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Wang J, Chen H, Xu H, Cai R, Zhao Y, Tan S. Relationship between ruminative style and adolescent depression. Asian J Psychiatr 2024; 96:104008. [PMID: 38598933 DOI: 10.1016/j.ajp.2024.104008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 02/28/2024] [Accepted: 03/17/2024] [Indexed: 04/12/2024]
Abstract
BACKGROUND The role of rumination in depression remains controversial. We aimed to establish the ruminative tendency style theory (RTST), discuss the occurrence of depression in adolescents with rumination as the core, and explore the different associations between adolescent ruminative tendency, ruminative style, and depression. METHODS This study employed an online questionnaire survey of 1110 Chinese adolescents aged 12-17 years, assessing ruminative tendency, ruminative style, stressful life events, depressive state, depressive trait, the Big Five personality traits, and social support. Conditional process analysis was used to test the chain mediation effect with Ruminative Style as a moderator. After screening for the predictor variables, a logistic regression risk prediction model was established and validated internally. RESULTS The chain mediation effect of ruminative tendency and depressive trait between stressful life events and depressive state was significant, with the indirect effect accounting for 63.4%. Ruminative Style negatively moderated the relationship between Ruminative Tendency and Depressive Trait (β=-0.053,P<0.001). The risk prediction model for depressive state showed good calibration and clinical utility. Area under the curve values for the validation and training sets were 0.926 and 0.927, respectively. CONCLUSION Different associations may exist between adolescent ruminative tendency, ruminative style, and depression, and the proposal of ruminative style is of great significance for intervention in adolescent depression.
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Affiliation(s)
- Jinghan Wang
- Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Haitao Chen
- Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Hao Xu
- Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China; North China University of Science and Technology, Tangshan, China
| | - Ruiwen Cai
- North China University of Science and Technology, Tangshan, China; No. 5 Middle School Miyun, Beijing, China
| | - Yanli Zhao
- Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Shuping Tan
- Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China; North China University of Science and Technology, Tangshan, China.
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Johnson KA, Okun MS, Scangos KW, Mayberg HS, de Hemptinne C. Deep brain stimulation for refractory major depressive disorder: a comprehensive review. Mol Psychiatry 2024; 29:1075-1087. [PMID: 38287101 DOI: 10.1038/s41380-023-02394-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 12/18/2023] [Accepted: 12/21/2023] [Indexed: 01/31/2024]
Abstract
Deep brain stimulation (DBS) has emerged as a promising treatment for select patients with refractory major depressive disorder (MDD). The clinical effectiveness of DBS for MDD has been demonstrated in meta-analyses, open-label studies, and a few controlled studies. However, randomized controlled trials have yielded mixed outcomes, highlighting challenges that must be addressed prior to widespread adoption of DBS for MDD. These challenges include tracking MDD symptoms objectively to evaluate the clinical effectiveness of DBS with sensitivity and specificity, identifying the patient population that is most likely to benefit from DBS, selecting the optimal patient-specific surgical target and stimulation parameters, and understanding the mechanisms underpinning the therapeutic benefits of DBS in the context of MDD pathophysiology. In this review, we provide an overview of the latest clinical evidence of MDD DBS effectiveness and the recent technological advancements that could transform our understanding of MDD pathophysiology, improve the clinical outcomes for MDD DBS, and establish a path forward to develop more effective neuromodulation therapies to alleviate depressive symptoms.
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Affiliation(s)
- Kara A Johnson
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, USA
- Department of Neurology, University of Florida, Gainesville, FL, USA
| | - Michael S Okun
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, USA
- Department of Neurology, University of Florida, Gainesville, FL, USA
| | - Katherine W Scangos
- Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Helen S Mayberg
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Coralie de Hemptinne
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, USA.
- Department of Neurology, University of Florida, Gainesville, FL, USA.
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Wang J, Li B, Liu J, Li J, Razi A, Zheng K, Yan B, Wang H, Lu H, Friston K. Large-scale effective connectivity analysis reveals the existence of two mutual inhibitory systems in patients with major depression. Neuroimage Clin 2023; 41:103556. [PMID: 38134741 PMCID: PMC10784315 DOI: 10.1016/j.nicl.2023.103556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 12/12/2023] [Accepted: 12/16/2023] [Indexed: 12/24/2023]
Abstract
It is posited that cognitive and affective dysfunction in patients with major depression disorder (MDD) may be caused by dysfunctional signal propagation in the brain. By leveraging dynamic causal modeling, we investigated large-scale directed signal propagation (effective connectivity) among distributed large-scale brain networks with 43 MDD patients and 56 healthy controls. The results revealed the existence of two mutual inhibitory systems: the anterior default mode network, auditory network, sensorimotor network, salience network and visual networks formed an "emotional" brain, while the posterior default mode network, central executive networks, cerebellum and dorsal attention network formed a "rational brain". These two networks exhibited excitatory intra-system connectivity and inhibitory inter-system connectivity. Patients were characterized by potentiated intra-system connections within the "emotional/sensory brain", as well as over-inhibition of the "rational brain" by the "emotional/sensory brain". The hierarchical architecture of the large-scale effective connectivity networks was then analyzed using a PageRank algorithm which revealed a shift of the controlling role of the "rational brain" to the "emotional/sensory brain" in the patients. These findings inform basic organization of distributed large-scale brain networks and furnish a better characterization of the neural mechanisms of depression, which may facilitate effective treatment.
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Affiliation(s)
- Jia Wang
- School of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Baojuan Li
- School of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Jian Liu
- Network Center, Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Jiaming Li
- School of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Adeel Razi
- The Wellcome Trust Centre for Neuroimaging, University College London, Queen Square, London WC1N 3BG, UK
| | - Kaizhong Zheng
- Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Baoyu Yan
- Air Force Hangzhou Special Service Nursing Center, Hangzhou, Zhejiang 310000, China
| | - Huaning Wang
- Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710032, China.
| | - Hongbing Lu
- School of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi 710032, China.
| | - Karl Friston
- The Wellcome Trust Centre for Neuroimaging, University College London, Queen Square, London WC1N 3BG, UK
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Mısır E, Alıcı YH, Kocak OM. Functional connectivity in rumination: a systematic review of magnetic resonance imaging studies. J Clin Exp Neuropsychol 2023; 45:928-955. [PMID: 38346167 DOI: 10.1080/13803395.2024.2315312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 12/28/2023] [Indexed: 03/10/2024]
Abstract
INTRODUCTION Rumination, defined as intrusive and repetitive thoughts in response to negative emotions, uncertainty, and inconsistency between goal and current situation, is a significant risk factor for depressive disorders. The rumination literature presents diverse findings on functional connectivity and shows heterogeneity in research methods. This systematic review seeks to integrate these findings and provide readers diverse perspectives. METHOD For this purpose, the literature on functional connectivity in rumination was reviewed according to the PRISMA guidelines. Regional connectivity and network connectivity results were scrutinized according to the presence of depression, research methods, and type of rumination. After screening 492 articles, a total of 36 studies were included. RESULTS The results showed that increased connectivity of the default mode network (DMN) was consistently reported. Other important findings include alterations in the connectivity between the DMN and the frontoparietal network and the salience network (SN) and impaired regulatory function of the SN. Region-level connectivity studies consistently show that increased connectivity between the posterior cingulate cortex and the prefrontal cortex is associated with rumination, which may cause the loss of control of the frontoparietal network over self-referential processes. We have seen that the number of studies examining brooding and reflective rumination as separate dimensions are relatively limited. Although there are overlaps between the connectivity patterns of the two types of rumination in these studies, it can be thought that reflective rumination is more associated with more increased functional connectivity of the prefrontal cortex. CONCLUSIONS Although there are many consistent functional connectivity outcomes associated with trait rumination, less is known about connectivity changes during state rumination. Relatively few studies have taken into account the subjective aspect of this thinking style. In order to better explain the relationship between rumination and depression, rumination induction studies during episode and remission periods of depression are needed.
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Affiliation(s)
- Emre Mısır
- Department of Psychiatry, Baskent University Faculty of Medicine, Ankara, Turkey
- Department of Interdisciplinary Neuroscience, Ankara University, Ankara, Turkey
| | - Yasemin Hoşgören Alıcı
- Department of Psychiatry, Baskent University Faculty of Medicine, Ankara, Turkey
- Department of Interdisciplinary Neuroscience, Ankara University, Ankara, Turkey
| | - Orhan Murat Kocak
- Department of Psychiatry, Baskent University Faculty of Medicine, Ankara, Turkey
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Liu C, Belleau EL, Dong D, Sun X, Xiong G, Pizzagalli DA, Auerbach RP, Wang X, Yao S. Trait- and state-like co-activation pattern dynamics in current and remitted major depressive disorder. J Affect Disord 2023; 337:159-168. [PMID: 37245549 PMCID: PMC10897955 DOI: 10.1016/j.jad.2023.05.074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Revised: 05/02/2023] [Accepted: 05/21/2023] [Indexed: 05/30/2023]
Abstract
BACKGROUND Distinguishing between trait- and state-like neural alternations in major depressive disorder (MDD) may advance our understanding of this recurring disorder. We aimed to investigate dynamic functional connectivity alternations in unmedicated individuals with current or past MDD using co-activation pattern analyses. METHODS Resting-state functional magnetic resonance imaging data were acquired from individuals with first-episode current MDD (cMDD, n = 50), remitted MDD (rMDD, n = 44), and healthy controls (HCs, n = 64). Using a data-driven consensus clustering technique, four whole-brain states of spatial co-activation were identified and associated metrics (dominance, entries, transition frequency) were analyzed with respect to clinical characteristics. RESULTS Relative to rMDD and HC, cMDD showed increased dominance and entries of state 1 (primarily involving default mode network (DMN)), and decreased dominance of state 4 (mostly involving frontal-parietal network (FPN)). Among cMDD, state 1 entries correlated positively with trait rumination. Conversely, relative to cMDD and HC, individuals with rMDD were characterized by increased state 4 entries. Relative to HC, both MDD groups showed increased state 4-to-1 (FPN to DMN) transition frequency but reduction in state 3 (spanning visual attention, somatosensory, limbic networks), with the former metric specifically related to trait rumination. LIMITATIONS Further confirmation with longitudinal studies are required. CONCLUSIONS Regardless of symptoms, MDD was characterized by increased FPN-to-DMN transitions and reduced dominance of a hybrid network. State-related effect emerged in regions critically implicated in repetitive introspection and cognitive control. Asymptomatic individuals with past MDD were uniquely linked to increased FPN entries. Our findings identify trait-like brain network dynamics that might increase vulnerability to future MDD.
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Affiliation(s)
- Chengwen Liu
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center for Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Emily L Belleau
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Daifeng Dong
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center for Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Xiaoqiang Sun
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center for Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Ge Xiong
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center for Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Diego A Pizzagalli
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Randy P Auerbach
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - Xiang Wang
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center for Mental Disorders (Xiangya), Changsha, Hunan, PR China.
| | - Shuqiao Yao
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center for Mental Disorders (Xiangya), Changsha, Hunan, PR China.
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van Kleef RS, Kaushik P, Besten M, Marsman JBC, Bockting CLH, van Vugt M, Aleman A, van Tol MJ. Understanding and predicting future relapse in depression from resting state functional connectivity and self-referential processing. J Psychiatr Res 2023; 165:305-314. [PMID: 37556963 DOI: 10.1016/j.jpsychires.2023.07.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 07/21/2023] [Accepted: 07/24/2023] [Indexed: 08/11/2023]
Abstract
BACKGROUND The recurrent nature of Major Depressive Disorder (MDD) asks for a better understanding of mechanisms underlying relapse. Previously, self-referential processing abnormalities have been linked to vulnerability for relapse. We investigated whether abnormalities in self-referential cognitions and functioning of associated brain-networks persist upon remission and predict relapse. METHODS Remitted recurrent MDD patients (n = 48) and never-depressed controls (n = 23) underwent resting-state fMRI scanning at baseline and were additionally assessed for their implicit depressed self-associations and ruminative behaviour. A template-based dual regression approach was used to investigate between-group differences in default mode, cingulo-opercular and frontoparietal network resting-state functional connectivity (RSFC). Additional prediction of relapse status at 18-month follow-up was investigated within patients using both regression analyses and machine learning classifiers. RESULTS Remitted patients showed higher rumination, but no implicit depressed self-associations or RSFC abnormalities were observed between patients and controls. Nevertheless, relapse was related to i) baseline RSFC between the ventral default mode network and the precuneus, dorsomedial frontal gyrus, and inferior occipital lobe, ii) implicit self-associations, and iii) uncontrollability of ruminative thinking, when controlled for depressive symptomatology. Moreover, preliminary machine learning classifiers demonstrated that RSFC within the investigated networks predicted relapse on an individual basis. CONCLUSIONS Remitted MDD patients seem to be commonly characterized by abnormal rumination, but not by implicit self-associations or abnormalities in relevant brain networks. Nevertheless, relapse was predicted by self-related cognitions and default mode RSFC during remission, suggesting that variations in self-relevant processing play a role in the complex dynamics associated with the vulnerability to developing recurrent depressive episodes. CLINICAL TRIAL REGISTRATION Netherlands Trial Register, August 18, 2015, trial number NL53205.042.15.
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Affiliation(s)
- Rozemarijn S van Kleef
- Cognitive Neuroscience Center, Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, Groningen, the Netherlands.
| | - Pallavi Kaushik
- Bernoulli Institute of Mathematics, Computer Science and Artificial Intelligence, University of Groningen, the Netherlands; Department of Computer Science and Engineering, Indian Institute of Technology, Roorkee, India
| | - Marlijn Besten
- Cognitive Neuroscience Center, Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, Groningen, the Netherlands; Department of Clinical and Developmental Neuropsychology, Faculty of Behavioural and Social Sciences, University of Groningen, Groningen, the Netherlands
| | - Jan-Bernard C Marsman
- Cognitive Neuroscience Center, Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, Groningen, the Netherlands
| | - Claudi L H Bockting
- Department of Psychiatry, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Marieke van Vugt
- Bernoulli Institute of Mathematics, Computer Science and Artificial Intelligence, University of Groningen, the Netherlands
| | - André Aleman
- Cognitive Neuroscience Center, Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, Groningen, the Netherlands; Department of Clinical and Developmental Neuropsychology, Faculty of Behavioural and Social Sciences, University of Groningen, Groningen, the Netherlands
| | - Marie-José van Tol
- Cognitive Neuroscience Center, Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, Groningen, the Netherlands
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Zhong J, Xu J, Wang Z, Yang H, Li J, Yu H, Huang W, Wan C, Ma H, Zhang N. Changes in brain functional networks in remitted major depressive disorder: a six-month follow-up study. BMC Psychiatry 2023; 23:628. [PMID: 37641013 PMCID: PMC10464087 DOI: 10.1186/s12888-023-05082-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 08/06/2023] [Indexed: 08/31/2023] Open
Abstract
BACKGROUND Patients with remitted major depressive disorder (rMDD) show abnormal functional connectivity of the central executive network (CEN), salience networks (SN) and default mode network (DMN). It is unclear how these change during remission, or whether changes are related to function. METHODS Three spatial networks in 17 patients with rMDD were compared between baseline and the six-month follow-up, and to 22 healthy controls. Correlations between these changes and psychosocial functioning were also assessed. RESULTS In the CEN, patients at baseline had abnormal functional connectivity in the right anterior cingulate, right dorsolateral prefrontal cortex (DLPFC) and inferior parietal lobule (IPL) compare with HCs. There were functional connection differences in the right DLPFC and left IPL at baseline during follow-up. Abnormal connectivity in the right DLPFC and medial prefrontal cortex (mPFC) were found at follow-up. In the SN, patients at baseline had abnormal functional connectivity in the insula, left anterior cingulate, left IPL, and right precuneus; compared with baseline, patients had higher connectivity in the right DLPFC at follow-up. In the DMN, patients at baseline had abnormal functional connectivity in the right mPFC. Resting-state functional connectivity of the IPL and DLPFC in the CEN correlated with psychosocial functioning. CONCLUSIONS At six-month follow-up, the CEN still showed abnormal functional connectivity in those with rMDD, while anomalies in the SN and DMN has disappeared. Resting-state functional connectivity of the CEN during early rMDD is associated with psychosocial function. CLINICAL TRIALS REGISTRATION Pharmacotherapy and Psychotherapy for MDD after Remission on Psychology and Neuroimaging. https://www. CLINICALTRIALS gov/ , registration number: NCT01831440 (15/4/2013).
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Affiliation(s)
- Jiaqi Zhong
- Affiliated Nanjing Brain Hospital of Nanjing Medical University, No.264 Guangzhou Street, Gulou District, Nanjing, 210029, Jiangsu, China
- Cognitive Behavioral Therapy Institute of Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Jingren Xu
- Affiliated Nanjing Brain Hospital of Nanjing Medical University, No.264 Guangzhou Street, Gulou District, Nanjing, 210029, Jiangsu, China
| | - Zhenzhen Wang
- Affiliated Nanjing Brain Hospital of Nanjing Medical University, No.264 Guangzhou Street, Gulou District, Nanjing, 210029, Jiangsu, China
- School of psychological and cognitive sciences, Peking University, Beijing, 100871, China
| | - Hao Yang
- Affiliated Nanjing Brain Hospital of Nanjing Medical University, No.264 Guangzhou Street, Gulou District, Nanjing, 210029, Jiangsu, China
| | - Jiawei Li
- Affiliated Nanjing Brain Hospital of Nanjing Medical University, No.264 Guangzhou Street, Gulou District, Nanjing, 210029, Jiangsu, China
| | - Haoran Yu
- Affiliated Nanjing Brain Hospital of Nanjing Medical University, No.264 Guangzhou Street, Gulou District, Nanjing, 210029, Jiangsu, China
| | - Wenyan Huang
- Affiliated Nanjing Brain Hospital of Nanjing Medical University, No.264 Guangzhou Street, Gulou District, Nanjing, 210029, Jiangsu, China
| | - Cheng Wan
- Department of Medical Informatic, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Hui Ma
- Affiliated Nanjing Brain Hospital of Nanjing Medical University, No.264 Guangzhou Street, Gulou District, Nanjing, 210029, Jiangsu, China.
| | - Ning Zhang
- Affiliated Nanjing Brain Hospital of Nanjing Medical University, No.264 Guangzhou Street, Gulou District, Nanjing, 210029, Jiangsu, China.
