ArticleScientific reports2020
Dynamic Tracking Algorithm for Time-Varying Neuronal Network Connectivity using Wide-Field Optical Image Video Sequences.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Article
- Temporal Patterns of Angular Displacement of Endosomes: Insights into Motor Protein Exchange Dynamics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Phase-sensitive detection of anomalous diffusion dynamics in the neuronal membrane induced by ion channel gating.Physics in medicine and biology · 2023Article
- Ultra-parallel label-free optophysiology of neural activity.iScience · 2022Article
- Simultaneous two-photon activation and imaging of neural activity based on spectral-temporal modulation of supercontinuum light.Neurophotonics · 2020Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
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.
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Registered trials
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