Editorial: Cognitive-related and connectome-based biomarkers for depression: the application of state-of-the-art techniques and models to uncover

Depression, particularly major depressive disorder (MDD), is one of the key contributing to human 13 disability and suicide, with almost 800,000 for depression-related suicide per year (Moridi, Dowran & 14 Sepandi, 2021). In addition, the economic burden of MDD are increasing faster than ever across the globe, 15 especially in depression-related unemployment, homelessness and diagnostic/therapeutic costs (Greenberg et al.,16 2021; Shah et al., 2021). Thus, these issues necessitate the development and validation of low-cost, rapid, reliable, 17 and interpretable biomarkers for MDD. To do so, many efforts had been made to probe into neuromarkers of 18 MDD from neuroimaging-related studies with local neural features, which not only showed high measure 19 reliability and neural interpretability but also provided tremendous insights into neuropathological substrates of 20 this psychiatric condition (Castanheira et al., 2019). Despite these promising biomarkers, connectome-based 21 neural architecture, in conjunction of state-of-the-art techniques and groundbreaking conceptional models, is 22 increasingly becoming a promising direction to capture intrinsic brain pattern as novel neuromarkers in MDD 23 diagnostics (Gong & He, 2015). 24Traditional diagnostics based on strucutred interviews (i.e., the Diagnostic Statistical Manual, DSM-5) are 25 somewhat grounded on subjective observations and judgement from clinicians (Vahia, 2013).