ArticleFrontiers in neuroscience2020
Investigating the Reliability of Population Receptive Field Size Estimates Using fMRI.
Article in Frontiers in neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Robust and reproducible population receptive field mapping in patients with retinal pathologies.Eye (London, England) · 2026Article
- Distinct Roles of Deep and Superficial Cortical Layers in Tone Prediction, Comparison, and Adaptation in Human Auditory Cortices.Nature communications · 2026Article
- Quantification of planar cortical magnification with optimal transport and topological smoothing.NeuroImage · 2026Article
- Article
- Improving the reliability and accuracy of population receptive field measures using a logarithmically warped stimulus.Journal of vision · 2025Article
- Improving the Reliability and Accuracy of Population Receptive Field Measures Using a Logarithmically Warped Stimulus.bioRxiv : the preprint server for biology · 2024Article
- Characterizing Spatiotemporal Population Receptive Fields in Human Visual Cortex with fMRI.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- A selection and targeting framework of cortical locations for line-scanning fMRI.Human brain mapping · 2023Article
- Selective attention sharpens population receptive fields in human auditory cortex.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- Characterizing visual cortical magnification with topological smoothing and optimal transportation.Proceedings of SPIE--the International Society for Optical Engineering · 2023Article
- What has vision science taught us about functional MRI?NeuroImage · 2022Article
- Quantitative characterization of the human retinotopic map based on quasiconformal mapping.Medical image analysis · 2022Article
- A method for mapping retinal images in early visual cortical areas.NeuroImage · 2021Article
- Cross-dataset reproducibility of human retinotopic maps.NeuroImage · 2021Article
- Topology-preserving smoothing of retinotopic maps.PLoS computational biology · 2021Article
- Population Receptive Field Shapes in Early Visual Cortex Are Nearly Circular.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Article
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4 authors.
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Abstract
In functional MRI (fMRI), population receptive field (pRF) models allow a quantitative description of the response as a function of the features of the stimuli that are relevant for each voxel. The most popular pRF model used in fMRI assumes a Gaussian shape in the features space (e.g., the visual field) reducing the description of the voxel's pRF to the Gaussian mean (the pRF preferred feature) and standard deviation (the pRF size). The estimation of the pRF mean has been proven to be highly reliable. However, the estimate of the pRF size has been shown not to be consistent within and between subjects. While this issue has been noted experimentally, here we use an optimization theory perspective to describe how the inconsistency in estimating the pRF size is linked to an inherent property of the Gaussian pRF model. When fitting such models, the goodness of fit is less sensitive to variations in the pRF size than to variations in the pRF mean. We also show how the same issue can be considered from a bias-variance perspective. We compare different estimation procedures in terms of the reliability of their estimates using simulated and real fMRI data in the visual (using the Human Connectome Project database) and auditory domain. We show that, the reliability of the estimate of the pRF size can be improved considering a linear combination of those pRF models with similar goodness of fit or a permutation based approach. This increase in reliability of the pRF size estimate does not affect the reliability of the estimate of the pRF mean and the prediction accuracy.
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