Evidence map›Paper›PMID 30522854›Full record

ArticleDevelopmental cognitive neuroscience2019

Development of brain networks for social functions: Confirmatory analyses in a large open source dataset.

Hilary Richardson

Abstract read
In one paragraph

Article in Developmental cognitive neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

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  6. The Cognitive-Affective Social Processing and Emotion Regulation (CASPER) model.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026
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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

1 author.

Hilary RichardsonMassachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 43 Vassar Street, 46-4021, Cambridge, MA, 02139, United States. Electronic address: hlrich@mit.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human observers show robust activity in distinct brain networks during movie-viewing. For example, scenes that emphasize characters' thoughts evoke activity in the "Theory of Mind" (ToM) network, whereas scenes that emphasize characters' bodily sensations evoke activity in the "Pain Matrix." A prior exploratory fMRI study used a naturalistic movie-viewing stimulus to study the developmental origins of this functional dissociation, and the links between cortical and cognitive changes in children's social development (Richardson et al., 2018). To replicate and extend this work, the current study utilized a large publicly available dataset (n = 241, ages 5-20 years) (Alexander et al., 2017) who viewed "The Present" (Frey, 2014) and completed a resting state scan (n = 200) while undergoing fMRI. This study provides confirmatory evidence that 1) ToM and pain networks are functionally dissociated early in development, 2) selectivity increases with age, and in ToM regions, with a behavioral index of social reasoning. Additionally, while inter-region correlations are similar when measured during the movie and at rest, only inter-region correlations measured during movie-viewing correlated with functional maturity. This study demonstrates the scientific benefits of open source data in developmental cognitive neuroscience, and provides insight into the relationship between functional and intrinsic properties of the developing brain.

Indexed as

AdolescentAdultBrainChildChild, PreschoolDatasets as TopicFemaleHumansMagnetic Resonance ImagingMaleTheory of MindYoung AdultDevelopmentfMRIFunctional connectivityOpen source dataResting stateTheory of mind

Identifiers

PMID30522854
PMCPMC6969289

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.