NCS-FR: Protecting the Aging Brain: Self-Organizing Networks and Multi-Scale Dynamics under Energy Constraints

大脑使用能量的能力与基于年龄的认知障碍密切相关，这将极大地影响不成比例的老龄化人口。在全球范围内，到2030年，65岁或65岁以上的成年人人数估计将增加一倍以上，痴呆症发病率将从65岁人口的1% -2%呈指数增长，到94岁人口的58%。该项目探讨了一种假设，即基于年龄的认知障碍反映了大脑内的胰岛素抵抗（2型糖尿病），限制了神经元对血糖的获取，并测试是否可以通过使用替代脑燃料：酮来逆转衰老效应。该项目利用跨学科团队在神经科学、统计物理和机器学习方面的专业知识，解决个性和变异问题，以解决神经生物学中最基本的未解决问题之一：大脑在应对资源限制时自我组织的“规则”是什么？跨尺度和学科的统一项目是一个计算模型，旨在预测单个主体的网络轨迹，以响应能量约束的收紧和释放，这是理解个体和大脑衰老变化的第一步。该项目团队先前已经表明，衰老与大脑网络的不稳定有关，该团队的初步结果表明，这种影响可以通过将神经代谢从葡萄糖转变为酮来调节。其他研究表明，随着年龄的增长，胰岛素抵抗会加速认知衰退。因此，研究小组假设，当大脑试图优化网络以保存能量以响应神经元胰岛素抵抗时，网络不稳定可能是由重组引起的。利用胰岛素抵抗来收紧能量限制和酮类来释放它们，研究小组计划使用动物（DREADD/膜片钳/钙成像）和人类（31P/1H-MRS, 7T fMRI）数据来表征兴奋性/抑制性神经元放电动力学的变化及其对连通性的影响。从统计物理中的“约束下的优化”问题（例如，最大口径）中改编的技术将应用于这些数据，以识别类似细胞自动机的“规则”，神经元在指导紧急自组织时可能遵循这些“规则”。在这样做的过程中，该项目考虑了基于生物学原理的优化，以及开发生成技术来识别不受先验假设影响的约束。使用迭代方法，其中每个个体的网络轨迹提供反馈，通知模型，然后根据下一个个体的数据进行预测，模型最终将在预测基于个体变量参数的人类网络轨迹方面收敛。通过能够模拟不同初始条件和/或临床干预的潜在后果，这些将为个性化神经学迈出第一步。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The brain's ability to use energy has been strongly implicated in age-based cognitive impairment, which will dramatically affect a disproportionally aging demographic. Globally, the number of adults aged 65 or older is estimated to more than double by 2030, with dementia rates exponentially increasing from 1-2% of the population for those age 65, to 58% for those age 94. This project probes the hypothesis that age-based cognitive impairment reflects insulin resistance (Type 2 diabetes) within the brain, limiting neurons' access to blood sugar, and tests whether one can reverse aging effects through the use of an alternative brain fuel: ketones. This project addresses individuality and variation, leveraging the interdisciplinary team's expertise in neuroscience, statistical physics, and machine learning, to tackle one of neurobiology's most fundamental unanswered questions: what are the "rules" by which the brain self-organizes in response to resource constraints? Unifying the project across scales and disciplines is a computational model designed to predict single-subject network trajectories in response to tightening and releasing of energy constraints, a first step towards understanding individuality and variation in brain aging. The project team have previously shown that aging is associated with destabilization of brain networks, an effect that the team's preliminary results suggest can be modulated by switching neuro-metabolism from glucose to ketones. Others have shown that age-based cognitive deterioration accelerates with insulin resistance. Thus, the team hypothesizes that network destabilization may result from reorganization as the brain attempts to optimize networks to conserve energy in response to neuron insulin-resistance. Using insulin resistance to tighten energy constraints and ketones to release them, the team plans to use animal (DREADD/patch-clamp/calcium imaging) and human (31P/1H-MRS, 7T fMRI) data to characterize changes in excitatory/inhibitory neuron firing dynamics and their implications for connectivity. Techniques adapted from "optimization under constraint" problems in statistical physics (e.g., Maximum Caliber) will then be applied to these data to identify cellular automaton-like "rules" that neurons might follow in guiding emergent self-organization. In so doing, the project considers optimization based upon biological principles as well as developing generative techniques for identifying constraints unbiased by the a priori hypotheses. Using an iterative approach, in which each individual subject's network trajectory provides feedback, informing the models, which then make predictions that are tested against the next individual's data, models will eventually converge in predicting human network trajectories based upon individually variable parameters. These would provide first steps towards personalized neurology, by being able to simulate - for a single individual - the potential consequences of different initial conditions and/or clinical interventions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.