Ultrafast Frame-Free Imaging of Neural Activity with Event Cameras

Abstract

Frame-based fluorescence imaging has long defined how neural activity is optically measured. This approach requires acquiring all pixels within an image, regardless of whether they carry meaningful neural dynamics, thereby intrinsically coupling spatial and temporal resolution while increasing data output. Here, we introduce an entirely different, frame-free approach that leverages the sparse nature of neural activity using event-based cameras, which asynchronously report fluorescence changes as spatiotemporal events. Compared with a frame-based camera, our method preserves signal fidelity while eliminating the fixed trade-off between spatial resolution, temporal resolution and data rate, thereby reducing data output by orders of magnitude. Applied to hippocampal preparations we demonstrate that the frame-free approach can resolve both single action potentials and fast network dynamics over large fields of view at kilohertz rates, enabling scalable, ultrafast optical recordings.