Evidence map›Paper›PMID 38343814›Full record

ArticleResearch square2024

Aberrant neural computation of social controllability in nicotine-dependent humans.

Xiaosi Gu, Caroline McLaughlin, Qixiu Fu, Soojung Na, Matthew Heflin, Vincenzo Fiore

Open access · greenAbstract readPreprint
In one paragraph

Article in Research square, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Xiaosi GuIcahn School of Medicine at Mount Sinai.ORCID 0000-0002-9373-987X
Caroline McLaughlin
Qixiu Fu
Soojung Na
Matthew Heflin
Vincenzo Fiore
Icahn School of Medicine at Mount Sinai · US

Funding

Computational and Neural Modeling of Cue Reactivity in AddictionR01DA043695 · NIDA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI GU, XIAOSI · 2018 to 2022
$2.9M
Neurocomputational Mechanisms for Addiction Heterogeneity, Impulsivity and PerseveranceR21DA049243 · NIDA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI GU, XIAOSI · 2019 to 2020
$466k
NIDA NIH HHS R01 DA043695NIDA NIH HHS R21 DA049243
6 · The paper itself

Abstract

Social controllability, defined as the ability to exert influence when interacting with others, is crucial for optimal decision-making. Inability to do so might contribute to maladaptive behaviors such as drug use, which often takes place in social settings. Here, we examined nicotine-dependent humans using fMRI, as they made choices that could influence the proposals from simulated partners. Computational modeling revealed that smokers under-estimated the influence of their actions and self-reported a reduced sense of control, compared to non-smokers. These findings were replicated in a large independent sample of participants recruited online. Neurally, smokers showed reduced tracking of forward projected choice values in the ventromedial prefrontal cortex, and impaired computation of social prediction errors in the midbrain. These results demonstrate that smokers were less accurate in estimating their personal influence when the social environment calls for control, providing a neurocomputational account for the social cognitive deficits in this population.

Indexed as

computational psychiatryfunctional magnetic resonance imaging (fMRI)midbrainnicotine addictionsocial controllabilityvmPFC

Identifiers

PMID38343814
PMCPMC10854308
OpenAlexW4391162969

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.