Altered effective brain network topology in tinnitus: An EEG source connectivity analysis. (February 2021)
- Record Type:
- Journal Article
- Title:
- Altered effective brain network topology in tinnitus: An EEG source connectivity analysis. (February 2021)
- Main Title:
- Altered effective brain network topology in tinnitus: An EEG source connectivity analysis
- Authors:
- Mohagheghian, Fahimeh
Khajehpour, Hassan
Samadzadehaghdam, Nasser
Eqlimi, Ehsan
Jalilvand, Hamid
Makkiabadi, Bahador
Deevband, Mohammad Reza - Abstract:
- Abstract: Tinnitus is defined as the auditory phantom perception in the absence of any objective external sound source. In this paper, we used the resting-state electroencephalography (EEG) data to reconstruct the neural sources based on the unit-noise-gain linearly constrained minimum-variance (LCMV) beamformer and applied the effective connectivity analysis on the reconstructed sources to examine the directional neuronal interactions between brain regions in tinnitus patients compared to the healthy controls. We found significantly disrupted patterns of effective connectivity in several brain areas including the frontal, temporal, and occipital cortices as well as the caudate nucleus. Particularly, significant aberrant causal couplings were observed in the orbitofrontal cortex, inferior frontal gyrus_triangular, and parahippocampal region that could potentially illustrate the auditory information retrieval, perception, and evaluation of the phantom sound in the brain of tinnitus patients. Furthermore, topological alterations of the brain network were investigated using graph theoretical analysis. Our findings demonstrated significantly decreased both global integration and segregation of the brain network in tinnitus patients accompanied by the topological shift of tinnitus network to a more random structure in the high-frequency bands. These findings were consistent with the hypothesis of the brain network deviation from small-worldness topology accompanied by reducedAbstract: Tinnitus is defined as the auditory phantom perception in the absence of any objective external sound source. In this paper, we used the resting-state electroencephalography (EEG) data to reconstruct the neural sources based on the unit-noise-gain linearly constrained minimum-variance (LCMV) beamformer and applied the effective connectivity analysis on the reconstructed sources to examine the directional neuronal interactions between brain regions in tinnitus patients compared to the healthy controls. We found significantly disrupted patterns of effective connectivity in several brain areas including the frontal, temporal, and occipital cortices as well as the caudate nucleus. Particularly, significant aberrant causal couplings were observed in the orbitofrontal cortex, inferior frontal gyrus_triangular, and parahippocampal region that could potentially illustrate the auditory information retrieval, perception, and evaluation of the phantom sound in the brain of tinnitus patients. Furthermore, topological alterations of the brain network were investigated using graph theoretical analysis. Our findings demonstrated significantly decreased both global integration and segregation of the brain network in tinnitus patients accompanied by the topological shift of tinnitus network to a more random structure in the high-frequency bands. These findings were consistent with the hypothesis of the brain network deviation from small-worldness topology accompanied by reduced global integration in brain-related disorders. … (more)
- Is Part Of:
- Biomedical signal processing and control. Volume 64(2021)
- Journal:
- Biomedical signal processing and control
- Issue:
- Volume 64(2021)
- Issue Display:
- Volume 64, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 64
- Issue:
- 2021
- Issue Sort Value:
- 2021-0064-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-02
- Subjects:
- Tinnitus -- EEG -- Brain source imaging -- Source reconstruction -- Connectivity analysis -- Graph theory analysis
Signal processing -- Periodicals
Biomedical engineering -- Periodicals
Signal Processing, Computer-Assisted -- Periodicals
Image Processing, Computer-Assisted -- Periodicals
Biomedical Engineering -- Periodicals
610.28 - Journal URLs:
- http://www.sciencedirect.com/science/journal/17468094 ↗
http://www.elsevier.com/journals ↗
http://www.sciencedirect.com/science?_ob=PublicationURL&_tockey=%23TOC%2329675%232006%23999989998%23626449%23FLA%23&_cdi=29675&_pubType=J&_auth=y&_acct=C000045259&_version=1&_urlVersion=0&_userid=836873&md5=664b5cf9a57fc91971a17faf20c32ec1 ↗ - DOI:
- 10.1016/j.bspc.2020.102331 ↗
- Languages:
- English
- ISSNs:
- 1746-8094
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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- British Library DSC - 2087.880400
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