Cortical Magnification in Human Visual Cortex Parallels Task Performance around the Visual Field

  1. Noah C Benson  Is a corresponding author
  2. Eline R Kupers
  3. Antoine Babot
  4. Marisa Carrasco
  5. Jonathan Winawer
  1. University of Washington, United States
  2. New York University, United States
  3. Spinoza Centre for Neuroimaging, Netherlands

Abstract

Human vision has striking radial asymmetries, with performance on many tasks varying sharply with stimulus polar angle. Performance is generally better on the horizontal than vertical meridian, and on the lower than upper vertical meridian, and these asymmetries decrease gradually with deviation from the vertical meridian. Here we report cortical magnification at a fine angular resolution around the visual field. This precision enables comparisons between cortical magnification and behavior, between cortical magnification and retinal cell densities, and between cortical magnification in twin pairs. We show that cortical magnification in human primary visual cortex, measured in 163 subjects, varies substantially around the visual field, with a pattern similar to behavior. These radial asymmetries in cortex are larger than those found in the retina, and they are correlated between monozygotic twin pairs. These findings indicate a tight link between cortical topography and behavior, and suggest that visual field asymmetries are partly heritable.

Data availability

All source code and data have been permanently archived on the Open Science Framework with DOI 10.17605/OSF.IO/5GPRZ.

The following data sets were generated
    1. Benson NC
    2. Kupers ER
    3. Barbot A
    4. Carrasco M
    5. Winawer J
    (2020) Visual Performance Fields
    Open Science Framework, doi:10.17605/OSF.IO/5GPRZ.
The following previously published data sets were used
    1. Benson NC et al.
    (2018) The Human Connectome Project 7 Tesla Retinotopy Dataset
    Open Science Framework, doi:10.17605/OSF.IO/BW9EC.

Article and author information

Author details

  1. Noah C Benson

    eScience Institute, University of Washington, Seattle, United States
    For correspondence
    nben@uw.edu
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2365-8265
  2. Eline R Kupers

    Department of Psychology, New York University, New York, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4972-5307
  3. Antoine Babot

    Netherlands Institute for Neuroscience, Spinoza Centre for Neuroimaging, Amsterdam, Netherlands
    Competing interests
    No competing interests declared.
  4. Marisa Carrasco

    Department of Psychology, New York University, New York, United States
    Competing interests
    Marisa Carrasco, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1002-9056
  5. Jonathan Winawer

    Department of Psychology, New York University, New York, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7475-5586

Funding

National Eye Institute (RO1-EY027401)

  • Marisa Carrasco
  • 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: No human subjects data were collected for this paper. All data used in this paper were obtained from previous publications and publicly-available datasets in which subjects provided informed consent. Primarily, analyses were performed using data from the HCP (D. C. Van Essen et al. 2012, Neuroimage 62:2222-2231), including data from the HCP that were reanalyzed by subsequent studies (Benson et al. 2018, J Vis 18:23; Benson et al. 2021, bioRxiv 10.1101/2020.12.30.424856). Additionally, Figures 1 and 3 includes data replotted from previous publications by the authors (Carrasco et al. 2001, Spat Vis 15:61-75; Abrams et al. 2012, Vision Res 52:70-78; Barbot et al. 2021, J Vis 21:2), and Figure 5 includes publicly available data from Curcio et al. (1990, J Comp Neurol 292:497-523). In all cases, informed consent was obtained from subjects in the original studies, and all applicable use policies were followed in the use of the data. No personal health information is included in this paper or in the associated dataset or code.

Copyright

© 2021, Benson et al.

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

  • 2,652
    views
  • 304
    downloads
  • 63
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

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)

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

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

  1. Noah C Benson
  2. Eline R Kupers
  3. Antoine Babot
  4. Marisa Carrasco
  5. Jonathan Winawer
(2021)
Cortical Magnification in Human Visual Cortex Parallels Task Performance around the Visual Field
eLife 10:e67685.
https://doi.org/10.7554/eLife.67685

Share this article

https://doi.org/10.7554/eLife.67685

Further reading

    1. Neuroscience
    Rituja S Bisen, Fathima Mukthar Iqbal ... Jan M Ache
    Research Article

    Insulin plays a key role in metabolic homeostasis. Drosophila insulin-producing cells (IPCs) are functional analogues of mammalian pancreatic beta cells and release insulin directly into circulation. To investigate the in vivo dynamics of IPC activity, we quantified the effects of nutritional and internal state changes on IPCs using electrophysiological recordings. We found that the nutritional state strongly modulates IPC activity. IPC activity decreased with increasing periods of starvation. Refeeding flies with glucose or fructose, two nutritive sugars, significantly increased IPC activity, whereas non-nutritive sugars had no effect. In contrast to feeding, glucose perfusion did not affect IPC activity. This was reminiscent of the mammalian incretin effect, where glucose ingestion drives higher insulin release than intravenous application. Contrary to IPCs, Diuretic hormone 44-expressing neurons in the pars intercerebralis (DH44PINs) responded to glucose perfusion. Functional connectivity experiments demonstrated that these DH44PINs do not affect IPC activity, while other DH44Ns inhibit them. Hence, populations of autonomously and systemically sugar-sensing neurons work in parallel to maintain metabolic homeostasis. Accordingly, activating IPCs had a small, satiety-like effect on food-searching behavior and reduced starvation-induced hyperactivity, whereas activating DH44Ns strongly increased hyperactivity. Taken together, we demonstrate that IPCs and DH44Ns are an integral part of a modulatory network that orchestrates glucose homeostasis and adaptive behavior in response to shifts in the metabolic state.

    1. Neuroscience
    Yichun Shuai, Megan Sammons ... Yoshinori Aso
    Tools and Resources

    The mushroom body (MB) is the center for associative learning in insects. In Drosophila, intersectional split-GAL4 drivers and electron microscopy (EM) connectomes have laid the foundation for precise interrogation of the MB neural circuits. However, investigation of many cell types upstream and downstream of the MB has been hindered due to lack of specific driver lines. Here we describe a new collection of over 800 split-GAL4 and split-LexA drivers that cover approximately 300 cell types, including sugar sensory neurons, putative nociceptive ascending neurons, olfactory and thermo-/hygro-sensory projection neurons, interneurons connected with the MB-extrinsic neurons, and various other cell types. We characterized activation phenotypes for a subset of these lines and identified a sugar sensory neuron line most suitable for reward substitution. Leveraging the thousands of confocal microscopy images associated with the collection, we analyzed neuronal morphological stereotypy and discovered that one set of mushroom body output neurons, MBON08/MBON09, exhibits striking individuality and asymmetry across animals. In conjunction with the EM connectome maps, the driver lines reported here offer a powerful resource for functional dissection of neural circuits for associative learning in adult Drosophila.