Evidence map›Paper›PMID 33995932›Full record

ArticleBasic and clinical neuroscience

Functional Brain Response to Emotional Musical Stimuli in Depression, Using INLA Approach for Approximate Bayesian Inference.

Parisa Naseri, Hamid Alavi Majd, Seyyed Mohammad Tabatabaei, Naghmeh Khadembashi, Seyed Morteza Najibi, Atiye Nazari

Open access · diamondAbstract read
In one paragraph

Article in Basic and clinical neuroscience. 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
–field-weighted citation impact, top 80% 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, 3 citations in OpenAlex.

  1. Article
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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

6 authors at 3 institutions in 1 country.

Parisa NaseriDepartment of Biostatistics, School of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.ORCID https://orcid.org/0000-0003-1484-2391
Hamid Alavi MajdDepartment of Biostatistics, School of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.ORCID https://orcid.org/0000-0001-7772-2923
Seyyed Mohammad TabatabaeiDepartment of Medical Informatics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.ORCID https://orcid.org/0000-0002-3153-8968
Naghmeh KhadembashiDepartment of English Language, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.ORCID https://orcid.org/0000-0002-6654-7039
Seyed Morteza NajibiDepartment of Statistics, School of Sciences, Shiraz University, Shiraz, Iran.
Atiye NazariDepartment of Biostatistics, School of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Shahid Beheshti University of Medical Sciences · IRMashhad University of Medical Sciences · IRShiraz University · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionOne of the vital skills which has an impact on emotional health and well-being is the regulation of emotions. In recent years, the neural basis of this process has been considered widely. One of the powerful tools for eliciting and regulating emotion is music. The Anterior Cingulate Cortex (ACC) is part of the emotional neural circuitry involved in Major Depressive Disorder (MDD). The current study uses functional Magnetic Resonance Imaging (fMRI) to examine how neural processing of emotional musical auditory stimuli is changed within the ACC in depression. Statistical inference is conducted using a Bayesian Generalized Linear Model (GLM) approach with an Integrated Nested Laplace Approximation (INLA) algorithm.

methodsA new proposed Bayesian approach was applied for assessing functional response to emotional musical auditory stimuli in a block design fMRI data with 105 scans of two healthy and depressed women. In this Bayesian approach, Unweighted Graph-Laplacian (UGL) prior was chosen for spatial dependency, and autoregressive (AR) (1) process was used for temporal correlation via pre-weighting residuals. Finally, the inference was conducted using the Integrated Nested Laplace Approximation (INLA) algorithm in the R-INLA package.

resultsThe results revealed that positive music, as compared to negative music, elicits stronger activation within the ACC area in both healthy and depressed subjects. In comparing MDD and Never-Depressed (ND) individuals, a significant difference was found between MDD and ND groups in response to positive music vs negative music stimuli. The activations increase from baseline to positive stimuli and decrease from baseline to negative stimuli in ND subjects. Also, a significant decrease from baseline to positive stimuli was observed in MDD subjects, but there was no significant difference between baseline and negative stimuli.

conclusionAssessing the pattern of activations within ACC in a depressed individual may be useful in retraining the ACC and improving its function, and lead to more effective therapeutic interventions.

Indexed as

Anterior cingulate cortexBayesian GLM approachDepressionfunctional magnetic resonance imagingIntegrated nested Laplace approximationUnweighted graph-Laplacian

Identifiers

PMID33995932
PMCPMC8114858
OpenAlexW3004926036

What OpenQuestion holds

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LicenceCC BY-NC
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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.