ArticleNature communications2020
A neural circuit model for human sensorimotor timing.
Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed, 78 citations in OpenAlex.
- Modeling the rhythmic complexity of professional drumming with an oscillation-driven reservoir computer.Cognitive neurodynamics · 2026Article
- Simulated field potentials capture multiple simultaneous processes underlying human temporal attention.bioRxiv : the preprint server for biology · 2026Article
- The anticipation of imminent events is time-scale invariant.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Computational modeling of rhythmic expectations: Perspectives, pitfalls, and prospects.PLoS computational biology · 2025Review
- Limited Evidence to Review-Is There an Association Between Cognition and Upper Extremity Motor Reaction Time in Older Adults?NeuroSci · 2025Review
- Pitch biases sensorimotor synchronization to auditory rhythms.Scientific reports · 2025Article
- Neural signatures of temporal anticipation in human cortex represent event probability density.Nature communications · 2025Article
- Latent circuit inference from heterogeneous neural responses during cognitive tasks.Nature neuroscience · 2025Article
- Perturbation context in paced finger tapping tunes the error-correction mechanism.Scientific reports · 2024Article
- Dynamical mechanisms of how an RNN keeps a beat, uncovered with a low-dimensional reduced model.Scientific reports · 2024Article
- Challenges and Approaches in the Study of Neural Entrainment.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Review
- Adaptive oscillators support Bayesian prediction in temporal processing.PLoS computational biology · 2023Article
- Article
- Context-specific and context-invariant computations of interval timing.Frontiers in neuroscience · 2023Article
- Dynamic models for musical rhythm perception and coordination.Frontiers in computational neuroscience · 2023Review
- Functional architecture of executive control and associated event-related potentials in macaques.Nature communications · 2022Article
- Rhythms in cognition: The evidence revisited.The European journal of neuroscience · 2022Article
- Thunderstruck: The ACDC model of flexible sequences and rhythms in recurrent neural circuits.PLoS computational biology · 2022Article
- The EBRAINS Hodgkin-Huxley Neuron Builder: An online resource for building data-driven neuron models.Frontiers in neuroinformatics · 2022Article
- Mapping between sound, brain and behaviour: four-level framework for understanding rhythm processing in humans and non-human primates.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
Humans and animals can effortlessly coordinate their movements with external stimuli. This capacity indicates that sensory inputs can rapidly and flexibly reconfigure the ongoing dynamics in the neural circuits that control movements. Here, we develop a circuit-level model that coordinates movement times with expected and unexpected temporal events. The model consists of two interacting modules, a motor planning module that controls movement times and a sensory anticipation module that anticipates external events. Both modules harbor a reservoir of latent dynamics, and their interaction forms a control system whose output is adjusted adaptively to minimize timing errors. We show that the model's output matches human behavior in a range of tasks including time interval production, periodic production, synchronization/continuation, and Bayesian time interval reproduction. These results demonstrate how recurrent interactions in a simple and modular neural circuit could create the dynamics needed to control timing behavior.
Indexed as
Identifiers
What OpenQuestion holds
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.