The rhythms generated by the stomatogastric and cardiac ganglia of the Jonah crab are surprisingly robust but differentially sensitive to acute changes in extracellular pH from pH 5.5 to 10.4.

Reliable neuronal physiology can arise from variable and inefficient morphologies.

Animal-to-animal variability in neuronal geometry may be compensated for by compact electrotonic structure.

Neurite geometry enables expansive and highly-branched neuronal structures to operate like single electrical compartments and simple linear integrators.

Nuanced changes in the mechanism of oscillation in reciprocally inhibitory circuits can profoundly alter the circuit stability in response to perturbations and inputs.

Deep neural networks can be trained to automatically find mechanistic models which quantitatively agree with experimental data, providing new opportunities for building and visualizing interpretable models of neural dynamics.

The mechanism that couples two rhythmic circuits is maintained over a large temperature range although both circuits are temperature-sensitive.

Neural networks like the crustacean cardiac ganglion employ multi-faceted compensatory mechanisms to achieve the stability and robustness that are critical to long-term function.

Mapping spike patterns from a small identified circuit reveals the diversity and complexity of circuit dynamics across animals and in response to perturbations.

Animal-to-animal variability in neural circuit elements is often hidden under normal conditions, but becomes functionally relevant when the system is challenged by injury.