ArticleNeuroImage2018
Brain state flexibility accompanies motor-skill acquisition.
Article in NeuroImage, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 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.
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
29 citing papers in PubMed.
- The impact of structured motor learning intervention on preschool children's executive functions.Scientific reports · 2025Trial
- Brain functional connectivity in children with developmental coordination disorder following rehabilitation intervention.Pediatric research · 2022Trial
- The role of the subcortical structures in subthreshold depression: evidence from static and dynamic functional connectivity.Brain structure & function · 2026Article
- Distinct roles of brain network flexibility in motor learning across age.Imaging neuroscience (Cambridge, Mass.) · 2026Article
- Flexibility of Brain Networks May Curtail Cognitive Consequences of Poor Sleep.Human brain mapping · 2025Article
- Dynamic reconfiguration of brain functional networks in world class gymnasts: a resting-state functional MRI study.Brain communications · 2025Article
- Development of performance and learning rate evaluation models in robot-assisted surgery using electroencephalography and eye-tracking.NPJ science of learning · 2024Article
- Surgical skill level classification model development using EEG and eye-gaze data and machine learning algorithms.Journal of robotic surgery · 2023Article
- Performance and learning rate prediction models development in FLS and RAS surgical tasks using electroencephalogram and eye gaze data and machine learning.Surgical endoscopy · 2023Article
- Developing cognitive workload and performance evaluation models using functional brain network analysis.npj aging · 2023Article
- Dynamic Functional Connectome Harmonics.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2023Article
- Article
- Dynamic rewiring of electrophysiological brain networks during learning.Network neuroscience (Cambridge, Mass.) · 2023Article
- Sensory stimulation for upper limb amputations modulates adaptability of cortical large-scale systems and combination of somatosensory and visual inputs.Scientific reports · 2022Article
- Assessing the functions underlying learning using by-trial and by-participant models: Evidence from two visual perceptual learning paradigms.Journal of vision · 2021Article
- Dissociable plasticity of visual-motor system in functional specialization and flexibility in expert table tennis players.Brain structure & function · 2021Article
- Time-Varying Functional Connectivity Decreases as a Function of Acute Nicotine Abstinence.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2021Article
- Temporal Dynamics of Functional Brain States Underlie Cognitive Performance.Cerebral cortex (New York, N.Y. : 1991) · 2021Article
- Dynamic neural circuit disruptions associated with antisocial behaviors.Human brain mapping · 2021Article
- Static and dynamic functional connectivity supports the configuration of brain networks associated with creative cognition.Scientific reports · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Learning requires the traversal of inherently distinct cognitive states to produce behavioral adaptation. Yet, tools to explicitly measure these states with non-invasive imaging - and to assess their dynamics during learning - remain limited. Here, we describe an approach based on a distinct application of graph theory in which points in time are represented by network nodes, and similarities in brain states between two different time points are represented as network edges. We use a graph-based clustering technique to identify clusters of time points representing canonical brain states, and to assess the manner in which the brain moves from one state to another as learning progresses. We observe the presence of two primary states characterized by either high activation in sensorimotor cortex or high activation in a frontal-subcortical system. Flexible switching among these primary states and other less common states becomes more frequent as learning progresses, and is inversely correlated with individual differences in learning rate. These results are consistent with the notion that the development of automaticity is associated with a greater freedom to use cognitive resources for other processes. Taken together, our work offers new insights into the constrained, low dimensional nature of brain dynamics characteristic of early learning, which give way to less constrained, high-dimensional dynamics in later learning.
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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.