FPmotion an Automated Signal Processing and Statistical Analysis Tool for Fiber Photometry Data

Fiber photometry measures neural activity in vivo from genetically encoded indicators. Recordings generate large datasets that require extensive preprocessing and robust statistical methods for meaningful interpretation. However, existing analysis tools demand programming expertise, limiting accessibility. Here we describe FPmotion , a comprehensive, user-friendly software platform for batchwise processing, integration, and statistical analysis of fiber photometry data with or without accompanying behavioral information. FPmotion performs filtering, isosbestic regression, ΔF/F computation, detrending, and z-scoring. It also extracts detailed peak properties at whole-file, block-level, and individual-peak resolution. When behavioral data is provided, FPmotion automatically identifies behavioral bouts, computes bout-level statistics, performs peri-event signal extraction, and supports multi-group comparisons through ANOVA- and LMEM-based statistical frameworks. All analyses generate publication-ready figures and structured CSV outputs suitable for downstream workflows. FPmotion also introduces a dedicated alignment module for peri-event signal analysis. This module applies dynamic time warping followed by barycenter averaging to realign peri-event traces while preserving the behavioral time anchor, producing cleaner and more temporally coherent peri-event motifs. We demonstrate FPmotion’s capabilities using the dlight1.1 sensor to measure dopamine responses from ventral striatum in behaving mice before and after amphetamine treatment. Together, FPmotion offers a fully automated framework for FP data analysis that improves interpretability and accessibility while reducing analysis time substantially.