Evidence map›Paper›PMID 40861082›Full record

ArticleJournal of medical signals and sensors2025

A New Method for Dynamic Brain Connectivity Analysis Based on Tensor Decomposition in Tinnitus Using High-density Electroencephalogram in Source Domain.

Moein Bahman, Seyed Saman Sajadi, Iman Ghodrati Toostani, Bahador MakkiAbadi

Abstract read
In one paragraph

Article in Journal of medical signals and sensors, 2025. 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.

No citing paper in PubMed yet.

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

4 authors.

Moein BahmanDepartment of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
Seyed Saman SajadiDepartment of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
Iman Ghodrati ToostaniDepartment of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
Bahador MakkiAbadiDepartment of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Functional connectivity (FC), defined as the statistical reliance among different brain regions, has been an effective tool for studying cognitive brain functions. The majority of existing FC-based research has relied on the premise that networks are temporally stationary. However, there exist few research that support nonstationarity of FC which can be due to cognitive functioning. However, still there is a gap in tracking the dynamics of FC to gain a deeper understanding of how brain networks form and adapt in response to therapeutic interventions by identifying the change points that signify substantial shifts in network connectivity across the participants. Methods: The proposed approach in this study is based on tensor representation of FC networks of the source signals of electroencephalogram (EEG) activities yielding a multi-mode tensor. Then analysis of variance has been used to investigate changing points in connectivity of brain activity in sources domain in different conditions of tasks, frequency bands, and among subjects in time. High-density EEG signals (256 channels) were acquired from 30 tinnitus patients under visual (positive emotion induction) and transcranial direct current stimulation (tDCS) stimuli. Results: The proposed method of this study could effectively identify the significant brain connectivity change points, indicating enhanced effectiveness in capturing connectivity shifts comparing to conventional methods. Findings in tinnitus patients suggest that visual stimulation alone may not significantly alter brain connectivity networks. Conclusion: Based on the results, a combination of visual stimulation with simultaneous High-Definition tDCS is recommended, potentially informing optimal intervention strategies to enhance tinnitus treatment effectiveness.

Indexed as

Electroencephalogramfunctional connectivitytensor decompositiontinnitus

Identifiers

PMID40861082
PMCPMC12373379

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.