Evidence map›Paper›PMID 37213411›Full record

ArticleNeurophotonics2023

Behavioral modeling and neuroimaging of impaired risky decision making in patients with chronic musculoskeletal pain.

Xinglin Zeng, Wen Tang, Fei Gao, Ziyue Tang, Zhou Zhang, Juan Zhang, Meng Du, Zhiyi Chen, Xueli Chen, Zhen Yuan

Open access · goldAbstract read
In one paragraph

Article in Neurophotonics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 34% of its field
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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. 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

10 authors at 6 institutions in 2 countries.

Xinglin ZengUniversity of Macau, Centre for Cognitive and Brain Sciences, Macau, China.ORCID https://orcid.org/0000-0003-2152-9977
Wen TangThe First Affiliated Hospital, Sun Yat-Sen University, Department of Rehabilitation Medicine, Guangzhou, China.
Fei GaoUniversity of Macau, Centre for Cognitive and Brain Sciences, Macau, China.
Ziyue TangThe First Affiliated Hospital, Sun Yat-Sen University, Department of Rehabilitation Medicine, Guangzhou, China.
Zhou ZhangThe First Affiliated Hospital, Sun Yat-Sen University, Department of Rehabilitation Medicine, Guangzhou, China.ORCID https://orcid.org/0000-0002-4314-1052
Juan ZhangUniversity of Macau, Centre for Cognitive and Brain Sciences, Macau, China.
Meng DuUniversity of South China, Institute of Medical Imaging, Hengyang Medical School, Hengyang, China.
Zhiyi ChenUniversity of South China, Institute of Medical Imaging, Hengyang Medical School, Hengyang, China.
Xueli ChenXidian University, School of Life Science and Technology, Xi'an, China.
Zhen YuanUniversity of Macau, Centre for Cognitive and Brain Sciences, Macau, China.ORCID https://orcid.org/0000-0003-3061-6263
University of Macau · MOThe First Affiliated Hospital, Sun Yat-sen University · CNUniversity of South China · CNFudan University · CNSun Yat-sen University · CNXidian University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Significance: Performance during risky decision making is one of the essential cognitive functions that is impaired in several psychiatric disorders including addiction. However, the cognitive mechanism and neural correlates underlying risky decision making in chronic pain patients are unclear. To our knowledge, this study is among the first to construct computational models to detect the underlying cognitive process of chronic pain patients during risky decision making. Aim: This study aimed at inspecting the significantly abnormal risky decision-making patterns of chronic pain patients and its neuro-cognitive correlates. Approach: In this case-control study, 19 chronic pain patients and 32 healthy controls (HCs) were included to measure the risky decision making in a balloon analogue risk task (BART). Optical neuroimaging using functional near-infrared spectroscopy, together with computational modeling, was carried out to systematically characterize the specific impairments based on BART. Results: Computational modeling findings on behavioral performance demonstrated that the chronic pain patient group exhibited significant deficits in learning during BART ( Conclusions: Long-term aberrant pain responses significantly disrupted the PFC function and behavioral performance in chronic pain patients. The joint behavioral modeling and neuroimaging techniques open a new avenue for fully understanding the cognitive impairment and brain dysfunction of risky decision making associated with chronic pain.

Indexed as

chronic musculoskeletal paincomputational modelingfunctional near-infrared spectroscopyprefrontal cortexrisky decision-making

Identifiers

PMID37213411
PMCPMC10194091
OpenAlexW4377107487

What OpenQuestion holds

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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 OpenQuestion graph.