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, 210029, Jiangsu, China.
- Cognitive Behavioral Therapy Institute of Nanjing Medical University, Nanjing, 210029, Jiangsu, China.
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Picci G, Petro NM, Son JJ, Agcaoglu O, Eastman JA, Wang YP, Stephen JM, Calhoun VD, Taylor BK, Wilson TW. Transdiagnostic indicators predict developmental changes in cognitive control resting-state networks. Dev Psychopathol 2023:1-11. [PMID: 37615120 PMCID: PMC11140239 DOI: 10.1017/s0954579423001013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/25/2023]
Abstract
Over the past decade, transdiagnostic indicators in relation to neurobiological processes have provided extensive insight into youth's risk for psychopathology. During development, exposure to childhood trauma and dysregulation (i.e., so-called AAA symptomology: anxiety, aggression, and attention problems) puts individuals at a disproportionate risk for developing psychopathology and altered network-level neural functioning. Evidence for the latter has emerged from resting-state fMRI studies linking mental health symptoms and aberrations in functional networks (e.g., cognitive control (CCN), default mode networks (DMN)) in youth, although few of these investigations have used longitudinal designs. Herein, we leveraged a three-year longitudinal study to identify whether traumatic exposures and concomitant dysregulation trigger changes in the developmental trajectories of resting-state functional networks involved in cognitive control (N = 190; 91 females; time 1 Mage = 11.81). Findings from latent growth curve analyses revealed that greater trauma exposure predicted increasing connectivity between the CCN and DMN across time. Greater levels of dysregulation predicted reductions in within-network connectivity in the CCN. These findings presented in typically developing youth corroborate connectivity patterns reported in clinical populations, suggesting there is predictive utility in using transdiagnostic indicators to forecast alterations in resting-state networks implicated in psychopathology.
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Affiliation(s)
- Giorgia Picci
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
- Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, USA
| | - Nathan M Petro
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Jake J Son
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
- College of Medicine, University of Nebraska Medical Center, Omaha, NE, USA
| | - Oktay Agcaoglu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of technology, and Emory University, Atlanta, GA, USA
| | - Jacob A Eastman
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Yu-Ping Wang
- Department of Biomedical Engineering, Tulane University, New Orleans, LA, USA
| | | | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of technology, and Emory University, Atlanta, GA, USA
| | - Brittany K Taylor
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
- Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, USA
| | - Tony W Wilson
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
- Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, USA
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9
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Javaheripour N, Colic L, Opel N, Li M, Maleki Balajoo S, Chand T, Van der Meer J, Krylova M, Izyurov I, Meller T, Goltermann J, Winter NR, Meinert S, Grotegerd D, Jansen A, Alexander N, Usemann P, Thomas-Odenthal F, Evermann U, Wroblewski A, Brosch K, Stein F, Hahn T, Straube B, Krug A, Nenadić I, Kircher T, Croy I, Dannlowski U, Wagner G, Walter M. Altered brain dynamic in major depressive disorder: state and trait features. Transl Psychiatry 2023; 13:261. [PMID: 37460460 DOI: 10.1038/s41398-023-02540-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 06/21/2023] [Accepted: 06/22/2023] [Indexed: 07/20/2023] Open
Abstract
Temporal neural synchrony disruption can be linked to a variety of symptoms of major depressive disorder (MDD), including mood rigidity and the inability to break the cycle of negative emotion or attention biases. This might imply that altered dynamic neural synchrony may play a role in the persistence and exacerbation of MDD symptoms. Our study aimed to investigate the changes in whole-brain dynamic patterns of the brain functional connectivity and activity related to depression using the hidden Markov model (HMM) on resting-state functional magnetic resonance imaging (rs-fMRI) data. We compared the patterns of brain functional dynamics in a large sample of 314 patients with MDD (65.9% female; age (mean ± standard deviation): 35.9 ± 13.4) and 498 healthy controls (59.4% female; age: 34.0 ± 12.8). The HMM model was used to explain variations in rs-fMRI functional connectivity and averaged functional activity across the whole-brain by using a set of six unique recurring states. This study compared the proportion of time spent in each state and the average duration of visits to each state to assess stability between different groups. Compared to healthy controls, patients with MDD showed significantly higher proportional time spent and temporal stability in a state characterized by weak functional connectivity within and between all brain networks and relatively strong averaged functional activity of regions located in the somatosensory motor (SMN), salience (SN), and dorsal attention (DAN) networks. Both proportional time spent and temporal stability of this brain state was significantly associated with depression severity. Healthy controls, in contrast to the MDD group, showed proportional time spent and temporal stability in a state with relatively strong functional connectivity within and between all brain networks but weak averaged functional activity across the whole brain. These findings suggest that disrupted brain functional synchrony across time is present in MDD and associated with current depression severity.
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Affiliation(s)
- Nooshin Javaheripour
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Philosophenweg 3, 07743, Jena, Germany
- Clinical Affective Neuroimaging Laboratory (CANLAB), Leipziger Str. 44, Building 65, 39120, Magdeburg, Germany
| | - Lejla Colic
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Philosophenweg 3, 07743, Jena, Germany
- German Center for Mental Health (DZPG), Jena, Germany
| | - Nils Opel
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Philosophenweg 3, 07743, Jena, Germany
- German Center for Mental Health (DZPG), Jena, Germany
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Center for Intervention and Research on adaptive and maladaptive brain Circuits underlying mental health (C-I-R-C), Jena-Magdeburg-Halle, Jena, Germany
| | - Meng Li
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Philosophenweg 3, 07743, Jena, Germany
- Clinical Affective Neuroimaging Laboratory (CANLAB), Leipziger Str. 44, Building 65, 39120, Magdeburg, Germany
- Center for Intervention and Research on adaptive and maladaptive brain Circuits underlying mental health (C-I-R-C), Jena-Magdeburg-Halle, Jena, Germany
| | - Somayeh Maleki Balajoo
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, 40225, Jülich, Germany
- Institute of Neuroscience and Medicine (INM-7), Research Centre Jülich, 52425, Jülich, Germany
| | - Tara Chand
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Philosophenweg 3, 07743, Jena, Germany
- Clinical Affective Neuroimaging Laboratory (CANLAB), Leipziger Str. 44, Building 65, 39120, Magdeburg, Germany
- Department of Clinical Psychology, Friedrich Schiller University Jena, Am Steiger 3-1, 07743, Jena, Germany
| | - Johan Van der Meer
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, The Netherlands
| | - Marina Krylova
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Philosophenweg 3, 07743, Jena, Germany
- Institute for Diagnostic and Interventional Radiology, Jena University Hospital, Jena, Germany
| | - Igor Izyurov
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Philosophenweg 3, 07743, Jena, Germany
| | - Tina Meller
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
| | - Janik Goltermann
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Nils R Winter
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039, Marburg, Germany
- Core-Facility Brainimaging, Faculty of Medicine, University of Marburg, Marburg, Germany
| | - Nina Alexander
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039, Marburg, Germany
- Core-Facility Brainimaging, Faculty of Medicine, University of Marburg, Marburg, Germany
| | - Paula Usemann
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039, Marburg, Germany
| | - Florian Thomas-Odenthal
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039, Marburg, Germany
| | - Ulrika Evermann
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039, Marburg, Germany
| | - Adrian Wroblewski
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039, Marburg, Germany
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039, Marburg, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Benjamin Straube
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
| | - Axel Krug
- Department of Psychiatry and Psychotherapy, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039, Marburg, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039, Marburg, Germany
| | - Ilona Croy
- Center for Intervention and Research on adaptive and maladaptive brain Circuits underlying mental health (C-I-R-C), Jena-Magdeburg-Halle, Jena, Germany
- Department of Clinical Psychology, Friedrich Schiller University Jena, Am Steiger 3-1, 07743, Jena, Germany
- Department of Psychotherapie and Psychosomatic Medicine, Carl Gustav Carus University Hospital Dresden, Fetscherstr. 74, 01307, Dresden, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Gerd Wagner
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Philosophenweg 3, 07743, Jena, Germany.
- Center for Intervention and Research on adaptive and maladaptive brain Circuits underlying mental health (C-I-R-C), Jena-Magdeburg-Halle, Jena, Germany.
| | - Martin Walter
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Philosophenweg 3, 07743, Jena, Germany.
- Clinical Affective Neuroimaging Laboratory (CANLAB), Leipziger Str. 44, Building 65, 39120, Magdeburg, Germany.
- German Center for Mental Health (DZPG), Jena, Germany.
- Center for Intervention and Research on adaptive and maladaptive brain Circuits underlying mental health (C-I-R-C), Jena-Magdeburg-Halle, Jena, Germany.
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany.
- Department of Psychiatry and Psychotherapy, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
- Leibniz Institute for Neurobiology, Magdeburg, Germany.
- Center for Behavioral Brain Sciences, Magdeburg, Germany.
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany.
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10
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Abstract
OBJECTIVE Impulsivity is an important risk for suicidality, which is common in patients with major depressive disorder (MDD). The goal of this study was to examine multiple facets of impulsivity in depressed patients compared with healthy controls and to assess their relationship to suicidality. METHOD Outpatients diagnosed with MDD using the Structured Clinical Interview for DSM-IV were recruited. Two groups were constituted as "MDD in remission" (n=32) and "MDD" (n=71). The "healthy control" group (n=30) consisted of individuals who had never been diagnosed with any psychiatric disorder. Impulsivity was assessed with the Barratt Impulsivity Scale (BIS), a self-rating measure, and with the following behavioral tasks: Go/No-go Task, Iowa Gambling Task, and Balloon Analogue Risk Task. The scores of the 3 groups (n=133) were compared to evaluate the effect of MDD. The scores were also analyzed and compared in the patients in the 2 MDD groups (n=103) with respect to their current and lifetime suicidality. RESULTS There was no difference in the 3 groups in task scores, but nonplanning BIS was correlated with the severity of depressive symptoms. Patients with suicidal ideation (SI) had higher BIS total and attention impulsivity scores and more commission errors on the Go/No-go Task, reflecting failure in response inhibition, compared with the patients without SI. CONCLUSIONS Failure to show differences in impulsivity-related tasks suggests that there might be no relationship between the state of depression and impulsivity. However, these findings confirm that there is an association between SI and response inhibition and the attention facet of impulsivity in depression.
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11
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Wang X, Xia J, Wang W, Lu J, Liu Q, Fan J, Soondrum T, Yu Q, Tan C, Zhu X. Disrupted functional connectivity of the cerebellum with default mode and frontoparietal networks in young adults with major depressive disorder. Psychiatry Res 2023; 324:115192. [PMID: 37054552 DOI: 10.1016/j.psychres.2023.115192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 03/15/2023] [Accepted: 04/04/2023] [Indexed: 04/15/2023]
Abstract
Cerebellar dysconnectivity has repeatedly been documented in major depressive disorder (MDD). The cerebellum is composed of multiple functionally distinct subunits, and whether those subunits show similar or distinct dysconnectivity patterns with the cerebrum in MDD, is still unclear and needs to be further clarified. In this study, 91 MDD patients (23 male and 68 female) and 59 demographically matched healthy controls (22 male and 37 female) were enrolled to explore the cerebellar-cerebral dysconnectivity pattern in MDD by using the cutting-edge cerebellar partition atlas. Results showed that MDD patients exhibit decreased cerebellar connectivity with cerebral regions of default mode (DMN), frontoparietal networks (FPN), and visual areas. The dysconnectivity pattern was statistically similar across cerebellar subunits, with no significant diagnosis-by-subunit interactions. Correlation analyzes showed that cerebellar-dorsal lateral prefrontal cortex (DLPFC) connectivity is significantly correlated with anhedonia in MDD patients. Such dysconnectivity pattern was not affected by sex, which, however, should be further replicated in larger samples. These findings suggest a generalized disrupted cerebellar-cerebral connectivity pattern in MDD across all cerebellar subunits, which partially accounts for depressive symptoms in MDD, thus highlighting the pivotal role of the disrupted connectivity of cerebellum with DMN and FPN in the neuropathology of depression.
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Affiliation(s)
- Xiang Wang
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Medical Psychological Institute of Central South University, Changsha, Hunan, China; National Clinical Research Center for Mental Disorders, Changsha, Hunan, China
| | - Jie Xia
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Medical Psychological Institute of Central South University, Changsha, Hunan, China; National Clinical Research Center for Mental Disorders, Changsha, Hunan, China
| | - Weiyan Wang
- National Clinical Research Center for Mental Disorders, Changsha, Hunan, China; Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Jingjie Lu
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Medical Psychological Institute of Central South University, Changsha, Hunan, China; National Clinical Research Center for Mental Disorders, Changsha, Hunan, China
| | - Qian Liu
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Medical Psychological Institute of Central South University, Changsha, Hunan, China; National Clinical Research Center for Mental Disorders, Changsha, Hunan, China
| | - Jie Fan
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Medical Psychological Institute of Central South University, Changsha, Hunan, China; National Clinical Research Center for Mental Disorders, Changsha, Hunan, China
| | - Tamini Soondrum
- Association Alzheimer of Mauritius, Old Moka Road, Belle Rose, Quatre Bornes, Mauritius
| | - Quanhao Yu
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Medical Psychological Institute of Central South University, Changsha, Hunan, China; National Clinical Research Center for Mental Disorders, Changsha, Hunan, China
| | - Changlian Tan
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Xiongzhao Zhu
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Medical Psychological Institute of Central South University, Changsha, Hunan, China; National Clinical Research Center for Mental Disorders, Changsha, Hunan, China.
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12
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Jing R, Lin X, Ding Z, Chang S, Shi L, Liu L, Wang Q, Si J, Yu M, Zhuo C, Shi J, Li P, Fan Y, Lu L. Heterogeneous brain dynamic functional connectivity patterns in first-episode drug-naive patients with major depressive disorder. Hum Brain Mapp 2023; 44:3112-3122. [PMID: 36919400 PMCID: PMC10171501 DOI: 10.1002/hbm.26266] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 02/15/2023] [Accepted: 02/16/2023] [Indexed: 03/16/2023] Open
Abstract
It remains challenging to identify depression accurately due to its biological heterogeneity. As people suffering from depression are associated with functional brain network alterations, we investigated subtypes of patients with first-episode drug-naive (FEDN) depression based on brain network characteristics. This study included data from 91 FEDN patients and 91 matched healthy individuals obtained from the International Big-Data Center for Depression Research. Twenty large-scale functional connectivity networks were computed using group information guided independent component analysis. A multivariate unsupervised normative modeling method was used to identify subtypes of FEDN and their associated networks, focusing on individual-level variability among the patients for quantifying deviations of their brain networks from the normative range. Two patient subtypes were identified with distinctive abnormal functional network patterns, consisting of 10 informative connectivity networks, including the default mode network and frontoparietal network. 16% of patients belonged to subtype I with larger extreme deviations from the normal range and shorter illness duration, while 84% belonged to subtype II with weaker extreme deviations and longer illness duration. Moreover, the structural changes in subtype II patients were more complex than the subtype I patients. Compared with healthy controls, both increased and decreased gray matter (GM) abnormalities were identified in widely distributed brain regions in subtype II patients. In contrast, most abnormalities were decreased GM in subtype I. The informative functional network connectivity patterns gleaned from the imaging data can facilitate the accurate identification of FEDN-MDD subtypes and their associated neurobiological heterogeneity.
