maladaptive rumination in depressed and non-depressed individuals have rarely been investigated separately. In the pursuit of resiliency, reconsidering adaptive and maladaptive rumination separately is especially necessary to acquire a more comprehensive understanding of its role in the physiopathology and clinical phenotypes of MDD.Īlthough neuroimaging evidence using functional magnetic resonance imaging (fMRI) ( Hamilton et al., 2015 Peters et al., 2019 Jacob et al., 2020) has shown that rumination is related to alterations in activation patterns and in the functional organization of different brain areas and networks, the neural substrates of adaptive vs. According to the Ruminative Responses Scale (RRS), which is a frequently used self-report measure of rumination ( Nolen-Hoeksema et al., 1993), rumination includes three facets: depressive rumination (RRS-D, e.g., “How often do you think about your feelings of fatigue and achiness?,” maladaptive) brooding rumination (RRS-B, e.g., “How often do you think ‘Why do I have problems other people don’t have?”’, maladaptive) and reflective rumination (RRS-R, e.g., “How often do you analyze recent events to try to understand why you are depressed?,” adaptive). Accumulated evidence has highlighted that rumination is a multidimensional construct ( Nolen-Hoeksema et al., 2008 Zahn et al., 2015). As a central feature of MDD, it predicts severe depressive symptoms, predicts chronicity in depressed individuals, and indicates a higher risk of depressive relapses. Rumination in major depressive disorder (MDD) is characterized as a recurrent, self-reflective, and uncontrollable focus on depressed mood and its potential antecedents or repercussions ( Nolen-Hoeksema et al., 2008). These findings may provide potential implications on probing and modulating dynamic neuronal fluctuations during the rumination in depression. Our findings support the disturbed neural communications and point to the spatial reorganization of brain networks in a timescale-dependent migration toward local during adaptive and maladaptive rumination in MDD. Besides, the depressive and brooding rumination in MDD showed the lack of correlations with global long-range EEG variables. Higher reflective rumination in MDD was region-specifically associated with the more localized EEG dynamics, including the greater MSE in scales finer than 8 (cluster P = 0.008), power in gamma (cluster P = 0.018) and PAC in low beta-gamma (cluster P = 0.042), as well as weaker alpha-gamma PAC (cluster P = 0.016- 0.029). MDD patients showed higher MSE in timescales finer than 5 (cluster P = 0.038) and gamma power (cluster P = 0.034), as well as lower PAC values between alpha/low beta and gamma bands (cluster P = 0.002- 0.021). The depressive, brooding, and reflective subscales of the Ruminative Response Scale were assessed. We employed the multi-scale entropy (MSE), power and phase-amplitude coupling (PAC) to estimate the complexity of rhythmic dynamics from the eye-closed high-density electroencephalographic (EEG) data in treatment-naive patients with MDD ( n = 24) and healthy controls ( n = 22). We hypothesize that divergent spatiotemporal complexity of brain oscillations would be associated with the levels of rumination in MDD. However, the neural substrates of rumination in depression remain poorly understood. Patients with major depressive disorder (MDD) exhibit abnormal rumination, including both adaptive and maladaptive forms. 3School of Psychological Sciences and Health, Department of Psychology, University of Strathclyde, Glasgow, United Kingdom.2Department of Psychiatry, The Second Hospital of Shanxi Medical University, Taiyuan, China.1Peking University Sixth Hospital (Institute of Mental Health), National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health, Peking University, Beijing, China.Jing Wang 1, Qi Liu 1, Feng Tian 1,2, Shuzhe Zhou 1, Mario Alfredo Parra 3, Huali Wang 1† and Xin Yu 1*†

Step enb adaptive quality