ReviewNature neuroscience2014
Dimensionality reduction for large-scale neural recordings.
Review in Nature neuroscience, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 602 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
602 citing papers in PubMed.
- Neural subspaces of imagined movements in parietal cortex remain stable over several years in humans.Journal of neural engineering · 2024Trial
- Mapping the psychosis spectrum - imaging neurosubtypes from multiscale functional network connectivity.Molecular psychiatry · 2026Article
- Cannabinoid modulation of central amygdala population dynamics during threat investigation.Nature communications · 2026Article
- Population geometries in frontal cortex coordinate value-based decisions.bioRxiv : the preprint server for biology · 2026Article
- A geniculocortical circuit model predicts functional organization underlying efficient spatial frequency coding in the mouse visual system.bioRxiv : the preprint server for biology · 2026Article
- Behavioral demands organize a decision process into distinct yet coordinated neural representations in parietal cortex.bioRxiv : the preprint server for biology · 2026Article
- Article
- Shallow recurrent decoders for neural and behavioural dynamics.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2026Article
- Assistive algorithms influence neural representations in motor brain-computer interfaces.Nature communications · 2026Article
- Amygdalostriatal transition zone neurons encode sustained cue responses to guide defensive behaviors.Neuron · 2026Article
- Sampling bias corrections for discrete and Gaussian partial information decompositions.Patterns (New York, N.Y.) · 2026Article
- A standard model for the vertebrate retina.Vision research · 2026Article
- Distinct Neural Modes Carry Information About Attempted Grasp Timing and Force in the Sensorimotor Cortex.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026Article
- Loss of neuronal population organization links pathology to behavior in a model of Alzheimer's disease.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Geometric constraints and cognitive inputs jointly shape emergent brain dynamics and topology.bioRxiv : the preprint server for biology · 2026Article
- Pretraining of Embodied Recurrent Networks Bridges the Gap Between Artificial and Cortical Neural Activities.Biomimetics (Basel, Switzerland) · 2026Article
- Inferring brain-wide interactions using data-constrained recurrent neural network models.Neuron · 2026Article
- Artificial neural manifolds.Nature communications · 2026Article
- Computation embodied in population geometry.Nature communications · 2026Article
- Constructing mesoscale functionomics by neural dynamics subspace clustering.National science review · 2026Article
542 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Most sensory, cognitive and motor functions depend on the interactions of many neurons. In recent years, there has been rapid development and increasing use of technologies for recording from large numbers of neurons, either sequentially or simultaneously. A key question is what scientific insight can be gained by studying a population of recorded neurons beyond studying each neuron individually. Here, we examine three important motivations for population studies: single-trial hypotheses requiring statistical power, hypotheses of population response structure and exploratory analyses of large data sets. Many recent studies have adopted dimensionality reduction to analyze these populations and to find features that are not apparent at the level of individual neurons. We describe the dimensionality reduction methods commonly applied to population activity and offer practical advice about selecting methods and interpreting their outputs. This review is intended for experimental and computational researchers who seek to understand the role dimensionality reduction has had and can have in systems neuroscience, and who seek to apply these methods to their own data.
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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.