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Affiliation(s)
- Rixing Jing
- School of Instrument Science and Opto-Electronics Engineering, Beijing Information Science and Technology University, Beijing, China
| | - Xiao Lin
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Chinese Academy of Medical Sciences Research Unit, Peking University, Beijing, China
| | - Zengbo Ding
- National Institute on Drug Dependence and Beijing Key Laboratory on Drug Dependence Research, Peking University, Beijing, China
| | - Suhua Chang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Chinese Academy of Medical Sciences Research Unit, Peking University, Beijing, China
| | - Le Shi
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Chinese Academy of Medical Sciences Research Unit, Peking University, Beijing, China
| | - Lin Liu
- National Institute on Drug Dependence and Beijing Key Laboratory on Drug Dependence Research, Peking University, Beijing, China
| | - Qiandong Wang
- Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education (Beijing Normal University), Faculty of Psychology, Beijing Normal University, Beijing, China
| | - Juanning Si
- School of Instrument Science and Opto-Electronics Engineering, Beijing Information Science and Technology University, Beijing, China
| | - Mingxin Yu
- School of Instrument Science and Opto-Electronics Engineering, Beijing Information Science and Technology University, Beijing, China
| | - Chuanjun Zhuo
- Key Laboratory of Real-Time Tracing of Brain Circuits of Neurology and Psychiatry (RTBNB_Lab), Tianjin Fourth Centre Hospital, Tianjin Medical University Affiliated Tianjin Fourth Centre Hospital, Nankai University Affiliated Fourth Hospital, Tianjin, China
| | - Jie Shi
- National Institute on Drug Dependence and Beijing Key Laboratory on Drug Dependence Research, Peking University, Beijing, China
| | - Peng Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Chinese Academy of Medical Sciences Research Unit, Peking University, Beijing, China
| | - Yong Fan
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Lin Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Chinese Academy of Medical Sciences Research Unit, Peking University, Beijing, China.,National Institute on Drug Dependence and Beijing Key Laboratory on Drug Dependence Research, Peking University, Beijing, China.,Peking-Tsinghua Center for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
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13
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Thomas LR, Bessette KL, Westlund Schreiner M, Dillahunt AK, Frandsen SB, Pocius SL, Schubert BL, Farstead BW, Roberts H, Watkins ER, Kerig PK, Crowell SE, Langenecker SA. Early Emergence of Rumination has no Association with Performance on a Non-affective Inhibitory Control Task. Child Psychiatry Hum Dev 2023:10.1007/s10578-022-01484-8. [PMID: 36637686 PMCID: PMC9839218 DOI: 10.1007/s10578-022-01484-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 11/16/2022] [Accepted: 12/08/2022] [Indexed: 01/14/2023]
Abstract
Rumination is a vulnerability for depression and potentially linked to inhibitory control weaknesses. We aimed to replicate the association observed in adults between inhibitory control and rumination in adolescents, and to examine putative moderating roles of childhood maltreatment and perceived family cohesion in an adolescent sample at risk for depression due to familial/personal history. Ninety adolescents aged 11-17 (M = 14.6, SD = 1.8) completed self-report scales of rumination, maltreatment, and family cohesion, and performed a task assessing inhibitory control. Hierarchical regression models showed no significant relation between inhibitory control and moderator variables on rumination. However, adolescents who reported higher levels of maltreatment and who perceived lower family cohesion tended to indicate higher levels of rumination (BChilhood Maltreatment = 27.52, 95% CIs [5.63, 49.41], BFamily Cohesion = -0.40, 95% CIs [-0.65, -0.15]). These findings demonstrate an alternative understanding of factors that increase depression onset risk and recurrence in adolescents.
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Affiliation(s)
- Leah R Thomas
- Department of Psychiatry, Huntsman Mental Health Institute, University of Utah, 501 Chipeta Way, 84108, Salt Lake City, UT, USA.
- Department of Psychology, University of Utah, 84112, Salt Lake City, UT, USA.
| | - Katie L Bessette
- Department of Psychiatry, Huntsman Mental Health Institute, University of Utah, 501 Chipeta Way, 84108, Salt Lake City, UT, USA
- Department of Psychology, University of Illinois at Chicago, 60607, Chicago, IL, USA
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, 90024, Los Angeles, CA, USA
| | - Melinda Westlund Schreiner
- Department of Psychiatry, Huntsman Mental Health Institute, University of Utah, 501 Chipeta Way, 84108, Salt Lake City, UT, USA
| | - Alina K Dillahunt
- Department of Psychiatry, Huntsman Mental Health Institute, University of Utah, 501 Chipeta Way, 84108, Salt Lake City, UT, USA
| | - Summer B Frandsen
- Department of Psychiatry, Huntsman Mental Health Institute, University of Utah, 501 Chipeta Way, 84108, Salt Lake City, UT, USA
| | - Stephanie L Pocius
- Department of Psychiatry, Huntsman Mental Health Institute, University of Utah, 501 Chipeta Way, 84108, Salt Lake City, UT, USA
| | - Briana Lee Schubert
- Department of Psychiatry, Huntsman Mental Health Institute, University of Utah, 501 Chipeta Way, 84108, Salt Lake City, UT, USA
| | - Brian W Farstead
- Department of Psychiatry, Huntsman Mental Health Institute, University of Utah, 501 Chipeta Way, 84108, Salt Lake City, UT, USA
| | | | | | - Patricia K Kerig
- Department of Psychology, University of Utah, 84112, Salt Lake City, UT, USA
| | - Sheila E Crowell
- Department of Psychiatry, Huntsman Mental Health Institute, University of Utah, 501 Chipeta Way, 84108, Salt Lake City, UT, USA
- Department of Psychology, University of Utah, 84112, Salt Lake City, UT, USA
- Department of Obstetrics and Gynecology, University of Utah, 84112, Salt Lake City, UT, USA
| | - Scott A Langenecker
- Department of Psychiatry, Huntsman Mental Health Institute, University of Utah, 501 Chipeta Way, 84108, Salt Lake City, UT, USA
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14
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Philippi CL, Leutzinger K, Pessin S, Cassani A, Mikel O, Walsh EC, Hoks RM, Birn RM, Abercrombie HC. Neural signal variability relates to maladaptive rumination in depression. J Psychiatr Res 2022; 156:570-578. [PMID: 36368247 PMCID: PMC9817305 DOI: 10.1016/j.jpsychires.2022.10.070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 10/28/2022] [Accepted: 10/31/2022] [Indexed: 11/05/2022]
Abstract
Rumination is a common feature of depression and predicts the onset and maintenance of depressive episodes. Maladaptive and adaptive subtypes of rumination contribute to distinct outcomes, with brooding worsening negative mood and reflection related to fewer depression symptoms in healthy populations. Neuroimaging studies have implicated several cortical midline and lateral prefrontal brain regions in rumination. Recent research indicates that blood oxygen level-dependent (BOLD) signal variability may be a novel predictor of cognitive flexibility. However, no prior studies have investigated whether brooding and reflection are associated with distinct patterns of BOLD signal variability in depression. We collected resting-state fMRI data for 79 women with different depression histories: no history, past history, and current depression. We examined differences in BOLD signal variability (BOLDSD) related to rumination subtypes for the following regions of interest previously implicated in rumination: amygdala, medial prefrontal, anterior cingulate, posterior cingulate, and dorsolateral prefrontal cortices (dlPFC). Rumination subtype was associated with BOLDSD in the dlPFC, with greater levels of brooding associated with lower BOLDSD in the dlPFC, even after controlling for depression severity. Depression history was related to BOLDSD in the dlPFC, with reduced BOLDSD in those with current depression versus no history of depression. These findings provide a novel demonstration of the neural circuitry associated with maladaptive rumination in depression and implicate decreased prefrontal neural signal variability in the pathophysiology of depression.
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Affiliation(s)
- Carissa L Philippi
- Department of Psychological Sciences, University of Missouri-St. Louis, 1 University Blvd., St. Louis, Missouri, 63121, USA.
| | - Katie Leutzinger
- Department of Psychological Sciences, University of Missouri-St. Louis, 1 University Blvd., St. Louis, Missouri, 63121, USA
| | - Sally Pessin
- Department of Psychological Sciences, University of Missouri-St. Louis, 1 University Blvd., St. Louis, Missouri, 63121, USA
| | - Alexis Cassani
- Department of Psychological Sciences, University of Missouri-St. Louis, 1 University Blvd., St. Louis, Missouri, 63121, USA
| | - Olivia Mikel
- Department of Psychological Sciences, University of Missouri-St. Louis, 1 University Blvd., St. Louis, Missouri, 63121, USA
| | - Erin C Walsh
- Department of Psychiatry, University of North Carolina at Chapel Hill School of Medicine, CB# 7167, Chapel Hill, NC, 27599, USA
| | - Roxanne M Hoks
- Center for Healthy Minds, University of Wisconsin-Madison, 625 W. Washington Ave., Madison, WI, 53703, USA
| | - Rasmus M Birn
- Department of Psychiatry, University of Wisconsin-Madison, University of Wisconsin-Madison, 6001 Research Park Blvd., Madison, WI, 53719, USA
| | - Heather C Abercrombie
- Center for Healthy Minds, University of Wisconsin-Madison, 625 W. Washington Ave., Madison, WI, 53703, USA
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15
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Lin Z, Xu X, Wang T, Huang Z, Wang G. Abnormal regional homogeneity and functional connectivity in major depressive disorder patients with long-term remission: An exploratory study. Psychiatry Res Neuroimaging 2022; 327:111557. [PMID: 36327866 DOI: 10.1016/j.pscychresns.2022.111557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 09/13/2022] [Accepted: 10/18/2022] [Indexed: 11/07/2022]
Abstract
This study was the first to explore whether abnormal spontaneous neuronal activities exist in patients in the long-term remission stage of major depressive disorder (MDD). We recruited 34 MDD patients (PTs) and 30 sex- and age-matched healthy controls (HCs). Resting-state functional magnetic resonance imaging (rs-fMRI) was employed to scan all subjects' brain regions, and independent two-sample t-test was used for regional homogeneity (ReHo) and functional connectivity (FC) analysis. Compared with the HCs, the ReHo of PTs increased in the right superior frontal gyrus and left middle frontal gyrus, and decreased in the right anterior and collateral cingulate gyrus, right middle frontal gyrus, right inferior parietal lobule. The cingulate gyrus as a mask showed that FC of the cingulate gyrus with the bilateral lingual gyrus and the right middle temporal gyrus decreased, and FC with the left supper frontal gyrus increased. The correlation analysis revealed no significant correlation between the abnormal ReHo and HAMD-24 scores in PTs. The ReHo of inferior parietal lobule and the duration of remission were positively correlated. We concluded that the spontaneous neuronal activities might be disrupted in MDD patients in the long-term remission stage. Our findings provided new reasons for MDD relapse.
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Affiliation(s)
- Zouqing Lin
- Department of Psychiatry, Wuxi Mental Health Center, Wuxi, China.
| | - Xiaoyan Xu
- Department of Psychiatry, Wuxi Mental Health Center, Wuxi, China; Department of Psychiatry, Wuxi Hospital of traditional Chinese Medicine, Wuxi, China.
| | - Tenglong Wang
- Department of geriatric psychiatry, Wuxi Mental Health Center, Wuxi, China.
| | | | - Guoqiang Wang
- Department of Psychiatry, Wuxi Mental Health Center, Wuxi, China.
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16
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Wijaya MT, Jin R, Liu X, Zhang R, Lee TM. Towards a multidimensional model of inflamed depression. Brain Behav Immun Health 2022; 26:100564. [DOI: 10.1016/j.bbih.2022.100564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 11/10/2022] [Accepted: 11/13/2022] [Indexed: 11/21/2022] Open
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17
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Minami F, Hirano J, Ueda R, Takamiya A, Yamagishi M, Kamiya K, Mimura M, Yamagata B. Intergenerational concordance of brain structure between depressed mothers and their never-depressed daughters. Psychiatry Clin Neurosci 2022; 76:579-586. [PMID: 36082981 DOI: 10.1111/pcn.13461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 07/06/2022] [Accepted: 08/08/2022] [Indexed: 11/30/2022]
Abstract
AIM Parents have significant genetic and environmental influences, which are known as intergenerational effects, on the cognition, behavior, and brain of their offspring. These intergenerational effects are observed in patients with mood disorders, with a particularly strong association of depression between mothers and daughters. The main purpose of our study was to investigate female-specific intergenerational transmission patterns in the human brain among patients with depression and their never-depressed offspring. METHODS We recruited 78 participants from 34 families, which included remitted parents with a history of depression and their never-depressed biological offspring. We used source-based and surface-based morphometry analyses of magnetic resonance imaging data to examine the degree of associations in brain structure between four types of parent-offspring dyads (i.e. mother-daughter, mother-son, father-daughter, and father-son). RESULTS Using independent component analysis, we found a significant positive correlation of gray matter structure between exclusively the mother-daughter dyads within brain regions located in the default mode and central executive networks, such as the bilateral anterior cingulate cortex, posterior cingulate cortex, precuneus, middle frontal gyrus, middle temporal gyrus, superior parietal lobule, and left angular gyrus. These similar observations were not identified in other three parent-offspring dyads. CONCLUSIONS The current study provides biological evidence for greater vulnerability of daughters, but not sons, in developing depression whose mothers have a history of depression. Our findings extend our knowledge on the pathophysiology of major psychiatric conditions that show sex biases and may contribute to the development of novel interventions targeting high-risk individuals.
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Affiliation(s)
- Fusaka Minami
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Jinichi Hirano
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Ryo Ueda
- Office of Radiation Technology, Keio University Hospital, Tokyo, Japan
| | - Akihiro Takamiya
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Mika Yamagishi
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Kei Kamiya
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Masaru Mimura
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Bun Yamagata
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
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18
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Altered functional connectivity in common resting-state networks in patients with major depressive disorder: A resting-state functional connectivity study. J Psychiatr Res 2022; 155:33-41. [PMID: 35987176 DOI: 10.1016/j.jpsychires.2022.07.040] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 06/09/2022] [Accepted: 07/20/2022] [Indexed: 11/23/2022]
Abstract
The neural correlates of major depressive disorder (MDD) remain disputed. In the absence of reliable biological markers, the dysfunction and interaction of neural networks have been proposed as pathophysiological neural mechanisms in depression. Here, we examined the functional connectivity (FC) of brain networks. 51 healthy volunteers (mean age 33.57 ± 7.80) and 55 individuals diagnosed with MDD (mean age 33.89 ± 11.00) participated by performing a resting-state (rs) fMRI scan. Seed to voxel FC analyses were performed. Compared to healthy control (HC), MDD patients showed higher connectivity between the hippocampus and the anterior cingulate cortex (ACC) and lower connectivity between the insula and the ACC. The MDD group displayed lower connectivity between the inferior parietal lobule (IPL) and the superior frontal gyrus (SFG). The current data replicate previous findings regarding the cortico-limbic network (hippocampus - ACC connection) and the salience network (insula - ACC connection) and provide novel insight into altered rsFC in MDD, in particular involving the hippocampus - ACC and the insula - ACC connection. Furthermore, altered connectivity between the IPL and SFG indicates that the processing in higher cognitive processes such as attention and working memory is affected in MDD. These data further support dysfunctional neuronal networks as an interesting pathophysiological marker in depression.
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19
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Zhang X, Zhang R, Lv L, Qi X, Shi J, Xie S. Correlation between cognitive deficits and dorsolateral prefrontal cortex functional connectivity in first-episode depression. J Affect Disord 2022; 312:152-158. [PMID: 35752217 DOI: 10.1016/j.jad.2022.06.024] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 05/17/2022] [Accepted: 06/16/2022] [Indexed: 01/24/2023]
Abstract
INTRODUCTION Although depression is commonly accompanied by cognitive deficits, the underlying mechanism remains unclear. One possibility is that such deficits are related to abnormal brain network connections. The purpose of this study was thus to investigate changes in brain functional connectivity (FC) in depression and its relationship with cognitive deficits. METHODS We enrolled 37 first-episode MDD patients and 53 matched healthy controls (HC). All participants completed clinical and neurocognitive assessments and underwent resting-state functional MRI. Seed-based analysis was used to define the dorsolateral prefrontal cortex (DLPFC) and FC analysis was then performed. We used bias correlation to analyze the correlation between FC and clinical and neurocognitive scores. RESULTS MDD patients showed increased FC of the right DLPFC with the left inferior temporal gyrus, left cuneus, right inferior frontal gyrus, right anterior cingulate cortex, left BA39, right angular gyrus, right precuneus, left middle frontal gyrus, and right precentral gyrus. MDD patients also showed stronger FC in the left thalamus and reduced FC between the left superior occipital gyrus and left DLPFC seed region. Interestingly, increased FC was related to disease severity (with the right precentral gyrus) and social cognitive dysfunction (with the right angular gyrus) in MDD patients. LIMITATIONS The sample size was relatively small and it is unclear how age may influence FC changes in patients with depression. CONCLUSIONS These findings support changes in FC of the DLPFC in early MDD patients related to cognitive function. FC is a potential biomarker for the diagnosis of MDD.
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Affiliation(s)
- Xuemei Zhang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China; Department of Neurology, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, China
| | - Rongrong Zhang
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Lanlan Lv
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Xinyang Qi
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Jingping Shi
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
| | - Shiping Xie
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
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20
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Yu RQ, Tan H, Wang ED, Huang J, Wang PJ, Li XM, Zheng HH, Lv FJ, Hu H. Antidepressants combined with psychodrama improve the coping style and cognitive control network in patients with childhood trauma-associated major depressive disorder. World J Psychiatry 2022; 12:1016-1030. [PMID: 36158310 PMCID: PMC9476846 DOI: 10.5498/wjp.v12.i8.1016] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 06/24/2022] [Accepted: 07/31/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND The use of antidepressant therapy alone has a limited efficacy in patients with childhood trauma-associated major depressive disorder (MDD). However, the effectiveness of antidepressant treatment combined with psychodrama in these patients is unclear.
AIM To evaluate the effectiveness of antidepressant treatment combined with psychodrama.
METHODS Patients with childhood trauma-associated MDD treated with antidepressants were randomly assigned to either the psychodrama intervention (observation group) or the general health education intervention (control group) and received combination treatment for 6 mo. The observation group received general health education given by the investigator together with the “semi-structured group intervention model” of Yi Shu psychodrama. A total of 46 patients were recruited, including 29 cases in the observation group and 17 cases in the control group. Symptoms of depression and anxiety as well as coping style and resting-state functional magnetic resonance imaging were assessed before and after the intervention.
RESULTS Symptoms of depression and anxiety, measured by the Hamilton Depression Scale, Beck Depression Inventory, and Beck Anxiety Inventory, were reduced after the intervention in both groups of patients. The coping style of the observation group improved significantly in contrast to the control group, which did not. In addition, an interaction between treatment and time in the right superior parietal gyrus node was found. Furthermore, functional connectivity between the right superior parietal gyrus and left inferior frontal gyrus in the observation group increased after the intervention, while in the control group the connectivity decreased.
