Evidence map›Paper›PMID 32405029›Full record

ArticleScientific reports2020

Anatomically revealed morphological patterns of pyramidal neurons in layer 5 of the motor cortex.

Siqi Jiang, Yue Guan, Shangbin Chen, Xueyan Jia, Hong Ni, Yalun Zhang, Yutong Han, Xue Peng, Can Zhou, Anan Li and 2 more

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
3.6field-weighted citation impact, top 7% 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

18 citing papers in PubMed, 30 citations in OpenAlex.

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  10. Learning and Control in Motor Cortex across Cell Types and Scales.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024
    Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 3 institutions in 1 country.

Siqi JiangBritton Chance Center for Biomedical Photonics, Key Laboratory for Biomedical Photonics of Ministry of Education, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, 430074, China.
Yue GuanBritton Chance Center for Biomedical Photonics, Key Laboratory for Biomedical Photonics of Ministry of Education, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, 430074, China.
Shangbin ChenBritton Chance Center for Biomedical Photonics, Key Laboratory for Biomedical Photonics of Ministry of Education, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, 430074, China.
Xueyan JiaHUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, 215100, China.
Hong NiBritton Chance Center for Biomedical Photonics, Key Laboratory for Biomedical Photonics of Ministry of Education, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, 430074, China.
Yalun ZhangBritton Chance Center for Biomedical Photonics, Key Laboratory for Biomedical Photonics of Ministry of Education, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, 430074, China.
Yutong HanBritton Chance Center for Biomedical Photonics, Key Laboratory for Biomedical Photonics of Ministry of Education, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, 430074, China.
Xue PengBritton Chance Center for Biomedical Photonics, Key Laboratory for Biomedical Photonics of Ministry of Education, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, 430074, China.
Can ZhouBritton Chance Center for Biomedical Photonics, Key Laboratory for Biomedical Photonics of Ministry of Education, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, 430074, China.
Anan LiBritton Chance Center for Biomedical Photonics, Key Laboratory for Biomedical Photonics of Ministry of Education, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, 430074, China.
Qingming LuoBritton Chance Center for Biomedical Photonics, Key Laboratory for Biomedical Photonics of Ministry of Education, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, 430074, China.
Hui GongBritton Chance Center for Biomedical Photonics, Key Laboratory for Biomedical Photonics of Ministry of Education, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, 430074, China. huigong@mail.hust.edu.cn.
Wuhan National Laboratory for Optoelectronics · CNHuazhong University of Science and Technology · CNSuzhou Research Institute · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neuronal cell types are essential to the comprehensive understanding of the neuronal function and neuron can be categorized by their anatomical property. However, complete morphology data for neurons with a whole brain projection, for example the pyramidal neurons in the cortex, are sparse because it is difficult to trace the neuronal fibers across the whole brain and acquire the neuron morphology at the single axon resolution. Thus the cell types of pyramidal neurons have yet to be studied at the single axon resolution thoroughly. In this work, we acquire images for a Thy1 H-line mouse brain using a fluorescence micro-optical sectioning tomography system. Then we sample 42 pyramidal neurons whose somata are in the layer 5 of the motor cortex and reconstruct their morphology across the whole brain. Based on the reconstructed neuronal anatomy, we analyze the axonal and dendritic fibers of the neurons in addition to the soma spatial distributions, and identify two axonal projection pattern of pyramidal tract neurons and two dendritic spreading patterns of intratelencephalic neurons. The raw image data are available upon request as an additional asset to the community. The morphological patterns identified in this work can be a typical representation of neuron subtypes and reveal the possible input-output function of a single pyramidal neuron.

Indexed as

AnimalsAxonsDendritesFluorescent Antibody TechniqueMiceMotor CortexMotor NeuronsPyramidal Cells

Identifiers

PMID32405029
PMCPMC7220918
OpenAlexW3025417206

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.