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Bore MC, Liu X, Huang X, Kendrick KM, Zhou B, Zhang J, Klugah-Brown B, Becker B. Common and separable neural alterations in adult and adolescent depression - Evidence from neuroimaging meta-analyses. Neurosci Biobehav Rev 2024; 164:105835. [PMID: 39084585 DOI: 10.1016/j.neubiorev.2024.105835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Revised: 07/25/2024] [Accepted: 07/28/2024] [Indexed: 08/02/2024]
Abstract
Depression is a highly prevalent and debilitating mental disorder that often begins in adolescence. However, it remains unclear whether adults and adolescents with depression exhibit common or distinct brain dysfunctions during reward processing. We aimed to identify common and separable neurofunctional alterations during receipt of rewards and brain structure in adolescents and adults with depression. A coordinate-based meta-analysis was employed using Seed-based d mapping with permutation of subject images (SDM-PSI). Compared with healthy controls, both age groups exhibited common activity decreases in the right striatum (putamen, caudate) and subgenual ACC. Adults with depression showed decreased reactivity in the right putamen and subgenual ACC, while adolescents with depression showed decreased activity in the left mid cingulate, right caudate but increased reactivity in the right postcentral gyrus. This meta-analysis revealed shared (caudate) and separable (putamen and mid cingulate cortex) reward-related alterations in adults and adolescents with depression. The findings suggest age-specific neurofunctional alterations and stress the importance of adolescent-specific interventions that target social functions.
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Affiliation(s)
- Mercy Chepngetich Bore
- Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China; MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Xiqin Liu
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular lmaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Xiaoqi Huang
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular lmaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China; The Xiaman Key Lab of Psychoradiology and Neuromodulation, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China
| | - Keith M Kendrick
- Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China; MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Bo Zhou
- Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China; MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Jie Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Benjamin Klugah-Brown
- Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China; MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
| | - Benjamin Becker
- Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China; MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China; Department of Psychology, The University of Hong Kong, Hong Kong, China.
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2
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Amemori S, Graybiel AM, Amemori KI. Cingulate microstimulation induces negative decision-making via reduced top-down influence on primate fronto-cingulo-striatal network. Nat Commun 2024; 15:4201. [PMID: 38760337 PMCID: PMC11101474 DOI: 10.1038/s41467-024-48375-1] [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: 09/04/2023] [Accepted: 04/26/2024] [Indexed: 05/19/2024] Open
Abstract
The dorsolateral prefrontal cortex (dlPFC) is crucial for regulation of emotion that is known to aid prevention of depression. The broader fronto-cingulo-striatal (FCS) network, including cognitive dlPFC and limbic cingulo-striatal regions, has been associated with a negative evaluation bias often seen in depression. The mechanism by which dlPFC regulates the limbic system remains largely unclear. Here we have successfully induced a negative bias in decision-making in female primates performing a conflict decision-making task, by directly microstimulating the subgenual cingulate cortex while simultaneously recording FCS local field potentials (LFPs). The artificially induced negative bias in decision-making was associated with a significant decrease in functional connectivity from cognitive to limbic FCS regions, represented by a reduction in Granger causality in beta-range LFPs from the dlPFC to the other regions. The loss of top-down directional influence from cognitive to limbic regions, we suggest, could underlie negative biases in decision-making as observed in depressive states.
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Affiliation(s)
- Satoko Amemori
- Institute for the Advanced Study of Human Biology (ASHBi), Kyoto University, Kyoto, Japan
- Japan Society for the Promotion of Science, Tokyo, Japan
| | - Ann M Graybiel
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ken-Ichi Amemori
- Institute for the Advanced Study of Human Biology (ASHBi), Kyoto University, Kyoto, Japan.
