Speaker
Description
Understanding how the vertebrate brain coordinates behavior requires recording its activity across the whole brain and at the speed of neural dynamics. We use light-field microscopy (LFM) to image behaving larval zebrafish volumetrically and at high frame rates, capturing calcium activity across the entire brain while the animal responds to visual stimuli and generates swimming, eye, and fin movements. Because every camera frame encodes a full high-resolution 3D volume, a single experiment yields hundreds of gigabytes of raw light-field frames.
We have built an end-to-end pipeline that runs on the bwForCluster NEMO2 in Freiburg:
(1) Volumetric reconstruction. Every raw light-field frame is deconvolved into a 3D volume by a GPU-accelerated wave-optics solver. We distribute this parallel workload across NEMO2's NVIDIA L40S GPU nodes (four GPUs per job).
(2) Preprocessing and registration. Reconstructed movies are motion-corrected and converted to ΔF/F. Each animal is imaged from a slightly different angle and position, and also has slightly different anatomical brain structures. Mapping brains into a common reference atlas allows us to perform volumetric statistical analyses across animals. These steps require large-memory CPU nodes (128 cores, 512 GB RAM).
(3) Decomposition and aggregation. Each recording is factorized by PCA-whitening plus independent component analysis (PICA) into ~2,500 spatiotemporal components — each a 3D spatial map with a time series. Components are then filtered, clustered (HDBSCAN and k-means) across the whole brain, and curated into a reproducible atlas of functional ensembles.