https://www.ncbi.nlm.nih.gov/pubmed/29975722
An open-source tool for analysis and automatic identification of dendritic spines using machine learning.
Author information
- 1
- Neuronal Signal Transduction, Max Planck Florida Institute for Neuroscience, Jupiter, Florida, United States of America.
- 2
- Neuroscience, Oregon Health and Science University School of Medicine, Portland, Oregon, United States of America.
Abstract
Synaptic plasticity, the cellular basis for learning and memory, is mediated by a complex biochemical network of signaling proteins. These proteins are compartmentalized in dendritic spines, the tiny, bulbous, post-synaptic structures found on neuronal dendrites. The ability to screen a high number of molecular targets for their effect on dendritic spine structural plasticity will require a high-throughput imaging system capable of stimulating and monitoring hundreds of dendritic spines in various conditions. For this purpose, we present a program capable of automatically identifying dendritic spines in live, fluorescent tissue. Our software relies on a machine learning approach to minimize any need for parameter tuning from the user. Custom thresholding and binarization functions serve to "clean" fluorescent images, and a neural network is trained using features based on the relative shape of the spine perimeter and its corresponding dendritic backbone. Our algorithm is rapid, flexible, has over 90% accuracy in spine detection, and bundled with our user-friendly, open-source, MATLAB-based software package for spine analysis.
- PMID:
- 29975722
- DOI:
- 10.1371/journal.pone.0199589
시냅시스 가소성
척수의 Dentric cell 의 변화는 learning 과 memory 에 중요.
NN 으로 이것을 in live 로 구분하는 프로그램.
미국, 플로리다, 오리건, 신경과학.
user-friendly, open-source, MATLAB-based software package
segmentation -> training NN, 221 values (feature vectors), conjugated propagation algorithm
https://github. com/mikeusru/Braintown.
2018 PLoS One PLoS One An open-source tool for analysis and automatic identification of dendritic spines using machine learning.pdf
