Evidence map›Paper›PMID 40933538›Full record

ArticleFrontiers in computational neuroscience2025

Closed-loop coupling of both physiological spindle model and spinal pathways for sensorimotor control of human center-out reaching.

Pablo Filipe Santana Chacon, Isabell Wochner, Maria Hammer, Jochen Martin Eppler, Susanne Kunkel, Syn Schmitt

Abstract read
In one paragraph

Article in Frontiers in computational neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Pablo Filipe Santana ChaconInstitute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany.
Isabell WochnerHertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.
Maria HammerInstitute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany.
Jochen Martin EpplerFaculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway.
Susanne KunkelFaculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway.
Syn SchmittInstitute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

biomechanicsmuscle spindleneuromusculoskeletal modelproprioceptionsensorimotor controlspiking neural networkspinal cordsynaptic learning

Identifiers

PMID40933538
PMCPMC12417497

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.