PDF(Pubmed)
Abstract：
Despite being composed of highly plastic neurons with extensive positive feedback, the nervous system maintains stable overall function. To keep activity within bounds, it relies on a set of negative feedback mechanisms that can induce stabilizing adjustments and that are collectively termed \"homeostatic plasticity.\" Recently, a highly excitable microdomain, located at the proximal end of the axon-the axon initial segment (AIS)-was found to exhibit structural modifications in response to activity perturbations. Though AIS plasticity appears to serve a homeostatic purpose, many aspects governing its expression and its functional role in regulating neuronal excitability remain elusive. A central challenge in studying the phenomenon is the rich heterogeneity of its expression (distal/proximal relocation, shortening, lengthening) and the variability of its functional role. A potential solution is to track AISs of a large number of neurons over time and attempt to induce structural plasticity in them. To this end, a promising approach is to use extracellular electrophysiological readouts to track a large number of neurons at high spatiotemporal resolution by means of high-density microelectrode arrays (HD-MEAs). However, an analysis framework that reliably identifies specific activity signatures that uniquely map on to underlying microstructural changes is missing. In this study, we assessed the feasibility of such a task and used the distal relocation of the AIS as an exemplary problem. We used sophisticated computational models to systematically explore the relationship between incremental changes in AIS positions and the specific consequences observed in simulated extracellular field potentials. An ensemble of feature changes in the extracellular fields that reliably characterize AIS plasticity was identified. We trained models that could detect these signatures with remarkable accuracy. Based on these findings, we propose a hybrid analysis framework that could potentially enable high-throughput experimental studies of activity-dependent AIS plasticity using HD-MEAs.
摘要：
尽管由具有广泛正反馈的高度可塑性神经元组成，神经系统维持稳定的整体功能。为了将活动保持在界限内，它依赖于一组负反馈机制，这些机制可以引起稳定调整，统称为“稳态可塑性”。\"最近,一个高度兴奋的微域，发现位于轴突近端-轴突初始段（AIS）-响应于活动扰动而表现出结构修饰。虽然AIS可塑性似乎有稳态的目的，控制其表达及其在调节神经元兴奋性中的功能作用的许多方面仍然难以捉摸。研究该现象的主要挑战是其表达的丰富异质性（远端/近端重新定位，缩短，延长)及其功能作用的可变性。一个潜在的解决方案是随着时间的推移跟踪大量神经元的AIS，并试图在其中诱导结构可塑性。为此,一种有前途的方法是使用细胞外电生理读数通过高密度微电极阵列（HD-MEAs）以高时空分辨率跟踪大量神经元。然而,缺少一个能够可靠地识别唯一映射到底层微观结构变化的特定活动特征的分析框架。在这项研究中,我们评估了这项任务的可行性,并将AIS的远端重新定位作为一个示例性问题.我们使用复杂的计算模型来系统地探索AIS位置的增量变化与模拟细胞外场电位中观察到的特定后果之间的关系。确定了可靠表征AIS可塑性的细胞外场特征变化的集合。我们训练了可以以惊人的准确性检测这些特征的模型。基于这些发现,我们提出了一种混合分析框架，该框架可能使使用HD-MEA对活性依赖性AIS可塑性进行高通量实验研究成为可能。
