Evidence map›Paper›PMID 38517838›Full record

ArticlePloS one2024

See Elegans: Simple-to-use, accurate, and automatic 3D detection of neural activity from densely packed neurons.

Enrico Lanza, Valeria Lucente, Martina Nicoletti, Silvia Schwartz, Ilaria F Cavallo, Davide Caprini, Christopher W Connor, Mashel Fatema A Saifuddin, Julia M Miller, Noelle D L'Etoile and 1 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 96% of its field
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

1 citing paper in PubMed, 0 citations in OpenAlex.

  1. Article
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

11 authors at 4 institutions in 2 countries.

Enrico LanzaCenter for Life Nano- and Neuro-Science@Sapienza, Istituto Italiano di Tecnologia (IIT), Rome, Italy.ORCID 0000-0001-7224-8900
Valeria LucenteCenter for Life Nano- and Neuro-Science@Sapienza, Istituto Italiano di Tecnologia (IIT), Rome, Italy.
Martina NicolettiCenter for Life Nano- and Neuro-Science@Sapienza, Istituto Italiano di Tecnologia (IIT), Rome, Italy.ORCID 0000-0003-0154-0482
Silvia SchwartzCenter for Life Nano- and Neuro-Science@Sapienza, Istituto Italiano di Tecnologia (IIT), Rome, Italy.
Ilaria F CavalloCenter for Life Nano- and Neuro-Science@Sapienza, Istituto Italiano di Tecnologia (IIT), Rome, Italy.
Davide CapriniCenter for Life Nano- and Neuro-Science@Sapienza, Istituto Italiano di Tecnologia (IIT), Rome, Italy.
Christopher W ConnorDepartment of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States of America.
Mashel Fatema A SaifuddinDepartment of Cell and Tissue Biology, University of California, San Francisco, San Francisco, CA, United States of America.
Julia M MillerDepartment of Cell and Tissue Biology, University of California, San Francisco, San Francisco, CA, United States of America.
Noelle D L'EtoileDepartment of Cell and Tissue Biology, University of California, San Francisco, San Francisco, CA, United States of America.
Viola FolliCenter for Life Nano- and Neuro-Science@Sapienza, Istituto Italiano di Tecnologia (IIT), Rome, Italy.
Italian Institute of Technology · ITUniversity of California, San Francisco · USBrigham and Women's Hospital · USUniversità Campus Bio-Medico · IT

Funding

Pan-neuronal functional imaging and anesthesiaR35GM145319 · NIGMS · BRIGHAM AND WOMEN'S HOSPITAL · PI Christopher W Connor · 2022 to 2026
$1.8M
NIGMS NIH HHS R35 GM145319
6 · The paper itself

Abstract

In the emerging field of whole-brain imaging at single-cell resolution, which represents one of the new frontiers to investigate the link between brain activity and behavior, the nematode Caenorhabditis elegans offers one of the most characterized models for systems neuroscience. Whole-brain recordings consist of 3D time series of volumes that need to be processed to obtain neuronal traces. Current solutions for this task are either computationally demanding or limited to specific acquisition setups. Here, we propose See Elegans, a direct programming algorithm that combines different techniques for automatic neuron segmentation and tracking without the need for the RFP channel, and we compare it with other available algorithms. While outperforming them in most cases, our solution offers a novel method to guide the identification of a subset of head neurons based on position and activity. The built-in interface allows the user to follow and manually curate each of the processing steps. See Elegans is thus a simple-to-use interface aimed at speeding up the post-processing of volumetric calcium imaging recordings while maintaining a high level of accuracy and low computational demands. (Contact: enrico.lanza@iit.it).

Indexed as

Caenorhabditis elegansNeuronsAlgorithmsAnimalsBrainMicroscopy, Fluorescence

Identifiers

PMID38517838
PMCPMC10959381
OpenAlexW4393097315

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.