ArticleFrontiers in human neuroscience2021
Effects of Perturbation Velocity, Direction, Background Muscle Activation, and Task Instruction on Long-Latency Responses Measured From Forearm Muscles.
Article in Frontiers in human neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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.
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Who cites it
3 citing papers in PubMed, 6 citations in OpenAlex.
- fMRI reveals brainstem and cortical networks contribute to the instruction-dependent modulation of stretch-evoked motor responses.Imaging neuroscience (Cambridge, Mass.) · 2026Article
- Grip force makes wrist joint position sense worse.Frontiers in human neuroscience · 2023Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
The central nervous system uses feedback processes that occur at multiple time scales to control interactions with the environment. The long-latency response (LLR) is the fastest process that directly involves cortical areas, with a motoneuron response measurable 50 ms following an imposed limb displacement. Several behavioral factors concerning perturbation mechanics and the active role of muscles prior or during the perturbation can modulate the long-latency response amplitude (LLRa) in the upper limbs, but the interactions among many of these factors had not been systematically studied before. We conducted a behavioral study on thirteen healthy individuals to determine the effect and interaction of four behavioral factors - background muscle torque, perturbation direction, perturbation velocity, and task instruction - on the LLRa evoked from the flexor carpi radialis (FCR) and extensor carpi ulnaris (ECU) muscles after velocity-controlled wrist displacements. The effects of the four factors were quantified using both a 0D statistical analysis on the average perturbation-evoked EMG signal in the period corresponding to an LLR, and using a timeseries analysis of EMG signals. All factors significantly modulated LLRa, and their combination nonlinearly contributed to modulating the LLRa. Specifically, all the three-way interaction terms that could be computed without including the interaction between instruction and velocity significantly modulated the LLR. Analysis of the three-way interaction terms of the 0D model indicated that for the ECU muscle, the LLRa evoked when subjects are asked to maintain their muscle activation in response to the perturbations was greater than the one observed when subjects yielded to the perturbations (
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