ArticleeLife2020
High-fidelity musculoskeletal modeling reveals that motor planning variability contributes to the speed-accuracy tradeoff.
Article in eLife, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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
8 citing papers in PubMed, 14 citations in OpenAlex.
- JiSuJi, a virtual muscle for small animal simulations, accurately predicts force from naturalistic spike trains.bioRxiv : the preprint server for biology · 2025Article
- A novel biomechanical model of the proximal mouse forelimb predicts muscle activity in optimal control simulations of reaching movements.Journal of neurophysiology · 2025Article
- Methylphenidate modulates motor cortical dynamics and behavior.bioRxiv : the preprint server for biology · 2023Article
- Biomimetic Approaches for Human Arm Motion Generation: Literature Review and Future Directions.Sensors (Basel, Switzerland) · 2023Review
- Visual programming for accessible interactive musculoskeletal models.BMC research notes · 2022Article
- Article
- Prolonged response time helps eliminate residual errors in visuomotor adaptation.Psychonomic bulletin & review · 2021Article
- The effects of motor modularity on performance, learning and generalizability in upper-extremity reaching: a computational analysis.Journal of the Royal Society, Interface · 2020Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
A long-standing challenge in motor neuroscience is to understand the relationship between movement speed and accuracy, known as the speed-accuracy tradeoff. Here, we introduce a biomechanically realistic computational model of three-dimensional upper extremity movements that reproduces well-known features of reaching movements. This model revealed that the speed-accuracy tradeoff, as described by Fitts' law, emerges even without the presence of motor noise, which is commonly believed to underlie the speed-accuracy tradeoff. Next, we analyzed motor cortical neural activity from monkeys reaching to targets of different sizes. We found that the contribution of preparatory neural activity to movement duration (MD) variability is greater for smaller targets than larger targets, and that movements to smaller targets exhibit less variability in population-level preparatory activity, but greater MD variability. These results propose a new theory underlying the speed-accuracy tradeoff: Fitts' law emerges from greater task demands constraining the optimization landscape in a fashion that reduces the number of 'good' control solutions (i.e., faster reaches). Thus, contrary to current beliefs, the speed-accuracy tradeoff could be a consequence of motor planning variability and not exclusively signal-dependent noise.
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Registered trials
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 OpenQuestion graph.