Asymmetry Factors Shaping Regular and Irregular Bursting Rhythms in Central Pattern Generators

Abstract

Central Pattern Generator (CPG) circuits are neural networks that generate rhythmic motor patterns. These circuits are typically built of half-center oscillator subcircuits with reciprocally inhibitory connections. Another common property in many CPGs is the remarkable rich spiking-bursting dynamics of their constituent cells, which balance robustness and flexibility to generate their joint coordinated rhythms. In this paper, we use conductance-based models and realistic connection topologies inspired by the crustacean pyloric CPG to address the study of asymmetry factors shaping CPG bursting rhythms. In particular, we assess the role of asymmetric maximal synaptic conductances, time constants and gap-junction connectivity to establish the regularity of half-center oscillator based CPGs. We map and characterize the synaptic parameter space that lead to regular and irregular bursting activity in these networks. The analysis indicates that asymmetric configurations display robust regular rhythms and that large regions of both regular and irregular but coordinated rhythms exist as a function of the asymmetry in the circuit. Our results show that asymmetry both in the maximal conductances and in the temporal dynamics of mutually inhibitory neurons can synergistically contribute to shape wide regimes of regular spiking-bursting activity in CPGs. Finally, we discuss how a closed-loop protocol driven by a regularity goal can be used to find and characterize regular regimes when there is not time to perform an exhaustive search, as in most experimental studies.

Neural Coding With Bursts—Current State and Future Perspectives

“…Elices and Varona ( 2017 ) study the role of connectivity on bursting rhythms in a central pattern generator (CPG) network responsible for the oscillatory activity that is needed for rhythmic motor patterns such as walking. Using conductance-based neuron models they show how asymmetries in these networks shape the (ir)regularity of the network activity.…”

“…An overview of those mechanisms is provided in Section Burst generation. Zakharov et al ( 2016 ) present novel insights into intrinsic and Elices and Varona ( 2017 ) into network burst generation. (B) Detection and analysis of bursts first requires that a burst is identified and separated from other sets of spikes.…”

Detection of Activation Sequences in Spiking-Bursting Neurons by means of the Recognition of Intraburst Neural Signatures

“…This conductance-based model (proposed for snail CPG cells) includes a slow-wave generating mechanism, a spike generating mechanism, an inward calcium current, an intracellular Ca 2+ buffer and a [Ca 2+ ] in -inhibited calcium current. Komendantov-Kononenko model neurons exhibit the rich slow-fast dynamics observed in the spiking-bursting activity of several living neuron types, which underlies their ability to produce cooperative coordinated rhythms 63 . The membrane potential equation is: …”

Dynamics of antiphase bursting modulated by the inhibitory synaptic and hyperpolarization-activated cation currents

“…These complex bifurcations will be studied in details in future. The rhythmic patterns of two-neuron circuit with inhibition coupling, such as the antiphase bursting, are associated with complex nonlinear dynamics and motor patterns (Daun et al, 2009;Nagornov et al, 2016;Elices and Varona, 2017;Ausborn et al, 2018). Especially, the rhythmic patterns have been widely used to control motion of the robot in recent studies (Habu et al, 2019;Li J. et al, 2021;Fukuoka et al, 2022).…”