CONCLUSION This study supports the use of combined treatment with antidepressants and psychodrama to improve the coping style of patients with childhood trauma-associated MDD. Functional connectivity between the superior parietal gyrus and inferior frontal gyrus was increased after this combined treatment. We speculate that psychodrama enhances the internal connectivity of the cognitive control network and corrects the negative attention bias of patients with childhood trauma-associated MDD. Elucidating the neurobiological features of patients with childhood trauma-associated MDD is important for the development of methods that can assist in early diagnosis and intervention.
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Affiliation(s)
- Ren-Qiang Yu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Huan Tan
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Er-Dong Wang
- College of Art, Soochow University, Suzhou 215006, Jiangsu Province, China
| | - Jie Huang
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing 40016, China
| | - Pei-Jia Wang
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing 40016, China
| | - Xiao-Mei Li
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing 40016, China
| | - Han-Han Zheng
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing 40016, China
| | - Fa-Jin Lv
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Hua Hu
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing 40016, China
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21
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Demchenko I, Tassone VK, Kennedy SH, Dunlop K, Bhat V. Intrinsic Connectivity Networks of Glutamate-Mediated Antidepressant Response: A Neuroimaging Review. Front Psychiatry 2022; 13:864902. [PMID: 35722550 PMCID: PMC9199367 DOI: 10.3389/fpsyt.2022.864902] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Accepted: 04/12/2022] [Indexed: 11/23/2022] Open
Abstract
Conventional monoamine-based pharmacotherapy, considered the first-line treatment for major depressive disorder (MDD), has several challenges, including high rates of non-response. To address these challenges, preclinical and clinical studies have sought to characterize antidepressant response through monoamine-independent mechanisms. One striking example is glutamate, the brain's foremost excitatory neurotransmitter: since the 1990s, studies have consistently reported altered levels of glutamate in MDD, as well as antidepressant effects following molecular targeting of glutamatergic receptors. Therapeutically, this has led to advances in the discovery, testing, and clinical application of a wide array of glutamatergic agents, particularly ketamine. Notably, ketamine has been demonstrated to rapidly improve mood symptoms, unlike monoamine-based interventions, and the neurobiological basis behind this rapid antidepressant response is under active investigation. Advances in brain imaging techniques, including functional magnetic resonance imaging, magnetic resonance spectroscopy, and positron emission tomography, enable the identification of the brain network-based characteristics distinguishing rapid glutamatergic modulation from the effect of slow-acting conventional monoamine-based pharmacology. Here, we review brain imaging studies that examine brain connectivity features associated with rapid antidepressant response in MDD patients treated with glutamatergic pharmacotherapies in contrast with patients treated with slow-acting monoamine-based treatments. Trends in recent brain imaging literature suggest that the activity of brain regions is organized into coherent functionally distinct networks, termed intrinsic connectivity networks (ICNs). We provide an overview of major ICNs implicated in depression and explore how treatment response following glutamatergic modulation alters functional connectivity of limbic, cognitive, and executive nodes within ICNs, with well-characterized anti-anhedonic effects and the enhancement of "top-down" executive control. Alterations within and between the core ICNs could potentially exert downstream effects on the nodes within other brain networks of relevance to MDD that are structurally and functionally interconnected through glutamatergic synapses. Understanding similarities and differences in brain ICNs features underlying treatment response will positively impact the trajectory and outcomes for adults suffering from MDD and will facilitate the development of biomarkers to enable glutamate-based precision therapeutics.
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Affiliation(s)
- Ilya Demchenko
- Interventional Psychiatry Program, Mental Health and Addictions Service, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Center for Depression and Suicide Studies, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
| | - Vanessa K Tassone
- Interventional Psychiatry Program, Mental Health and Addictions Service, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
| | - Sidney H Kennedy
- Interventional Psychiatry Program, Mental Health and Addictions Service, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Center for Depression and Suicide Studies, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Keenan Research Center for Biomedical Science, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Katharine Dunlop
- Interventional Psychiatry Program, Mental Health and Addictions Service, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Center for Depression and Suicide Studies, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Keenan Research Center for Biomedical Science, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Venkat Bhat
- Interventional Psychiatry Program, Mental Health and Addictions Service, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Center for Depression and Suicide Studies, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Keenan Research Center for Biomedical Science, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
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22
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Langenecker SA, Westlund Schreiner M, Thomas LR, Bessette KL, DelDonno SR, Jenkins LM, Easter RE, Stange JP, Pocius SL, Dillahunt A, Love TM, Phan KL, Koppelmans V, Paulus M, Lindquist MA, Caffo B, Mickey BJ, Welsh RC. Using Network Parcels and Resting-State Networks to Estimate Correlates of Mood Disorder and Related Research Domain Criteria Constructs of Reward Responsiveness and Inhibitory Control. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2022; 7:76-84. [PMID: 34271215 PMCID: PMC8748287 DOI: 10.1016/j.bpsc.2021.06.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 05/14/2021] [Accepted: 06/13/2021] [Indexed: 01/03/2023]
Abstract
BACKGROUND Resting-state graph-based network edges can be powerful tools for identification of mood disorders. We address whether these edges can be integrated with Research Domain Criteria (RDoC) constructs for accurate identification of mood disorder-related markers, while minimizing active symptoms of disease. METHODS We compared 132 individuals with currently remitted or euthymic mood disorder with 65 healthy comparison participants, ages 18-30 years. Subsets of smaller brain parcels, combined into three prominent networks and one network of parcels overlapping across these networks, were used to compare edge differences between groups. Consistent with the RDoC framework, we evaluated individual differences with performance measure regressors of inhibitory control and reward responsivity. Within an omnibus regression model, we predicted edges related to diagnostic group membership, performance within both RDoC domains, and relevant interactions. RESULTS There were several edges of mood disorder group, predominantly of greater connectivity across networks, different than those related to individual differences in inhibitory control and reward responsivity. Edges related to diagnosis and inhibitory control did not align well with prior literature, whereas edges in relation to reward responsivity constructs showed greater alignment with prior literature. Those edges in interaction between RDoC constructs and diagnosis showed a divergence for inhibitory control (negative interactions in default mode) relative to reward (positive interactions with salience and emotion network). CONCLUSIONS In conclusion, there is evidence that prior simple network models of mood disorders are currently of insufficient biological or diagnostic clarity or that parcel-based edges may be insufficiently sensitive for these purposes.
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Affiliation(s)
| | | | - Leah R Thomas
- Department of Psychiatry, University of Utah, Salt Lake City, Utah; Department of Psychology, University of Utah, Salt Lake City, Utah
| | - Katie L Bessette
- Department of Psychiatry, University of Utah, Salt Lake City, Utah; Department of Psychiatry & Psychology, University of Illinois at Chicago, Chicago, Illinois
| | - Sophia R DelDonno
- Department of Psychiatry & Psychology, University of Illinois at Chicago, Chicago, Illinois
| | - Lisanne M Jenkins
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Evanston, Illinois
| | - Rebecca E Easter
- Department of Psychiatry & Psychology, University of Illinois at Chicago, Chicago, Illinois
| | - Jonathan P Stange
- Department of Psychiatry & Psychology, University of Illinois at Chicago, Chicago, Illinois; Department of Psychology, University of Southern California, Los Angeles, California
| | | | - Alina Dillahunt
- Department of Psychiatry, University of Utah, Salt Lake City, Utah
| | - Tiffany M Love
- Department of Psychiatry, University of Utah, Salt Lake City, Utah
| | - K Luan Phan
- Department of Psychiatry and Behavioral Health, The Ohio State University, Columbus, Ohio
| | | | - Martin Paulus
- Laureate Institute for Brain Research, Tulsa, Oklahoma
| | | | - Brian Caffo
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Brian J Mickey
- Department of Psychiatry, University of Utah, Salt Lake City, Utah
| | - Robert C Welsh
- Department of Psychiatry, University of Utah, Salt Lake City, Utah
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23
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Hsu LM, Lane TJ, Wu CW, Lin CY, Yeh CB, Kao HW, Lin CP. Spontaneous thought-related network connectivity predicts sertraline effect on major depressive disorder. Brain Imaging Behav 2021; 15:1705-1717. [PMID: 32710339 DOI: 10.1007/s11682-020-00364-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Sertraline is one of the most commonly prescribed antidepressants. Major depressive disorder (MDD) is characterized by spontaneous thoughts that are laden with negative affect-a "malignant sadness". Prior neuroimaging studies have identified abnormal resting-state functional connectivity (rsFC) in the spontaneous brain networks of MDD patients. But how antidepressant medication acts to relieve the experience of depression as well as adjust its associated spontaneous networks and mood-regulation circuits remains an open question. In this study, we recruited 22 drug-naïve MDD patients along with 35 normal controls and investigated whether the functional integrity of cortical networks associated with spontaneous thoughts is modulated by sertraline treatment. We attempted to predict post-treatment effects based upon what we observed in the pre-treatment rsFC of drug-naïve MDD patients. In the result, we demonstrated that (1) after the sertraline treatment, the medial temporal lobe of default network (DNMTL) and mood regulation pathway-the fronto-parietal control network (FPCN), the thalamus, and the salience network (SN)-were restored to normal connectivity, relative to the pre-treatment condition; however, the altered connections of FPCN-core DN (DNCORE), FPCN-SN, and intra-FPCN among MDD patients remained impaired; (2) thalamo-prefrontal connectivity provides moderate predictive power (r2 = 0.63) for the effectiveness of sertraline treatment. In summary, our findings contribute to a body of evidence that suggests salubrious effects of sertraline treatment primarily involve the FPCN-thalamus-SN pathway. The pre-treatment rsFC in this pathway could serve as a predictor of sertraline treatment outcome.
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Affiliation(s)
- Li-Ming Hsu
- Department of Radiology and Brain Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan
| | - Timothy Joseph Lane
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan
- Brain and Consciousness Research Center, Taipei Medical University-Shuang Ho Hospital, New Taipei, Taiwan
- Institute of European and American Studies, Academia Sinica, Taipei, Taiwan
| | - Changwei W Wu
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan
- Brain and Consciousness Research Center, Taipei Medical University-Shuang Ho Hospital, New Taipei, Taiwan
| | | | - Chi-Bin Yeh
- Department of Psychiatry, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan.
| | - Hung-Wen Kao
- Department of Radiology, Tri-Service General Hospital, National Defense Medical Center, No. 325, Section 2, Chenggong Road, Neihu District, Taipei City, 114, Taiwan.
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang-Ming University, Taipei, Taiwan
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24
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Depping MS, Schmitgen MM, Bach C, Listunova L, Kienzle J, Kubera KM, Roesch-Ely D, Wolf RC. Abnormal Cerebellar Volume in Patients with Remitted Major Depression with Persistent Cognitive Deficits. THE CEREBELLUM 2021; 19:762-770. [PMID: 32642931 PMCID: PMC8214579 DOI: 10.1007/s12311-020-01157-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Cerebellar involvement in major depressive disorder (MDD) has been demonstrated by a growing number of studies, but it is unknown whether cognitive functioning in depressed individuals is related to cerebellar gray matter volume (GMV) abnormalities. Impaired attention and executive dysfunction are characteristic cognitive deficits in MDD, and critically, they often persist despite remission of mood symptoms. In this study, we investigated cerebellar GMV in patients with remitted MDD (rMDD) that showed persistent cognitive impairment. We applied cerebellum-optimized voxel-based morphometry in 37 patients with rMDD and with cognitive deficits, in 12 patients with rMDD and without cognitive deficits, and in 36 healthy controls (HC). Compared with HC, rMDD patients with cognitive deficits had lower GMV in left area VIIA, crus II, and in vermal area VIIB. In patients with rMDD, regression analyses demonstrated significant associations between GMV reductions in both regions and impaired attention and executive dysfunction. Compared with HC, patients without cognitive deficits showed increased GMV in bilateral area VIIIB. This study supports cerebellar contributions to the cognitive dimension of MDD. The data also point towards cerebellar area VII as a potential target for non-invasive brain stimulation to treat cognitive deficits related to MDD.
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Affiliation(s)
- Malte S Depping
- Center for Psychosocial Medicine, Department of General Psychiatry, University of Heidelberg, Vossstr. 4, 69115, Heidelberg, Germany
| | - Mike M Schmitgen
- Center for Psychosocial Medicine, Department of General Psychiatry, University of Heidelberg, Vossstr. 4, 69115, Heidelberg, Germany
| | - Claudia Bach
- Center for Psychosocial Medicine, Department of General Psychiatry, University of Heidelberg, Vossstr. 4, 69115, Heidelberg, Germany
| | - Lena Listunova
- Center for Psychosocial Medicine, Department of General Psychiatry, University of Heidelberg, Vossstr. 4, 69115, Heidelberg, Germany
| | - Johanna Kienzle
- Center for Psychosocial Medicine, Department of General Psychiatry, University of Heidelberg, Vossstr. 4, 69115, Heidelberg, Germany
| | - Katharina M Kubera
- Center for Psychosocial Medicine, Department of General Psychiatry, University of Heidelberg, Vossstr. 4, 69115, Heidelberg, Germany
| | - Daniela Roesch-Ely
- Center for Psychosocial Medicine, Department of General Psychiatry, University of Heidelberg, Vossstr. 4, 69115, Heidelberg, Germany
| | - R Christian Wolf
- Center for Psychosocial Medicine, Department of General Psychiatry, University of Heidelberg, Vossstr. 4, 69115, Heidelberg, Germany.
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25
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Dini H, Sendi MSE, Sui J, Fu Z, Espinoza R, Narr KL, Qi S, Abbott CC, van Rooij SJH, Riva-Posse P, Bruni LE, Mayberg HS, Calhoun VD. Dynamic Functional Connectivity Predicts Treatment Response to Electroconvulsive Therapy in Major Depressive Disorder. Front Hum Neurosci 2021; 15:689488. [PMID: 34295231 PMCID: PMC8291148 DOI: 10.3389/fnhum.2021.689488] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Accepted: 05/31/2021] [Indexed: 12/28/2022] Open
Abstract
Background: Electroconvulsive therapy (ECT) is one of the most effective treatments for major depressive disorder. Recently, there has been increasing attention to evaluate the effect of ECT on resting-state functional magnetic resonance imaging (rs-fMRI). This study aims to compare rs-fMRI of depressive disorder (DEP) patients with healthy participants, investigate whether pre-ECT dynamic functional network connectivity network (dFNC) estimated from patients rs-fMRI is associated with an eventual ECT outcome, and explore the effect of ECT on brain network states. Method: Resting-state functional magnetic resonance imaging (fMRI) data were collected from 119 patients with depression or depressive disorder (DEP) (76 females), and 61 healthy (HC) participants (34 females), with an age mean of 52.25 (N = 180) years old. The pre-ECT and post-ECT Hamilton Depression Rating Scale (HDRS) were 25.59 ± 6.14 and 11.48 ± 9.07, respectively. Twenty-four independent components from default mode (DMN) and cognitive control network (CCN) were extracted, using group-independent component analysis from pre-ECT and post-ECT rs-fMRI. Then, the sliding window approach was used to estimate the pre-and post-ECT dFNC of each subject. Next, k-means clustering was separately applied to pre-ECT dFNC and post-ECT dFNC to assess three distinct states from each participant. We calculated the amount of time each subject spends in each state, which is called “occupancy rate” or OCR. Next, we compared OCR values between HC and DEP participants. We also calculated the partial correlation between pre-ECT OCRs and HDRS change while controlling for age, gender, and site. Finally, we evaluated the effectiveness of ECT by comparing pre- and post-ECT OCR of DEP and HC participants. Results: The main findings include (1) depressive disorder (DEP) patients had significantly lower OCR values than the HC group in state 2, where connectivity between cognitive control network (CCN) and default mode network (DMN) was relatively higher than other states (corrected p = 0.015), (2) Pre-ECT OCR of state, with more negative connectivity between CCN and DMN components, is linked with the HDRS changes (R = 0.23 corrected p = 0.03). This means that those DEP patients who spent less time in this state showed more HDRS change, and (3) The post-ECT OCR analysis suggested that ECT increased the amount of time DEP patients spent in state 2 (corrected p = 0.03). Conclusion: Our finding suggests that dynamic functional network connectivity (dFNC) features, estimated from CCN and DMN, show promise as a predictive biomarker of the ECT outcome of DEP patients. Also, this study identifies a possible underlying mechanism associated with the ECT effect on DEP patients.
