Robust dynamical invariants in sequential neural activity
Entity
UAM. Departamento de Ingeniería InformáticaPublisher
Nature Research (part of Springer Nature)Date
2019-06-21Citation
10.1101/379909
Scientific Reports 9.1 (2019): 9048
ISSN
2045-2322DOI
10.1101/379909Funded by
This work has been supported by Spanish grants MINECO DPI2015-65833-P, TIN2017-84452-R, PGC2018-095895-B-I00 (http:// www.mineco.gob.es/), and ONRG grant N62909-14-1-N279.Project
Gobierno de España. DPI2015-65833-P; Gobierno de España. TIN2017-84452-R; Gobierno de España. PGC2018-095895-B-I00Editor's Version
https://doi.org/10.1101/379909Subjects
Rhythm; Central Pattern Generator; Coordination; InformáticaRights
© The Author(s) 2019Abstract
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
Files in this item
Google Scholar:Elices, Irene
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Levi, Rafael
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Arroyo, David
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Rodríguez Ortiz, Francisco Borja
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Varona Martínez, Pablo
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