NeuroSparkSNT: An Eight-Operator Framework for Behavioral Phase Dynamics in C. elegans Neural Simulation

The nematode C. elegans possesses one of the most thoroughly characterized nervous systems in biology, yet existing computational models of its locomotion occupy opposite architectural extremes: biophysi-cally detailed conductance-based simulations that faithfully reproduce single-neuron membrane dynamics but cannot account for the discrete, mutually exclusive transitions between behavioral states, and mean-field rate models that capture certain population-level statistics but sacrifice circuit specificity. Neither class was designed to reproduce the abrupt, all-or-none phase switching—forward crawling, reversal , omega-turn reorientation—that whole-brain calcium imaging has shown to be the defining dynamical signature of freely behaving C. elegans. We present NeuroSparkSNT, an eight-operator framework built directly on the Cook et al. (2019) connectome (114 of 300 neurons, spanning sensory, interneuron, and motor groups), in which a semi-Markov phase controller gates operator activity so that competing loco-motor drives are structurally, not merely numerically, exclusive. Two architectural variants are evaluated under identical biological parameters: a monolithic implementation in which all operators are evaluated at every simulation step, and a pool-dispatch implementation in which only the operators appropriate to the current phase are evaluated. Across twelve quantitative benchmarks calibrated against five independent experimental datasets, the pool-dispatch variant reproduces AVA–AVB interneuron antagonism to within 14% of the calcium-imaging reference (r = −0.477 vs. −0.420), and the omega-turn dwell time matches the experimental value exactly (0.50 s; Pierce-Shimomura et al., 1999). Critically, a six-stimulus generative test—in which stimulus conditions were presented that had never been used to set any model parameter—yields correct behavioral predictions in all six cases, providing evidence that the architecture captures circuit mechanism rather than reproducing calibration data. A biologically grounded stimulus-awareness layer encodes seven documented sensory–interneuron reflex arcs as innate, parameter-free phase biases derived directly from connectome polarity. Seven additional model-derived predictions, including a phase-dependent reversal-latency ratio of 7.3× and a specific interneuron dissociation prediction at PVP, constitute falsifiable experimental targets. We close by outlining a minimal one-variable extension through which the existing dopamine/serotonin and gradient-following components could be unified into a homeostatically regulated foraging agent that requires no externally specified reward function .