Advanced Information Processing for Healthy Life

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，并揭示预测神经退行性疾病转化的因素。事实上，了解神经元活动，脑代谢和病理生理过程将使创新的数学模型（非线性常微分方程系统）的发展，或用于结合生物和生物医学图像从大脑的解剖功能电路的基本建模到人类大脑中的tau蛋白积累模型（偏微分方程形式主义）。在这种“虚拟脑活动和病理”的环境中，可以通过模拟来预测个体受试者的脑疾病发展的结果。数值模拟工具将有助于预测疾病的进展情况，并了解其原因，而原因仍不确定。这种数值方法是一种新的范式的病理生理过程中的健康老龄化的受试者的神经退行性疾病的风险的研究。这种方法被称为“预测性病理生理学”，通过预防提供更好的健康。为了实现这些目标，我们将开发一个新的神经胶质细胞血管计算模型（NGV模型）在本地和网络的大脑水平，代表本地神经元活动之间的关系，通过脑电图和脑血流量（CBF）的变化，通过磁共振成像或正电子发射断层扫描测量，并引入星形胶质细胞的神经元和CBF激活的贡献。在我们的神经元建模工作的连续性，包括星形胶质细胞和它们的代谢作用，我们使用计算模型占神经递质的交换。一个重要的焦点和重点将放在NGV模型在大规模网络和神经退行性疾病模型之间的相互作用。数值模拟工具将使人们能够预测疾病的进展情况，并了解其原因，而原因仍不确定。这种数值方法是一种新的范式的病理生理过程中的受试者在神经退行性疾病的风险的研究。至关重要的是，病理生理过程的动态性质和因素，可能会导致认知能力下降的解决，因为他们的特点是必要的定义可能的干预策略的基础上早期诊断的疾病。这个问题还没有达到更好地理解促进健康生活方式和促进健康大脑长寿的因素所需的可靠性水平。

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.