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Liu N, Sun H, Yang C, Li X, Gao Z, Gong Q, Zhang W, Lui S. The difference in volumetric alternations of the orbitofrontal-limbic-striatal system between major depressive disorder and anxiety disorders: A systematic review and voxel-based meta-analysis. J Affect Disord 2024; 350:65-77. [PMID: 38199394 DOI: 10.1016/j.jad.2024.01.043] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 12/12/2023] [Accepted: 01/03/2024] [Indexed: 01/12/2024]
Abstract
BACKGROUND Major depressive disorder (MDD) and anxiety disorders (ANX) are psychiatric disorders with high mutual comorbidity rates that might indicate some shared neurobiological pathways between them, but they retain diverse phenotypes that characterize themselves specifically. However, no consistent evidence exists for common and disorder-specific gray matter volume (GMV) alternations between them. METHODS A systematic review and meta-analysis on voxel-based morphometry studies of patients with MDD and ANX were performed. The effect of comorbidity was explicitly controlled during disorder-specific analysis and particularly investigated in patient with comorbidity. RESULTS A total of 45 studies with 54 datasets comprising 2196 patients and 2055 healthy participants met the inclusion criteria. Deficits in the orbitofrontal cortex, striatum, and limbic regions were found in MDD and ANX. The disorder-specific analyses showed decreased GMV in the bilateral anterior cingulate cortex, right striatum, hippocampus, and cerebellum in MDD, while decreased GMV in the left striatum, amygdala, insula, and increased cerebellar volume in ANX. A totally different GMV alternation pattern was shown involving bilateral temporal and parietal gyri and left fusiform gyrus in patients with comorbidity. LIMITATIONS Owing to the design of included studies, only partial patients in the comorbid group had a secondary comorbidity diagnosis. CONCLUSION Patients with MDD and ANX shared a structural disruption in the orbitofrontal-limbic-striatal system. The disorder-specific effects manifested their greatest severity in distinct lateralization and directionality of these changes that differentiate MDD from ANX. The comorbid group showed a totally different GMV alternation pattern, possibly suggesting another illness subtype that requires further investigation.
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Affiliation(s)
- Naici Liu
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China; Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Hui Sun
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China; Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Chengmin Yang
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China; Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Xing Li
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China; Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Ziyang Gao
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China; Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Qiyong Gong
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China; Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China; Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China
| | - Wenjing Zhang
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China; Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.
| | - Su Lui
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China; Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.
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Zhang J, Wu X, Si Y, Liu Y, Wang X, Geng Y, Chang Q, Jiang X, Zhang H. Abnormal caudate nucleus activity in patients with depressive disorder: Meta-analysis of task-based functional magnetic resonance imaging studies with behavioral domain. Psychiatry Res Neuroimaging 2024; 338:111769. [PMID: 38141592 DOI: 10.1016/j.pscychresns.2023.111769] [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: 11/30/2022] [Revised: 11/17/2023] [Accepted: 11/26/2023] [Indexed: 12/25/2023]
Abstract
During task-based functional magnetic resonance imaging (t-fMRI) patients with depressive disorder (DD) have shown abnormal caudate nucleus activation. There have been no meta-analyses that are conducted on the caudate nucleus using Activation Likelihood Estimation (ALE) in patients with DD, and the relationships between abnormal caudate activity and different behavior domains in patients with DD remain unclear. There were 24 previously published t-fMRI studies included in the study with the caudate nucleus as the region of interest. Meta-analyses were performed using the method of ALE. Included five ALE meta-analyses: (1) the hypoactivated caudate nucleus relative to healthy controls (HCs); (2) the hyper-activated caudate nucleus; (3) the abnormal activation in the caudate nucleus in the emotion domain; (4) the abnormal activation in cognition domain; (5) the abnormal activation in the affective cognition domain. Results revealed that the hypo-/hyper-activity in the caudate subregions is mainly located in the caudate body and head, while the relationships between abnormal caudate subregions and different behavior domains are complex. The hypoactivation of the caudate body and head plays a key role in the emotions which indicates there is a positive relationship between the decreased caudate activity and depressed emotional behaviors in patients with DD.
