The Bcm rule allows a spinal cord model to learn rhythmic movements
(2023) In Biological Cybernetics 117(4-5). p.275-284- Abstract
Currently, it is accepted that animal locomotion is controlled by a central pattern generator in the spinal cord. Experiments and models show that rhythm generating neurons and genetically determined network properties could sustain oscillatory output activity suitable for locomotion. However, current central pattern generator models do not explain how a spinal cord circuitry, which has the same basic genetic plan across species, can adapt to control the different biomechanical properties and locomotion patterns existing in these species. Here we demonstrate that rhythmic and alternating movements in pendulum models can be learned by a monolayer spinal cord circuitry model using the Bienenstock–Cooper–Munro learning rule, which has been... (More)
Currently, it is accepted that animal locomotion is controlled by a central pattern generator in the spinal cord. Experiments and models show that rhythm generating neurons and genetically determined network properties could sustain oscillatory output activity suitable for locomotion. However, current central pattern generator models do not explain how a spinal cord circuitry, which has the same basic genetic plan across species, can adapt to control the different biomechanical properties and locomotion patterns existing in these species. Here we demonstrate that rhythmic and alternating movements in pendulum models can be learned by a monolayer spinal cord circuitry model using the Bienenstock–Cooper–Munro learning rule, which has been previously proposed to explain learning in the visual cortex. These results provide an alternative theory to central pattern generator models, because rhythm generating neurons and genetically defined connectivity are not required in our model. Though our results are not in contradiction to current models, as existing neural mechanism and structures, not used in our model, can be expected to facilitate the kind of learning demonstrated here. Therefore, our model could be used to augment existing models.
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- author
- Kohler, Matthias ; Röhrbein, Florian ; Knoll, Alois ; Albu-Schäffer, Alin and Jörntell, Henrik LU
- organization
- publishing date
- 2023
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- BCM rule, Central pattern generator, Learning, Locomotion, Neurons
- in
- Biological Cybernetics
- volume
- 117
- issue
- 4-5
- pages
- 10 pages
- publisher
- Springer
- external identifiers
-
- pmid:37594531
- scopus:85168382798
- ISSN
- 0340-1200
- DOI
- 10.1007/s00422-023-00970-z
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2023, The Author(s).
- id
- 7b79db64-9dbe-4512-8eab-8ee6fb48c411
- date added to LUP
- 2023-11-13 13:22:52
- date last changed
- 2024-04-25 04:40:34
@article{7b79db64-9dbe-4512-8eab-8ee6fb48c411,
abstract = {{<p>Currently, it is accepted that animal locomotion is controlled by a central pattern generator in the spinal cord. Experiments and models show that rhythm generating neurons and genetically determined network properties could sustain oscillatory output activity suitable for locomotion. However, current central pattern generator models do not explain how a spinal cord circuitry, which has the same basic genetic plan across species, can adapt to control the different biomechanical properties and locomotion patterns existing in these species. Here we demonstrate that rhythmic and alternating movements in pendulum models can be learned by a monolayer spinal cord circuitry model using the Bienenstock–Cooper–Munro learning rule, which has been previously proposed to explain learning in the visual cortex. These results provide an alternative theory to central pattern generator models, because rhythm generating neurons and genetically defined connectivity are not required in our model. Though our results are not in contradiction to current models, as existing neural mechanism and structures, not used in our model, can be expected to facilitate the kind of learning demonstrated here. Therefore, our model could be used to augment existing models.</p>}},
author = {{Kohler, Matthias and Röhrbein, Florian and Knoll, Alois and Albu-Schäffer, Alin and Jörntell, Henrik}},
issn = {{0340-1200}},
keywords = {{BCM rule; Central pattern generator; Learning; Locomotion; Neurons}},
language = {{eng}},
number = {{4-5}},
pages = {{275--284}},
publisher = {{Springer}},
series = {{Biological Cybernetics}},
title = {{The Bcm rule allows a spinal cord model to learn rhythmic movements}},
url = {{http://dx.doi.org/10.1007/s00422-023-00970-z}},
doi = {{10.1007/s00422-023-00970-z}},
volume = {{117}},
year = {{2023}},
}