| title | c302 | ||||||
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| created | 2025-01-15 | ||||||
| updated | 2026-05-06 | ||||||
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The c302 model framework is a computational platform for generating network models of the nematode Caenorhabditis elegans nervous system, developed as part of the OpenWorm project. The name "c302" refers to the 302 neurons that comprise the complete connectome of the adult C. elegans hermaphrodite, making it one of the few complete neural connectome models available in computational neuroscience. This [[connectomics]]-driven approach provides a unique testbed for studying [[neural-mass-models]] and [[network-dynamics]] in a biologically constrained system where every neuron and synapse has been empirically mapped.
The c302 framework allows researchers to generate neuronal network models at multiple levels of anatomical and physiological detail, from simplified [[neuron]] representations to biophysically detailed conductance-based models. Unlike traditional single-neuron models, c302 models the entire nervous system of an organism—the nematode C. elegans—enabling whole-organism simulations of neural activity and behavior. C. elegans has been a foundational organism in neuroscience due to its completely mapped nervous system. Every neuron has been named, its connections documented, and its role in various behaviors characterized. The c302 framework leverages this wealth of connectomic data to create computational models that can be simulated and analyzed using standardized tools and formats.
The c302 framework offers several distinctive capabilities that set it apart from other neural modeling approaches. First, it provides a choice of four parameter sets representing increasing levels of biophysical detail: Parameter Set A uses leaky integrate-and-fire (LIF) neurons with spike-triggered synaptic transmission; Parameter Set B adds firing rate-based activity modeling and gap junction connections; Parameter Set C implements single-compartment, conductance-based neurons with Hodgkin-Huxley style ion channels; and Parameter Set D extends this to multicompartmental neurons with detailed morphologies.
Second, the framework supports flexible network configurations. Users can generate models containing all 302 neurons and 96 muscle cells of the full hermaphrodite, or any subset thereof—such as the 20-neuron pharyngeal circuit or the motor circuits involved in locomotion. This modularity enables researchers to focus on specific neural subsystems without the overhead of the complete nervous system.
Third, c302 generates models in the standardized [[neuroml]] 2 format, which is based on the LEMS (Low Entropy Model Specification) language. This standardization ensures interoperability with a wide range of simulation engines and visualization tools, including [[neuron]], [[nest]], jNeuroML, pyNeuroML, and the Open Source Brain platform.
Fourth, the framework supports multiple synapse types including chemical synapses (excitatory and inhibitory) and electrical gap junctions. Importantly, c302 implements analogue synaptic transmission—a continuous form of synaptic communication that better represents C. elegans neuromuscular junction physiology than the spike-triggered approach commonly used in vertebrate models.
The c302 framework supports multiple levels of biophysical abstraction, each with distinct mathematical formulations. At the simplest level (Parameter Set A), neurons are modeled as leaky integrate-and-fire (LIF) units with membrane potential dynamics described by:
where
The framework implements both chemical synapses with synaptic conductance dynamics and electrical gap junctions modeled as ohmic currents between neuronal compartments. A distinctive feature of c302 is analogue synaptic transmission—a continuous graded form of neurotransmitter release that better represents the physiology of C. elegans neuromuscular junctions compared to the spike-triggered approach common in vertebrate models.
The c302 framework relates to [[the-virtual-brain]] through the broader context of [[neural-mass-models]] and whole-brain modeling methodologies. While TVB operates at the level of brain regions rather than individual neurons, c302 exemplifies multiscale modeling approaches that bridge cellular-level dynamics with network-level phenomena. The techniques developed for c302—particularly parameter optimization, connectivity specification, and model validation—have informed mean-field approximations used in larger-scale brain simulations.
Researchers working on [[personalized-brain-modeling]] may draw inspiration from c302's approach to constraining models with empirical [[structural-connectivity]] data. The framework demonstrates how detailed single-neuron and circuit-level models can inform the parameterization of population-level representations. Additionally, the NeuroML-based format allows c302-generated networks to interface with broader neuroscience modeling ecosystems that feed into whole-brain simulation frameworks alongside [[tvb-nest]] adapters and other connectivity pipelines.
The c302 framework represents an important reference point for understanding how [[connectome]]-level constraints can be applied at different scales. While TVB typically works with [[structural-connectivity]] matrices derived from [[diffusion-imaging]] and tractography, c302 shows how empirically mapped neuronal wiring diagrams can directly constrain [[spiking-neural-networks]] simulations. This approach has implications for [[parameter-estimation]] methods in whole-brain models, where the challenge of fitting model parameters to empirical data remains an active research area.
- [[neuroml]] — The standardized model specification language used by c302 for network description
- [[neuron]] — The simulation environment capable of running multicompartmental c302 models
- [[nest]] — Alternative simulator for large-scale spiking neural network modeling
- [[brain-network]] — The broader concept that c302 instantiates for a complete nervous system
- [[connectome]] — The full neural wiring diagram that c302 implements computationally
- [[structural-connectivity]] — The empirical connectivity data that constrains c302 models
- [[spiking-neural-networks]] — The computational paradigm that c302 implements at scale
- pyNeuroML — Python-based tool for working with NeuroML models
- Open Source Brain — Online platform for visualizing and simulating c302-generated networks