Evidence map›Paper›PMID 28619657›Full record

ArticleNeuroImage2017

Low-frequency oscillations employ a general coding of the spatio-temporal similarity of dynamic faces.

Nicholas Furl, Michael Lohse, Francesca Pizzorni-Ferrarese

Open access · hybridAbstract read
In one paragraph

Article in NeuroImage, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.3field-weighted citation impact, top 20% 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

7 citing papers in PubMed, 21 citations in OpenAlex.

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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

3 authors at 2 institutions in 1 country.

Nicholas FurlDepartment of Psychology, Royal Holloway, University of London, Surrey TW20 0EX, United Kingdom; Cognition and Brain Sciences Unit, Medical Research Council, Cambridge CB2 7EF, United Kingdom. Electronic address: nicholas.furl@rhul.ac.uk.
Michael LohseCognition and Brain Sciences Unit, Medical Research Council, Cambridge CB2 7EF, United Kingdom; Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford OX1 3QX, United Kingdom.
Francesca Pizzorni-FerrareseDepartment of Psychology, Royal Holloway, University of London, Surrey TW20 0EX, United Kingdom.
MRC Cognition and Brain Sciences Unit · GBRoyal Holloway University of London · GB

Funding

Wellcome TrustWellcome Trust 105241/Z/14/Z
6 · The paper itself

Abstract

Brain networks use neural oscillations as information transfer mechanisms. Although the face perception network in occipitotemporal cortex is well-studied, contributions of oscillations to face representation remain an open question. We tested for links between oscillatory responses that encode facial dimensions and the theoretical proposal that faces are encoded in similarity-based "face spaces". We quantified similarity-based encoding of dynamic faces in magnetoencephalographic sensor-level oscillatory power for identity, expression, physical and perceptual similarity of facial form and motion. Our data show that evoked responses manifest physical and perceptual form similarity that distinguishes facial identities. Low-frequency induced oscillations (< 20Hz) manifested more general similarity structure, which was not limited to identity, and spanned physical and perceived form and motion. A supplementary fMRI-constrained source reconstruction implicated fusiform gyrus and V5 in this similarity-based representation. These findings introduce a potential link between "face space" encoding and oscillatory network communication, which generates new hypotheses about the potential oscillation-mediated mechanisms that might encode facial dimensions.

Indexed as

Facial ExpressionAdultBrain WavesCerebral CortexEvoked PotentialsFacial RecognitionFunctional NeuroimagingHumansMagnetic Resonance ImagingMagnetoencephalographyMotion PerceptionYoung AdultAction perceptionEmotional expressionsFace perceptionMagnetoencephalographyNeural oscillationsRepresentational similarity analysis

Identifiers

PMID28619657
PMCPMC6390175
OpenAlexW2626765758

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.