Unifying community whole-brain imaging datasets enables robust neuron identification and reveals determinants of neuron position in C. elegans.

ABSTRACT: We develop a data harmonization approach for C. elegans volumetric microscopy data, consisting of a standardized format, pre-processing techniques, and human-in-the-loop machine-learning-based analysis tools. Using this approach, we unify a diverse collection of 118 whole-brain neural activity imaging datasets from five labs, storing these and accompanying tools in an online repository WormID (wormid.org). With this repository, we train three existing automated cell-identification algorithms, CPD, StatAtlas, and CRF_ID, to enable accuracy that generalizes across labs, recovering all human-labeled neurons in some cases. We mine this repository to identify factors that influence the developmental positioning of neurons. This growing resource of data, code, apps, and tutorials enables users t

SUBMITTER: Sprague DY 

PROVIDER: S-EPMC11840940 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature