SYNCHRONIZATION, EXCITABILITY AND VARIABILITY IN SEQUENTIAL RHYTHMIC ACTIVITY

Rhythmic activity acts as a fundamental mechanism of neural coordination in many neural systems across multiple description levels. In many cases robust sequences build up these rhythms, showing a wide range of variability. In this study, we analyze the interplay between synchronization, excitability, and variability in relation to the sequentiality observed in the pyloric central pattern generator (CPG), a well-known circuit composed of both electrical and chemical synapses.

Previous works found the existence of strong linear relationships between intervals that shape the cycle-by-cycle sequence and its instantaneous period. These relationships called sequential dynamical invariants can be a key mechanism of autonomous motor coordination providing a set of auto-organizing constraints to produce robust yet flexible sequential rhythms. Recent computational studies in circuit models have found a dependence between electrical coupling, the neurons’ excitability, and the presence of these dynamical invariants.

We acquired long intracellular and extracellular recordings from neurons in the pyloric CPG and applied multilevel analyses assessing inter-experiment trends, intra-experiments states, and quantifying cycle-by-cycle relationships. Our results show linear and non-linear dependencies between excitability, variability, and the sequential dynamical invariants. Synchronization between the two electrically coupled PD neurons was related to their excitability.

The results of combining integrated and cycle-by-cycle analyses of the CPG sequential rhythm provide novel insight on autonomous motor coordination in robust yet flexible sequential rhythms.

Research funded by grants PID2024-155923NB-I00, PID2023-149669NB-I00 and CPP2023-010818.