C. elegans as a Platform for Multimodal Neural Data Integration

Abstract

Systems neuroscience has traditionally been fragmented into investigations at discrete levels of organization, creating methodological and conceptual gaps that hinder unified understanding of neural function. This thesis examines the nematode Caenorhabditis elegans as a platform for integrating diverse neural data modalities, offering a pathway to bridge these gaps. The hermaphrodite C. elegans, with its completely mapped connectome, optical transparency, genetic tractability, and stereotyped nervous system of only 302 neurons, presents an opportunity for comprehensive measurements across multiple dimensions of neural function. The review is organized around three fundamental neural data modalities accessible in C. elegans: (1) molecular genetic profiles, (2) network connectivity, and (3) neural activity dynamics. Historically studied in isolation, these complementary data types are increasingly being bridged through technological and computational innovations. We examine experimental advances enabling whole-nervous-system measurements of these modalities, as well as data standardization efforts and computational frameworks for cross-modal integration. While understanding the relationship between neural activity and behavior remains a fundamental goal of systems neuroscience, this thesis focuses on neural data acquisition and integration rather than behavioral analysis, which has been extensively covered elsewhere.1 We conclude with some original proposals to overcome current limitations in multimodal data acquisition and synthesis, and suggest future directions toward a holistic understanding of how molecular components, network connectivity, and cellular physiology collectively give rise to neural function in C. elegans. These integrative approaches establish a roadmap that may eventually scale to more complex nervous systems and advance our understanding of neural computation across species.