{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,26]],"date-time":"2025-08-26T06:10:25Z","timestamp":1756188625715,"version":"3.44.0"},"reference-count":119,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,8,26]],"date-time":"2025-08-26T00:00:00Z","timestamp":1756166400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Comput. Neurosci."],"abstract":"<jats:p>The development of new studies that consider different structures of the hierarchical sensorimotor control system is essential to enable a more holistic understanding about movement. The incorporation of more biological proprioceptive and neuronal circuit models to muscles can turn neuromusculoskeletal systems more appropriate to investigate and elucidate motor control. Specifically, further studies that consider the closed-loop between proprioception and central nervous system may allow to better understand the yet open question about the importance of afferent feedback for sensorimotor learning and execution in the intact biological system. Therefore, this study aims to investigate the processing of spindle afferent firings by spiking neuronal network and their relevance for sensorimotor control. We integrated our previously published physiological model of the muscle spindle in a biological arm model, corresponding to a musculoskeletal system able to reproduce biological motion inside of the demoa multi-body simulation framework. We coupled this musculoskeletal system to physiologically-motivated neuronal spinal pathways, which were implemented based on literature in the NEST spiking neural network simulator, intended to perform human center-out reaching arising from spinal synaptic learning. As result, the spindle connections to the spinal neurons were strengthened for the more difficult targets (i.e. higher above placed targets) under perturbation, highlighting the importance of spindle proprioception to succeed in more difficult scenarios. Furthermore, an additionally-implemented simpler spinal network (that does not include the pathways with spindle proprioception) presented an inferior performance in the task by not being able to reach all the evaluated targets.<\/jats:p>","DOI":"10.3389\/fncom.2025.1575630","type":"journal-article","created":{"date-parts":[[2025,8,26]],"date-time":"2025-08-26T05:28:05Z","timestamp":1756186085000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Closed-loop coupling of both physiological spindle model and spinal pathways for sensorimotor control of human center-out reaching"],"prefix":"10.3389","volume":"19","author":[{"given":"Pablo Filipe Santana","family":"Chacon","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Isabell","family":"Wochner","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maria","family":"Hammer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jochen Martin","family":"Eppler","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Susanne","family":"Kunkel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Syn","family":"Schmitt","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2025,8,26]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"209","DOI":"10.2976\/1.2803419","article-title":"Building a realistic neuronal model that simulates multi-joint arm and hand movements in 3d space","volume":"1","author":"Alstermark","year":"2007","journal-title":"HFSP J"},{"key":"B2","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1109\/TBME.2015.2485301","article-title":"Spiking neural network with distributed plasticity reproduces cerebellar learning in eye blink conditioning paradigms","volume":"63","author":"Antonietti","year":"2016","journal-title":"IEEE Trans. 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