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Affiliation(s)
- Hossein Dini
- Department of Architecture, Design and Media Technology, Aalborg University, Copenhagen, Denmark
| | - Mohammad S E Sendi
- Wallace H. Coulter Department of Biomedical Engineering at Georgia Institute of Technology and Emory University, Atlanta, GA, United States.,Department of Electrical and Computer Engineering at Georgia Institute of Technology, Atlanta, GA, United States.,Tri-Institutional Center for Translational Research in Neuroimaging and Data Science, Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States
| | - Jing Sui
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science, Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Zening Fu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science, Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States
| | - Randall Espinoza
- Departments of Neurology, Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
| | - Katherine L Narr
- Departments of Neurology, Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
| | - Shile Qi
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science, Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States
| | - Christopher C Abbott
- Department of Psychiatry, University of New Mexico, Albuquerque, NM, United States
| | - Sanne J H van Rooij
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States
| | - Patricio Riva-Posse
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States
| | - Luis Emilio Bruni
- Department of Architecture, Design and Media Technology, Aalborg University, Copenhagen, Denmark
| | - Helen S Mayberg
- Departments of Neurology, Neurosurgery, Psychiatry and Neuroscience, Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Vince D Calhoun
- Wallace H. Coulter Department of Biomedical Engineering at Georgia Institute of Technology and Emory University, Atlanta, GA, United States.,Department of Electrical and Computer Engineering at Georgia Institute of Technology, Atlanta, GA, United States.,Tri-Institutional Center for Translational Research in Neuroimaging and Data Science, Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States
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26
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Taylor M, Hammonds R, Filbey FM. The Relationship Between Behavioral Inhibition and Approach Motivation Systems (BIS/BAS) and Intrinsic Brain Network Connectivity in Adult Cannabis Users. Soc Cogn Affect Neurosci 2021; 16:985-994. [PMID: 34490458 PMCID: PMC8610091 DOI: 10.1093/scan/nsab054] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Revised: 04/16/2021] [Accepted: 05/04/2021] [Indexed: 11/23/2022] Open
Abstract
Dampened behavioral inhibition and overactive behavioral approach motivation systems
(i.e. BIS/BAS) are associated with cannabis use disorder (CUD), although the underlying
neural mechanisms of these alterations have not yet been examined. The brain’s executive
control network (ECN) plays a role in decision-making and is associated with BIS/BAS. In
this study, we tested the hypothesis that altered ECN resting-state functional
connectivity (rsFC) underlies dysfunctional behavioral inhibition and approach motivation
in cannabis users. To that end, we collected resting-state functional magnetic resonance
imaging scans in 86 cannabis using adults and 59 non-using adults to examine group
differences in the relationship between ECN rsFC and BIS/BAS. Our results showed that BIS
was positively correlated with left ECN rsFC in cannabis users, while it was positively
correlated with right ECN rsFC in non-users. There was a trend-level moderation effect of
group on the association between BIS/BAS and ECN rsFC, showing a weaker association in
BIS/BAS and ECN rsFC in cannabis users compared to non-users. An exploratory mediation
analysis found that the severity of CUD mediated the relationship between users’ BIS
scores and left ECN rsFC. These findings suggest that cannabis use may lead to
dysregulation in typical ECN functional organization related to BIS/BAS.
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Affiliation(s)
- M Taylor
- School of Behavioral and Brain Sciences, The University of Texas at Dallas, Center for BrainHealth, 2200 W. Mockingbird Lane, Dallas, TX 75235, USA
| | - R Hammonds
- School of Behavioral and Brain Sciences, The University of Texas at Dallas, Center for BrainHealth, 2200 W. Mockingbird Lane, Dallas, TX 75235, USA
| | - F M Filbey
- School of Behavioral and Brain Sciences, The University of Texas at Dallas, Center for BrainHealth, 2200 W. Mockingbird Lane, Dallas, TX 75235, USA
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Roberts H, Jacobs RH, Bessette KL, Crowell SE, Westlund-Schreiner M, Thomas L, Easter RE, Pocius SL, Dillahunt A, Frandsen S, Schubert B, Farstead B, Kerig P, Welsh RC, Jago D, Langenecker SA, Watkins ER. Mechanisms of rumination change in adolescent depression (RuMeChange): study protocol for a randomised controlled trial of rumination-focused cognitive behavioural therapy to reduce ruminative habit and risk of depressive relapse in high-ruminating adolescents. BMC Psychiatry 2021; 21:206. [PMID: 33892684 PMCID: PMC8062943 DOI: 10.1186/s12888-021-03193-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Accepted: 04/01/2021] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Adolescent-onset depression often results in a chronic and recurrent course, and is associated with worse outcomes relative to adult-onset depression. Targeting habitual depressive rumination, a specific known risk factor for relapse, may improve clinical outcomes for adolescents who have experienced a depressive episode. Randomized controlled trials (RCTs) thus far have demonstrated that rumination-focused cognitive behavioral therapy (RFCBT) reduces depressive symptoms and relapse rates in patients with residual depression and adolescents and young adults with elevated rumination. This was also observed in a pilot RCT of adolescents at risk for depressive relapse. Rumination can be measured at the self-report, behavioral, and neural levels- using patterns of connectivity between the Default Mode Network (DMN) and Cognitive Control Network (CCN). Disrupted connectivity is a putative important mechanism for understanding reduced rumination via RFCBT. A feasibility trial in adolescents found that reductions in connectivity between DMN and CCN regions following RFCBT were correlated with change in rumination and depressive symptoms. METHOD This is a phase III two-arm, two-stage, RCT of depression prevention. The trial tests whether RFCBT reduces identified risk factors for depressive relapse (rumination, patterns of neural connectivity, and depressive symptoms) in adolescents with partially or fully remitted depression and elevated rumination. In the first stage, RFCBT is compared to treatment as usual within the community. In the second stage, the comparator condition is relaxation therapy. Primary outcomes will be (a) reductions in depressive rumination, assessed using the Rumination Response Scale, and (b) reductions in resting state functional magnetic resonance imaging connectivity of DMN (posterior cingulate cortex) to CCN (inferior frontal gyrus), at 16 weeks post-randomization. Secondary outcomes include change in symptoms of depression following treatment, recurrence of depression over 12 months post-intervention period, and whether engagement with therapy homework (as a dose measure) is related to changes in the primary outcomes. DISCUSSION RFCBT will be evaluated as a putative preventive therapy to reduce the risk of depressive relapse in adolescents, and influence the identified self-report, behavioral, and neural mechanisms of change. Understanding mechanisms that underlie change in rumination is necessary to improve and further disseminate preventive interventions. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT03859297 , registered 01 March 2019.
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Affiliation(s)
- Henrietta Roberts
- Mood Disorders Centre, School of Psychology, Sir Henry Wellcome Building for Mood Disorders Research, University of Exeter, Exeter, EX4 4LN, UK
| | | | - Katie L Bessette
- Department of Psychiatry, University of Utah, Salt Lake City, UT, 84108, USA
| | - Sheila E Crowell
- Department of Psychology, University of Utah, Salt Lake City, UT, 84108, USA
| | | | - Leah Thomas
- Department of Psychiatry, University of Utah, Salt Lake City, UT, 84108, USA
| | - Rebecca E Easter
- Department of Psychiatry, University of Utah, Salt Lake City, UT, 84108, USA
| | - Stephanie L Pocius
- Department of Psychiatry, University of Utah, Salt Lake City, UT, 84108, USA
| | - Alina Dillahunt
- Department of Psychiatry, University of Utah, Salt Lake City, UT, 84108, USA
| | - Summer Frandsen
- Department of Psychiatry, University of Utah, Salt Lake City, UT, 84108, USA
| | - Briana Schubert
- Department of Psychiatry, University of Utah, Salt Lake City, UT, 84108, USA
| | - Brian Farstead
- Department of Psychiatry, University of Utah, Salt Lake City, UT, 84108, USA
| | - Patricia Kerig
- Department of Psychology, University of Utah, Salt Lake City, UT, 84108, USA
| | - Robert C Welsh
- Department of Psychiatry, University of Utah, Salt Lake City, UT, 84108, USA
| | - David Jago
- Mood Disorders Centre, School of Psychology, Sir Henry Wellcome Building for Mood Disorders Research, University of Exeter, Exeter, EX4 4LN, UK
| | - Scott A Langenecker
- Department of Psychiatry, University of Utah, Salt Lake City, UT, 84108, USA
| | - Edward R Watkins
- Mood Disorders Centre, School of Psychology, Sir Henry Wellcome Building for Mood Disorders Research, University of Exeter, Exeter, EX4 4LN, UK.
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Lai CH. Fronto-limbic neuroimaging biomarkers for diagnosis and prediction of treatment responses in major depressive disorder. Prog Neuropsychopharmacol Biol Psychiatry 2021; 107:110234. [PMID: 33370569 DOI: 10.1016/j.pnpbp.2020.110234] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 12/02/2020] [Accepted: 12/21/2020] [Indexed: 12/23/2022]
Abstract
The neuroimaging is an important tool for understanding the biomarkers and predicting treatment responses in major depressive disorder (MDD). The potential biomarkers and prediction of treatment response in MDD will be addressed in the review article. The brain regions of cognitive control and emotion regulation, such as the frontal and limbic regions, might represent the potential targets for MDD biomarkers. The potential targets of frontal lobes might include anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC) and orbitofrontal cortex (OFC). For the limbic system, hippocampus and amygdala might be the potentially promising targets for MDD. The potential targets of fronto-limbic regions have been found in the studies of several major neuroimaging modalities, such as the magnetic resonance imaging, near-infrared spectroscopy, electroencephalography, positron emission tomography, and single-photon emission computed tomography. Additional regions, such as brainstem and midbrain, might also play a part in the MDD biomarkers. For the prediction of treatment response, the gray matter volumes, white matter tracts, functional representations and receptor bindings of ACC, DLPFC, OFC, amygdala, and hippocampus might play a role in the prediction of antidepressant responses in MDD. For the response prediction of psychotherapies, the fronto-limbic, reward regions, and insula will be the potential targets. For the repetitive transcranial magnetic stimulation, the DLPFC, ACC, limbic, and visuospatial regions might represent the predictive targets for treatment. The neuroimaging targets of MDD might be focused in the fronto-limbic regions. However, the neuroimaging targets for the prediction of treatment responses might be inconclusive and beyond the fronto-limbic regions.
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Affiliation(s)
- Chien-Han Lai
- Institute of Biophotonics, National Yang-Ming University, Taipei, Taiwan; PhD Psychiatry & Neuroscience Clinic, Taoyuan, Taiwan.
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Robert G, Bannier E, Comte M, Domain L, Corouge I, Dondaine T, Batail JM, Ferre JC, Fakra E, Drapier D. Multimodal brain imaging connectivity analyses of emotional and motivational deficits in depression among women. J Psychiatry Neurosci 2021; 46:E303-E312. [PMID: 33844485 PMCID: PMC8061737 DOI: 10.1503/jpn.200074] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Revised: 07/28/2020] [Accepted: 11/01/2020] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Major depressive disorder (MDD) is characterized by impaired cortical-subcortical functional connectivity. Apathy adds to functional impairment, but its cerebral basis in MDD remains unknown. Our objective was to describe impairments in functional connectivity during emotional processing in MDD (with varying levels of congruency and attention), and to determine their correlation with apathy. METHODS We used the Variable Attention Affective Task during functional MRI, followed by diffusion-weighted MRI, to assess 55 right-handed women (30 with MDD and 25 healthy controls) between September 2012 and February 2015. We estimated functional connectivity using generalized psychophysiologic interaction and anatomic connectivity with tract-based spatial statistics. We measured apathy using the Apathy Evaluation Scale. RESULTS We found decreased functional connectivity between the left amygdala and the left anterior cingulate cortex (ACC) during negative stimuli in participants with MDD (t54 = 4.2; p = 0.035, family-wise error [FWE]-corrected). During high-attention stimuli, participants with MDD showed reduced functional connectivity between the right dorsolateral prefrontal cortex (dlPFC) and the right ACC (t54 = 4.06, pFWE = 0.02), but greater functional connectivity between the right dlPFC and the right amygdala (t54 = 3.35, p = 0.048). Apathy was associated with increased functional connectivity between the right dlPFC and the right ACC during high-attention stimuli (t28 = 5.2, p = 0.01) and increased fractional anisotropy in the right posterior cerebellum, the anterior and posterior cingulum and the bilateral internal capsule (all pFWE < 0.05). LIMITATIONS Limitations included a moderate sample size, concomitant antidepressant therapy and no directed connectivity. CONCLUSION We found that MDD was associated with impairments in cortical-subcortical functional connectivity during negative stimuli that might alter the recruitment of networks engaged in attention. Apathy-related features suggested networks similar to those observed in degenerative disorders, but possible different mechanisms.
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Affiliation(s)
- Gabriel Robert
- From the EA 4712 Comportement et noyaux gris centraux, Université de Rennes 1, France (Robert, Batail, Drapier); the Psychiatry Department, Centre Hospitalier Guillaume Régnier, 108 Boulevard Général Leclerc, 35000, Rennes, France (Robert, Domain, Batail, Drapier); the Radiology Department, CHU Rennes, 2 Rue Henri le Guilloux, 35000 Rennes, France (Bannier, Ferre); the University of Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, Empenn-ERL U 1228, 35000 Rennes, France (Bannier, Corouge, Ferre, Barillot); the Institut de Neurosciences de la Timone, Campus Santé Timone, 27, Bd Jean Moulin 13005 Marseille, France (Comte); the University of Lille & CHU Lille, Inserm, U1171, Degenerative and Vascular Cognitive Disorders, 59000, Lille, France (Dondaine); and the Psychiatry Department, CHU Saint-Etienne, Team PsyR2-Centre de Recherche en Neuroscience de Lyon, (CRNL) CNRS UMR 5292-Inserm U1028, University of Lyon and Saint Etienne, France (Fakra)
| | - Elise Bannier
- From the EA 4712 Comportement et noyaux gris centraux, Université de Rennes 1, France (Robert, Batail, Drapier); the Psychiatry Department, Centre Hospitalier Guillaume Régnier, 108 Boulevard Général Leclerc, 35000, Rennes, France (Robert, Domain, Batail, Drapier); the Radiology Department, CHU Rennes, 2 Rue Henri le Guilloux, 35000 Rennes, France (Bannier, Ferre); the University of Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, Empenn-ERL U 1228, 35000 Rennes, France (Bannier, Corouge, Ferre, Barillot); the Institut de Neurosciences de la Timone, Campus Santé Timone, 27, Bd Jean Moulin 13005 Marseille, France (Comte); the University of Lille & CHU Lille, Inserm, U1171, Degenerative and Vascular Cognitive Disorders, 59000, Lille, France (Dondaine); and the Psychiatry Department, CHU Saint-Etienne, Team PsyR2-Centre de Recherche en Neuroscience de Lyon, (CRNL) CNRS UMR 5292-Inserm U1028, University of Lyon and Saint Etienne, France (Fakra)
| | - Magali Comte
- From the EA 4712 Comportement et noyaux gris centraux, Université de Rennes 1, France (Robert, Batail, Drapier); the Psychiatry Department, Centre Hospitalier Guillaume Régnier, 108 Boulevard Général Leclerc, 35000, Rennes, France (Robert, Domain, Batail, Drapier); the Radiology Department, CHU Rennes, 2 Rue Henri le Guilloux, 35000 Rennes, France (Bannier, Ferre); the University of Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, Empenn-ERL U 1228, 35000 Rennes, France (Bannier, Corouge, Ferre, Barillot); the Institut de Neurosciences de la Timone, Campus Santé Timone, 27, Bd Jean Moulin 13005 Marseille, France (Comte); the University of Lille & CHU Lille, Inserm, U1171, Degenerative and Vascular Cognitive Disorders, 59000, Lille, France (Dondaine); and the Psychiatry Department, CHU Saint-Etienne, Team PsyR2-Centre de Recherche en Neuroscience de Lyon, (CRNL) CNRS UMR 5292-Inserm U1028, University of Lyon and Saint Etienne, France (Fakra)
| | - Lea Domain
- From the EA 4712 Comportement et noyaux gris centraux, Université de Rennes 1, France (Robert, Batail, Drapier); the Psychiatry Department, Centre Hospitalier Guillaume Régnier, 108 Boulevard Général Leclerc, 35000, Rennes, France (Robert, Domain, Batail, Drapier); the Radiology Department, CHU Rennes, 2 Rue Henri le Guilloux, 35000 Rennes, France (Bannier, Ferre); the University of Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, Empenn-ERL U 1228, 35000 Rennes, France (Bannier, Corouge, Ferre, Barillot); the Institut de Neurosciences de la Timone, Campus Santé Timone, 27, Bd Jean Moulin 13005 Marseille, France (Comte); the University of Lille & CHU Lille, Inserm, U1171, Degenerative and Vascular Cognitive Disorders, 59000, Lille, France (Dondaine); and the Psychiatry Department, CHU Saint-Etienne, Team PsyR2-Centre de Recherche en Neuroscience de Lyon, (CRNL) CNRS UMR 5292-Inserm U1028, University of Lyon and Saint Etienne, France (Fakra)
| | - Isabelle Corouge
- From the EA 4712 Comportement et noyaux gris centraux, Université de Rennes 1, France (Robert, Batail, Drapier); the Psychiatry Department, Centre Hospitalier Guillaume Régnier, 108 Boulevard Général Leclerc, 35000, Rennes, France (Robert, Domain, Batail, Drapier); the Radiology Department, CHU Rennes, 2 Rue Henri le Guilloux, 35000 Rennes, France (Bannier, Ferre); the University of Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, Empenn-ERL U 1228, 35000 Rennes, France (Bannier, Corouge, Ferre, Barillot); the Institut de Neurosciences de la Timone, Campus Santé Timone, 27, Bd Jean Moulin 13005 Marseille, France (Comte); the University of Lille & CHU Lille, Inserm, U1171, Degenerative and Vascular Cognitive Disorders, 59000, Lille, France (Dondaine); and the Psychiatry Department, CHU Saint-Etienne, Team PsyR2-Centre de Recherche en Neuroscience de Lyon, (CRNL) CNRS UMR 5292-Inserm U1028, University of Lyon and Saint Etienne, France (Fakra)
