Targeted approaches to delineate neuronal morphology during early development.

development morphology neonatal mice neural circuit neural labeling

Journal

Frontiers in cellular neuroscience
ISSN: 1662-5102
Titre abrégé: Front Cell Neurosci
Pays: Switzerland
ID NLM: 101477935

Informations de publication

Date de publication:
2023
Historique:
received: 15 07 2023
accepted: 18 09 2023
medline: 19 10 2023
pubmed: 19 10 2023
entrez: 19 10 2023
Statut: epublish

Résumé

Understanding the developmental changes that affect neurons is a key step in exploring the assembly and maturation of neural circuits in the brain. For decades, researchers have used a number of labeling techniques to visualize neuronal morphology at different stages of development. However, the efficiency and accuracy of neuronal labeling technologies are limited by the complexity and fragility of neonatal brains. In this review, we illustrate the various labeling techniques utilized for examining the neurogenesis and morphological changes occurring during the early stages of development. We compare the advantages and limitations of each technique from different aspects. Then, we highlight the gaps remaining in our understanding of the structure of neurons in the neonatal mouse brain.

Identifiants

pubmed: 37854514
doi: 10.3389/fncel.2023.1259360
pmc: PMC10579594
doi:

Types de publication

Journal Article Review

Langues

eng

Pagination

1259360

Informations de copyright

Copyright © 2023 Liu, Li, Ren and Li.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Bimin Liu (B)

State Key Laboratory of Digital Medical Engineering, School of Biomedical Engineering, Hainan University, Haikou, China.
Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, China.

Yuxiao Li (Y)

State Key Laboratory of Digital Medical Engineering, School of Biomedical Engineering, Hainan University, Haikou, China.
Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, China.

Miao Ren (M)

State Key Laboratory of Digital Medical Engineering, School of Biomedical Engineering, Hainan University, Haikou, China.
Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, China.

Xiangning Li (X)

State Key Laboratory of Digital Medical Engineering, School of Biomedical Engineering, Hainan University, Haikou, China.
Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, China.
Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Sciences, HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, China.

Classifications MeSH