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Affiliation(s)
- Jiajia Zhang
- Department of Psychology, Xinxiang Medical University, Henan 453003, PR China; Xinxiang Key Laboratory of Psychopathology and Cognitive Neuroscience, Xinxiang, 453003, PR China; Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan 453002, PR China
| | - Xin Wu
- Department of Psychology, Xinxiang Medical University, Henan 453003, PR China; Xinxiang Key Laboratory of Psychopathology and Cognitive Neuroscience, Xinxiang, 453003, PR China
| | - Yajing Si
- Department of Psychology, Xinxiang Medical University, Henan 453003, PR China; Xinxiang Key Laboratory of Psychopathology and Cognitive Neuroscience, Xinxiang, 453003, PR China
| | - Yahui Liu
- Department of Psychology, Xinxiang Medical University, Henan 453003, PR China; Xinxiang Key Laboratory of Psychopathology and Cognitive Neuroscience, Xinxiang, 453003, PR China
| | - Xueke Wang
- Department of Psychology, Xinxiang Medical University, Henan 453003, PR China; Xinxiang Key Laboratory of Psychopathology and Cognitive Neuroscience, Xinxiang, 453003, PR China; Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan 453002, PR China
| | - Yibo Geng
- Department of Radiology, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, PR China
| | - Qiaohua Chang
- Department of Nursing, Xinxiang Medical University, Henan 453003, PR China
| | - Xiaoxiao Jiang
- Department of Nursing, Xinxiang Medical University, Henan 453003, PR China
| | - Hongxing Zhang
- Department of Psychology, Xinxiang Medical University, Henan 453003, PR China; Xinxiang Key Laboratory of Psychopathology and Cognitive Neuroscience, Xinxiang, 453003, PR China; Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan 453002, PR China.
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Liu X, Wang Z, Liu S, Gong L, Sosa PAV, Becker B, Jung TP, Dai XJ, Wan F. Activation network improves spatiotemporal modelling of human brain communication processes. Neuroimage 2024; 285:120472. [PMID: 38007187 DOI: 10.1016/j.neuroimage.2023.120472] [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: 06/28/2023] [Revised: 11/08/2023] [Accepted: 11/22/2023] [Indexed: 11/27/2023] Open
Abstract
Dynamic functional networks (DFN) have considerably advanced modelling of the brain communication processes. The prevailing implementation capitalizes on the system and network-level correlations between time series. However, this approach does not account for the continuous impact of non-dynamic dependencies within the statistical correlation, resulting in relatively stable connectivity patterns of DFN over time with limited sensitivity for communication dynamic between brain regions. Here, we propose an activation network framework based on the activity of functional connectivity (AFC) to extract new types of connectivity patterns during brain communication process. The AFC captures potential time-specific fluctuations associated with the brain communication processes by eliminating the non-dynamic dependency of the statistical correlation. In a simulation study, the positive correlation (r=0.966,p<0.001) between the extracted dynamic dependencies and the simulated "ground truth" validates the method's dynamic detection capability. Applying to autism spectrum disorders (ASD) and COVID-19 datasets, the proposed activation network extracts richer topological reorganization information, which is largely invisible to the DFN. Detailed, the activation network exhibits significant inter-regional connections between function-specific subnetworks and reconfigures more efficiently in the temporal dimension. Furthermore, the DFN fails to distinguish between patients and healthy controls. However, the proposed method reveals a significant decrease (p<0.05) in brain information processing abilities in patients. Finally, combining two types of networks successfully classifies ASD (83.636 % ± 11.969 %,mean±std) and COVID-19 (67.333 % ± 5.398 %). These findings suggest the proposed method could be a potential analytic framework for elucidating the neural mechanism of brain dynamics.
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Affiliation(s)
- Xucheng Liu
- Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau 999078, China; Centre for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Macau, 999078, China
| | - Ze Wang
- Macao Centre for Mathematical Sciences, and the Respiratory Disease AI Laboratory on Epidemic Intelligence and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau, 999078, China
| | - Shun Liu
- Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau 999078, China; Centre for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Macau, 999078, China
| | - Lianggeng Gong
- Department of Radiology, The Second Affiliated Hospital of Nanchang University, Nanchang, 330006, China
| | - Pedro A Valdes Sosa
- The Clinical Hospital of Chengdu Brain Sciences Institute. University of Electronic Sciences and Technology of China, Chengdu, 611731, China; Cuban Neuroscience Center, La Habana 10200, Cuba
| | - Benjamin Becker
- State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong 999077, China; Department of Psychology, The University of Hong Kong, Hong Kong 999077, China
| | - Tzyy-Ping Jung
- Department of Bioengineering, University of California at San Diego, La Jolla 92092, United States; Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California at San Diego, La Jolla 92093, United States
| | - Xi-Jian Dai
- Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau 999078, China; Centre for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Macau, 999078, China; Department of Radiology, The Second Affiliated Hospital of Nanchang University, Nanchang, 330006, China.
| | - Feng Wan
- Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau 999078, China; Centre for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Macau, 999078, China.
