Advanced Information Processing for Healthy Life

先进的信息处理促进健康生活

• 批准号: RGPIN-2018-06809
• 负责人: Benali, Habib
• 金额: $ 2.4万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=645113
• 关键词: Advanced; Information; Processing; Healthy; Life

The objective of the research program is to better understand brain activity in healthy aging and to shed light on factors predicting conversion to neurodegenerative disease. Indeed, understanding neuronal activity, brain metabolism and the patho-physiological process will enable the development of innovative mathematical models (non-linear ordinary differential equation system) by or for combining biological and biomedical images from the basic modelling of the brain's anatomo-functional circuits to models of tau protein accumulation in the human brain (partial differential equation formalism). In such “virtual brain activity and pathology” environment, the outcome of brain disease development for individual subjects can be foreseen by simulations. Numerical simulation tools would allow for the prediction of the progress of the disease as well as an understanding of its causes, which remain uncertain. This numerical approach is a new paradigm of the study of the patho-physiological process in healthy aging of subjects at-risk for neurodegenerative disease. This approach, referred to as “predictive physiopathology”, offers better health through prevention. To achieve these objectives we will develop a new Neuro-Glia-Vascular computational model (NGV-model) both at the local and at the network brain level, representing the relationship between local neuronal activity measured by Electroencephalography and the Cerebral Blood Flow (CBF) changes measured by Magnetic Resonance Imaging or Positron Emission Tomography and introducing an astrocytes cells contribution to the neuronal and CBF activation. In the continuity of our neuronal modeling work including astrocytes and their metabolic role, we use a computational model accounting for neurotransmitters exchanges. An important focus and emphasis will be placed on the interaction between the NGV-model at a large-scale network and the neurodegenerative diseases model. Numerical simulation tools would allow prediction of the progress of the disease as well as an understanding of its causes, which remain uncertain. This numerical approach is a new paradigm of the study of the patho-physiological process in subjects at-risk for neurodegenerative disease. It is paramount that the dynamical nature of the patho-physiological processes and factors that may contribute to cognitive decline be addressed as their characterization are essential for the definition of possible intervention strategies based on early diagnostic of the disease. This problem has not yet reached the reliability level required for better understanding the factors that promote a healthy lifestyle and contribute to the longevity of a healthy brain.

该研究计划的目的是更好地了解健康老龄化中的大脑活动，并阐明预测转化为神经退行性疾病的因素。事实上，了解神经元活动、大脑新陈代谢和病理生理过程将有助于开发创新的数学模型(非线性常微分方程组)，通过或用于组合生物和生物医学图像，从大脑解剖功能电路的基本模型到tau蛋白在人脑中积累的模型(偏微分方程式形式)。在这种虚拟的大脑活动和病理环境中，可以通过模拟来预测单个受试者的脑部疾病发展的结果。数值模拟工具将能够预测疾病的进展，并了解其原因，这些原因仍然不确定。这种数值方法是研究神经退行性疾病高危人群健康衰老过程中病理生理过程的新范式。这种方法被称为“预测生理病理学”，通过预防提供更好的健康。为了实现这些目标，我们将在局部和网络脑水平上开发一个新的神经-胶质-血管计算模型(NGV-MODEL)，该模型表示脑电测量的局部神经元活动与磁共振成像或正电子发射断层扫描测量的脑血流量(CBF)变化之间的关系，并引入星形胶质细胞对神经元和CBF激活的贡献。在包括星形胶质细胞及其代谢作用在内的神经元建模工作的连续性中，我们使用了一个考虑神经递质交换的计算模型。一个重要的焦点和重点将放在大规模网络中的NGV模型和神经退行性疾病模型之间的相互作用上。数值模拟工具将使人们能够预测疾病的进展，并了解其原因，这些原因仍然不确定。这种数值方法是研究神经退行性疾病高危受试者病理生理过程的新范式。至关重要的是，必须解决可能导致认知下降的病理生理过程和因素的动态性质，因为它们的特征对于基于疾病早期诊断的可能干预策略的确定至关重要。这个问题还没有达到更好地理解促进健康生活方式和有助于健康大脑长寿的因素所需的可靠性水平。