ReviewF1000Research2020
Recent advances in understanding object recognition in the human brain: deep neural networks, temporal dynamics, and context.
Review in F1000Research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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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
13 citing papers in PubMed, 31 citations in OpenAlex.
- The neural processes of illusory occlusion in object recognition.Journal of vision · 2026Article
- The role of event understanding in guiding attentional selection in real-world scenes: The Scene Perception & Event Comprehension Theory (SPECT).Attention, perception & psychophysics · 2026Review
- Brief Encounters with Real Objects Modulate the Medial Parietal But Not Occipitotemporal Cortex.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Deep oscillatory neural network.Scientific reports · 2025Article
- Text-related functionality and dynamics of visual human pre-frontal activations revealed through neural network convergence.Communications biology · 2025Article
- Revealing the Concealed in Monocular and Binocular Vision.Vision (Basel, Switzerland) · 2025Review
- Human infant EEG recordings for 200 object images presented in rapid visual streams.Scientific data · 2025Article
- Spatiotemporal Properties of Common Semantic Categories for Words and Pictures.Journal of cognitive neuroscience · 2024Article
- Cortical time-course of evidence accumulation during semantic processing.Communications biology · 2023Article
- Multisensory perception constrains the formation of object categories: a review of evidence from sensory-driven and predictive processes on categorical decisions.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Review
- Human EEG recordings for 1,854 concepts presented in rapid serial visual presentation streams.Scientific data · 2022Article
- Do Humans and Deep Convolutional Neural Networks Use Visual Information Similarly for the Categorization of Natural Scenes?Cognitive science · 2021Article
- Overfitting the Literature to One Set of Stimuli and Data.Frontiers in human neuroscience · 2021Article
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 at 1 institution in 1 country.
Funding
Abstract
Object recognition is the ability to identify an object or category based on the combination of visual features observed. It is a remarkable feat of the human brain, given that the patterns of light received by the eye associated with the properties of a given object vary widely with simple changes in viewing angle, ambient lighting, and distance. Furthermore, different exemplars of a specific object category can vary widely in visual appearance, such that successful categorization requires generalization across disparate visual features. In this review, we discuss recent advances in understanding the neural representations underlying object recognition in the human brain. We highlight three current trends in the approach towards this goal within the field of cognitive neuroscience. Firstly, we consider the influence of deep neural networks both as potential models of object vision and in how their representations relate to those in the human brain. Secondly, we review the contribution that time-series neuroimaging methods have made towards understanding the temporal dynamics of object representations beyond their spatial organization within different brain regions. Finally, we argue that an increasing emphasis on the context (both visual and task) within which object recognition occurs has led to a broader conceptualization of what constitutes an object representation for the brain. We conclude by identifying some current challenges facing the experimental pursuit of understanding object recognition and outline some emerging directions that are likely to yield new insight into this complex cognitive process.
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What OpenQuestion holds
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.