Evidence map›Paper›PMID 39811658›Full record

ArticleiScience2025

Microsaccade selectivity as discriminative feature for object decoding.

Salar Nouri, Amirali Soltani Tehrani, Niloufar Faridani, Ramin Toosi, Jalaledin Noroozi, Mohammad-Reza A Dehaqani

Abstract read
In one paragraph

Article in iScience, 2025. 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

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Salar NouriSchool of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran 14399-57131, Iran.
Amirali Soltani TehraniSchool of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran 14399-57131, Iran.
Niloufar FaridaniSchool of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran 14399-57131, Iran.
Ramin ToosiSchool of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran 14399-57131, Iran.
Jalaledin NorooziSchool of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran 19395-5746, Iran.
Mohammad-Reza A DehaqaniSchool of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran 14399-57131, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microsaccades, a form of fixational eye movements, help maintain visual stability during stationary observations. This study examines the modulation of microsaccadic rates by various stimulus categories in monkeys and humans during a passive viewing task. Stimulus sets were grouped into four primary categories: human, animal, natural, and man-made. Distinct post-stimulus microsaccade patterns were identified across these categories, enabling successful decoding of the stimulus category with accuracy and recall of up to 85%. We observed that microsaccade rates are independent of pupil size changes. Neural data showed that category classification in the inferior temporal (IT) cortex peaks earlier than changes in microsaccade rates, suggesting feedback from the IT cortex influences eye movements after stimulus discrimination. These results contribute to neurobiological models, enhance human-machine interfaces, optimize experimental visual stimuli, and deepen understanding of microsaccades' role in object decoding.

Indexed as

Artificial intelligenceComputer scienceHuman-computer interaction

Identifiers

PMID39811658
PMCPMC11731985

What OpenQuestion holds

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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.