ArticleNature methods2023
Statistically unbiased prediction enables accurate denoising of voltage imaging data.
Article in Nature methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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Who cites it
41 citing papers in PubMed.
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- Highly attenuated dendritic propagation of isolated synaptic potentials in vivo.Science advances · 2026Article
- A versatile platform for two-photon neuronal population voltage imaging across cortical depths.Nature methods · 2026Article
- High-fidelity fast fluorescence lifetime imaging by event-based denoising.Nature biotechnology · 2026Article
- A developmental shift in glucocorticoid receptor expression preserves glucocorticoid sensitivity in the adult suprachiasmatic nucleus.PLoS biology · 2026Article
- Three-dimensional voltage imaging in live larval zebrafish brains using fully genetically encoded voltage indicator.Scientific reports · 2026Article
- Heterogeneous evolution of pancreatic cancer microvasculature revealed by longitudinal intravital imaging.Cancer cell international · 2026Article
- Enhancing biomedical optical volumetric imaging via self-supervised orthogonal learning.Science advances · 2026Article
- MiniFAST: a sensitive and fast miniaturized microscope forNeurophotonics · 2026Article
- Zebrafish Ace2N-mNeon expression toolkit forNeurophotonics · 2026Article
- Voltage imaging as a window into neural computation.Neurophotonics · 2026Article
- CaBLAM: a high-contrast bioluminescent CaNature methods · 2026Article
- Model-Driven Deep Learning Enables Speckle-Free Holography for 3D Parallel Nanofabrication.Research (Washington, D.C.) · 2026Article
- NeuronID: An automatic toolkit for identifying neurons in two-photon calcium imaging data.PloS one · 2026Article
- Optical Approaches to Dissect the Structure and Dynamics of the Synapse at Nanoscale Resolution.Advances in neurobiology · 2026Review
- Noise Sources and Strategies for Signal Quality Improvement in Biological Imaging: A Review Focused on Calcium and Cell Membrane Voltage Imaging.Biosensors · 2026Review
- Real-time self-supervised denoising for high-speed fluorescence neural imaging.Nature communications · 2025Article
- Sensitive red fluorescent indicators for real-time visualization of potassium ion dynamics in vivo.PLoS biology · 2025Article
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25 authors.
Funding
Abstract
Here we report SUPPORT (statistically unbiased prediction utilizing spatiotemporal information in imaging data), a self-supervised learning method for removing Poisson-Gaussian noise in voltage imaging data. SUPPORT is based on the insight that a pixel value in voltage imaging data is highly dependent on its spatiotemporal neighboring pixels, even when its temporally adjacent frames alone do not provide useful information for statistical prediction. Such dependency is captured and used by a convolutional neural network with a spatiotemporal blind spot to accurately denoise voltage imaging data in which the existence of the action potential in a time frame cannot be inferred by the information in other frames. Through simulations and experiments, we show that SUPPORT enables precise denoising of voltage imaging data and other types of microscopy image while preserving the underlying dynamics within the scene.
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