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  Balancing central control and sensory feedback produces adaptable and robust locomotor patterns in a spiking, neuromechanical model of the salamander spinal cord

Pazzaglia, A., Bicanski, A., Ferrario, A., Arreguit, J., Ryczko, D., & Ijspeert, A. (2025). Balancing central control and sensory feedback produces adaptable and robust locomotor patterns in a spiking, neuromechanical model of the salamander spinal cord. PLOS Computational Biology, 21(1): e1012101. doi:10.1371/journal.pcbi.1012101.

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 Creators:
Pazzaglia, Alessandro1, Author
Bicanski, Andrej2, Author           
Ferrario, Andrea1, Author
Arreguit, Jonathan1, Author
Ryczko, Dimitri3, Author
Ijspeert, Auke1, Author
Serre, Thomas1, Editor
Affiliations:
1Biorobotics Laboratory (BioRob), Swiss Federal Institute of Technology in Lausanne, Switzerland, ou_persistent22              
2Department Psychology (Doeller), MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_2591710              
3Ryczko Laboratory, Department of Pharmacology-Physiology, Université de Sherbrooke, QC, Canada, ou_persistent22              

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 Abstract: This study introduces a novel neuromechanical model employing a detailed spiking neural network to explore the role of axial proprioceptive sensory feedback, namely stretch feedback, in salamander locomotion. Unlike previous studies that often oversimplified the dynamics of the locomotor networks, our model includes detailed simulations of the classes of neurons that are considered responsible for generating movement patterns. The locomotor circuits, modeled as a spiking neural network of adaptive leaky integrate-and-fire neurons, are coupled to a three-dimensional mechanical model of a salamander with realistic physical parameters and simulated muscles. In open-loop simulations (i.e., without sensory feedback), the model replicates locomotor patterns observed in-vitro and in-vivo for swimming and trotting gaits. Additionally, a modular descending reticulospinal drive to the central pattern generation network allows to accurately control the activation, frequency and phase relationship of the different sections of the limb and axial circuits. In closed-loop swimming simulations (i.e. including axial stretch feedback), systematic evaluations reveal that intermediate values of feedback strength increase the tail beat frequency and reduce the intersegmental phase lag, contributing to a more coordinated, faster and energy-efficient locomotion. Interestingly, the result is conserved across different feedback topologies (ascending or descending, excitatory or inhibitory), suggesting that it may be an inherent property of axial proprioception. Moreover, intermediate feedback strengths expand the stability region of the network, enhancing its tolerance to a wider range of descending drives, internal parameters' modifications and noise levels. Conversely, high values of feedback strength lead to a loss of controllability of the network and a degradation of its locomotor performance. Overall, this study highlights the beneficial role of proprioception in generating, modulating and stabilizing locomotion patterns, provided that it does not excessively override centrally-generated locomotor rhythms. This work also underscores the critical role of detailed, biologically-realistic neural networks to improve our understanding of vertebrate locomotion.

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Language(s): eng - English
 Dates: 2024-04-242024-12-262025-01-212025-01-21
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1371/journal.pcbi.1012101
Other: eCollection 2025
PMID: 39836708
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Grant ID : 951477
Funding program : Horizon 2020
Funding organization : European Research Council (ERC)

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Title: PLOS Computational Biology
  Abbreviation : PLOS Comput Biol
Source Genre: Journal
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Publ. Info: San Francisco, CA : Public Library of Science
Pages: - Volume / Issue: 21 (1) Sequence Number: e1012101 Start / End Page: - Identifier: ISSN: 1553-734X
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000017180_1