An interactive time series image analysis software for dendritic spines.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
20 07 2022
20 07 2022
Historique:
received:
06
03
2022
accepted:
05
07
2022
entrez:
20
7
2022
pubmed:
21
7
2022
medline:
23
7
2022
Statut:
epublish
Résumé
Live fluorescence imaging has demonstrated the dynamic nature of dendritic spines, with changes in shape occurring both during development and in response to activity. The structure of a dendritic spine correlates with its functional efficacy. Learning and memory studies have shown that a great deal of the information stored by a neuron is contained in the synapses. High precision tracking of synaptic structures can give hints about the dynamic nature of memory and help us understand how memories evolve both in biological and artificial neural networks. Experiments that aim to investigate the dynamics behind the structural changes of dendritic spines require the collection and analysis of large time-series datasets. In this paper, we present an open-source software called SpineS for automatic longitudinal structural analysis of dendritic spines with additional features for manual intervention to ensure optimal analysis. We have tested the algorithm on in-vitro, in-vivo, and simulated datasets to demonstrate its performance in a wide range of possible experimental scenarios.
Identifiants
pubmed: 35859092
doi: 10.1038/s41598-022-16137-y
pii: 10.1038/s41598-022-16137-y
pmc: PMC9300710
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
12405Subventions
Organisme : NINDS NIH HHS
ID : R01 NS112485
Pays : United States
Organisme : European Research Council
ID : 679175
Pays : International
Informations de copyright
© 2022. The Author(s).
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