Multi-day Neuron Tracking in High Density Electrophysiology Recordings using EMD.
Multi-day Neuron Tracking in High Density Electrophysiology Recordings using EMD.
复制标题
使用 EMD 进行高密度电生理学记录中的多日神经元跟踪。
DOI：
10.1101/2023.08.03.551724
复制
发表时间：
2024
期刊：
影响因子：
--
通讯作者：
Harris,TimothyD
中科院分区：
文献类型：
--
作者：
Yuan,AugustineXiaoran;Colonell,Jennifer;Lebedeva,Anna;Okun,Michael;Charles,AdamS;Harris,TimothyD
在多天内准确跟踪相同的神经元对于研究学习和适应过程中神经元活动的变化至关重要。高密度细胞外电生理记录探针（例如 Neuropixel）的进步为实现这一目标提供了一条有希望的途径。然而，在多个记录中识别相同的神经元由于组织相对于记录位点的非刚性运动（漂移）以及某些神经元的信号丢失而变得复杂。在这里，我们提出了一种神经元跟踪方法，可以独立于大多数现有方法使用的放电统计来识别相同的细胞。我们的方法基于尖峰排序簇的日间非刚性对齐。我们使用测量的视觉感受野在小鼠中验证了相同的细胞身份。此方法在间隔 1 到 47 天的数据集上取得了成功，平均恢复率为 84%。
Accurate tracking of the same neurons across multiple days is crucial for studying changes in neuronal activity during learning and adaptation. Advances in high-density extracellular electrophysiology recording probes, such as Neuropixels, provide a promising avenue to accomplish this goal. Identifying the same neurons in multiple recordings is, however, complicated by non-rigid movement of the tissue relative to the recording sites (drift) and loss of signal from some neurons. Here, we propose a neuron tracking method that can identify the same cells independent of firing statistics, that are used by most existing methods. Our method is based on between-day non-rigid alignment of spike-sorted clusters. We verified the same cell identity in mice using measured visual receptive fields. This method succeeds on datasets separated from 1 to 47 days, with an 84% average recovery rate.