Neural Anatomy and Optical Microscopy (NAOMi) Simulation for evaluating calcium imaging methods

Abstract The past decade has seen a multitude of new in vivo functional imaging methodologies. However, the lack of ground-truth comparisons or evaluation metrics makes large-scale, systematic validation impossible. Here we provide a new framework for evaluating TPM methods via in silico Neural Anatomy and Optical Microscopy (NAOMi) simulation. Our computationally efficient model generates large anatomical volumes of mouse cortex, simulates neural activity, and incorporates optical propagation and scanning to create realistic calcium imaging datasets. We verify NAOMi simulations against in vivo two-photon recordings from mouse cortex. We leverage this access to in silico ground truth to perform direct comparisons between different segmentation algorithms and optical designs. We find modern segmentation algorithms extract strong neural time-courses comparable to estimation using oracle spatial information, but with an increase in the false positive rate. Comparison between optical setups demonstrate improved resilience to motion artifacts in sparsely labeled samples using Bessel beams, increased signal-to-noise ratio and cell-count using low numerical aperture Gaussian beams and nuclear GCaMP, and more uniform spatial sampling with temporal focusing versus multi-plane imaging. Overall, by leveraging the rich accumulated knowledge of neural anatomy and optical physics, we provide a powerful new tool to assess and develop important methods in neural imaging.