Light-field deep learning enables high-throughput, scattering-mitigated calcium imaging.

ABSTRACT: Light-field microscopy (LFM) enables high-throughput functional imaging by scanlessly encoding entire volumes in single snapshots. However, LFM's computational burden and vulnerability to scattering limit its application to biological imaging. We present a light-field strategy for volumetric, scattering-mitigated neural circuit activity monitoring. A physics-based deep neural network, 2PiLnet, is trained with two-photon volumes and one-photon light fields. Light-field videos of jGCaMP8f-expressing neurons are acquired in neocortical brain slices. 2PiLnet reconstructs volumes with two-photon-like contrast and source confinement from scattered, blurry one-photon light fields from fields-of-view for which no two-photon images are provided. This enables automated segmentation and extraction of

SUBMITTER: Howe CL 

PROVIDER: S-EPMC12685042 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature