ArticleNature neuroscience2021
Burst-dependent synaptic plasticity can coordinate learning in hierarchical circuits.
Article in Nature neuroscience, 2021. 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 111 papers.
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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.
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Who cites it
111 citing papers in PubMed, 253 citations in OpenAlex.
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- Tuft Dendrite Spikes Are Accompanied by Selective Input From Distinct Functional Networks.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026Article
- Top-down feedback in deep neural networks leads to functional differences during audiovisual integration.eLife · 2026Article
- Thalamocortical bursts encode reward contingencies and drive associative learning.Nature communications · 2026Article
- Subicular plateaus signal reward locations during goal-directed behavior.Cell reports · 2026Article
- Voltage dynamics of cortical dendrites in vivo.Nature neuroscience · 2026Article
- Spike-based alignment learning solves the weight transport problem.Nature communications · 2026Article
- The primate claustrum as a hub for precision weighting of prediction errors across the cortical hierarchy.PLoS biology · 2026Article
- Tuft dendrite spikes are accompanied by selective input from distinct functional networks.bioRxiv : the preprint server for biology · 2026Article
- Ontology-constrained multi-LLM scoring of hypothesis support in the predictive processing literature.Research square · 2026Article
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- Neuronal spiking in the mammalian forebrain is dominated by a heterogeneous ground state.Neuron · 2026Article
- Cellular and subcellular specialization enables biology-constrained deep learning.Cell reports · 2026Article
- Local lateral connectivity is sufficient for replicating cortex-like topographical organization in deep neural networks.Nature communications · 2026Article
- Corticothalamic layer 6 controls cortical activity and thalamic firing mode in a bidirectional manner.Cerebral cortex (New York, N.Y. : 1991) · 2026Article
- Behavioral timescale synaptic plasticity: properties, elements and functions.Nature neuroscience · 2026Review
- Brain-inspired energy efficient technologies for next-generation artificial intelligence.Biological cybernetics · 2026Review
- Subicular Plateaus Signal Reward Locations during Goal-Directed Behavior.bioRxiv : the preprint server for biology · 2026Article
- Article
51 more citing papers are in PubMed but not listed here.
Corrections and comments
- Commented on by
- Erratum issued
Authors and funding
5 authors at 4 institutions in 3 countries.
Funding
Abstract
Synaptic plasticity is believed to be a key physiological mechanism for learning. It is well established that it depends on pre- and postsynaptic activity. However, models that rely solely on pre- and postsynaptic activity for synaptic changes have, so far, not been able to account for learning complex tasks that demand credit assignment in hierarchical networks. Here we show that if synaptic plasticity is regulated by high-frequency bursts of spikes, then pyramidal neurons higher in a hierarchical circuit can coordinate the plasticity of lower-level connections. Using simulations and mathematical analyses, we demonstrate that, when paired with short-term synaptic dynamics, regenerative activity in the apical dendrites and synaptic plasticity in feedback pathways, a burst-dependent learning rule can solve challenging tasks that require deep network architectures. Our results demonstrate that well-known properties of dendrites, synapses and synaptic plasticity are sufficient to enable sophisticated learning in hierarchical circuits.
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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.