1. Neuroscience
Download icon

Bayesian analysis of retinotopic maps

  1. Noah C Benson  Is a corresponding author
  2. Jonathan Winawer
  1. New York University, United States
Tools and Resources
  • Cited 0
  • Views 379
  • Annotations
Cite this article as: eLife 2018;7:e40224 doi: 10.7554/eLife.40224

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.

Article and author information

Author details

  1. Noah C Benson

    Department of Psychology, New York University, New York, United States
    For correspondence
    nben@nyu.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2365-8265
  2. Jonathan Winawer

    Department of Psychology, New York University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7475-5586

Funding

National Eye Institute (R01 EY027401)

  • Jonathan Winawer

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: This study was conducted with the approval of the New York University Institutional Review Board (IRB-FY2016-363) and in accordance with the Declaration of Helsinki. Informed consent was obtained for all subjects.

Reviewing Editor

  1. Mark Schira, University of Wollongong, Australia

Publication history

  1. Received: July 18, 2018
  2. Accepted: November 29, 2018
  3. Accepted Manuscript published: December 6, 2018 (version 1)

Copyright

© 2018, Benson & Winawer

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 379
    Page views
  • 67
    Downloads
  • 0
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

Further reading

    1. Neuroscience
    2. Structural Biology and Molecular Biophysics
    Dipak N Patil et al.
    Research Article
    1. Biochemistry and Chemical Biology
    2. Neuroscience
    Apurwa M Sharma et al.
    Research Advance