。***(b)提供对以下方面的见解：(1)神经胶质网络的低频和高频节律之间的交叉频率耦合机制，(2)脑状态的分类，(3)星形胶质细胞在调节许多神经源性脑疾病的超兴奋网络中的神经元放电中的作用。***(c)为各种神经调节策略的“原理验证”测试和比较提供计算机模型平台。