Fig. 1: SUPPORT can be applied to functional imaging data with a fast dynamics indicator.
From: Statistically unbiased prediction enables accurate denoising of voltage imaging data
a, SUPPORT’s self-supervised learning scheme and previous methods that exploit temporally adjacent frames for denoising functional imaging data with slow and fast dynamics indicators. Functional imaging data are represented by green and red surfaces, which indicate the receptive field and prediction target area, respectively. b, Noisy frames are fed into the SUPPORT network and output the denoised image. Red tiles indicate the receptive field of the SUPPORT network, which uses spatially adjacent pixels in the same frame. c, Impulse response of the SUPPORT network on the current frame. The magnified view is presented on the right side. Response value of the center pixel is 0, which forces the network to predict the center pixel without using it. d, In vivo population voltage imaging data. The left shows the raw data and the right shows the SUPPORT-denoised data. Baseline and activity components are decomposed from raw data and SUPPORT-denoised data. The baseline component with gray colormap and activity component with hot colormap are overlaid. Magnified views of the boxed regions are presented below at the time points near spikes. Consecutive frames of two spikes (t = 0.2650 and 2.2325 s).
