An integrated workflow for long-term fiber photometry analysis

Abstract

Long-term fiber photometry enables measurement of neural dynamics across hours to days, but these recordings create analytical and reproducibility challenges that are not well addressed by tools developed for short, stimulus-locked experiments. Here we present a software environment for long-term photometry analysis organized around a structured, revisitable workflow for run execution, inspection, and post-run refinement. The software separates correction retuning from downstream event reanalysis, allowing both signal correction and event-analysis settings to be revised after the initial run. We show that correction choice can substantially change the corrected signal itself and that post-run reanalysis can revise event-detection outcomes. The software also preserves tonic and phasic outputs and supports inspection of the same recording at both multiday and session-level scales. Together, these capabilities provide a practical workflow for more interpretable, revisitable, and reproducible analysis of long-term photometry recordings.