Evidence map›Paper›PMID 36027910›Full record

ArticleCurrent biology : CB2022

A highly selective response to food in human visual cortex revealed by hypothesis-free voxel decomposition.

Meenakshi Khosla, N Apurva Ratan Murty, Nancy Kanwisher

Open access · greenAbstract read
In one paragraph

Article in Current biology : CB, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed
8.0field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

51 citing papers in PubMed, 75 citations in OpenAlex.

  1. Article
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  3. Multidimensional Feature Tuning in Category Selective Areas of Human Visual Cortex.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
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  8. The cortical canvas.Proceedings of the National Academy of Sciences of the United States of America · 2026
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  19. The cerebellar components of the human language network.bioRxiv : the preprint server for biology · 2025
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Meenakshi KhoslaMcGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA. Electronic address: mkhosla@mit.edu.
N Apurva Ratan MurtyMcGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
Nancy KanwisherMcGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
McGovern Institute for Brain Research · USMassachusetts Institute of Technology · US

Funding

How Does the Functional Organization of the Human Brain Arise in Development?DP1HD091947 · NICHD · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI KANWISHER, NANCY · 2016 to 2020
$5.4M
Towards a computationally precise characterization of the human ventral visual pathwayR00EY032603 · NEI · GEORGIA INSTITUTE OF TECHNOLOGY · PI N Apurva Ratan Murty · 2024 to 2026
$746k
Towards a computationally precise characterization of the human ventral visual pathwayK99EY032603 · NEI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI RATAN MURTY, N APURVA · 2021 to 2022
$221k
NEI NIH HHS K99 EY032603NEI NIH HHS R00 EY032603NICHD NIH HHS DP1 HD091947
6 · The paper itself

Abstract

Prior work has identified cortical regions selectively responsive to specific categories of visual stimuli. However, this hypothesis-driven work cannot reveal how prominent these category selectivities are in the overall functional organization of the visual cortex, or what others might exist that scientists have not thought to look for. Furthermore, standard voxel-wise tests cannot detect distinct neural selectivities that coexist within voxels. To overcome these limitations, we used data-driven voxel decomposition methods to identify the main components underlying fMRI responses to thousands of complex photographic images. Our hypothesis-neutral analysis rediscovered components selective for faces, places, bodies, and words, validating our method and showing that these selectivities are dominant features of the ventral visual pathway. The analysis also revealed an unexpected component with a distinct anatomical distribution that responded highly selectively to images of food. Alternative accounts based on low- to mid-level visual features, such as color, shape, or texture, failed to account for the food selectivity of this component. High-throughput testing and control experiments with matched stimuli on a highly accurate computational model of this component confirm its selectivity for food. We registered our methods and hypotheses before replicating them on held-out participants and in a novel dataset. These findings demonstrate the power of data-driven methods and show that the dominant neural responses of the ventral visual pathway include not only selectivities for faces, scenes, bodies, and words but also the visually heterogeneous category of food, thus constraining accounts of when and why functional specialization arises in the cortex.

Indexed as

Brain MappingVisual CortexHumansMagnetic Resonance ImagingPattern Recognition, VisualVisual Pathwaysbig datacategory selectivityfunctional organizationhigh-resolution fMRIhypothesis-freenatural stimuli

Identifiers

PMID36027910
PMCPMC9561032
OpenAlexW4293044477

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

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.