EAGER: Toward a New Information Theory for Neuronal Memory

许多目标激发了科学家对人类记忆的兴趣。大脑创造、储存和获取记忆的能力有助于视觉、语言、学习、思考和身份识别；理解记忆既阐明了记忆的功能，也阐明了依赖于记忆的功能。受伤和疾病会抑制或过度刺激记忆功能，在极端情况下，会导致阿尔茨海默病和痴呆症，以及创伤后应激障碍和成瘾等疾病；一种解释生物机制如何产生记忆现象的理论可能有助于查明导致记忆失效的机制变化。这个项目概述了一条通往一个根本的新理论的道路，这个理论是关于单个神经元的微观行为如何产生记忆表现的宏观现象的。这个项目的潜在成果可以更好地理解人类记忆及其影响过程。该项目旨在建立大脑行为和记忆现象的模型，并应用数学工具来研究大脑模型是否可以产生这些记忆现象。在这里，大脑行为被构建为一个马尔可夫过程，这个马尔可夫过程来源于单个神经元、它们的连接和刺激的模型。马尔可夫过程假定过去只通过对现在的影响来影响未来，它表现出一种称为随机收敛的特征行为，即随着时间的推移，马尔可夫过程趋向于可预测的稳态行为。记忆模型试图将记忆的检索、形成和存储作为一种现象来捕捉，在这种现象中，大脑状态在相应的刺激下收敛到期望的结果，通过神经元的可塑性创造新的收敛关系，并保护旧的收敛关系免受相同可塑性造成的损害。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。

Many goals motivate scientific interest in human memory. The brain's ability to create, store, and access memories helps enable vision, speech, learning, thought, and identity; understanding memory elucidates both the functions of remembering and the functions that rely on them. Injury and illness can suppress or overstimulate memory function, with extreme cases causing ailments like Alzheimer's disease and dementia on the one hand and PTSD and addiction on the other; a theory explaining how biological mechanisms create memory phenomena may help pinpoint the mechanistic changes responsible for memory failures. This project outlines a path to a fundamentally new theory for how the microscopic behavior of individual neurons generates the macroscopic phenomena of memory performance. The potential outcomes of this project can shed greater light on the understanding of human memory and the processes that influence it.This project seeks to create models for brain behavior and memory phenomena and applies mathematical tools to investigate whether the brain model can generate those memory phenomena. Brain behavior is structured here as a Markov process derived from models of individual neurons, their connectivity, and stimuli. Markov processes, which capture the assumption that the past affects the future only through its effects on the present, exhibit a characteristic behavior called stochastic convergence, where the Markov process trends toward a predictable steady-state behavior over time. The memory model seeks to capture memory retrieval, formation, and storage as phenomena where the brain state converges to desired outcomes under corresponding stimuli, creates new convergence relationships through neuronal plasticity, and protects old convergence relationships from damage caused by that same plasticity.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.