ArticleCommunications biology2023
Human brain responses are modulated when exposed to optimized natural images or synthetically generated images.
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 6 papers.
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Who cites it
6 citing papers in PubMed.
- In silico discovery of representational relationships across visual cortex.Nature human behaviour · 2025Article
- Article
- Direct perception of affective valence from vision.Nature communications · 2024Article
- Comparison of whole-brain task-modulated functional connectivity methods for fMRI task connectomics.Communications biology · 2024Article
- Comparison of whole-brain task-modulated functional connectivity methods for fMRI task connectomics.bioRxiv : the preprint server for biology · 2024Article
- Human brain responses are modulated when exposed to optimized natural images or synthetically generated images.Communications biology · 2023Article
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Authors and funding
4 authors.
Funding
Abstract
Understanding how human brains interpret and process information is important. Here, we investigated the selectivity and inter-individual differences in human brain responses to images via functional MRI. In our first experiment, we found that images predicted to achieve maximal activations using a group level encoding model evoke higher responses than images predicted to achieve average activations, and the activation gain is positively associated with the encoding model accuracy. Furthermore, anterior temporal lobe face area (aTLfaces) and fusiform body area 1 had higher activation in response to maximal synthetic images compared to maximal natural images. In our second experiment, we found that synthetic images derived using a personalized encoding model elicited higher responses compared to synthetic images from group-level or other subjects' encoding models. The finding of aTLfaces favoring synthetic images than natural images was also replicated. Our results indicate the possibility of using data-driven and generative approaches to modulate macro-scale brain region responses and probe inter-individual differences in and functional specialization of the human visual system.
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