Evidence map›Paper›PMID 37998090›Full record

ArticleJournal of imaging2023

NeuroActivityToolkit-Toolbox for Quantitative Analysis of Miniature Fluorescent Microscopy Data.

Evgenii Gerasimov, Alexander Mitenev, Ekaterina Pchitskaya, Viacheslav Chukanov, Ilya Bezprozvanny

Abstract read
In one paragraph

Article in Journal of imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Evgenii GerasimovLaboratory of Molecular Neurodegeneration, Peter the Great St. Petersburg Polytechnic University, Khlopina St. 11, 194021 St. Petersburg, Russia.
Alexander MitenevLaboratory of Molecular Neurodegeneration, Peter the Great St. Petersburg Polytechnic University, Khlopina St. 11, 194021 St. Petersburg, Russia.
Ekaterina PchitskayaLaboratory of Molecular Neurodegeneration, Peter the Great St. Petersburg Polytechnic University, Khlopina St. 11, 194021 St. Petersburg, Russia.ORCID 0000-0002-3644-6886
Viacheslav ChukanovLaboratory of Molecular Neurodegeneration, Peter the Great St. Petersburg Polytechnic University, Khlopina St. 11, 194021 St. Petersburg, Russia.
Ilya BezprozvannyLaboratory of Molecular Neurodegeneration, Peter the Great St. Petersburg Polytechnic University, Khlopina St. 11, 194021 St. Petersburg, Russia.ORCID 0000-0001-7006-6951

Funding

The research was funded by the Ministry of Science and Higher Education of the Russian Federation under the strategic academic leadership program "Priority 2030" (Agreement 075-15-2023-380 dated 20.02.2023) (E.P.).
6 · The paper itself

Abstract

The visualization of neuronal activity in vivo is an urgent task in modern neuroscience. It allows neurobiologists to obtain a large amount of information about neuronal network architecture and connections between neurons. The miniscope technique might help to determine changes that occurred in the network due to external stimuli and various conditions: processes of learning, stress, epileptic seizures and neurodegenerative diseases. Furthermore, using the miniscope method, functional changes in the early stages of such disorders could be detected. The miniscope has become a modern approach for recording hundreds to thousands of neurons simultaneously in a certain brain area of a freely behaving animal. Nevertheless, the analysis and interpretation of the large recorded data is still a nontrivial task. There are a few well-working algorithms for miniscope data preprocessing and calcium trace extraction. However, software for further high-level quantitative analysis of neuronal calcium signals is not publicly available. NeuroActivityToolkit is a toolbox that provides diverse statistical metrics calculation, reflecting the neuronal network properties such as the number of neuronal activations per minute, amount of simultaneously co-active neurons, etc. In addition, the module for analyzing neuronal pairwise correlations is implemented. Moreover, one can visualize and characterize neuronal network states and detect changes in 2D coordinates using PCA analysis. This toolbox, which is deposited in a public software repository, is accompanied by a detailed tutorial and is highly valuable for the statistical interpretation of miniscope data in a wide range of experimental tasks.

Indexed as

metricsMinianminiature fluorescence microscopyminiscopeopen-source toolboxsoftwarestatistical analysis

Identifiers

PMID37998090
PMCPMC10672520

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.