ArticleCurrent biology : CB2020
Generative Feedback Explains Distinct Brain Activity Codes for Seen and Mental Images.
Article in Current biology : CB, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.
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Who cites it
49 citing papers in PubMed, 116 citations in OpenAlex.
- Medial temporal default mode network selectively encodes autobiographical visual imagery.Science advances · 2026Article
- Retinotopic coding organizes the interaction between internally and externally oriented brain networks.eLife · 2026Article
- Hippocampal mechanisms underlying the resolution of competition in memory and perception.Nature communications · 2026Article
- Article
- The primate claustrum as a hub for precision weighting of prediction errors across the cortical hierarchy.PLoS biology · 2026Article
- MIRAGE: Robust multi-modal architectures translate fMRI-to-image models from vision to mental imagery.PLoS computational biology · 2026Article
- The representation of object concepts across the brain.bioRxiv : the preprint server for biology · 2025Article
- Sensory reformatting for a working visual memory.Trends in cognitive sciences · 2025Review
- Early Visual Cortex Supports One-Shot Episodic Memory via Spatially Tuned Reactivation.bioRxiv : the preprint server for biology · 2025Article
- A transformation from vision to imagery in the human brain.bioRxiv : the preprint server for biology · 2025Article
- Task-relevant representational spaces in human memory traces.PLoS computational biology · 2025Article
- Domain Adaptation-enhanced searchlight: enabling classification of brain states from visual perception to mental imagery.Brain informatics · 2025Article
- Evolving Engrams Demand Changes in Effective Cues.Hippocampus · 2025Review
- Reinstatement and transformation of memory traces for recognition.Science advances · 2025Article
- Feedback scales the spatial tuning of cortical responses during both visual working memory and long-term memory.bioRxiv : the preprint server for biology · 2024Article
- Metacontrol Regulates Creative Thinking: An EEG Complexity Analysis Based on Multiscale Entropy.Brain sciences · 2024Article
- Maintenance and transformation of representational formats during working memory prioritization.Nature communications · 2024Article
- Neuronal representation of visual working memory content in the primate primary visual cortex.Science advances · 2024Article
- The attentive reconstruction of objects facilitates robust object recognition.PLoS computational biology · 2024Article
- Linguistic modulation of the neural encoding of phonemes.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
The relationship between mental imagery and vision is a long-standing problem in neuroscience. Currently, it is not known whether differences between the activity evoked during vision and reinstated during imagery reflect different codes for seen and mental images. To address this problem, we modeled mental imagery in the human brain as feedback in a hierarchical generative network. Such networks synthesize images by feeding abstract representations from higher to lower levels of the network hierarchy. When higher processing levels are less sensitive to stimulus variation than lower processing levels, as in the human brain, activity in low-level visual areas should encode variation in mental images with less precision than seen images. To test this prediction, we conducted an fMRI experiment in which subjects imagined and then viewed hundreds of spatially varying naturalistic stimuli. To analyze these data, we developed imagery-encoding models. These models accurately predicted brain responses to imagined stimuli and enabled accurate decoding of their position and content. They also allowed us to compare, for every voxel, tuning to seen and imagined spatial frequencies, as well as the location and size of receptive fields in visual and imagined space. We confirmed our prediction, showing that, in low-level visual areas, imagined spatial frequencies in individual voxels are reduced relative to seen spatial frequencies and that receptive fields in imagined space are larger than in visual space. These findings reveal distinct codes for seen and mental images and link mental imagery to the computational abilities of generative networks.
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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.