Dynamic Tracking Algorithm for Time-Varying Neuronal Network Connectivity using Wide-Field Optical Image Video Sequences

Dynamic Tracking Algorithm for Time-Varying Neuronal Network Connectivity using Wide-Field Optical Image Video Sequences
复制标题

使用广域光学图像视频序列的时变神经网络连接的动态跟踪算法

DOI:
10.1038/s41598-020-59227-5
复制
发表时间:
2020
期刊:
影响因子:
4.6
通讯作者:
Boppart, Stephen A.
Boppart, Stephen A.
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Renteria, Carlos;Liu, Yuan-Zhi;Chaney, Eric J.;Barkalifa, Ronit;Sengupta, Parijat;Boppart, Stephen A.

文献摘要

参考文献

被引文献

相似文献

神经元和大脑区域之间的信号传播提供了有关神经网络功能特性的信息,从而提供了信息传递。光学成像和采集光信号的统计分析的进步已经产生了各种各样的指标来推断神经连接,从而映射信号的相互关系。然而,传统上推导单个系数来分类两个细胞之间的连接强度,忽略了神经系统本质上是时变系统的事实。为了克服这些局限性,我们利用了时变的Pearson相关系数、尖波排序、小波变换和小波相干性,对GCaMP6s小鼠的DIV 12-15海马神经元施加不同浓度谷氨酸后的钙瞬态进行了分析。结果提供了所产生的发射模式、网络连接、信号方向性和网络属性的全面概述。总之,这些指标提供了一种更全面、更可靠的方法来分析瞬态神经信号,并使未来的研究能够跟踪不同刺激对网络特性的影响。
Propagation of signals between neurons and brain regions provides information about the functional properties of neural networks, and thus information transfer. Advances in optical imaging and statistical analyses of acquired optical signals have yielded various metrics for inferring neural connectivity, and hence for mapping signal intercorrelation. However, a single coefficient is traditionally derived to classify the connection strength between two cells, ignoring the fact that neural systems are inherently time-variant systems. To overcome these limitations, we utilized a time-varying Pearson’s correlation coefficient, spike-sorting, wavelet transform, and wavelet coherence of calcium transients from DIV 12–15 hippocampal neurons from GCaMP6s mice after applying various concentrations of glutamate. Results provide a comprehensive overview of resulting firing patterns, network connectivity, signal directionality, and network properties. Together, these metrics provide a more comprehensive and robust method of analyzing transient neural signals, and enable future investigations for tracking the effects of different stimuli on network properties.
DOI: 10.1371/journal.pcbi.1005268
发表时间: 2017-01
影响因子: 4.3
作者:
Jonas E;Kording KP
通讯作者: Kording KP
DOI: 10.3389/fncir.2013.00199
发表时间: 2013
影响因子: 3.5
作者:
Tibau E;Valencia M;Soriano J
通讯作者: Soriano J
DOI: 10.4314/mmj.v24i3
发表时间: 2012-09
期刊: Malawi medical journal : the journal of Medical Association of Malawi
影响因子: --
作者:
M. Mukaka
通讯作者: M. Mukaka
DOI: 10.7554/elife.32671
发表时间: 2018-02-07
期刊: eLife
影响因子: 7.7
作者:
Yang W;Carrillo-Reid L;Bando Y;Peterka DS;Yuste R
通讯作者: Yuste R
DOI: 10.1371/journal.pcbi.1005526
发表时间: 2017-06
影响因子: 4.3
作者:
Romano SA;Pérez-Schuster V;Jouary A;Boulanger-Weill J;Candeo A;Pietri T;Sumbre G
通讯作者: Sumbre G