PUBLICATION
A deep learning framework for automated and generalized synaptic event analysis
- Authors
- O'Neill, P.S., Baccino-Calace, M., Rupprecht, P., Lee, S., Hao, Y.A., Lin, M.Z., Friedrich, R.W., Mueller, M., Delvendahl, I.
- ID
- ZDB-PUB-250307-7
- Date
- 2025
- Source
- eLIFE 13: (Other)
- Registered Authors
- Keywords
- D. melanogaster, data analysis, electrophysiology, human, imaging, machine learning, mouse, neurons, neuroscience, synaptic transmission, zebrafish
- MeSH Terms
-
- Deep Learning*
- Animals
- Synapses*/physiology
- Synaptic Transmission/physiology
- Mice
- PubMed
- 40042890 Full text @ Elife
Citation
O'Neill, P.S., Baccino-Calace, M., Rupprecht, P., Lee, S., Hao, Y.A., Lin, M.Z., Friedrich, R.W., Mueller, M., Delvendahl, I. (2025) A deep learning framework for automated and generalized synaptic event analysis. eLIFE. 13:.
Abstract
Quantitative information about synaptic transmission is key to our understanding of neural function. Spontaneously occurring synaptic events carry fundamental information about synaptic function and plasticity. However, their stochastic nature and low signal-to-noise ratio present major challenges for the reliable and consistent analysis. Here, we introduce miniML, a supervised deep learning-based method for accurate classification and automated detection of spontaneous synaptic events. Comparative analysis using simulated ground-truth data shows that miniML outperforms existing event analysis methods in terms of both precision and recall. miniML enables precise detection and quantification of synaptic events in electrophysiological recordings. We demonstrate that the deep learning approach generalizes easily to diverse synaptic preparations, different electrophysiological and optical recording techniques, and across animal species. miniML provides not only a comprehensive and robust framework for automated, reliable, and standardized analysis of synaptic events, but also opens new avenues for high-throughput investigations of neural function and dysfunction.
Genes / Markers
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Orthology
Engineered Foreign Genes
Mapping