ArticleCommunications biology2023
Recurrent connectivity supports higher-level visual and semantic object representations in the brain.
Article in Communications biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Preserving Harmonic Structure in FPVS-Oddball: A Two-Dimensional Cluster-Based Permutation Approach.Psychophysiology · 2026Article
- Disrupted Higher-Order Topology in OCD Brain Networks Revealed by Hodge Laplacian - an ENIGMA Study.bioRxiv : the preprint server for biology · 2026Article
- What makes memories vivid?Journal of experimental psychology. General · 2026Article
- Controlled Semantic Cognition: Precision Recordings Converge With in Silico Experiments to Reveal the Inner Workings of the Anterior Temporal Lobe Hub.Neurobiology of language (Cambridge, Mass.) · 2026Review
- Neural oscillations and top-down connectivity are modulated by object-scene congruency.Cerebral cortex (New York, N.Y. : 1991) · 2025Article
- Recurrence affects the geometry of visual representations across the ventral visual stream in the human brain.PLoS biology · 2025Article
- Neural Distinction between Visual Word and Object Recognition: An fMRI Study Using Pictographs.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Misspelled-Word Reading Modulates Late Cortical Dynamics.Human brain mapping · 2025Article
- Layer-specific spatiotemporal dynamics of feedforward and feedback in human visual object perception.bioRxiv : the preprint server for biology · 2025Article
- Overt Word Reading and Visual Object Naming in Adults with Dyslexia: Electroencephalography Study in Transparent Orthography.Bioengineering (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Visual object recognition has been traditionally conceptualised as a predominantly feedforward process through the ventral visual pathway. While feedforward artificial neural networks (ANNs) can achieve human-level classification on some image-labelling tasks, it's unclear whether computational models of vision alone can accurately capture the evolving spatiotemporal neural dynamics. Here, we probe these dynamics using a combination of representational similarity and connectivity analyses of fMRI and MEG data recorded during the recognition of familiar, unambiguous objects. Modelling the visual and semantic properties of our stimuli using an artificial neural network as well as a semantic feature model, we find that unique aspects of the neural architecture and connectivity dynamics relate to visual and semantic object properties. Critically, we show that recurrent processing between the anterior and posterior ventral temporal cortex relates to higher-level visual properties prior to semantic object properties, in addition to semantic-related feedback from the frontal lobe to the ventral temporal lobe between 250 and 500 ms after stimulus onset. These results demonstrate the distinct contributions made by semantic object properties in explaining neural activity and connectivity, highlighting it as a core part of object recognition not fully accounted for by current biologically inspired neural networks.
Indexed as
Identifiers
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.