Evidence map›Paper›PMID 19949718›Full record

SynthesisJournal of psychiatry & neuroscience : JPN2009

Functional atlas of emotional faces processing: a voxel-based meta-analysis of 105 functional magnetic resonance imaging studies.

Paolo Fusar-Poli, Anna Placentino, Francesco Carletti, Paola Landi, Paul Allen, Simon Surguladze, Francesco Benedetti, Marta Abbamonte, Roberto Gasparotti, Francesco Barale and 3 more

Open access · greenAbstract readMeta-AnalysisReview
In one paragraph

Synthesis in Journal of psychiatry & neuroscience : JPN, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 673 papers, 13 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
673citing papers in PubMed, 13 pooled it
23.5field-weighted citation impact, top 1% 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

673 citing papers in PubMed, 13 syntheses or guidelines pooled it, 1,284 citations in OpenAlex.

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  19. Oxytocin effects on amygdala reactivity to angry faces in males and females with antisocial personality disorder.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2023
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613 more citing papers are in PubMed but not listed here.

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

13 authors at 6 institutions in 2 countries.

Paolo Fusar-PoliFusar-Poli, Carletti, Allen, McGuire - Section of Neuroimaging, Department of Psychological Medicine, Institute of Psychiatry, King's College London, United Kingdom. p.fusar@libero.it
Anna Placentino
Francesco Carletti
Paola Landi
Paul Allen
Simon Surguladze
Francesco Benedetti
Marta Abbamonte
Roberto Gasparotti
Francesco Barale
Jorge Perez
Philip McGuire
Pierluigi Politi
University of Pavia · ITCentro San Giovanni di Dio Fatebenefratelli · ITKing's College London · GBUniversity of Brescia · ITVita-Salute San Raffaele University · ITWellcome Centre for Human Neuroimaging · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMost of our social interactions involve perception of emotional information from the faces of other people. Furthermore, such emotional processes are thought to be aberrant in a range of clinical disorders, including psychosis and depression. However, the exact neurofunctional maps underlying emotional facial processing are not well defined.

methodsTwo independent researchers conducted separate comprehensive PubMed (1990 to May 2008) searches to find all functional magnetic resonance imaging (fMRI) studies using a variant of the emotional faces paradigm in healthy participants. The search terms were: "fMRI AND happy faces," "fMRI AND sad faces," "fMRI AND fearful faces," "fMRI AND angry faces," "fMRI AND disgusted faces" and "fMRI AND neutral faces." We extracted spatial coordinates and inserted them in an electronic database. We performed activation likelihood estimation analysis for voxel-based meta-analyses.

resultsOf the originally identified studies, 105 met our inclusion criteria. The overall database consisted of 1785 brain coordinates that yielded an overall sample of 1600 healthy participants. Quantitative voxel-based meta-analysis of brain activation provided neurofunctional maps for 1) main effect of human faces; 2) main effect of emotional valence; and 3) modulatory effect of age, sex, explicit versus implicit processing and magnetic field strength. Processing of emotional faces was associated with increased activation in a number of visual, limbic, temporoparietal and prefrontal areas; the putamen; and the cerebellum. Happy, fearful and sad faces specifically activated the amygdala, whereas angry or disgusted faces had no effect on this brain region. Furthermore, amygdala sensitivity was greater for fearful than for happy or sad faces. Insular activation was selectively reported during processing of disgusted and angry faces. However, insular sensitivity was greater for disgusted than for angry faces. Conversely, neural response in the visual cortex and cerebellum was observable across all emotional conditions. LIMITATIONS: Although the activation likelihood estimation approach is currently one of the most powerful and reliable meta-analytical methods in neuroimaging research, it is insensitive to effect sizes.

conclusionOur study has detailed neurofunctional maps to use as normative references in future fMRI studies of emotional facial processing in psychiatric populations. We found selective differences between neural networks underlying the basic emotions in limbic and insular brain regions.

Indexed as

Facial ExpressionAdolescentAdultAgingAngerBrainEmotionsFaceFearFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedNerve NetSex Characteristics

Identifiers

PMID19949718
PMCPMC2783433
OpenAlexW2110431345

What OpenQuestion holds

Textmetadata
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.