ArticleNature neuroscience2018
Learning by neural reassociation.
Article in Nature neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 122 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.
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Who cites it
122 citing papers in PubMed, 282 citations in OpenAlex.
- Human learning of noninvasive brain-computer interfaces via manifold geometry.Nature neuroscience · 2026Article
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- Assistive algorithms influence neural representations in motor brain-computer interfaces.Nature communications · 2026Article
- Pretraining of Embodied Recurrent Networks Bridges the Gap Between Artificial and Cortical Neural Activities.Biomimetics (Basel, Switzerland) · 2026Article
- Manifold-constrained plasticity enables stable learning in recurrent neural circuits.PLoS computational biology · 2026Article
- Learning-related population dynamics in right and left dorsal premotor cortex during typing skill acquisition.bioRxiv : the preprint server for biology · 2026Article
- Duration-modulated neural population dynamics in humans during BMI controls.Communications biology · 2026Article
- Live Spike Sorting of Large-scale Neural Recordings.bioRxiv : the preprint server for biology · 2026Article
- Millimeter-scale selective amplification in the developing visual cortex.bioRxiv : the preprint server for biology · 2026Article
- Functional reorganization of motor cortex connectivity during learning.bioRxiv : the preprint server for biology · 2026Article
- Granule cells reorient cortical manifolds to separate contexts but preserve their geometry.bioRxiv : the preprint server for biology · 2026Article
- Integration of learned artificial sensation with vision during freely moving navigation.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Article
- Brain-computer interfaces as a causal probe for scientific inquiry.Trends in cognitive sciences · 2026Review
- Transient boosting of action potential backpropagation for few-shot temporal pattern learning.PLoS computational biology · 2025Article
- Motor cortex flexibly deploys a high-dimensional repertoire of subskills.bioRxiv : the preprint server for biology · 2025Article
- Frontal and parietal planning signals encode adapted motor commands when learning to control a brain-computer interface.PLoS biology · 2025Article
- Coordinated multi-level adaptations across neocortical areas during task learning.Nature communications · 2025Article
- Context flexibly modulates cue representations in visual cortex.Nature communications · 2025Article
- Metaplasticity and continual learning: mechanisms subserving brain computer interface proficiency.Journal of neural engineering · 2025Article
62 more citing papers are in PubMed but not listed here.
Corrections and comments
- Commented on by
- Erratum issued
Authors and funding
9 authors at 3 institutions in 1 country.
Funding
Abstract
Behavior is driven by coordinated activity across a population of neurons. Learning requires the brain to change the neural population activity produced to achieve a given behavioral goal. How does population activity reorganize during learning? We studied intracortical population activity in the primary motor cortex of rhesus macaques during short-term learning in a brain-computer interface (BCI) task. In a BCI, the mapping between neural activity and behavior is exactly known, enabling us to rigorously define hypotheses about neural reorganization during learning. We found that changes in population activity followed a suboptimal neural strategy of reassociation: animals relied on a fixed repertoire of activity patterns and associated those patterns with different movements after learning. These results indicate that the activity patterns that a neural population can generate are even more constrained than previously thought and might explain why it is often difficult to quickly learn to a high level of proficiency.
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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.