ArticleeLife2018
Bayesian analysis of retinotopic maps.
Article in eLife, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 107 papers.
What it found
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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.
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Who cites it
107 citing papers in PubMed.
- Mapping human visual contrast sensitivity and vision loss across the visual field with model-based fMRI.eLife · 2026Article
- Increased Attentive Use Is Linked to More Idiosyncratic Functional Connections.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026Article
- Hippocampal mechanisms underlying the resolution of competition in memory and perception.Nature communications · 2026Article
- Sulcal pleating captures functional boundaries in human visual cortex.bioRxiv : the preprint server for biology · 2026Article
- Cortex-specific inversion of visual responses during sleep.Nature communications · 2026Article
- Protracted Functional and Structural Reorganization of Human Prefrontal Cortex Supports Lateralized Category Geometries.bioRxiv : the preprint server for biology · 2026Article
- An increasingly efficient narrowband object-recognition channel along the ventral stream.bioRxiv : the preprint server for biology · 2026Article
- A Systematic Characterization of Causal Interactions Between Human Visual Areas.bioRxiv : the preprint server for biology · 2026Article
- Bridging the gap with invasive imaging: promises and challenges of a new generation of ultrahigh resolution fMRI.bioRxiv : the preprint server for biology · 2026Article
- From adolescence to adulthood: functional fingerprints of high-level visual cortex reveal differential development of visuospatial processing.bioRxiv : the preprint server for biology · 2026Article
- Cortex-specific inversion of visual responses during sleep.bioRxiv : the preprint server for biology · 2026Article
- Article
- Quantification of planar cortical magnification with optimal transport and topological smoothing.NeuroImage · 2026Article
- Predicting functional topography of the human visual cortex from cortical anatomy at scale.bioRxiv : the preprint server for biology · 2026Article
- CNeuroMod-THINGS, a densely-sampled fMRI dataset for visual neuroscience.Scientific data · 2026Article
- Article
- No Unique Magnocellular Facilitation in Parafoveal Processing: A Combined EEG and Eye Tracking Study.Neurobiology of language (Cambridge, Mass.) · 2026Article
- Probabilistic working memory representations in human cortex guide behavior.bioRxiv : the preprint server for biology · 2025Article
- Spatial attention selectively alters visual cortical representation during target anticipation.Nature communications · 2025Article
- Cortical-layer EEG-fMRI at 7T: experimental setup and analysis pipeline to elucidate generating mechanisms of alpha oscillations.bioRxiv : the preprint server for biology · 2025Article
47 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Human visual cortex is organized into multiple retinotopic maps. Characterizing the arrangement of these maps on the cortical surface is essential to many visual neuroscience studies. Typically, maps are obtained by voxel-wise analysis of fMRI data. This method, while useful, maps only a portion of the visual field and is limited by measurement noise and subjective assessment of boundaries. We developed a novel Bayesian mapping approach which combines observation-a subject's retinotopic measurements from small amounts of fMRI time-with a prior-a learned retinotopic atlas. This process automatically draws areal boundaries, corrects discontinuities in the measured maps, and predicts validation data more accurately than an atlas alone or independent datasets alone. This new method can be used to improve the accuracy of retinotopic mapping, to analyze large fMRI datasets automatically, and to quantify differences in map properties as a function of health, development and natural variation between individuals.
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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.