Evidence map›Paper›PMID 32986115›Full record

ReviewSocial cognitive and affective neuroscience2021

Computational approaches to the neuroscience of social perception.

Jeffrey A Brooks, Ryan M Stolier, Jonathan B Freeman

Abstract readReview
In one paragraph

Review in Social cognitive and affective neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Exploring the relationships between first impressions and MMI ratings: a pilot study.Advances in health sciences education : theory and practice · 2023
    Article
  8. Article
  9. Review
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.

Jeffrey A BrooksDepartment of Psychology, New York University, New York, NY, USA.
Ryan M StolierColumbia University, 1190 Amsterdam Ave., New York, NY 10027, USA.
Jonathan B FreemanDepartment of Psychology, New York University, New York, NY, USA.ORCID 0000-0002-2061-8460

Funding

Investigating the Neural Basis of Flexible Emotion PerceptionR01MH112640 · NIMH · NEW YORK UNIVERSITY · PI FREEMAN, JONATHAN BRONNER · 2017 to 2021
$1.9M
NIMH NIH HHS R01 MH112640
6 · The paper itself

Abstract

Across multiple domains of social perception-including social categorization, emotion perception, impression formation and mentalizing-multivariate pattern analysis (MVPA) of functional magnetic resonance imaging (fMRI) data has permitted a more detailed understanding of how social information is processed and represented in the brain. As in other neuroimaging fields, the neuroscientific study of social perception initially relied on broad structure-function associations derived from univariate fMRI analysis to map neural regions involved in these processes. In this review, we trace the ways that social neuroscience studies using MVPA have built on these neuroanatomical associations to better characterize the computational relevance of different brain regions, and discuss how MVPA allows explicit tests of the correspondence between psychological models and the neural representation of social information. We also describe current and future advances in methodological approaches to multivariate fMRI data and their theoretical value for the neuroscience of social perception.

Indexed as

Brain MappingNeurosciencesBrainHumansMagnetic Resonance ImagingSocial Perceptioncomputational neuroscienceemotionmultivariate pattern analysissocial cognitionsocial perception

Identifiers

PMID32986115
PMCPMC8343569

What OpenQuestion holds

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LicenceCC BY-NC
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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.