Unifying community-wide whole-brain imaging datasets enables robust automated neuron identification and reveals determinants of neuron positioning in <i>C. elegans</i>.

ABSTRACT: We develop a data harmonization approach for C. elegans volumetric microscopy data, still or video, consisting of a standardized format, data pre-processing techniques, and a set of human-in-the-loop machine learning based analysis software tools. We unify a diverse collection of 118 whole-brain neural activity imaging datasets from 5 labs, storing these and accompanying tools in an online repository called WormID (wormid.org). We use this repository to train three existing automated cell identification algorithms to, for the first time, enable accuracy in neural identification that generalizes across labs, approaching human performance in some cases. We mine this repository to identify factors that influence the developmental positioning of neurons. To facilitate communal use of th

SUBMITTER: Sprague DY 

PROVIDER: S-EPMC11092512 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature