High fidelity estimates of spikes and subthreshold waveforms from 1-photon voltage imaging in vivo
The ability to probe the membrane potential of multiple genetically defined neurons simultaneously would have a profound impact on neuroscience research. Genetically encoded voltage indicators are a promising tool for this purpose, and recent developments have achieved high signal to noise ratio in vivo with 1-photon fluorescence imaging. However, these recordings exhibit several sources of noise that present analysis challenges, namely light scattering, out-of-focus sources, motion, and blood flow. We present a novel signal extraction methodology, Spike-Guided Penalized Matrix Decomposition-Nonnegative Matrix Factorization (SGPMD-NMF), which resolves supra- and sub-threshold voltages with high fidelity, even in the presence of correlated noise. The method incorporates biophysical constraints (shared soma profiles for spiking and subthreshold dynamics) and optical constraints (smoother spatial profiles from defocused vs. in-focus sources) to cleave signal from background. We validated the pipeline using simulated and composite datasets with realistic noise properties. We demonstrate applications to mouse hippocampus expressing paQuasAr3-s or SomArchon, mouse cortex expressing SomArchon or Voltron, and zebrafish spine expressing zArchon1.