| | - Thibaut Dondaine
- From the EA 4712 Comportement et noyaux gris centraux, Université de Rennes 1, France (Robert, Batail, Drapier); the Psychiatry Department, Centre Hospitalier Guillaume Régnier, 108 Boulevard Général Leclerc, 35000, Rennes, France (Robert, Domain, Batail, Drapier); the Radiology Department, CHU Rennes, 2 Rue Henri le Guilloux, 35000 Rennes, France (Bannier, Ferre); the University of Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, Empenn-ERL U 1228, 35000 Rennes, France (Bannier, Corouge, Ferre, Barillot); the Institut de Neurosciences de la Timone, Campus Santé Timone, 27, Bd Jean Moulin 13005 Marseille, France (Comte); the University of Lille & CHU Lille, Inserm, U1171, Degenerative and Vascular Cognitive Disorders, 59000, Lille, France (Dondaine); and the Psychiatry Department, CHU Saint-Etienne, Team PsyR2-Centre de Recherche en Neuroscience de Lyon, (CRNL) CNRS UMR 5292-Inserm U1028, University of Lyon and Saint Etienne, France (Fakra)
| | - Jean-Marie Batail
- From the EA 4712 Comportement et noyaux gris centraux, Université de Rennes 1, France (Robert, Batail, Drapier); the Psychiatry Department, Centre Hospitalier Guillaume Régnier, 108 Boulevard Général Leclerc, 35000, Rennes, France (Robert, Domain, Batail, Drapier); the Radiology Department, CHU Rennes, 2 Rue Henri le Guilloux, 35000 Rennes, France (Bannier, Ferre); the University of Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, Empenn-ERL U 1228, 35000 Rennes, France (Bannier, Corouge, Ferre, Barillot); the Institut de Neurosciences de la Timone, Campus Santé Timone, 27, Bd Jean Moulin 13005 Marseille, France (Comte); the University of Lille & CHU Lille, Inserm, U1171, Degenerative and Vascular Cognitive Disorders, 59000, Lille, France (Dondaine); and the Psychiatry Department, CHU Saint-Etienne, Team PsyR2-Centre de Recherche en Neuroscience de Lyon, (CRNL) CNRS UMR 5292-Inserm U1028, University of Lyon and Saint Etienne, France (Fakra)
| | - Jean-Christophe Ferre
- From the EA 4712 Comportement et noyaux gris centraux, Université de Rennes 1, France (Robert, Batail, Drapier); the Psychiatry Department, Centre Hospitalier Guillaume Régnier, 108 Boulevard Général Leclerc, 35000, Rennes, France (Robert, Domain, Batail, Drapier); the Radiology Department, CHU Rennes, 2 Rue Henri le Guilloux, 35000 Rennes, France (Bannier, Ferre); the University of Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, Empenn-ERL U 1228, 35000 Rennes, France (Bannier, Corouge, Ferre, Barillot); the Institut de Neurosciences de la Timone, Campus Santé Timone, 27, Bd Jean Moulin 13005 Marseille, France (Comte); the University of Lille & CHU Lille, Inserm, U1171, Degenerative and Vascular Cognitive Disorders, 59000, Lille, France (Dondaine); and the Psychiatry Department, CHU Saint-Etienne, Team PsyR2-Centre de Recherche en Neuroscience de Lyon, (CRNL) CNRS UMR 5292-Inserm U1028, University of Lyon and Saint Etienne, France (Fakra)
| | - Eric Fakra
- From the EA 4712 Comportement et noyaux gris centraux, Université de Rennes 1, France (Robert, Batail, Drapier); the Psychiatry Department, Centre Hospitalier Guillaume Régnier, 108 Boulevard Général Leclerc, 35000, Rennes, France (Robert, Domain, Batail, Drapier); the Radiology Department, CHU Rennes, 2 Rue Henri le Guilloux, 35000 Rennes, France (Bannier, Ferre); the University of Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, Empenn-ERL U 1228, 35000 Rennes, France (Bannier, Corouge, Ferre, Barillot); the Institut de Neurosciences de la Timone, Campus Santé Timone, 27, Bd Jean Moulin 13005 Marseille, France (Comte); the University of Lille & CHU Lille, Inserm, U1171, Degenerative and Vascular Cognitive Disorders, 59000, Lille, France (Dondaine); and the Psychiatry Department, CHU Saint-Etienne, Team PsyR2-Centre de Recherche en Neuroscience de Lyon, (CRNL) CNRS UMR 5292-Inserm U1028, University of Lyon and Saint Etienne, France (Fakra)
| | - Dominique Drapier
- From the EA 4712 Comportement et noyaux gris centraux, Université de Rennes 1, France (Robert, Batail, Drapier); the Psychiatry Department, Centre Hospitalier Guillaume Régnier, 108 Boulevard Général Leclerc, 35000, Rennes, France (Robert, Domain, Batail, Drapier); the Radiology Department, CHU Rennes, 2 Rue Henri le Guilloux, 35000 Rennes, France (Bannier, Ferre); the University of Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, Empenn-ERL U 1228, 35000 Rennes, France (Bannier, Corouge, Ferre, Barillot); the Institut de Neurosciences de la Timone, Campus Santé Timone, 27, Bd Jean Moulin 13005 Marseille, France (Comte); the University of Lille & CHU Lille, Inserm, U1171, Degenerative and Vascular Cognitive Disorders, 59000, Lille, France (Dondaine); and the Psychiatry Department, CHU Saint-Etienne, Team PsyR2-Centre de Recherche en Neuroscience de Lyon, (CRNL) CNRS UMR 5292-Inserm U1028, University of Lyon and Saint Etienne, France (Fakra)
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Brain Networks Connectivity in Mild to Moderate Depression: Resting State fMRI Study with Implications to Nonpharmacological Treatment. Neural Plast 2021; 2021:8846097. [PMID: 33510782 PMCID: PMC7822653 DOI: 10.1155/2021/8846097] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2020] [Revised: 12/04/2020] [Accepted: 12/21/2020] [Indexed: 12/27/2022] Open
Abstract
Network mechanisms of depression development and especially of improvement from nonpharmacological treatment remain understudied. The current study is aimed at examining brain networks functional connectivity in depressed patients and its dynamics in nonpharmacological treatment. Resting state fMRI data of 21 healthy adults and 51 patients with mild or moderate depression were analyzed with spatial independent component analysis; then, correlations between time series of the components were calculated and compared between-group (study 1). Baseline and repeated-measure data of 14 treated (psychotherapy or fMRI neurofeedback) and 15 untreated depressed participants were similarly analyzed and correlated with changes in depression scores (study 2). Aside from diverse findings, studies 1 and 2 both revealed changes in within-default mode network (DMN) and DMN to executive control network (ECN) connections. Connectivity in one pair, initially lower in depression, decreased in no treatment group and was inversely correlated with Montgomery-Asberg depression score change in treatment group. Weak baseline connectivity in this pair also predicted improvement on Montgomery-Asberg scale in both treatment and no treatment groups. Coupling of another pair, initially stronger in depression, increased in therapy though was unrelated to improvement. The results demonstrate possible role of within-DMN and DMN-ECN functional connectivity in depression treatment and suggest that neural mechanisms of nonpharmacological treatment action may be unrelated to normalization of initially disrupted connectivity.
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Liu G, Jiao K, Zhong Y, Hao Z, Wang C, Xu H, Teng C, Song X, Xiao C, Fox PT, Zhang N, Wang C. The alteration of cognitive function networks in remitted patients with major depressive disorder: an independent component analysis. Behav Brain Res 2020; 400:113018. [PMID: 33301816 DOI: 10.1016/j.bbr.2020.113018] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2020] [Revised: 07/22/2020] [Accepted: 11/11/2020] [Indexed: 02/08/2023]
Abstract
INTRODUCTION Dysfunctional connectivity of resting-state functional networks has been observed in patients with major depressive disorder (MDD), particularly in cognitive function networks including the central executive network (CEN), default mode network (DMN) and salience network (SN). Findings from studies examining how aberrant functional connectivity (FC) changed after antidepressant treatment, however, have been inconsistent. Thus, the purpose of the present study was to explore potential mechanisms of altered cognitive function networks during resting-state between remitted major depressive disorder (rMDD) patients and healthy controls (HCs) and furthermore, the relationship between dysfunctional connectivity patterns in rMDD and clinical symptoms. METHODOLOGY In this study, 19 HCs and 19 rMDD patients were recruited for resting-state functional magnetic resonance imaging (fMRI) scanning. FC was evaluated with independent component analysis for CEN, DMN and SN. Two sample t tests were conducted to compare differences between rMDD and HCs. A Pearson correlation analysis was also performed to examine the relationship between connectivity of networks and cognitive function scores and clinical symptoms. RESULTS Compared to healthy controls, remitted patients showed lower connectivity in CEN, mostly in the superior frontal gyrus (SFG), middle frontal gyrus (MFG), inferior parietal lobule (IPL) and part of the supramarginal gyrus (SMG). Conversely, the bilateral insula, part of the SMG (a key node of the CEN) and dorsal anterior cingulate cortex (dACC) of the DMN showed higher connectivity in rMDD patients. Pearson correlation results demonstrated that connectivity of the right IPL in CEN was positively correlated with cognitive function scores, and connectivity of the left insula was negatively correlated with BDI scores. CONCLUSIONS Though rMDD patients reached the standard of clinal remission, unique impairments of FC in cognitive function networks remained. Aberrant FC between cognitive function networks responsible for executive control was observed in rMDD and may be associated with residual clinical symptoms.
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Affiliation(s)
- Gang Liu
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China
| | - Kaili Jiao
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, Jiangsu, China; Cognitive Behavioral Therapy Institute of Nanjing Medical University, Nanjing, Jiangsu, China; Zhengzhou Ninth People's Hospital, Zhengzhou, China
| | - Yuan Zhong
- School of Psychology, Nanjing Normal University, Nanjing, Jiangsu, China; Jiangsu Key Laboratory of Mental Health and Cognitive Science, Nanjing Normal University, Nanjing 210097, China
| | - Ziyu Hao
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China; School of Psychology, Nanjing Normal University, Nanjing, Jiangsu, China
| | - Chiyue Wang
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China
| | - Huazhen Xu
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China
| | - Changjun Teng
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, Jiangsu, China; Cognitive Behavioral Therapy Institute of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xiu Song
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, Jiangsu, China; Cognitive Behavioral Therapy Institute of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Chaoyong Xiao
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China
| | - Peter T Fox
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, Jiangsu, China; South Texas Veterans Healthcare System, University of Texas Health San Antonio, United States; Research Imaging Institute, University of Texas Health San Antonio, United States
| | - Ning Zhang
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, Jiangsu, China; Cognitive Behavioral Therapy Institute of Nanjing Medical University, Nanjing, Jiangsu, China.
| | - Chun Wang
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, Jiangsu, China; Cognitive Behavioral Therapy Institute of Nanjing Medical University, Nanjing, Jiangsu, China; School of Psychology, Nanjing Normal University, Nanjing, Jiangsu, China.
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Bessette KL, Karstens AJ, Crane NA, Peters AT, Stange JP, Elverman KH, Morimoto SS, Weisenbach SL, Langenecker SA. A Lifespan Model of Interference Resolution and Inhibitory Control: Risk for Depression and Changes with Illness Progression. Neuropsychol Rev 2020; 30:477-498. [PMID: 31942706 PMCID: PMC7363517 DOI: 10.1007/s11065-019-09424-5] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2018] [Accepted: 12/06/2019] [Indexed: 12/20/2022]
Abstract
The cognitive processes involved in inhibitory control accuracy (IC) and interference resolution speed (IR) or broadly - inhibition - are discussed in this review, and both are described within the context of a lifespan model of mood disorders. Inhibitory control (IC) is a binary outcome (success or no for response selection and inhibition of unwanted responses) for any given event that is influenced to an extent by IR. IR refers to the process of inhibition, which can be manipulated by task design in earlier and later stages through use of distractors and timing, and manipulation of individual differences in response proclivity. We describe the development of these two processes across the lifespan, noting factors that influence this development (e.g., environment, adversity and stress) as well as inherent difficulties in assessing IC/IR prior to adulthood (e.g., cross-informant reports). We use mood disorders as an illustrative example of how this multidimensional construct can be informative to state, trait, vulnerability and neuroprogression of disease. We present aggregated data across numerous studies and methodologies to examine the lifelong development and degradation of this subconstruct of executive function, particularly in mood disorders. We highlight the challenges in identifying and measuring IC/IR in late life, including specificity to complex, comorbid disease processes. Finally, we discuss some potential avenues for treatment and accommodation of these difficulties across the lifespan, including newer treatments using cognitive remediation training and neuromodulation.
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Affiliation(s)
- Katie L Bessette
- Departments of Psychiatry and Psychology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Psychiatry, University of Utah, 501 Chipeta Way, Salt Lake City, UT, 84108, USA
| | - Aimee J Karstens
- Departments of Psychiatry and Psychology, University of Illinois at Chicago, Chicago, IL, USA
| | - Natania A Crane
- Departments of Psychiatry and Psychology, University of Illinois at Chicago, Chicago, IL, USA
| | - Amy T Peters
- Department of Psychiatry, Massachusetts General Hospital, 55 Fruit Street, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, 25 Shattuck St, Boston, MA, 02115, USA
| | - Jonathan P Stange
- Departments of Psychiatry and Psychology, University of Illinois at Chicago, Chicago, IL, USA
| | - Kathleen H Elverman
- Neuropsychology Center, Aurora St. Luke's Medical Center, Milwaukee, WI, USA
| | - Sarah Shizuko Morimoto
- Department of Psychiatry, University of Utah, 501 Chipeta Way, Salt Lake City, UT, 84108, USA
| | - Sara L Weisenbach
- Department of Psychiatry, University of Utah, 501 Chipeta Way, Salt Lake City, UT, 84108, USA
- Mental Health Services, VA Salt Lake City, Salt Lake City, UT, USA
| | - Scott A Langenecker
- Departments of Psychiatry and Psychology, University of Illinois at Chicago, Chicago, IL, USA.
- Department of Psychiatry, University of Utah, 501 Chipeta Way, Salt Lake City, UT, 84108, USA.
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Stange JP, Jenkins LM, Pocius S, Kreutzer K, Bessette KL, DelDonno SR, Kling LR, Bhaumik R, Welsh RC, Keilp JG, Phan KL, Langenecker SA. Using resting-state intrinsic network connectivity to identify suicide risk in mood disorders. Psychol Med 2020; 50:2324-2334. [PMID: 31597581 PMCID: PMC7368462 DOI: 10.1017/s0033291719002356] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
BACKGROUND Little is known about the neural substrates of suicide risk in mood disorders. Improving the identification of biomarkers of suicide risk, as indicated by a history of suicide-related behavior (SB), could lead to more targeted treatments to reduce risk. METHODS Participants were 18 young adults with a mood disorder with a history of SB (as indicated by endorsing a past suicide attempt), 60 with a mood disorder with a history of suicidal ideation (SI) but not SB, 52 with a mood disorder with no history of SI or SB (MD), and 82 healthy comparison participants (HC). Resting-state functional connectivity within and between intrinsic neural networks, including cognitive control network (CCN), salience and emotion network (SEN), and default mode network (DMN), was compared between groups. RESULTS Several fronto-parietal regions (k > 57, p < 0.005) were identified in which individuals with SB demonstrated distinct patterns of connectivity within (in the CCN) and across networks (CCN-SEN and CCN-DMN). Connectivity with some of these same regions also distinguished the SB group when participants were re-scanned after 1-4 months. Extracted data defined SB group membership with good accuracy, sensitivity, and specificity (79-88%). CONCLUSIONS These results suggest that individuals with a history of SB in the context of mood disorders may show reliably distinct patterns of intrinsic network connectivity, even when compared to those with mood disorders without SB. Resting-state fMRI is a promising tool for identifying subtypes of patients with mood disorders who may be at risk for suicidal behavior.
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Affiliation(s)
| | | | | | | | | | | | | | - Runa Bhaumik
- University of Illinois at Chicago, Chicago, IL, USA
| | | | | | - K. Luan Phan
- University of Illinois at Chicago, Chicago, IL, USA
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Cerebellar-cerebral dynamic functional connectivity alterations in major depressive disorder. J Affect Disord 2020; 275:319-328. [PMID: 32734925 DOI: 10.1016/j.jad.2020.06.062] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Revised: 05/14/2020] [Accepted: 06/14/2020] [Indexed: 12/20/2022]
Abstract
BACKGROUND The cerebellum plays an important role in the neural mechanism of depression and its static functional connectivity (FC) with the cerebrum is disrupted in patients with major depressive disorder (MDD). However, cerebellar-cerebral dynamic FC alterations in MDD remain largely unknown. METHODS 50 patients with MDD and 36 well-matched healthy controls underwent resting-state functional magnetic resonance imaging. Cerebellar-cerebral dynamic FC analyses were performed using the cerebellar seeds previously identified as being involved in the executive, default-mode, affective-limbic, and motor networks. Inter-group differences in the cerebellar dynamic FC and their associations with clinical and cognitive variables were examined. RESULTS Compared to healthy controls, patients with MDD had decreased cerebellar-cerebral dynamic FC of the cerebellar subregions connecting with the executive, default-mode and affective-limbic networks. The dynamic FC of the cerebellar subregion connecting with the affective-limbic network was related to severity of depression and anxiety symptoms in MDD patients. The dynamic FC of the cerebellar subregions connecting with the default-mode and affective-limbic networks were related to sustained attention and prospective memory in controls, while the correlations were inverse or non-significant in patients. LIMITATIONS The fairly modest sample size and potential medication effect may increase the instability of the results. CONCLUSIONS Our findings provide further evidence for the pivotal role of the cerebellum in the neuropathology of depression, pointing to potential targets of cerebellar-cerebral pathways for alternative intervention or monitoring therapeutic responses.
