ArticleJournal of cognitive neuroscience2021
Deep Predictive Learning in Neocortex and Pulvinar.
Article in Journal of cognitive neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 3 citations in OpenAlex.
- Synaptic Plasticity as a Function of the Temporal Derivative.bioRxiv : the preprint server for biology · 2026Article
- Processing of natural scenes in the human pulvinar.Nature communications · 2025Article
- Exploring the Architectural Biases of the Cortical Microcircuit.Neural computation · 2025Article
- A hierarchical multiscale model of forward and backward alpha-band traveling waves in the visual system.PLoS computational biology · 2025Article
- Fast and robust visual object recognition in young children.Science advances · 2025Article
- Parallel development of object recognition in newborn chicks and deep neural networks.PLoS computational biology · 2024Article
- A sensory-motor theory of the neocortex.Nature neuroscience · 2024Review
- What's Next? Advances and Challenges in Understanding How Environmental Predictability Shapes the Development of Cognitive Control.Current directions in psychological science · 2023Article
- How trial-to-trial learning shapes mappings in the mental lexicon: Modelling lexical decision with linear discriminative learning.Cognitive psychology · 2023Article
- Correcting the hebbian mistake: Toward a fully error-driven hippocampus.PLoS computational biology · 2022Article
- The Structure of Systematicity in the Brain.Current directions in psychological science · 2022Article
- A computational examination of the two-streams hypothesis: which pathway needs a longer memory?Cognitive neurodynamics · 2022Article
- Thalamocortical contribution to flexible learning in neural systems.Network neuroscience (Cambridge, Mass.) · 2022Article
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- Prior context influences motor brain areas in an auditory oddball task and prefrontal cortex multitasking modelling.Brain informatics · 2021Article
- The Thalamus as a Blackboard for Perception and Planning.Frontiers in behavioral neuroscience · 2021Article
- Corticothalamic Projections Gate Alpha Rhythms in the Pulvinar.Frontiers in cellular neuroscience · 2021Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
How do humans learn from raw sensory experience? Throughout life, but most obviously in infancy, we learn without explicit instruction. We propose a detailed biological mechanism for the widely embraced idea that learning is driven by the differences between predictions and actual outcomes (i.e., predictive error-driven learning). Specifically, numerous weak projections into the pulvinar nucleus of the thalamus generate top-down predictions, and sparse driver inputs from lower areas supply the actual outcome, originating in Layer 5 intrinsic bursting neurons. Thus, the outcome representation is only briefly activated, roughly every 100 msec (i.e., 10 Hz, alpha), resulting in a temporal difference error signal, which drives local synaptic changes throughout the neocortex. This results in a biologically plausible form of error backpropagation learning. We implemented these mechanisms in a large-scale model of the visual system and found that the simulated inferotemporal pathway learns to systematically categorize 3-D objects according to invariant shape properties, based solely on predictive learning from raw visual inputs. These categories match human judgments on the same stimuli and are consistent with neural representations in inferotemporal cortex in primates.
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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.