Evidence map›Paper›PMID 33826050›Full record

ArticleJournal of computational neuroscience2021

Reconstruction scheme for excitatory and inhibitory dynamics with quenched disorder: application to zebrafish imaging.

Lorenzo Chicchi, Gloria Cecchini, Ihusan Adam, Giuseppe de Vito, Roberto Livi, Francesco Saverio Pavone, Ludovico Silvestri, Lapo Turrini, Francesco Vanzi, Duccio Fanelli

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In one paragraph

Article in Journal of computational neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. 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

10 authors.

Lorenzo ChicchiDepartment of Physics and Astronomy, University of Florence, Sesto Fiorentino, Florence, Italy.ORCID http://orcid.org/0000-0003-4931-0651
Gloria CecchiniDepartment of Physics and Astronomy, University of Florence, Sesto Fiorentino, Florence, Italy. dott.gloriacecchini@gmail.com.ORCID http://orcid.org/0000-0003-3504-7039
Ihusan AdamDepartment of Physics and Astronomy, University of Florence, Sesto Fiorentino, Florence, Italy.
Giuseppe de VitoEuropean Laboratory for Non-Linear Spectroscopy, Sesto Fiorentino, Florence, Italy.
Roberto LiviDepartment of Physics and Astronomy, University of Florence, Sesto Fiorentino, Florence, Italy.
Francesco Saverio PavoneDepartment of Physics and Astronomy, University of Florence, Sesto Fiorentino, Florence, Italy.
Ludovico SilvestriDepartment of Physics and Astronomy, University of Florence, Sesto Fiorentino, Florence, Italy.
Lapo TurriniDepartment of Physics and Astronomy, University of Florence, Sesto Fiorentino, Florence, Italy.
Francesco VanziEuropean Laboratory for Non-Linear Spectroscopy, Sesto Fiorentino, Florence, Italy.
Duccio FanelliDepartment of Physics and Astronomy, University of Florence, Sesto Fiorentino, Florence, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An inverse procedure is developed and tested to recover functional and structural information from global signals of brains activity. The method assumes a leaky-integrate and fire model with excitatory and inhibitory neurons, coupled via a directed network. Neurons are endowed with a heterogenous current value, which sets their associated dynamical regime. By making use of a heterogenous mean-field approximation, the method seeks to reconstructing from global activity patterns the distribution of in-coming degrees, for both excitatory and inhibitory neurons, as well as the distribution of the assigned currents. The proposed inverse scheme is first validated against synthetic data. Then, time-lapse acquisitions of a zebrafish larva recorded with a two-photon light sheet microscope are used as an input to the reconstruction algorithm. A power law distribution of the in-coming connectivity of the excitatory neurons is found. Local degree distributions are also computed by segmenting the whole brain in sub-regions traced from annotated atlas.

Indexed as

Models, NeurologicalZebrafishAlgorithmsAnimalsNeuronsHeterogeneous mean field approximationLeak integrate and fireNetwork reconstructionNeuroscienceZebrafish larva

Identifiers

PMID33826050
PMCPMC8046699

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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.