Continuous memory stabilization based on different adaptive processes in neural circuits

基于神经回路中不同自适应过程的连续记忆稳定

• 批准号: 419866478
• 负责人: Professor Dr. Christian Tetzlaff
• 金额: --
• 依托单位: Institut für Neuro- und Sinnesphysiologie
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2019
• 资助国家: 德国
• 起止时间: 2018-12-31 至 2021-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/419866478?language=en
• 关键词: Continuous; memory; stabilization; based; different

The ability to learn and to create memories enables humans and animals to survive in complex and changing environments. Sensing our environment causes neural activity resulting in synaptic adaptation by various plasticity processes. Little is known about how neuronal and synaptic processes interact to select some specific input signals to remember while disregarding others. In particular, it is unclear how the neuronal network stabilizes a memory and maintains it for longer periods of time, especially given that the neuronal substrate does not remain constant but changes substantially during the lifetime of a memory. Memory formation, consolidation, and long-term stabilization are dynamic mechanisms based on neuronal and synaptic processes, which operate across many time scales. These processes are only partially understood and their interactions are still widely unknown. Thus, the goal of this work is to develop a neuro-theoretical framework to investigate formation, consolidation, and long-term stabilization. We will specifically focus on the underlying neural processes and their interactions across different time scales, which should lead to a better understanding of the dynamics of memory. Our central hypothesis is that memory consolidation or stabilization is a multi-step process: We propose that, by the input-dependent interaction of the processes of synaptic and sleep-induced network consolidation, first, memory representations or cell assemblies are formed by strongly interconnecting groups of neurons and, then, some of these cell assemblies are stabilized for longer durations (days), while others disintegrate leading to forgetting (selection by consolidation). Next, we suggest that the days-lasting stabilization of cell assemblies provides enough time to stabilize them for longer times by restructuring their internal connectivity through the slow processes of structural plasticity (long-term stabilization). The final outcome of this approach should be a dynamic memory model across different time scales, which allows investigating the continuous stabilization of memories.

学习和创造记忆的能力使人类和动物能够在复杂多变的环境中生存。感知我们的环境会引起神经活动，通过各种可塑性过程导致突触适应。关于神经元和突触过程如何相互作用来选择要记住的特定输入信号，而忽略其他输入信号，人们知之甚少。特别是，神经元网络如何稳定记忆并使其保持更长时间尚不清楚，特别是在神经元底物不是保持不变的情况下，而是在记忆的生命周期内发生实质性变化。记忆形成、巩固和长期稳定是基于神经元和突触过程的动态机制，这些过程跨越许多时间尺度。人们对这些过程只有部分了解，它们之间的相互作用也鲜为人知。因此，这项工作的目标是开发一个神经理论框架来研究形成、巩固和长期稳定。我们将特别关注潜在的神经过程及其在不同时间尺度上的相互作用，这应该会导致对记忆动力学的更好理解。我们的中心假设是记忆巩固或稳定是一个多步骤的过程：我们提出，通过突触和睡眠诱导的网络巩固过程的输入依赖的相互作用，首先，记忆表征或细胞组合由强相互连接的神经元组形成，然后，其中一些细胞组合稳定更长的时间(天)，而另一些细胞组合解体导致遗忘(通过巩固选择)。接下来，我们认为，细胞组件持续数天的稳定提供了足够的时间，通过结构可塑性(长期稳定)的缓慢过程重新构建其内部连接，从而提供足够的时间来稳定它们。这种方法的最终结果应该是一个跨越不同时间尺度的动态记忆模型，它允许研究记忆的连续稳定性。