Overview
Pipeline for 2D voltage imaging videos that flags ‘events’ (fast, localized changes) using statistical detectors inspired by radar signal processing, producing maps and summaries for downstream analysis.
Voltage imaging produces high-frame-rate videos where brightness changes correspond (imperfectly) to changes in neural electrical activity. The practical challenge is separating true events from noise, motion, and background drift. I built and tested detectors that highlight candidate events and produce interpretable outputs for scientists to review.
What I built
- Preprocessing routines for voltage imaging videos (normalization, background handling, and region-wise aggregation).
- Event detectors that score pixels/regions over time and surface candidate events for review.
- Evaluation utilities to compare detector behavior across recordings and parameter settings.
- Exportable visual summaries (event maps and time-series traces) to support interpretation.
How it works
- Treat each pixel/region as a time-series.
- Estimate a baseline/noise profile from nearby frames.
- Apply statistical tests to flag frames/regions whose changes are unlikely under the noise model.
- Aggregate detections into event maps and interpretable summaries.
