P267 Real-time closed-loop perturbation of electrically coupled neurons to characterize sequential dynamics in CPG circuits
Pablo Sanchez-Martin*¹, Alicia Garrido-Peña¹,Manuel Reyes-Sanchez, Irene Elices¹, Rafael Levi¹, Francisco B Rodriguez¹, Pablo Varona¹ 1. Grupo de Neurocomputación Biológica, Departamento de Ingeniería Informática, Escuela Politecnica Superior, Universidad Autónoma de Madrid, Madrid, Spain *Email: pablo.sanchezm@uam.es
Introduction Dynamical invariants in the form of robust cycle-by-cycle relationships between intervals that build robust neural sequences have beenobservedrecently in central pattern generatorscircuits (CPGs) [1]. In this study, we analyze the effect of different closed-loop perturbationson electrically coupled neurons that are part of aCPGtodeterminethe associated modulation of sequence interval variability,synchronizationand dynamical invariants.
Methods This research was performed in the pyloric CPG involving both voltage recordings and current injection in the PD neurons, which are electrically coupled cells in this circuit. Additionally, we recorded extracellularly from the LP neuron to quantify the LPPD delay, an interval that builds a dynamical invariant with the cycle-by-cycle period. We implemented an active electrical compensation procedure [2] on RTXi real-time software, which prevents the recording artifact using a single electrode. Three closed-loop perturbations were delivered on the PD neurons: 1. A Hindmarsh-Rose (HR) model neuron electrically coupled to a PD neuron, thus building a biohybrid circuit. 2. A square pulse current injection during the PD burst. 3. An additional artificial electrical synapse between the two PD neurons.
Results The electrical coupling with a negative artificial bidirectional synapse did not change the existing invariant relation between the LPPD delay and the period but increased the rhythm variability and increased the Victor-Purpura distance, i.e., reduced the PD synchronization level.The squared pulse perturbation decreased the variability and thus the LPPD delay linear relationship was reduced.The level of synchronization between both PDs was also reduced with the pulse perturbation with respect to the control.The biohybrid circuit built by adding anadditionalelectrical coupling to an artificial HR neuron also reduced the variability but changed the intercept of the linear relationshipi.e.,for the same LPPD delays thePD period was sorter.
Discussion In this study, we effectively disrupted the dynamics of two electrically coupled neurons with three different perturbations by injecting current into the neurons that modulated the synchronization level.This not onlymodifiedthe dynamics of these neurons but also the whole circuit variability and the associated dynamical invariants.All protocols have been proven effective to study the relationship of electrical coupling and sequential dynamics with the help of real-timeclosed-loopneurotechnologies.
Acknowledgements Work funded by PID2024-155923NB-I00, CPP2023-010818, PID2023-149669NB-I00 and PID2021-122347NB-I00. References [1] I. Elices, R. Levi, D. Arroyo, F. B. Rodriguez, and P. Varona. Robust dynamical invariants in sequential neural activity. Scientific Reports, 9(1):9048, 2019. [2] R. Brette, Z. Piwkowska, C. Monier, M. Rudolph-Lilith, J. Fournier, M. Levy, and A. Destexhe. High-resolution intracellular recordings using a real-time computational model of the electrode. Neuron, 59(3):379–391, 2008.
