Statistical Atlas of C. elegans Neurons

Erdem Varol, Amin Nejatbakhsh, Ruoxi Sun, Gonzalo Mena, Eviatar Yemini, Oliver Hobert, Liam Paninski

    Research output: Chapter in Book/Report/Conference proceedingConference contribution


    Constructing a statistical atlas of neuron positions in the nematode Caenorhabditis elegans enables a wide range of applications that require neural identity. These applications include annotating gene expression, extracting calcium activity, and evaluating nervous-system mutations. Large complete sets of neural annotations are necessary to determine canonical neuron positions and their associated confidence regions. Recently, a transgene of C. elegans (“NeuroPAL”) has been introduced to assign correct identities to all neurons in the worm via a deterministic, fluorescent colormap. This strain has enabled efficient and accurate annotation of worm neurons. Using a dataset of 10 worms, we propose a statistical model that captures the latent means and covariances of neuron locations, with efficient optimization strategies to infer model parameters. We demonstrate the utility of this model in two critical applications. First, we use our trained atlas to automatically annotate neuron identities in C. elegans at the state-of-the-art rate. Second, we use our atlas to compute correlations between neuron positions, thereby determining covariance in neuron placement. The code to replicate the statistical atlas is distributed publicly at

    Original languageEnglish (US)
    Title of host publicationMedical Image Computing and Computer Assisted Intervention – MICCAI 2020 - 23rd International Conference, Proceedings
    EditorsAnne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz
    PublisherSpringer Science and Business Media Deutschland GmbH
    Number of pages11
    ISBN (Print)9783030597214
    StatePublished - 2020
    Event23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020 - Lima, Peru
    Duration: Oct 4 2020Oct 8 2020

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume12265 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349


    Conference23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • General Computer Science


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