Evaluating tDCS Intervention Effectiveness via Functional Connectivity Network on Resting-State EEG Data in Major Depressive Disorder
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| Format: | Preprint |
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2024
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| _version_ | 1866916707737534464 |
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| author | Singh, Vishwani Verma, Rohit Shriyam, Shaurya Gandhi, Tapan K. |
| author_facet | Singh, Vishwani Verma, Rohit Shriyam, Shaurya Gandhi, Tapan K. |
| contents | Transcranial direct current stimulation (tDCS) has emerged as a promising non-invasive therapeutic intervention for major depressive disorder (MDD), yet its effects on neural mechanisms remain incompletely understood. This study investigates the impact of tDCS in individuals with MDD using resting-state EEG data and network neuroscience to analyze functional connectivity. We examined power spectral density (PSD) changes and functional connectivity (FC) patterns across theta, alpha, and beta bands before and after tDCS intervention. A notable aspect of this research involves the modification of the binarizing threshold algorithm to assess functional connectivity networks, facilitating a meaningful comparison at the group level. Our analysis using optimal threshold binarization techniques revealed significant modifications in network topology, particularly evident in the beta band, indicative of reduced randomization or enhanced small-worldness after tDCS. Furthermore, the hubness analysis identified specific brain regions, notably the dorsolateral prefrontal cortex (DLPFC) regions across all frequency bands, exhibiting increased functional connectivity, suggesting their involvement in the antidepressant effects of tDCS. Notably, tDCS intervention transformed the dispersed high connectivity into localized connectivity and increased left-sided asymmetry across all frequency bands. Overall, this study provides valuable insights into the effects of tDCS on neural mechanisms in MDD, offering a potential direction for further research and therapeutic development in the field of neuromodulation for mental health disorders. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2411_06359 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Evaluating tDCS Intervention Effectiveness via Functional Connectivity Network on Resting-State EEG Data in Major Depressive Disorder Singh, Vishwani Verma, Rohit Shriyam, Shaurya Gandhi, Tapan K. Quantitative Methods Neurons and Cognition Transcranial direct current stimulation (tDCS) has emerged as a promising non-invasive therapeutic intervention for major depressive disorder (MDD), yet its effects on neural mechanisms remain incompletely understood. This study investigates the impact of tDCS in individuals with MDD using resting-state EEG data and network neuroscience to analyze functional connectivity. We examined power spectral density (PSD) changes and functional connectivity (FC) patterns across theta, alpha, and beta bands before and after tDCS intervention. A notable aspect of this research involves the modification of the binarizing threshold algorithm to assess functional connectivity networks, facilitating a meaningful comparison at the group level. Our analysis using optimal threshold binarization techniques revealed significant modifications in network topology, particularly evident in the beta band, indicative of reduced randomization or enhanced small-worldness after tDCS. Furthermore, the hubness analysis identified specific brain regions, notably the dorsolateral prefrontal cortex (DLPFC) regions across all frequency bands, exhibiting increased functional connectivity, suggesting their involvement in the antidepressant effects of tDCS. Notably, tDCS intervention transformed the dispersed high connectivity into localized connectivity and increased left-sided asymmetry across all frequency bands. Overall, this study provides valuable insights into the effects of tDCS on neural mechanisms in MDD, offering a potential direction for further research and therapeutic development in the field of neuromodulation for mental health disorders. |
| title | Evaluating tDCS Intervention Effectiveness via Functional Connectivity Network on Resting-State EEG Data in Major Depressive Disorder |
| topic | Quantitative Methods Neurons and Cognition |
| url | https://arxiv.org/abs/2411.06359 |