ArticleScience advances2022
A data-based large-scale model for primary visual cortex enables brain-like robust and versatile visual processing.
Article in Science advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Interpretable machine learning reveals hemispheric asymmetry of state switching in the suprachiasmatic nucleus.Patterns (New York, N.Y.) · 2026Article
- Benchmarking criteria to determine latent linear dimensionality in neural data.Scientific reports · 2026Article
- Deep-learning-assisted simulation of a cortical circuit: integrating anatomy, physiology and function.bioRxiv : the preprint server for biology · 2026Article
- Article
- Modeling macroscopic brain dynamics with brain-inspired computing architecture.Nature communications · 2025Article
- Map of spiking activity underlying change detection in the mouse visual system.bioRxiv : the preprint server for biology · 2025Article
- Biologically grounded neocortex computational primitives implemented on neuromorphic hardware improve vision transformer performance.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Article
- Synergistic Reinforcement Learning by Cooperation of the Cerebellum and Basal Ganglia.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- The cortical critical power law balances energy and information in an optimal fashion.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Neural heterogeneity enhances reliable neural information processing: Local sensitivity and globally input-slaved transient dynamics.Science advances · 2025Article
- Integrating multimodal data to understand cortical circuit architecture and function.Nature neuroscience · 2025Review
- Pattern memory cannot be completely and truly realized in deep neural networks.Scientific reports · 2024Article
- Identification of movie encoding neurons enables movie recognition AI.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Large-Scale Mechanistic Models of Brain Circuits with Biophysically and Morphologically Detailed Neurons.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Review
- How can neuromorphic hardware attain brain-like functional capabilities?National science review · 2024Article
- Parvalbumin and Somatostatin: Biomarkers for Two Parallel Tectothalamic Pathways in the Auditory Midbrain.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- Emergence of syntax and word prediction in an artificial neural circuit of the cerebellum.Nature communications · 2024Article
- Memory-efficient neurons and synapses for spike-timing-dependent-plasticity in large-scale spiking networks.Frontiers in neuroscience · 2024Article
- How deep is the brain? The shallow brain hypothesis.Nature reviews. Neuroscience · 2023Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We analyze visual processing capabilities of a large-scale model for area V1 that arguably provides the most comprehensive accumulation of anatomical and neurophysiological data to date. We find that this brain-like neural network model can reproduce a number of characteristic visual processing capabilities of the brain, in particular the capability to solve diverse visual processing tasks, also on temporally dispersed visual information, with remarkable robustness to noise. This V1 model, whose architecture and neurons markedly differ from those of deep neural networks used in current artificial intelligence (AI), such as convolutional neural networks (CNNs), also reproduces a number of characteristic neural coding properties of the brain, which provides explanations for its superior noise robustness. Because visual processing is substantially more energy efficient in the brain compared with CNNs in AI, such brain-like neural networks are likely to have an impact on future technology: as blueprints for visual processing in more energy-efficient neuromorphic hardware.
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Registered trials
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