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Impact of depression on cooperation: An fNIRS hyperscanning study. ACTA PSYCHOLOGICA SINICA 2020. [DOI: 10.3724/sp.j.1041.2020.00609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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36
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Reflecting on rumination: Consequences, causes, mechanisms and treatment of rumination. Behav Res Ther 2020; 127:103573. [DOI: 10.1016/j.brat.2020.103573] [Citation(s) in RCA: 129] [Impact Index Per Article: 32.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Revised: 11/23/2019] [Accepted: 01/24/2020] [Indexed: 12/11/2022]
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37
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Vega JN, Taylor WD, Gandelman JA, Boyd BD, Newhouse PA, Shokouhi S, Albert KM. Persistent Intrinsic Functional Network Connectivity Alterations in Middle-Aged and Older Women With Remitted Depression. Front Psychiatry 2020; 11:62. [PMID: 32153440 PMCID: PMC7047962 DOI: 10.3389/fpsyt.2020.00062] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Accepted: 01/24/2020] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND In younger adults, residual alterations in functional neural networks persist during remitted depression. However, there are fewer data for midlife and older adults at risk of recurrence. Such residual network alterations may contribute to vulnerability to recurrence. This study examined intrinsic network functional connectivity in midlife and older women with remitted depression. METHODS A total of 69 women (24 with a history of depression, 45 with no psychiatric history) over 50 years of age completed 3T fMRI with resting-state acquisition. Participants with remitted depression met DSM-IV-TR criteria for an episode in the last 10 years but not the prior year. Whole-brain seed-to-voxel resting-state functional connectivity analyses examined the default mode network (DMN), executive control network (ECN), and salience network (SN), plus bilateral hippocampal seeds. All analyses were adjusted for age and used cluster-level correction for multiple comparisons with FDR < 0.05 and a height threshold of p < 0.001, uncorrected. RESULTS Women with a history of depression exhibited decreased functional connectivity between the SN (right insula seed) and ECN regions, specifically the left superior frontal gyrus. They also exhibited increased functional connectivity between the left hippocampus and the left postcentral gyrus. We did not observe any group differences in functional connectivity for DMN or ECN seeds. CONCLUSIONS Remitted depression in women is associated with connectivity differences between the SN and ECN and between the hippocampus and the postcentral gyrus, a region involved in interoception. Further work is needed to determine whether these findings are related to functional alterations or are predictive of recurrence.
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Affiliation(s)
- Jennifer N Vega
- Center for Cognitive Medicine, Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Warren D Taylor
- Center for Cognitive Medicine, Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, United States.,Geriatric Research, Education, and Clinical Center, Veterans Affairs Tennessee Valley Health System, Nashville, TN, United States
| | - Jason A Gandelman
- Vanderbilt University School of Medicine, Nashville, TN, United States
| | - Brian D Boyd
- Center for Cognitive Medicine, Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Paul A Newhouse
- Center for Cognitive Medicine, Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, United States.,Geriatric Research, Education, and Clinical Center, Veterans Affairs Tennessee Valley Health System, Nashville, TN, United States
| | - Sepideh Shokouhi
- Center for Cognitive Medicine, Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Kimberly M Albert
- Center for Cognitive Medicine, Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
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Andreescu C, Ajilore O, Aizenstein HJ, Albert K, Butters MA, Landman BA, Karim HT, Krafty R, Taylor WD. Disruption of Neural Homeostasis as a Model of Relapse and Recurrence in Late-Life Depression. Am J Geriatr Psychiatry 2019; 27:1316-1330. [PMID: 31477459 PMCID: PMC6842700 DOI: 10.1016/j.jagp.2019.07.016] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Revised: 06/26/2019] [Accepted: 07/29/2019] [Indexed: 12/29/2022]
Abstract
The significant public health burden associated with late-life depression (LLD) is magnified by the high rates of recurrence. In this manuscript, we review what is known about recurrence risk factors, conceptualize recurrence within a model of homeostatic disequilibrium, and discuss the potential significance and challenges of new research into LLD recurrence. The proposed model is anchored in the allostatic load theory of stress. We review the allostatic response characterized by neural changes in network function and connectivity and physiologic changes in the hypothalamic-pituitary-adrenal axis, autonomic nervous system, immune system, and circadian rhythm. We discuss the role of neural networks' instability following treatment response as a source of downstream disequilibrium, triggering and/or amplifying abnormal stress response, cognitive dysfunction and behavioral changes, ultimately precipitating a full-blown recurrent episode of depression. We propose strategies to identify and capture early change points that signal recurrence risk through mobile technology to collect ecologically measured symptoms, accompanied by automated algorithms that monitor for state shifts (persistent worsening) and variance shifts (increased variability) relative to a patient's baseline. Identifying such change points in relevant sensor data could potentially provide an automated tool that could alert clinicians to at-risk individuals or relevant symptom changes even in a large practice.
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Affiliation(s)
| | | | - Howard J. Aizenstein
- Department of Psychiatry, University of Pittsburgh,Department of Bioengineering, University of Pittsburgh
| | - Kimberly Albert
- The Center for Cognitive Medicine, the Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center
| | | | - Bennett A. Landman
- Departments of Computer Science, Electrical Engineering, and Biomedical Engineering, Vanderbilt University; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center
| | | | - Robert Krafty
- Department of Biostatistics, University of Pittsburgh
| | - Warren D. Taylor
- The Center for Cognitive Medicine, the Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center,Geriatric Research, Education and Clinical Center, Department of Veterans Affairs Medical Center, Tennessee Valley Healthcare System
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Jiao K, Xu H, Teng C, Song X, Xiao C, Fox PT, Zhang N, Wang C, Zhong Y. Connectivity patterns of cognitive control network in first episode medication-naive depression and remitted depression. Behav Brain Res 2019; 379:112381. [PMID: 31770543 DOI: 10.1016/j.bbr.2019.112381] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2018] [Revised: 11/19/2019] [Accepted: 11/22/2019] [Indexed: 01/19/2023]
Abstract
BACKGROUND Cognitive dysfunctions, such as impaired cognitive control, are frequently observed in patients with major depressive disorder (MDD). Although the cognitive control network (CCN) is widely considered a core feature of major depressive disorder (MDD), the relationship between cognitive dysfunction and symptom dimensions remains unclear. This study investigated differences in resting-state functional connectivity of the cognitive control network (CCN) between first-episode medication-naive MDD patients and remitted MDD. METHODS We collected resting-state functional MRI (rs-fMRI) data from 22 first-episode medication-naive major depressive disorder (fMDD) patients, 20 patients previously diagnosed with MDD in the remitted phase of depression (rMDD), and 20 healthy controls (HC). The CCN was derived from fMRI images using independent component analysis (ICA), a data-driven image analysis method. RESULTS Changes in functional connectivity (FC) within the CCN was mainly attenuated in the right dorsolateral prefrontal cortex and the left inferior parietal lobule, while strengthened in the right dorsal anterior cingulate cortex and the right insula in both fMDD and rMDD groups. Compared with the fMDD group, the rMDD group had decreased FC in the bilateral insula and the right dorsolateral prefrontal cortex. Further analysis explored that the FC in the bilateral insula, the right dorsal anterior cingulate cortex and the right inferior parietal lobule were correlated positively cognitive disturbance factor scores in both patients groups. CONCLUSIONS These findings are in agreement with the previous findings that the cognitive control network are impaired in MDD. Furthermore, our results suggest that the alteration of CCN might underpin the cognitive disturbance and the distinct patterns of the CCN between fMDD and rMDD patients may be an important target for effective cognitive remediation in MDD.
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Affiliation(s)
- Kaili Jiao
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China; Cognitive Behavioral Therapy Institute of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Huazhen Xu
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China; Cognitive Behavioral Therapy Institute of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Changjun Teng
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China; Cognitive Behavioral Therapy Institute of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xiu Song
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China; Cognitive Behavioral Therapy Institute of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Chaoyong Xiao
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China
| | - Peter T Fox
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, Jiangsu, China; South Texas Veterans Healthcare System, University of Texas Health Science Center at San Antonio, United States; Research Imaging Institute, University of Texas Health San Antonio, United States
| | - Ning Zhang
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China; Cognitive Behavioral Therapy Institute of Nanjing Medical University, Nanjing, Jiangsu, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Chun Wang
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China; Cognitive Behavioral Therapy Institute of Nanjing Medical University, Nanjing, Jiangsu, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, Jiangsu, China; School of Psychology, Nanjing Normal University, Nanjing, China.
| | - Yuan Zhong
- School of Psychology, Nanjing Normal University, Nanjing, China; Jiangsu Key Laboratory of Mental Health and Cognitive Science, Nanjing Normal University, Nanjing, China.
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Abstract
The neuroimaging has been applied in the study of pathophysiology in major depressive disorder (MDD). In this review article, several kinds of methodologies of neuroimaging would be discussed to summarize the promising biomarkers in MDD. For the magnetic resonance imaging (MRI) and magnetoencephalography field, the literature review showed the potentially promising roles of frontal lobes, such as anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC) and orbitofrontal cortex (OFC). In addition, the limbic regions, such as hippocampus and amygdala, might be the potentially promising biomarkers for MDD. The structures and functions of ACC, DLPFC, OFC, amygdala and hippocampus might be confirmed as the biomarkers for the prediction of antidepressant treatment responses and for the pathophysiology of MDD. The functions of cognitive control and emotion regulation of these regions might be crucial for the establishment of biomarkers. The near-infrared spectroscopy studies demonstrated that blood flow in the frontal lobe, such as the DLPFC and OFC, might be the biomarkers for the field of near-infrared spectroscopy. The electroencephalography also supported the promising role of frontal regions, such as the ACC, DLPFC and OFC in the biomarker exploration, especially for the sleep electroencephalogram to detect biomarkers in MDD. The positron emission tomography (PET) and single-photon emission computed tomography (SPECT) in MDD demonstrated the promising biomarkers for the frontal and limbic regions, such as ACC, DLPFC and amygdala. However, additional findings in brainstem and midbrain were also found in PET and SPECT. The promising neuroimaging biomarkers of MDD seemed focused in the fronto-limbic regions.
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Affiliation(s)
- Chien-Han Lai
- Institute of Biophotonics, National Yang-Ming University, Taipei, Taiwan.,Psychiatry & Neuroscience Clinic, Taoyuan, Taiwan.,Department of Psychiatry, Yeezen General Hospital, Taoyuan, Taiwan
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41
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Altered dynamic functional connectivity in weakly-connected state in major depressive disorder. Clin Neurophysiol 2019; 130:2096-2104. [PMID: 31541987 DOI: 10.1016/j.clinph.2019.08.009] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2019] [Revised: 05/27/2019] [Accepted: 08/14/2019] [Indexed: 12/11/2022]
Abstract
OBJECTIVE Major depressive disorder (MDD) is accompanied by abnormal changes in dynamic functional connectivity (FC) among brain regions. The aim of this study is to investigate whether the abnormalities of dynamic FC in MDD are state-dependent (related to a specific connectivity state). METHODS We performed time-varying connectivity analysis on resting-state functional magnetic resonance imaging (rs-fMRI) of 49 MDD patients and 54 matched healthy controls (HCs). FC differences between groups in each connectivity state were analyzed and associations between disease severity and dynamics of aberrant FC were explored. RESULTS Two distinct connectivity states (i.e., weakly-connected and strongly-connected state) were identified. Compared to HCs, MDD patients were associated with increased mean dwell time and decreased FC between and within subnetworks in the weakly-connected state. Dynamics of reduced FC between cognitive control network and default mode network as well as within cognitive control network predicted individual differences in depression symptom severity. CONCLUSIONS Our findings suggested that the MDD-caused FC alterations mostly appeared in the weakly-connected state, which might contribute to clinical diagnosis of MDD. SIGNIFICANCE These findings provide new perspectives for understanding the state-dependent neurophysiological mechanisms in MDD.
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42
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Stange JP, Jenkins LM, Bessette KL, Kling LR, Bark JS, Shepard R, Hamlat EJ, DelDonno S, Phan KL, Passarotti AM, Ajilore O, Langenecker SA. Predictors of Attrition in Longitudinal Neuroimaging Research: Inhibitory Control, Head Movement, and Resting-State Functional Connectivity. Brain Connect 2019; 8:527-536. [PMID: 30411975 DOI: 10.1089/brain.2018.0619] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Attrition is a major problem in longitudinal neuroimaging studies, as it may lead to unreliable estimates of the stability of trait-like processes over time, of the identification of risk factors for clinical outcomes, and of the effects of treatment. Identification of characteristics associated with attrition has implications for participant recruitment and participant retention to achieve representative longitudinal samples. We investigated inhibitory control deficits, head motion, and resting-state functional connectivity within the cognitive control network (CCN) as predictors of attrition. Ninety-seven individuals with remitted major depressive disorder or healthy controls completed a functional magnetic resonance imaging scan, which included a go/no-go task and resting-state functional connectivity. Approximately 2 months later, participants were contacted and invited to return for a second scan. Seventeen individuals were lost to follow-up or declined to participate in the follow-up scan. Worse inhibitory control was correlated with greater movement within the scanner, and each predicted a greater likelihood of attrition, with movement mediating the effects of inhibitory control on attrition. Individuals who dropped out of the study exhibited greater movement than nondropouts across 9 of the 14 runs of the scan, with medium-to-large effect sizes. Finally, exploratory analyses suggested that attenuated resting-state connectivity with the CCN (particularly in bilateral dorsolateral prefrontal cortex) was associated with greater likelihood of attrition after accounting for head motion at several levels of analysis. Inhibitory control and movement within the scanner are associated with attrition, and should be considered for strategic oversampling and participant retention strategies to ensure generalizability of results in longitudinal studies.
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Affiliation(s)
- Jonathan P Stange
- 1 Department of Psychiatry, University of Illinois at Chicago , Chicago, Illinois
| | | | - Katie L Bessette
- 1 Department of Psychiatry, University of Illinois at Chicago , Chicago, Illinois
| | - Leah R Kling
- 1 Department of Psychiatry, University of Illinois at Chicago , Chicago, Illinois
| | - John S Bark
- 1 Department of Psychiatry, University of Illinois at Chicago , Chicago, Illinois
| | - Robert Shepard
- 1 Department of Psychiatry, University of Illinois at Chicago , Chicago, Illinois
| | - Elissa J Hamlat
- 3 University of Illinois Urbana-Champaign , Urbana, Illinois
| | - Sophie DelDonno
- 1 Department of Psychiatry, University of Illinois at Chicago , Chicago, Illinois
| | - K Luan Phan
- 1 Department of Psychiatry, University of Illinois at Chicago , Chicago, Illinois
| | | | - Olusola Ajilore
- 1 Department of Psychiatry, University of Illinois at Chicago , Chicago, Illinois
| | - Scott A Langenecker
- 1 Department of Psychiatry, University of Illinois at Chicago , Chicago, Illinois
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Abstract
The anatomical structure of the human brain varies widely, as does individual cognitive behavior. It is important and interesting to study the relationship between brain structure and cognitive behavior. There has however been little previous work on the relationship between inhibitory control and brain structure. The goal of this study was to elucidate possible cortical markers related to inhibitory control using structural magnetic resonance imaging (sMRI) data. In this study, we analyzed sMRI data and inhibitory control behavior measurement values from 361 healthy adults from the Human Connectome Project (HCP). The data of all participants were divided into two datasets. In the first dataset, we first constructed individual brain morphometric similarity networks by calculating the inter-regional statistical similarity relationship of nine cortical characteristic measures (such as volume) for each brain area obtained from sMRI data. Areas that covary in their morphology are termed 'connected'. After that, we used a brain connectome-based predictive model (CPM) to search for 'connected' brain areas that were significantly related to inhibitory control. This is a purely data-driven method with built-in cross-validation. Two different 'connected' patterns were observed for high and low inhibitory control networks. The high inhibitory control network comprised 25 'connections' (edges between nodes), mostly involving nodes in the prefrontal and especially orbitofrontal cortex and inferior frontal gyrus. In the low inhibitory control network, nodes were scattered between parietal, occipital and limbic areas. Furthermore, these 'connections' were verified as reliable and generalizable in a cross-validation dataset. Two regions of interest, the right ventromedial prefrontal cortex including a part of medial area 10 (R.OFCmed) and left middle temporal gyrus (L.MTG) were crucial nodes in the two networks, respectively, which suggests that these two regions may be fundamentally involved in inhibitory control. Our findings potentially help to understand the relationship between areas with a correlated cortical structure and inhibitory control, and further help to reveal the brain systems related to inhibition and its disorders.
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He Y, Lim S, Fortunato S, Sporns O, Zhang L, Qiu J, Xie P, Zuo XN. Reconfiguration of Cortical Networks in MDD Uncovered by Multiscale Community Detection with fMRI. Cereb Cortex 2019; 28:1383-1395. [PMID: 29300840 PMCID: PMC6093364 DOI: 10.1093/cercor/bhx335] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2017] [Accepted: 11/30/2017] [Indexed: 02/06/2023] Open
Abstract
Major depressive disorder (MDD) is known to be associated with altered interactions between distributed brain regions. How these regional changes relate to the reorganization of cortical functional systems, and their modulation by antidepressant medication, is relatively unexplored. To identify changes in the community structure of cortical functional networks in MDD, we performed a multiscale community detection algorithm on resting-state functional connectivity networks of unmedicated MDD (uMDD) patients (n = 46), medicated MDD (mMDD) patients (n = 38), and healthy controls (n = 50), which yielded a spectrum of multiscale community partitions. we selected an optimal resolution level by identifying the most stable community partition for each group. uMDD and mMDD groups exhibited a similar reconfiguration of the community structure of the visual association and the default mode systems but showed different reconfiguration profiles in the frontoparietal control (FPC) subsystems. Furthermore, the central system (somatomotor/salience) and 3 frontoparietal subsystems showed strengthened connectivity with other communities in uMDD but, with the exception of 1 frontoparietal subsystem, returned to control levels in mMDD. These findings provide evidence for reconfiguration of specific cortical functional systems associated with MDD, as well as potential effects of medication in restoring disease-related network alterations, especially those of the FPC system.
