Evidence map›Paper›PMID 34996892›Full record

ArticleScientific reports2022

Neural correlates of integration processes during dynamic face perception.

Nihan Alp, Huseyin Ozkan

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

2 authors.

Nihan AlpPsychology, Sabanci University, Istanbul, Turkey. nihanalp@sabanciuniv.edu.
Huseyin OzkanElectronics Engineering, Sabanci University, Istanbul, Turkey.

Funding

Sabancı Üniversitesi B.A.CG-19-01966Türkiye Bilimsel ve Teknolojik Araştirma Kurumu 220K038
6 · The paper itself

Abstract

Integrating the spatiotemporal information acquired from the highly dynamic world around us is essential to navigate, reason, and decide properly. Although this is particularly important in a face-to-face conversation, very little research to date has specifically examined the neural correlates of temporal integration in dynamic face perception. Here we present statistically robust observations regarding the brain activations measured via electroencephalography (EEG) that are specific to the temporal integration. To that end, we generate videos of neutral faces of individuals and non-face objects, modulate the contrast of the even and odd frames at two specific frequencies ([Formula: see text] and [Formula: see text]) in an interlaced manner, and measure the steady-state visual evoked potential as participants view the videos. Then, we analyze the intermodulation components (IMs: ([Formula: see text]), a linear combination of the fundamentals with integer multipliers) that consequently reflect the nonlinear processing and indicate temporal integration by design. We show that electrodes around the medial temporal, inferior, and medial frontal areas respond strongly and selectively when viewing dynamic faces, which manifests the essential processes underlying our ability to perceive and understand our social world. The generation of IMs is only possible if even and odd frames are processed in succession and integrated temporally, therefore, the strong IMs in our frequency spectrum analysis show that the time between frames (1/60 s) is sufficient for temporal integration.

Indexed as

Brain MappingElectroencephalographyFacial ExpressionFacial RecognitionTime PerceptionVisual PerceptionBrainEvoked Potentials, VisualFemaleHumansMalePhotic StimulationPredictive Value of TestsRecognition, PsychologyTime FactorsVideo Recording

Identifiers

PMID34996892
PMCPMC8742062

What OpenQuestion holds

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LicenceCC BY
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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.