ArticleeLife2018
How biological attention mechanisms improve task performance in a large-scale visual system model.
Article in eLife, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- Predictive coding explains asymmetric connectivity in the brain: A neural network study.PLoS computational biology · 2026Article
- Modeling attention and binding in the brain through bidirectional recurrent gating.Nature communications · 2026Article
- Optimized feature gains explain and predict successes and failures of human selective listening.Nature human behaviour · 2026Article
- Modulation of feature attention by reward prediction error explains value learning behavior.bioRxiv : the preprint server for biology · 2026Article
- Adaptive stretching of representations across brain regions and deep learning model layers.Nature communications · 2025Article
- Emergent neuronal mechanisms mediating covert attention in convolutional neural networks.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Modulatory feedback determines attentional object segmentation in a model of the ventral stream.PloS one · 2025Article
- Perceptual Expertise and Attention: An Exploration using Deep Neural Networks.bioRxiv : the preprint server for biology · 2024Article
- Emergence of Emotion Selectivity in Deep Neural Networks Trained to Recognize Visual Objects.bioRxiv : the preprint server for biology · 2024Article
- Emergence of Emotion Selectivity in Deep Neural Networks Trained to Recognize Visual Objects.PLoS computational biology · 2024Article
- Targeted V1 comodulation supports task-adaptive sensory decisions.Nature communications · 2023Article
- The neuroconnectionist research programme.Nature reviews. Neuroscience · 2023Review
- Article
- A brain-inspired object-based attention network for multiobject recognition and visual reasoning.Journal of vision · 2023Article
- A rubric for human-like agents and NeuroAI.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Review
- Efficient coding theory of dynamic attentional modulation.PLoS biology · 2022Article
- Selective particle attention: Rapidly and flexibly selecting features for deep reinforcement learning.Neural networks : the official journal of the International Neural Network Society · 2022Article
- Article
- Emerged human-like facial expression representation in a deep convolutional neural network.Science advances · 2022Article
- Prediction of Time Series Gene Expression and Structural Analysis of Gene Regulatory Networks Using Recurrent Neural Networks.Entropy (Basel, Switzerland) · 2022Article
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Authors and funding
2 authors.
Funding
Abstract
How does attentional modulation of neural activity enhance performance? Here we use a deep convolutional neural network as a large-scale model of the visual system to address this question. We model the feature similarity gain model of attention, in which attentional modulation is applied according to neural stimulus tuning. Using a variety of visual tasks, we show that neural modulations of the kind and magnitude observed experimentally lead to performance changes of the kind and magnitude observed experimentally. We find that, at earlier layers, attention applied according to tuning does not successfully propagate through the network, and has a weaker impact on performance than attention applied according to values computed for optimally modulating higher areas. This raises the question of whether biological attention might be applied at least in part to optimize function rather than strictly according to tuning. We suggest a simple experiment to distinguish these alternatives.
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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.