Cascade is a deep learning-based method for inferring neuronal spike rates from calcium imaging signals (ΔF/F traces). It uses convolutional neural networks trained on a large ground-truth database of simultaneous electrophysiology and calcium recordings. The original publication in 2021 was trained on a broad range of datasets; more recent versions were trained on mouse spinal cord data and, most recently, on variants of the new sensor GCaMP8. GIF source: https://gcamp6f.com/2026/02/17/cascadetorch-a-pytorch-version-of-cascade-for-spike-inference/