Dynamic Functional Connectivity Changes Associated with Rumination by CBT in depression.
Poster No:
471
Submission Type:
Abstract Submission
Authors:
Nariko Katayama1, Kazushi Shinagawa2, Yuki Kobayashi1, Jinichi Hirano1, Atsuo Nakagawa3,4, Kei Kamiya5, Miyuki Tajima1, Yuri Terasawa2, Satoshi Umeda2, Toshiaki Kikuchi1, Masaru Mimura1, Hiroyuki Uchida1
Institutions:
1Department of Neuropsychiatry, Keio University school of Medicine, Shinjuku, Tokyo, 2Department of Psychology, Keio University, Mita, Tokyo, 3Department of Neuropsychiatry, St. Marianna University School of Medicine,, Kawasaki, Kanagawa, 4Department of Neuropsychiatry, Keio University school of Medicine, Tokyo, Japan, 5Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku
First Author:
Co-Author(s):
Atsuo Nakagawa
Department of Neuropsychiatry, St. Marianna University School of Medicine,|Department of Neuropsychiatry, Keio University school of Medicine
Kawasaki, Kanagawa|Tokyo, Japan
Department of Neuropsychiatry, St. Marianna University School of Medicine,|Department of Neuropsychiatry, Keio University school of Medicine
Kawasaki, Kanagawa|Tokyo, Japan
Introduction:
Rumination is the repetitive brooding about their symptoms, causes, meanings, and consequences of depression, and has recently been identified as one of the most important risk factors for chronicity and relapse or recurrence of depression. Depressed patients are easily trapped in a thinking process of abstract, repetitive, negative, nonfunctional rumination. Cognitive-behavioral therapy (CBT) is one of the psychotherapies with established efficacy for depression that also approaches biased cognition and rumination. However, the mechanism by which treatments for depression improve rumination has not yet been clearly elucidated by functional brain imaging studies. In the present study, we compared resting-state functional brain imaging with time-varying functional connectivity (TVFC) analysis to investigate the temporal network changes related to rumination in depressed patients and healthy controls, and to identify treatment mechanisms specific to CBT.
Methods:
Patients with a DSM-V diagnosis of major depressive disorder and healthy controls were eligible for the study. Depressed patients were assigned to a cognitive-behavioral therapy group, a pharmacotherapy group, a repetitive transcranial magnetic stimulation (TMS) group, or an electroconvulsive therapy (ECT) group, depending on the treatment they received. Participants underwent fMRI imaging at baseline and at the end of treatment. Participants underwent resting-fMRI and were assessed rumination (Rumination response score: RRS) at baseline and at the end of treatment. The CBT group underwent individual sessions once a week for about 50 min for 16 weeks based on Beck's manual. fMRI images were preprocessed by fMRI prep, divided into ROIs (Automated Anatomical Labeling: AAL2), and time-series data were extracted. After principal component analysis (PCA), the states were estimated by TVFC analysis using the hidden Markov model (HMM) method. States of the estimated brain network were compared between depressed patients and healthy controls, and indicators correlated with RRS were extracted (Pearson correlation analysis). Group-by-time interaction effect was examined by ANOVA and a within-group comparison before and after treatment was performed as a post-hoc analysis. The study was approved by the Ethics Committee of Keio University School of Medicine to assure ethical considerations and protection of the privacy of the participants.
Results:
A total of 138 adult participants, 80 patients with moderate to severe major depressive disorder and 58 healthy controls, were included in this study. Twelve states of brain networks were estimated and significant differences in the number of occurrences of state 9 and state 12 was found between the depressed patients and the healthy group (figure1). State 9 was mainly insula network activity, and state 12 was predominantly default mode network activity. The number of occurrences of state 12 was positively correlated with RRS (p=0.001). The number of occurrences of state 9 and state 12, and the transition probability had group-by-time interaction effect (p=0.01, p=0.055, p=0.011, respectively). The number of occurrences of state 12 changed significantly before and after treatment in the CBT group (p=0.047) (figure2).
Conclusions:
CBT differed from other treatments in reducing the number of DMN occurrences and the probability of transitions between networks, suggesting that these changes may be related to unique therapeutic mechanisms of CBT, such as its effect on rumination. In the treatment of depressed patients with diverse symptoms, the findings of this large-scale brain imaging study are expected to contribute to the establishment of more effective treatments and therapeutic strategies.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Modeling and Analysis Methods:
fMRI Connectivity and Network Modeling 2
Keywords:
Affective Disorders
FUNCTIONAL MRI
Other - Cognitive Behavioral Therapy; Rumination; Major depressive disorder
1|2Indicates the priority used for review
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Watkins, E.R., Mullan, E., Wingrove, J., Rimes, K., Steiner, H., Bathurst, N., Eastman, R.,Scott, J., 2011. Rumination-focused cognitive-behavioural therapy for residual depression: phase II randomised controlled trial. The British journal of psychiatry : the journal of mental science 199, 317-322.
Hui-Xia Zhoua,b,c, Xiao Chena,b,c, Yang-Qian Shena, Le Lia,b,c, Ning-Xuan Chena,b,c, Zhi-Chen Zhua,b,c, Francisco Xavier Castellanose,f, Chao-Gan Yan.2020. Rumination and the default mode network: Meta-analysis of brain imaging studies and implications for depression. NeuroImage 206 (2020) 116287