Evidence map›Paper›PMID 37759837›Full record

ArticleBrain sciences2023

Task and Resting-State Functional Connectivity Predict Driving Violations.

Uijong Ju

Abstract read
In one paragraph

Article in Brain sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Uijong JuDepartment of Information Display, Kyung Hee University, Seoul 02447, Republic of Korea.ORCID 0000-0002-9391-3938

Funding

National Research Foundation of Korea NRF-2020R1I1A1A01057915, NRF-2022R1F1A1060046, RS-2023-00242928
6 · The paper itself

Abstract

Aberrant driving behaviors cause accidents; however, there is a lack of understanding of the neural mechanisms underlying these behaviors. To address this issue, a task and resting-state functional connectivity was used to predict aberrant driving behavior and associated personality traits. The study included 29 right-handed participants with driving licenses issued for more than 1 year. During the functional magnetic resonance imaging experiment, participants first recorded their resting state and then watched a driving video while continuously rating the risk and speed on each block. Functional connectome-based predictive modeling was employed for whole brain tasks and resting-state functional connectivity to predict driving behavior (violation, error, and lapses), sensation-seeking, and impulsivity. Resting state and task-based functional connectivity were found to significantly predict driving violations, with resting state significantly predicting lapses and task-based functional connectivity showing a tendency to predict errors. Conversely, neither impulsivity nor sensation-seeking was associated with functional connectivity. The results suggest a significant association between aberrant driving behavior, but a nonsignificant association between impulsivity and sensation-seeking, and task-based or resting state functional connectivity. This could provide a deeper understanding of the neural processing underlying reckless driving that may ultimately be used to prevent accidents.

Indexed as

aberrant drivingerrorfunctional connectivityfunctional connectomelapsesresting stateviolations

Identifiers

PMID37759837
PMCPMC10526865

What OpenQuestion holds

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LicenceCC BY
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.