Fig. 2: Performance validation on simulated data.
From: Statistically unbiased prediction enables accurate denoising of voltage imaging data
a, Synthetic population voltage imaging data. From left to right are the clean, noisy, SUPPORT, DeepCAD-RT and PMD denoised data. Baseline and activity components are decomposed from the data. The baseline component with a gray colormap and activity component with a hot colormap are overlaid. Magnified views of the boxed regions are presented underneath with the consecutive frames of the spiking event (t = 0.222 s). Scale bar, 40 μm. b, PSNR of the baseline-corrected data before and after denoising data with different spike widths. Clean data were used as the ground truth for PSNR calculation. c, The left shows a box-and-whisker plot showing Pearson correlation coefficients before and after denoising data with different spike widths. The right shows a line chart showing average Pearson correlation coefficient before and after denoising data with different spike widths. Two-sided one-way analysis of variance with Tukey–Kramer post hoc test was used. n = 116 for each test, which represents the number of neurons (NS, not significant, *P < 0.1, **P < 0.01, ***P < 0.001). d, Single-pixel fluorescence traces extracted from baseline-corrected data. From top to bottom: clean, noisy, SUPPORT, DeepCAD-RT and PMD denoised data. The left shows each single-pixel trace occupies each row. The right shows three representative single-pixel traces visualized with different colors. e, Single cell fluorescence traces near spiking event extracted from baseline-corrected data. From top to bottom: clean, noisy, SUPPORT, DeepCAD-RT and PMD denoised data. From left to right: changing spike widths of 1, 3, 5, 7 and 9 ms.
