小柯机器人

瑞士巴塞尔大学Rainer W. Friedrich等研究人员合作开发出用于钙成像分析的深度学习工具。相关论文于2021年8月2日在线发表在《自然—神经科学》杂志上。

研究人员从公开的和新近进行的斑马鱼和小鼠记录中汇编了一个大型的、多样化的基础真相数据库，涵盖了广泛的钙指标、细胞类型和信噪比，包括298个神经元、总共超过35个小时的记录。研究人员开发了一种脉冲推断算法（称为CASCADE），该算法基于有监督的深度网络，利用真实数据库的优势，推断绝对脉冲率，并优于现有基于模型的算法。

为了优化未见过的成像数据的性能，CASCADE通过重新采样真实数据来重新训练自己，从而匹配各自的采样率和噪声水平；因此，用户不需要调整参数。此外，研究人员为未见过的数据开发了系统的性能评估，公开发布了一个资源工具箱，并提供了一个用户友好的云工具。

据介绍，从神经元钙信号中推断动作电位（"脉冲"），由于缺乏动作电位和钙信号的同步测量（"基础真相"）而变得复杂。

附：英文原文

Title: A database and deep learning toolbox for noise-optimized, generalized spike inference from calcium imaging

Author: Rupprecht, Peter, Carta, Stefano, Hoffmann, Adrian, Echizen, Mayumi, Blot, Antonin, Kwan, Alex C., Dan, Yang, Hofer, Sonja B., Kitamura, Kazuo, Helmchen, Fritjof, Friedrich, Rainer W.

Issue&Volume: 2021-08-02

Abstract: Inference of action potentials (‘spikes’) from neuronal calcium signals is complicated by the scarcity of simultaneous measurements of action potentials and calcium signals (‘ground truth’). In this study, we compiled a large, diverse ground truth database from publicly available and newly performed recordings in zebrafish and mice covering a broad range of calcium indicators, cell types and signal-to-noise ratios, comprising a total of more than 35 recording hours from 298 neurons. We developed an algorithm for spike inference (termed CASCADE) that is based on supervised deep networks, takes advantage of the ground truth database, infers absolute spike rates and outperforms existing model-based algorithms. To optimize performance for unseen imaging data, CASCADE retrains itself by resampling ground truth data to match the respective sampling rate and noise level; therefore, no parameters need to be adjusted by the user. In addition, we developed systematic performance assessments for unseen data, openly released a resource toolbox and provide a user-friendly cloud-based implementation.

DOI: 10.1038/s41593-021-00895-5

Source: https://www.nature.com/articles/s41593-021-00895-5

Nature Neuroscience：《自然—神经科学》，创刊于1998年。隶属于施普林格·自然出版集团，最新IF：28.771
官方网址：https://www.nature.com/neuro/
投稿链接：https://mts-nn.nature.com/cgi-bin/main.plex