Estimating average single-neuron visual receptive field sizes by fMRI
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Abstract
The noninvasive estimation of neuronal receptive field (RF) properties in vivo allows a detailed understanding of brain organization as well as its plasticity by longitudinal following of potential changes. Visual RFs measured invasively by electrophysiology in animal models have traditionally provided a great extent of our current knowledge about the visual brain and its disorders. Voxel-based estimates of population RF (pRF) by functional magnetic resonance imaging (fMRI) in humans revolutionized the field and have been used extensively in numerous studies. However, current methods cannot estimate single-neuron RF sizes as they reflect large populations of neurons with individual RF scatter. Here, we introduce an approach to estimate RF size using spatial frequency selectivity to checkerboard patterns. This method allowed us to obtain noninvasive, average single-neuron RF estimates over a large portion of human early visual cortex. These estimates were significantly smaller compared with prior pRF methods. Furthermore, fMRI and electrophysiology experiments in nonhuman primates demonstrated an exceptionally good match, validating the approach.
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Model predictions based on Keliris et al. receptive field size estimates are well correlated with patient data for phosphene size as a function of eccentricity (r(41) = 0.880, p < 0.0001).
“Simulations based on the Keliris et al. data were well correlated with the patient data, (r(41) = 0.880, p < 0.0001).”
From A virtual patient simulation modeling the neural and perceptual effects of human visual cortical stimulation, from pulse trains to percepts (2024) · cites this paper as [44]
The receptive field size estimates used (intercept 0.16, slope 0.08) are the smallest values reported in the literature.
“These are the smallest values reported in the literature.”
From A virtual patient simulation modeling the neural and perceptual effects of human visual cortical stimulation, from pulse trains to percepts (2024) · cites this paper as [44]
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da Costa, D., Kornemann, L., Goebel, R., & Senden, M. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.04.25.538251
Spatial frequency adaptation modulates population receptive field sizesPreprint
Altan, E., Morgan, C., Dakin, S. C., & Schwarzkopf, D. S. (2024) · eLife · doi:10.7554/elife.100734
Spatial frequency adaptation modulates population receptive field sizesPreprint
Altan, E., Morgan, C., Dakin, S. C., & Schwarzkopf, D. S. (2024) · eLife · doi:10.7554/elife.100734.1
Spatial frequency adaptation modulates population receptive field sizesPreprint
Altan, E., Morgan, C., Dakin, S. C., & Schwarzkopf, D. S. (2025) · eLife · doi:10.7554/elife.100734.2
Critical spatial separation at the scale of V1 receptive fields determines motion segmentationPreprint
Ghimire, B., Bakayat, R., Padala, A., Wiesner, S., & Huang, X. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.04.692462
Tactile Brain Function Mapping of Human Hand Based on Population Receptive Field Model
Luo, D., Wang, Y., Fu, S., Zhang, J., Wang, L., Wu, J., Yan, T., & Tong, X. (2026) · ICME International Conference on Complex Medical Engineering (CME) · doi:10.1109/cme70365.2026.11724210
- Authors
- Keliris, G. A., Li, Q., Papanikolaou, A., Logothetis, N. K., & Smirnakis, S. M.
- Affiliations
- University of Antwerp (BE)
- Max Planck Institute for Biological Cybernetics (DE)
- University of Manchester (GB)
- Brigham and Women's Hospital (US)
- Corresponding author
- Keliris, Georgios A.
- Smirnakis, Stelios M.
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2019-03-13
- Volume
- 116
- Issue
- 13
- Pages
- 6425-6434
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC6442598
- OpenAlex
- W2921960886
- Cited by
- 48
- References
- 64
- Citations by year
- 2026: 3 · 2025: 6 · 2024: 6 · 2023: 6 · 2022: 9 · 2021: 8 · 2020: 3 · 2019: 7
- FWCI
- 3.92
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion, cc-by-nc-nd)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Research Explorer (The University of Manchester) (publishedVersion, cc-by-nc-nd)
- UCL Discovery (University College London) (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Funders
- Bundesministerium für Bildung und Forschung (FKZ 01GQ1002, 01GQ1002)
- Max-Planck-Gesellschaft
- National Institutes of Health (5r01ey024019-05)
- National Eye Institute (R01 (EY024019), EY024019)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- population receptive field, spatial frequency selectivity, checkerboard pattern, early visual cortex, functional MRI, non-human primates, visual cortex organization
- MeSH terms
- Animals, Brain Mapping, Computer Simulation, Electrophysiology, Female, Humans, Magnetic Resonance Imaging, Male, Neurons, Visual Cortex, Visual Fields, Models, Animal
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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