ArticleNature neuroscience2021
Cerebellar granule cell axons support high-dimensional representations.
Article in Nature neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed, 81 citations in OpenAlex.
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- Hippocampal ripples initiate cortical dimensionality expansion for memory retrieval.Nature communications · 2026Article
- Cerebellar activity is triggered by reach endpoint during learning of a complex locomotor task.Nature communications · 2026Article
- Cerebellar neural populations orchestrate dopamine reward signaling with single-trial precision.Nature communications · 2026Article
- Cerebellum-inspired memtransistors enable emergent differentiation for hardware-efficient novelty detection.Nature communications · 2026Article
- Low-dimensional population dynamics in the brainstem gate REM sleep.Nature neuroscience · 2026Article
- Granule cells reorient cortical manifolds to separate contexts but preserve their geometry.bioRxiv : the preprint server for biology · 2026Article
- Cerebellar tonic inhibition orchestrates the maturation of information processing and motor coordination.Experimental & molecular medicine · 2026Article
- How does the cerebellum contribute to cognitive functions?PLoS biology · 2026Review
- Consensus Paper: Models of Cerebellar Functions.Cerebellum (London, England) · 2026Review
- Optogenetic interrogation of the zebrafish lateral line reveals brain-wide neural circuits involved in pattern separation.iScience · 2025Article
- All-optical voltage interrogation for probing synaptic plasticity in vivo.Nature communications · 2025Article
- Homeostatic bidirectional plasticity in upbound and downbound micromodules in a model of the olivocerebellar loop.PLoS computational biology · 2025Article
- Cerebellar circuit computations for predictive motor control.Nature reviews. Neuroscience · 2025Review
- A neural manifold view of the brain.Nature neuroscience · 2025Review
- High-dimensional neuronal activity from low-dimensional latent dynamics: a solvable model.bioRxiv : the preprint server for biology · 2025Article
- Fast implicit and slow explicit learning of temporal context.Scientific reports · 2025Article
- GlyT2-Positive Interneurons Regulate Timing and Variability of Information Transfer in a Cerebellar-Behavioral Loop.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Neuronal dynamics of cerebellum and medial prefrontal cortex in adaptive motor timing.Nature communications · 2025Article
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
Abstract
In classical theories of cerebellar cortex, high-dimensional sensorimotor representations are used to separate neuronal activity patterns, improving associative learning and motor performance. Recent experimental studies suggest that cerebellar granule cell (GrC) population activity is low-dimensional. To examine sensorimotor representations from the point of view of downstream Purkinje cell 'decoders', we used three-dimensional acousto-optic lens two-photon microscopy to record from hundreds of GrC axons. Here we show that GrC axon population activity is high dimensional and distributed with little fine-scale spatial structure during spontaneous behaviors. Moreover, distinct behavioral states are represented along orthogonal dimensions in neuronal activity space. These results suggest that the cerebellar cortex supports high-dimensional representations and segregates behavioral state-dependent computations into orthogonal subspaces, as reported in the neocortex. Our findings match the predictions of cerebellar pattern separation theories and suggest that the cerebellum and neocortex use population codes with common features, despite their vastly different circuit structures.
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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.