Robust dynamical invariants in sequential neural activity

Irene Elices,Pablo Varona,Francisco B Rodriguez,David Arroyo,Rafael Levi

doi:10.1038/s41598-019-44953-2

Irene Elices, Pablo Varona + Show 3 more

Open Access

https://doi.org/10.1038/s41598-019-44953-2

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Journal: Scientific Reports	Publication Date: Jun 21, 2019
Citations: 11	License type: open-access

Affiliation: Autonomous University of Madrid

Abstract

By studying different sources of temporal variability in central pattern generator (CPG) circuits, we unveil fundamental aspects of the instantaneous balance between flexibility and robustness in sequential dynamics -a property that characterizes many systems that display neural rhythms. Our analysis of the triphasic rhythm of the pyloric CPG (Carcinus maenas) shows strong robustness of transient dynamics in keeping not only the activation sequences but also specific cycle-by-cycle temporal relationships in the form of strong linear correlations between pivotal time intervals, i.e. dynamical invariants. The level of variability and coordination was characterized using intrinsic time references and intervals in long recordings of both regular and irregular rhythms. Out of the many possible combinations of time intervals studied, only two cycle-by-cycle dynamical invariants were identified, existing even outside steady states. While executing a neural sequence, dynamical invariants reflect constraints to optimize functionality by shaping the actual intervals in which activity emerges to build the sequence. Our results indicate that such boundaries to the adaptability arise from the interaction between the rich dynamics of neurons and connections. We suggest that invariant temporal sequence relationships could be present in other networks, including those shaping sequences of functional brain rhythms, and underlie rhythm programming and functionality.

Highlights

Robust sequences of neural activations can be found in any nervous system, from simple invertebrate circuits[1,2,3,4] to vertebrate systems[5,6,7,8,9,10,11,12]
In spite of the large variability seen in the experiments, we report two dynamical invariants in the form of strong linear correlations between pivotal time intervals that build the sequence
The pyloric central pattern generator (CPG) of the crustacean stomatogastric nervous system presents a characteristic rhythm with three main components in a robust sequence: the Lateral Pyloric (LP) neuron, a group of six to eight pyloric neurons (PY), two electrically coupled Pyloric Dilator (PD) neurons and the Anterior Burster (AB), electrically coupled to the PDs24,28,56

Summary

Introduction

Robust sequences of neural activations can be found in any nervous system, from simple invertebrate circuits[1,2,3,4] to vertebrate systems[5,6,7,8,9,10,11,12]. Central pattern generators (CPGs) are neural circuits that produce flexible rhythmic motor patterns[24,25] Their robust and highly coordinated neuron activation sequences arise from the combination of intrinsic cell and synaptic dynamics[26,27]. By quantifying average delays and periods and comparing across preparations, authors could show that certain elements of the rhythm maintain relative timing with changes in frequency[36,48,49] In this context, most works discard irregular activity, as well as, transient changes. We address the changes in a cycle-by-cycle ongoing CPG rhythm, and argue that there is an instantaneous negotiation of the resultant sequence To expose this process we included in our study irregular rhythms, i.e., activity that presented high variability within the same experiment. In spite of the large variability seen in the experiments, we report two dynamical invariants in the form of strong linear correlations between pivotal time intervals that build the sequence

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