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Affiliation(s)
- Ye He
- Department of Psychological and Brain Sciences, Indiana University Bloomington, Bloomington, IN 47405, USA
| | - Sol Lim
- Department of Psychological and Brain Sciences, Indiana University Bloomington, Bloomington, IN 47405, USA
| | - Santo Fortunato
- School of Informatics and Computing, Indiana University Bloomington, IN 47405, USA.,Indiana University Network Science Institute, Indiana University Bloomington, IN 47408, USA
| | - Olaf Sporns
- Department of Psychological and Brain Sciences, Indiana University Bloomington, Bloomington, IN 47405, USA.,Indiana University Network Science Institute, Indiana University Bloomington, IN 47408, USA
| | - Lei Zhang
- Department of Psychology, University of Chinese Academy of Sciences (CAS), Beijing 100049, China.,Key Laboratory for Brain and Education Sciences, Guangxi Teachers Education University, Nanning, Guangxi 530001, China
| | - Jiang Qiu
- Faculty of psychology, Southwest University, Chongqing 400715, China
| | - Peng Xie
- Institute of Neuroscience, Chongqing Medical University, Chongqing 400016, China.,Chongqing Key Laboratory of Neurobiology, Chongqing 400016, China.,Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Xi-Nian Zuo
- Department of Psychology, University of Chinese Academy of Sciences (CAS), Beijing 100049, China.,Key Laboratory for Brain and Education Sciences, Guangxi Teachers Education University, Nanning, Guangxi 530001, China.,CAS Key Laboratory of Behavioral Science and Research Center for Lifespan Development of Mind and Brain, Institute of Psychology, Beijing 100101, China
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Dong D, Li C, Ming Q, Zhong X, Zhang X, Sun X, Jiang Y, Gao Y, Wang X, Yao S. Topologically state-independent and dependent functional connectivity patterns in current and remitted depression. J Affect Disord 2019; 250:178-185. [PMID: 30856495 DOI: 10.1016/j.jad.2019.03.030] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Revised: 02/23/2019] [Accepted: 03/04/2019] [Indexed: 11/25/2022]
Abstract
OBJECTIVE Identification of state-independent and -dependent neural biomarkers may provide insight into the pathophysiology and effective treatment of major depressive disorder (MDD), therefore we aimed to investigate the state-independent and -dependent topological alterations of MDD. METHOD Brain resting-state functional magnetic resonance imaging (fMRI) data were acquired from 59 patients with unmedicated first episode current MDD (cMDD), 48 patients with remitted MDD (rMDD) and 60 demographically matched healthy controls (HCs). Using graph theory, we systematically studied the topological organization of their whole-brain functional networks at the global and nodal level. RESULTS At a global level, both patient groups showed decreased normalized clustering coefficient in relative to HCs. On a nodal level, both patient groups showed decreased nodal centrality, predominantly in cortex-mood-regulation brain regions including the dorsolateral prefrontal cortex, posterior parietal cortex and posterior cingulate cortex. By comparison to cMDD patients, rMDD group had a higher nodal centrality in right parahippocampal gyrus. LIMITATIONS The present study, an exploratory analysis, may require further confirmation with task-based and experimental studies. CONCLUSIONS Deficits in the topological organization of the whole brain and cortex-mood-regulation brain regions in both rMDD and cMDD represent state-independent biomarkers.
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Affiliation(s)
- Daifeng Dong
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; Medical Psychological Institute of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Chuting Li
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; Medical Psychological Institute of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Qingsen Ming
- Department of Psychiatry, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, PR China
| | - Xue Zhong
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; Medical Psychological Institute of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Xiaocui Zhang
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; Medical Psychological Institute of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Xiaoqiang Sun
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; Medical Psychological Institute of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Yali Jiang
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; Medical Psychological Institute of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Yidian Gao
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; Medical Psychological Institute of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Xiang Wang
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; Medical Psychological Institute of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Shuqiao Yao
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; Medical Psychological Institute of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, Hunan, PR China.
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46
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Langenecker SA, Klumpp H, Peters AT, Crane NA, DelDonno SR, Bessette KL, Ajilore O, Leow A, Shankman SA, Walker SJ, Ransom MT, Hsu DT, Phan KL, Zubieta JK, Mickey BJ, Stange JP. Multidimensional imaging techniques for prediction of treatment response in major depressive disorder. Prog Neuropsychopharmacol Biol Psychiatry 2019; 91:38-48. [PMID: 30009871 PMCID: PMC6556149 DOI: 10.1016/j.pnpbp.2018.07.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2018] [Revised: 05/31/2018] [Accepted: 07/03/2018] [Indexed: 12/21/2022]
Abstract
A large number of studies have attempted to use neuroimaging tools to aid in treatment prediction models for major depressive disorder (MDD). Most such studies have reported on only one dimension of function and prediction at a time. In this study, we used three different tasks across domains of function (emotion processing, reward anticipation, and cognitive control, plus resting state connectivity completed prior to start of medication to predict treatment response in 13-36 adults with MDD. For each experiment, adults with MDD were prescribed only label duloxetine (all experiments), whereas another subset were prescribed escitalopram. We used a KeyNet (both Task derived masks and Key intrinsic Network derived masks) approach to targeting brain systems in a specific match to tasks. The most robust predictors were (Dichter et al., 2010) positive response to anger and (Gong et al., 2011) negative response to fear within relevant anger and fear TaskNets and Salience and Emotion KeyNet (Langenecker et al., 2018) cognitive control (correct rejections) within Inhibition TaskNet (negative) and Cognitive Control KeyNet (positive). Resting state analyses were most robust for Cognitive control Network (positive) and Salience and Emotion Network (negative). Results differed by whether an -fwhm or -acf (more conservative) adjustment for multiple comparisons was used. Together, these results implicate the importance of future studies with larger sample sizes, multidimensional predictive models, and the importance of using empirically derived masks for search areas.
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Affiliation(s)
| | - Heide Klumpp
- University of Illinois at Chicago,University of Michigan
| | | | | | | | | | | | | | | | - Sara J. Walker
- University of Michigan,University of Oregon Health Sciences
| | | | | | - K. Luan Phan
- University of Illinois at Chicago,University of Michigan
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47
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Quinn ME, Stange JP, Jenkins LM, Corwin S, DelDonno SR, Bessette KL, Welsh RC, Langenecker SA. Cognitive control and network disruption in remitted depression: a correlate of childhood adversity. Soc Cogn Affect Neurosci 2019; 13:1081-1090. [PMID: 30285231 PMCID: PMC6204481 DOI: 10.1093/scan/nsy077] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2017] [Accepted: 09/04/2018] [Indexed: 12/20/2022] Open
Abstract
Individuals in a major depressive episode often display impairment in cognitive control, and this impairment exists outside of the acute phase of illness. Impairment in cognitive control also has been associated with exposure to childhood adversity (CA). The current study examined whether exposure to CA can explain variance in a component of cognitive control—inhibitory control—independent of diagnostic status in young adults with and without a history of depression. Healthy control individuals (n = 40) and individuals with remitted major depressive disorder (n = 53) completed a task measuring inhibitory control, reported level of CA and completed a scanning session to assess gray matter volume and resting state connectivity in regions associated with cognitive control. The results demonstrate that higher levels of CA were associated with poorer inhibitory control, reduced right middle frontal gyrus gray matter, decreased connectivity of salience and emotion networks and increased connectivity in cognitive control networks, even after controlling for diagnostic status, residual depression symptoms and current stressors. Together, the results suggest that inhibitory control impairment and intrinsic connectivity changes may be characterized as developmental sequelae of early stress exposure.
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Affiliation(s)
- Meghan E Quinn
- Department of Psychology and Human Development, Vanderbilt University, Nashville, TN, USA
| | - Jonathan P Stange
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA
| | | | - Samantha Corwin
- Department of Psychology, University of Illinois at Chicago, Chicago, IL, USA
| | - Sophie R DelDonno
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA.,Department of Psychology, University of Illinois at Chicago, Chicago, IL, USA
| | - Katie L Bessette
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA.,Department of Psychology, University of Illinois at Chicago, Chicago, IL, USA
| | | | - Scott A Langenecker
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA
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48
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Langenecker SA, Mickey BJ, Eichhammer P, Sen S, Elverman KH, Kennedy SE, Heitzeg MM, Ribeiro SM, Love TM, Hsu DT, Koeppe RA, Watson SJ, Akil H, Goldman D, Burmeister M, Zubieta JK. Cognitive Control as a 5-HT 1A-Based Domain That Is Disrupted in Major Depressive Disorder. Front Psychol 2019; 10:691. [PMID: 30984083 PMCID: PMC6450211 DOI: 10.3389/fpsyg.2019.00691] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2018] [Accepted: 03/12/2019] [Indexed: 12/21/2022] Open
Abstract
Heterogeneity within Major Depressive Disorder (MDD) has hampered identification of biological markers (e.g., intermediate phenotypes, IPs) that might increase risk for the disorder or reflect closer links to the genes underlying the disease process. The newer characterizations of dimensions of MDD within Research Domain Criteria (RDoC) domains may align well with the goal of defining IPs. We compare a sample of 25 individuals with MDD compared to 29 age and education matched controls in multimodal assessment. The multimodal RDoC assessment included the primary IP biomarker, positron emission tomography (PET) with a selective radiotracer for 5-HT1A [(11C)WAY-100635], as well as event-related functional MRI with a Go/No-go task targeting the Cognitive Control network, neuropsychological assessment of affective perception, negative memory bias and Cognitive Control domains. There was also an exploratory genetic analysis with the serotonin transporter (5-HTTLPR) and monamine oxidase A (MAO-A) genes. In regression analyses, lower 5-HT1A binding potential (BP) in the MDD group was related to diminished engagement of the Cognitive Control network, slowed resolution of interfering cognitive stimuli, one element of Cognitive Control. In contrast, higher/normative levels of 5-HT1A BP in MDD (only) was related to a substantial memory bias toward negative information, but intact resolution of interfering cognitive stimuli and greater engagement of Cognitive Control circuitry. The serotonin transporter risk allele was associated with lower 1a BP and the corresponding imaging and cognitive IPs in MDD. Lowered 5HT 1a BP was present in half of the MDD group relative to the control group. Lowered 5HT 1a BP may represent a subtype including decreased engagement of Cognitive Control network and impaired resolution of interfering cognitive stimuli. Future investigations might link lowered 1a BP to neurobiological pathways and markers, as well as probing subtype-specific treatment targets.
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Affiliation(s)
- Scott A. Langenecker
- The Molecular & Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, MI, United States
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, United States
| | - Brian J. Mickey
- The Molecular & Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, MI, United States
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, United States
| | - Peter Eichhammer
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, United States
| | - Srijan Sen
- The Molecular & Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, MI, United States
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, United States
| | | | - Susan E. Kennedy
- The Molecular & Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, MI, United States
| | - Mary M. Heitzeg
- The Molecular & Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, MI, United States
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, United States
| | - Saulo M. Ribeiro
- The Molecular & Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, MI, United States
| | - Tiffany M. Love
- The Molecular & Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, MI, United States
| | - David T. Hsu
- The Molecular & Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, MI, United States
| | - Robert A. Koeppe
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, United States
| | - Stanley J. Watson
- The Molecular & Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, MI, United States
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, United States
| | - Huda Akil
- The Molecular & Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, MI, United States
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, United States
| | - David Goldman
- National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, United States
| | - Margit Burmeister
- The Molecular & Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, MI, United States
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, United States
| | - Jon-Kar Zubieta
- The Molecular & Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, MI, United States
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, United States
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49
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Dong D, Ming Q, Zhong X, Pu W, Zhang X, Jiang Y, Gao Y, Sun X, Wang X, Yao S. State-independent alterations of intrinsic brain network in current and remitted depression. Prog Neuropsychopharmacol Biol Psychiatry 2019; 89:475-480. [PMID: 30193990 DOI: 10.1016/j.pnpbp.2018.08.031] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2018] [Revised: 08/15/2018] [Accepted: 08/29/2018] [Indexed: 01/30/2023]
Abstract
BACKGROUND It has been proposed that state-independent, or trait, neurobiological alterations across illness phases may contribute to the high recurrence of major depressive disorder (MDD). Although intrinsic brain network abnormalities have been implicated consistently in MDD neuropathology, MDD state-independent and -dependent resting-state network alterations have not been clearly studied. METHODS Resting-state functional magnetic resonance imaging (fMRI) data were collected from 57 medication-naive first-episode current MDD patients, 35 remitted MDD patients, and 66 healthy controls (HCs). Independent component analysis (ICA) was used to extract subnetworks of the default mode network (DMN), central executive network (CEN), and salience network (SN). RESULTS Relative to HCs, the current MDD and remitted MDD groups had decreased intra-intrinsic functional connectivity (iFC) in the dorsal lateral prefrontal cortex (dlPFC) of the left CEN, increased inter-FC between the SN and right CEN (rCEN), and decreased inter-FC between the anterior DMN (aDMN) and rCEN. The altered intra-iFC in the left CEN were correlated negatively with the depressive level in the remitted MDD. CONCLUSIONS Hypoactivity of the dlPFC in the left CEN, increased inter-FC between the SN and rCEN, and decreased inter-FC between the aDMN and rCEN may reflect state-independent biomarkers of MDD.
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Affiliation(s)
- Daifeng Dong
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; Medical Psychological Institute of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Qingsen Ming
- Dpartment of Psychiatry, The First Affiliated Hospital of Sochoow University, Suzhou, Jiangsu, PR China
| | - Xue Zhong
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; Medical Psychological Institute of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Weidan Pu
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; Medical Psychological Institute of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Xiaocui Zhang
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; Medical Psychological Institute of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Yali Jiang
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; Medical Psychological Institute of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Yidian Gao
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; Medical Psychological Institute of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Xiaoqiang Sun
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; Medical Psychological Institute of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Xiang Wang
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; Medical Psychological Institute of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Shuqiao Yao
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; Medical Psychological Institute of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, Hunan, PR China.
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50
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Burkhouse KL, Stange JP, Jacobs RH, Bhaumik R, Bessette KL, Peters AT, Crane NA, Kreutzer KA, Fitzgerald K, Monk C, Welsh RC, Phan KL, Langenecker SA. Developmental changes in resting-state functional networks among individuals with and without internalizing psychopathologies. Depress Anxiety 2019; 36:141-152. [PMID: 30516853 PMCID: PMC6519436 DOI: 10.1002/da.22864] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2018] [Revised: 10/31/2018] [Accepted: 11/06/2018] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Three well-established intrinsic connectivity networks (ICNs) involved in cognitive-affective processing include the cognitive control network (CCN), default mode network (DMN), and salience and emotional network (SEN). Despite recent advances in understanding developmental changes in these ICNs, the majority of research has focused on single seeds or networks in isolation with limited age ranges. Additionally, although internalizing psychopathologies (IPs), such as anxiety and depression, are often characterized by maladaptive cognitive-affective processing styles, it is not clear how IP history influences age-related changes in brain networks. METHOD The current study aimed to characterize the normative development of the CCN, DMN, and SEN across a large age-span (7-29 year olds) of typically developing (TD) individuals (n = 97). We also explore how age may impact differences in network connectivity between TD individuals and patients with IPs (n = 136). RESULTS Among TD individuals, DMN and CCN connectivity strengthened with age, whereas connectivity between the SEN and ventromedial prefrontal cortex weakened across development. When exploring group (IP vs. TD) differences, the IP group was characterized by greater connectivity between the CCN and cerebellum and between the SEN and caudate from childhood to early adulthood, relative to TD individuals. In addition, patients with IPs, versus TD individuals, exhibited reduced connectivity between the SEN and medial frontal gyrus from adolescence to adulthood. CONCLUSIONS The current findings shed light on differential age-related changes in brain network patterns among psychiatrically free, TD individuals and those with internalizing disorders, and may provide plausible targets for novel mechanism-based treatments that differ based on developmental stage.
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Affiliation(s)
| | | | | | - Runa Bhaumik
- University of Illinois-Chicago; Department of Psychiatry
| | - Katie L. Bessette
- University of Illinois-Chicago; Department of Psychiatry
- University of Illinois-Chicago; Department of Psychology
| | - Amy T. Peters
- University of Illinois-Chicago; Department of Psychiatry
- University of Illinois-Chicago; Department of Psychology
| | | | | | | | | | - Robert C. Welsh
- The University of Utah Medical Center, Department of Psychiatry
| | - K. Luan Phan
- University of Illinois-Chicago; Department of Psychiatry
- University of Illinois-Chicago; Department of Psychology
- Jesse Brown VA Medical Center; Mental Health Service Line
- University of Illinois-Chicago; Department of Anatomy and Cell Biology & the Graduate Program in Neuroscience
| | - Scott A. Langenecker
- University of Illinois-Chicago; Department of Psychiatry
- University of Illinois-Chicago; Department of Psychology
- The University of Utah Medical Center, Department of Psychiatry
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