Evidence map›Paper›PMID 39680431›Full record

ArticleeLife2024

Attention modulates human visual responses to objects by tuning sharpening.

Narges Doostani, Gholam-Ali Hossein-Zadeh, Radoslaw M Cichy, Maryam Vaziri-Pashkam

Abstract read
In one paragraph

Article in eLife, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Narges DoostaniSchool of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran.ORCID https://orcid.org/0000-0001-5775-6595
Gholam-Ali Hossein-ZadehSchool of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran.
Radoslaw M CichyDepartment of Education and Psychology, Freie Universität Berlin, Berlin, Germany.ORCID https://orcid.org/0000-0003-4190-6071
Maryam Vaziri-PashkamDepartment of Psychological and Brain Sciences, University of Delaware, Newark, United States.ORCID https://orcid.org/0000-0003-1830-2501

Funding

Functional Anatomy Of Perceptual and Attentional Systems in the Primate BrainZIAMH002035 · NIMH · NATIONAL INSTITUTE OF MENTAL HEALTH · PI UNGERLEIDER, LESLIE G · 2009 to 2021
$13.9M
Intramural NIH HHS ZIA MH002035NIH HHS ZIA-MH002035
6 · The paper itself

Abstract

Visual stimuli compete with each other for cortical processing and attention biases this competition in favor of the attended stimulus. How does the relationship between the stimuli affect the strength of this attentional bias? Here, we used functional MRI to explore the effect of target-distractor similarity in neural representation on attentional modulation in the human visual cortex using univariate and multivariate pattern analyses. Using stimuli from four object categories (human bodies, cats, cars, and houses), we investigated attentional effects in the primary visual area V1, the object-selective regions LO and pFs, the body-selective region EBA, and the scene-selective region PPA. We demonstrated that the strength of the attentional bias toward the target is not fixed but decreases with increasing target-distractor similarity. Simulations provided evidence that this result pattern is explained by tuning sharpening rather than an increase in gain. Our findings provide a mechanistic explanation for the behavioral effects of target-distractor similarity on attentional biases and suggest tuning sharpening as the underlying mechanism in object-based attention.

Indexed as

AttentionMagnetic Resonance ImagingPhotic StimulationVisual CortexVisual PerceptionAdultFemaleHumansMalePrimary Visual CortexYoung AdultfMRIhumanMVPAneuroscienceobject-based attentiontarget-distractor similaritytuning sharpening

Identifiers

PMID39680431
PMCPMC11649243

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Registered trials

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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.