A model for self-organization of sensorimotor function : spinal interneuronal integration
(2022) In Journal of Neurophysiology 127(6). p.1478-1495- Abstract
Control of musculoskeletal systems depends on integration of voluntary commands and somatosensory feedback in the complex neural circuits of the spinal cord. It has been suggested that the various connectivity patterns that have been identified experimentally may result from the many transcriptional types that have been observed in spinal interneurons. We ask instead whether the muscle-specific details of observed connectivity patterns can arise as a consequence of Hebbian adaptation during early development, rather than being genetically ordained. We constructed an anatomically simplified model musculoskeletal system with realistic muscles and sensors and connected it to a recurrent, random neuronal network consisting of both... (More)
Control of musculoskeletal systems depends on integration of voluntary commands and somatosensory feedback in the complex neural circuits of the spinal cord. It has been suggested that the various connectivity patterns that have been identified experimentally may result from the many transcriptional types that have been observed in spinal interneurons. We ask instead whether the muscle-specific details of observed connectivity patterns can arise as a consequence of Hebbian adaptation during early development, rather than being genetically ordained. We constructed an anatomically simplified model musculoskeletal system with realistic muscles and sensors and connected it to a recurrent, random neuronal network consisting of both excitatory and inhibitory neurons endowed with Hebbian learning rules. We then generated a wide set of randomized muscle twitches typical of those described during fetal development and allowed the network to learn. Multiple simulations consistently resulted in diverse and stable patterns of activity and connectivity that included subsets of the interneurons that were similar to “archetypical” interneurons described in the literature. We also found that such learning led to an increased degree of cooperativity between interneurons when performing larger limb movements on which it had not been trained. Hebbian learning gives rise to rich sets of diverse interneurons whose connectivity reflects the mechanical properties of the system. At least some of the transcriptomic diversity may reflect the effects of this process rather than the cause of the connectivity. Such a learning process seems better suited to respond to the musculoskeletal mutations that underlie the evolution of new species. NEW & NOTEWORTHY We present a model of a self-organizing early spinal cord circuitry, which is attached to a biologically realistic sensorized musculoskeletal system. Without any a priori-defined connectivity or organization, learning induced by spontaneous, fetal-like motor activity results in the emergence of a well-functioning spinal interneuronal circuit whose connectivity patterns resemble in many respects those observed in the adult mammalian spinal cord. Hence, our result questions the importance of genetically controlled wiring for spinal cord function.
(Less)
- author
- Enander, Jonas M.D. LU ; Loeb, Gerald E. and Jörntell, Henrik LU
- organization
- publishing date
- 2022-06
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- extrafusal muscle, interneurons, intrafusal muscle, neuron model, spinal development
- in
- Journal of Neurophysiology
- volume
- 127
- issue
- 6
- pages
- 1478 - 1495
- publisher
- American Physiological Society
- external identifiers
-
- scopus:85131108740
- pmid:35475709
- ISSN
- 0022-3077
- DOI
- 10.1152/jn.00054.2022
- language
- English
- LU publication?
- yes
- additional info
- Funding Information: This work was supported by the European Union Grant FET 829186 ph-coding (Predictive Haptic COding Devices In Next Generation interfaces). Publisher Copyright: Copyright © 2022 the American Physiological Society.
- id
- b1662b14-797c-433e-9b6e-95f200e3f194
- date added to LUP
- 2022-07-26 10:40:19
- date last changed
- 2024-06-10 16:00:38
@article{b1662b14-797c-433e-9b6e-95f200e3f194,
abstract = {{<p>Control of musculoskeletal systems depends on integration of voluntary commands and somatosensory feedback in the complex neural circuits of the spinal cord. It has been suggested that the various connectivity patterns that have been identified experimentally may result from the many transcriptional types that have been observed in spinal interneurons. We ask instead whether the muscle-specific details of observed connectivity patterns can arise as a consequence of Hebbian adaptation during early development, rather than being genetically ordained. We constructed an anatomically simplified model musculoskeletal system with realistic muscles and sensors and connected it to a recurrent, random neuronal network consisting of both excitatory and inhibitory neurons endowed with Hebbian learning rules. We then generated a wide set of randomized muscle twitches typical of those described during fetal development and allowed the network to learn. Multiple simulations consistently resulted in diverse and stable patterns of activity and connectivity that included subsets of the interneurons that were similar to “archetypical” interneurons described in the literature. We also found that such learning led to an increased degree of cooperativity between interneurons when performing larger limb movements on which it had not been trained. Hebbian learning gives rise to rich sets of diverse interneurons whose connectivity reflects the mechanical properties of the system. At least some of the transcriptomic diversity may reflect the effects of this process rather than the cause of the connectivity. Such a learning process seems better suited to respond to the musculoskeletal mutations that underlie the evolution of new species. NEW & NOTEWORTHY We present a model of a self-organizing early spinal cord circuitry, which is attached to a biologically realistic sensorized musculoskeletal system. Without any a priori-defined connectivity or organization, learning induced by spontaneous, fetal-like motor activity results in the emergence of a well-functioning spinal interneuronal circuit whose connectivity patterns resemble in many respects those observed in the adult mammalian spinal cord. Hence, our result questions the importance of genetically controlled wiring for spinal cord function.</p>}},
author = {{Enander, Jonas M.D. and Loeb, Gerald E. and Jörntell, Henrik}},
issn = {{0022-3077}},
keywords = {{extrafusal muscle; interneurons; intrafusal muscle; neuron model; spinal development}},
language = {{eng}},
number = {{6}},
pages = {{1478--1495}},
publisher = {{American Physiological Society}},
series = {{Journal of Neurophysiology}},
title = {{A model for self-organization of sensorimotor function : spinal interneuronal integration}},
url = {{http://dx.doi.org/10.1152/jn.00054.2022}},
doi = {{10.1152/jn.00054.2022}},
volume = {{127}},
year = {{2022}},
}