Introduction: Functional connectivity is attracting increasing attention for understanding the pathophysiology of depression and predicting the therapeutic efficacy of antidepressants. In this study, we evaluated effective connectivity using isolated effective coherence (iCoh), an effective functional connectivity analysis method developed from low-resolution brain electromagnetic tomography (LORETA) and estimated its practical usefulness for predicting the reaction to antidepressants in theta and alpha band iCoh values.

Methods: We enrolled 25 participants from a depression treatment randomized study (the GUNDAM study) in which electroencephalography was performed before treatment. We conducted iCoh between the rostral anterior cingulate cortex (rACC) and anterior insula (AI), which are associated with the salience network. The patients were divided into responder and nonresponder groups at 4 weeks after the start of treatment, and iCoh values were compared between the two groups. Additionally, the sensitivity and specificity of iCoh were calculated using the receiver-operating characteristic (ROC) curve.

Results: The Mann-Whitney U test showed significantly weaker connectivity flow from the rACC to the left AI in the alpha band in the responder group. The ROC curve for the connectivity flow from the rACC to the left AI in the alpha band showed 82% sensitivity and 86% specificity.

Discussion/conclusion: These findings suggest the pathological importance of effective connectivity flow from the rACC to the left AI in the alpha and theta bands and suggest its usefulness as a biomarker to distinguish responders to antidepressants.

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http://dx.doi.org/10.1159/000525338DOI Listing

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