Evidence map›Paper›PMID 37804834›Full record

ReviewNeuron2023

Characterizing the mechanisms of social connection.

Mauricio R Delgado, Dominic S Fareri, Luke J Chang

Abstract readReview
In one paragraph

Review in Neuron, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

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

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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.

Mauricio R DelgadoDepartment of Psychology, Rutgers University-Newark, Newark, NJ 07102, USA. Electronic address: delgado@psychology.rutgers.edu.
Dominic S FareriGordon F. Derner School of Psychology, Adelphi University, Garden City, NY 11530, USA.
Luke J ChangConsortium for Interacting Minds, Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH 03755, USA.

Funding

Characterizing the neural mechanisms of social connectionR01DA053311 · NIDA · RUTGERS THE STATE UNIV OF NJ NEWARK · PI Luke Joseph Chang, Mauricio R. Delgado · 2022 to 2026
$2.6M
The role of social support and close relationships on neural and behavioral computations of valueR15MH122927 · NIMH · ADELPHI UNIVERSITY · PI FARERI, DOMINIC · 2020 to 2020
$388k
NIDA NIH HHS R01 DA053311NIMH NIH HHS R15 MH122927
6 · The paper itself

Abstract

Understanding how individuals form and maintain strong social networks has emerged as a significant public health priority as a result of the increased focus on the epidemic of loneliness and the myriad protective benefits conferred by social connection. In this review, we highlight the psychological and neural mechanisms that enable us to connect with others, which in turn help buffer against the consequences of stress and isolation. Central to this process is the experience of rewards derived from positive social interactions, which encourage the sharing of perspectives and preferences that unite individuals. Sharing affective states with others helps us to align our understanding of the world with another's, thereby continuing to reinforce bonds and strengthen relationships. These psychological processes depend on neural systems supporting reward and social cognitive function. Lastly, we also consider limitations associated with pursuing healthy social connections and outline potential avenues of future research.

Indexed as

CognitionEmotionsHumansRewardHPA axismedial prefrontal cortexnaturalistic designsshared realitysocial isolationsocial networkstress bufferingtheory of mindventral striatumventral tegmental area

Identifiers

PMID37804834
PMCPMC10842352

What OpenQuestion holds

Textmetadata
LicenceTDM
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.