Evidence map›Paper›PMID 34512293›Full record

ReviewFrontiers in human neuroscience2021

Taking a Computational Cultural Neuroscience Approach to Study Parent-Child Similarities in Diverse Cultural Contexts.

Pin-Hao A Chen, Yang Qu

Abstract readReview
In one paragraph

Review in Frontiers in human neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Parent-Child Neural Similarity and Synchrony: Toward an Integrative Framework.The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry · 2026
    Review
  2. Review
  3. Article
  4. Family Cohesion Moderates the Relation between Parent-Child Neural Connectivity Pattern Similarity and Youth's Emotional Adjustment.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023
    Article
  5. Article
  6. 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

2 authors.

Pin-Hao A ChenDepartment of Psychology, National Taiwan University, Taipei, Taiwan.
Yang QuSchool of Education and Social Policy, Northwestern University, Evanston, IL, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Parent-child similarities and discrepancies at multiple levels provide a window to understand the cultural transmission process. Although prior research has examined parent-child similarities at the belief, behavioral, and physiological levels across cultures, little is known about parent-child similarities at the neural level. The current review introduces an interdisciplinary computational cultural neuroscience approach, which utilizes computational methods to understand neural and psychological processes being involved during parent-child interactions at intra- and inter-personal level. This review provides three examples, including the application of intersubject representational similarity analysis to analyze naturalistic neuroimaging data, the usage of computer vision to capture non-verbal social signals during parent-child interactions, and unraveling the psychological complexities involved during real-time parent-child interactions based on their simultaneous recorded brain response patterns. We hope that this computational cultural neuroscience approach can provide researchers an alternative way to examine parent-child similarities and discrepancies across different cultural contexts and gain a better understanding of cultural transmission processes.

Indexed as

computational neurosciencecultural neurosciencedevelopmental neuroscienceneuroimagingparent-child interactionsocial interaction

Identifiers

PMID34512293
PMCPMC8426574

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.