- Poster presentation
- Open Access
Regularization of a half-center oscillator network by closed-loop control
BMC Neuroscience volume 16, Article number: P275 (2015)
Central Pattern Generators (CPGs) are neural circuits that control muscle functioning by means of rhythmic patterns. These networks are usually built up on a minimal configuration based on reciprocal inhibitory connections responsible for the production of alternating spiking-bursting activity. Experimental observations in the crustacean pyloric CPG show that most neurons, when isolated, present a highly irregular, in fact chaotic, bursting activity [1–3]. This rich intrinsic dynamics provides flexibility for negotiating rhythms through the reciprocal inhibitory connections between neurons which lead to the regularization of the chaotic behavior when the neurons interact within the circuit .
Closed-loop interactions are typically used in electrophysiological experiments using dynamic clamp protocols  and have been generalized for different description levels of the nervous system . In this work we show that feedback protocols can also be used in theoretical studies to search for specific dynamics or explore the parameter space of a given model. We have built a CPG model based on a minimal network with two neurons connected by bidirectional fast chemical inhibitory synapses. The network generates alternating bursting activity in the neurons, which can be regular or irregular depending on the maximal conductances of the inhibitory synapses. We employ a simple adaptive closed-loop protocol to regularize the alternating chaotic activity of the model (see Figure 1 panel A). This protocol adapts online the maximal conductance of one of the synapsis to achieve the aimed regular alternating bursting activity (see Figure 1, panel B). Moreover, the closed-loop algorithm can be used to automatically map the region of maximal conductance values that lead to regular activity.
Abarbanel HD, Huerta R, Rabinovich MI, Rulkov NF, Rowa PF, Selverston AI: Synchronized action of synaptically coupled chaotic model neurons. Neural Comput. 1996, 8 (8): 1567-1602.
Elson RC, Huerta R, Abarbanel HD, Rabinovich MI, Selverston AI: Dynamic control of irregular bursting in an identified neuron of an oscillatory circuit. J Neurophysiol. 1999, 82 (1): 115-122.
Varona P, Torres JJ, Abarbanel HD, Rabinovich MI, Elson RC: Dynamics of two electrically coupled chaotic neurons: experimental observations and model analysis. Biological Cybernetics. 2001, 84 (2): 91-101.
Selverston AI, Rabinovich MI, Abarbanel HD, Elson R, Szücs A, Pinto RD, Huerta R, Varona P: Reliable circuits from irregular neurons: a dynamical approach to understanding central pattern generators. J Physiology-Paris. 2000, 94 (5): 357-374.
Destexhe A, Bal T (Eds): Dynamic-Clamp: From Principles to Applications. 2009, Springer, New York
Chamorro P, Muñiz C, Levi R, Arroyo D, Rodríguez FB, Varona P: Generalization of the dynamic clamp concept in neurophysiology and behavior. PLoS One. 2012, 7: e40887-
Authors acknowledge support by MINECO TIN2012-30883 and ONRG grant N62909-14-1-N279.
About this article
Cite this article
Elices, I., Varona, P. Regularization of a half-center oscillator network by closed-loop control. BMC Neurosci 16, P275 (2015). https://0-doi-org.brum.beds.ac.uk/10.1186/1471-2202-16-S1-P275
- Central Pattern Generator
- Burst Activity
- Maximal Conductance
- Inhibitory Synapse
- Rhythmic Pattern