ReviewTrends in cognitive sciences2019
Theories of Error Back-Propagation in the Brain.
Review in Trends in cognitive sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 123 papers, 1 of them a synthesis that pooled it.
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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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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
123 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Decoding the application of deep learning in neuroscience: a bibliometric analysis.Frontiers in computational neuroscience · 2024Pooled it
- Review
- Adaptive Residual Correction Network for Efficient Single Image Super-Resolution.Sensors (Basel, Switzerland) · 2026Article
- Neuromorphic Devices and Computing for Sensing, Memory, and Control.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Manifold-constrained plasticity enables stable learning in recurrent neural circuits.PLoS computational biology · 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
- The curriculum effect in visual learning: The role of readout dimensionality.PLoS computational biology · 2026Article
- Hippocampo-neocortical interaction as compressive retrieval-augmented generation.Nature communications · 2026Article
- Hierarchical recurrent temporal prediction as a model of the mammalian dorsal visual pathway.PLoS computational biology · 2026Article
- BrainTwin-AI: A Multimodal MRI-EEG-Based Cognitive Digital Twin for Real-Time Brain Health Intelligence.Brain sciences · 2026Article
- Aquila Optimization-Assisted Artificial Neural Network for Classification Problems.Biomimetics (Basel, Switzerland) · 2026Article
- 'Backpropagation and the brain' realized in cortical error neuron microcircuits.PLoS computational biology · 2026Article
- Perceived Complexity as Normalized, Integrated, Localized Shannon Entropy.Entropy (Basel, Switzerland) · 2026Article
- A minimal recurrent neural network models the robustness of interleaved practice on motor sequence learning.Scientific reports · 2026Article
- Neural Associative Skill Memories for Safer Robotics and Modeling Human Sensorimotor Repertoires.Neural computation · 2025Article
- Three-factor learning in spiking neural networks: An overview of methods and trends from a machine learning perspective.Patterns (New York, N.Y.) · 2025Review
- Review
- The neural basis for uncertainty processing in hierarchical decision making.Nature communications · 2025Article
- Article
63 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
This review article summarises recently proposed theories on how neural circuits in the brain could approximate the error back-propagation algorithm used by artificial neural networks. Computational models implementing these theories achieve learning as efficient as artificial neural networks, but they use simple synaptic plasticity rules based on activity of presynaptic and postsynaptic neurons. The models have similarities, such as including both feedforward and feedback connections, allowing information about error to propagate throughout the network. Furthermore, they incorporate experimental evidence on neural connectivity, responses, and plasticity. These models provide insights on how brain networks might be organised such that modification of synaptic weights on multiple levels of cortical hierarchy leads to improved performance on tasks.
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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.