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Fan H, Liu Z, Wu X, Yu G, Gu X, Kuang N, Zhang K, Liu Y, Jia T, Sahakian BJ, Robbins TW, Schumann G, Cheng W, Feng J, Becker B, Zhang J. Decoding anxiety-impulsivity subtypes in preadolescent internalising disorders: findings from the Adolescent Brain Cognitive Development study. Br J Psychiatry 2023; 223:542-554. [PMID: 37730654 DOI: 10.1192/bjp.2023.107] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
BACKGROUND Internalising disorders are highly prevalent emotional dysregulations during preadolescence but clinical decision-making is hampered by high heterogeneity. During this period impulsivity represents a major risk factor for psychopathological trajectories and may act on this heterogeneity given the controversial anxiety-impulsivity relationships. However, how impulsivity contributes to the heterogeneous symptomatology, neurobiology, neurocognition and clinical trajectories in preadolescent internalising disorders remains unclear. AIMS The aim was to determine impulsivity-dependent subtypes in preadolescent internalising disorders that demonstrate distinct anxiety-impulsivity relationships, neurobiological, genetic, cognitive and clinical trajectory signatures. METHOD We applied a data-driven strategy to determine impulsivity-related subtypes in 2430 preadolescents with internalising disorders from the Adolescent Brain Cognitive Development study. Cross-sectional and longitudinal analyses were employed to examine subtype-specific signatures of the anxiety-impulsivity relationship, brain morphology, cognition and clinical trajectory from age 10 to 12 years. RESULTS We identified two distinct subtypes of patients who internalise with comparably high anxiety yet distinguishable levels of impulsivity, i.e. enhanced (subtype 1) or decreased (subtype 2) compared with control participants. The two subtypes exhibited opposing anxiety-impulsivity relationships: higher anxiety at baseline was associated with higher lack of perseverance in subtype 1 but lower sensation seeking in subtype 2 at baseline/follow-up. Subtype 1 demonstrated thicker prefrontal and temporal cortices, and genes enriched in immune-related diseases and glutamatergic and GABAergic neurons. Subtype 1 exhibited cognitive deficits and a detrimental trajectory characterised by increasing emotional/behavioural dysregulations and suicide risks during follow-up. CONCLUSIONS Our results indicate impulsivity-dependent subtypes in preadolescent internalising disorders and unify past controversies about the anxiety-impulsivity interaction. Clinically, individuals with a high-impulsivity subtype exhibit a detrimental trajectory, thus early interventions are warranted.
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Affiliation(s)
- Huaxin Fan
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, China and Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Zhaowen Liu
- School of Computer Science, Northwestern Polytechnical University, China
| | - Xinran Wu
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, China and Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Gechang Yu
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Xinrui Gu
- Sino-European School of Technology, Shanghai University, China
| | - Nanyu Kuang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, China and Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Kai Zhang
- School of Computer Science and Technology, East China Normal University, Shanghai, China
| | - Yu Liu
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, China and Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Tianye Jia
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, China and Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Barbara J Sahakian
- Behavioural and Clinical Neuroscience Institute, University of Cambridge, UK and Department of Psychiatry, University of Cambridge School of Clinical Medicine, UK
| | - Trevor W Robbins
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, China; Behavioural and Clinical Neuroscience Institute, University of Cambridge, UK and Department of Psychology, University of Cambridge, UK
| | - Gunter Schumann
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, China and PONS-Center, Department of Psychiatry and Psychotherapy, Charité Campus Mitte, Charité Universitätsmedizin Berlin, Germany
| | - Wei Cheng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China; Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, China and Shanghai Medical College and Zhongshan Hospital Immunotherapy Technology Transfer Center, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, China and Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Benjamin Becker
- State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China; Department of Psychology, The University of Hong Kong, Hong Kong, China
| | - Jie Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, China and Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
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Liu Y, Zhao X, Hu W, Ren Y, Wei Z, Ren X, Tang Z, Wang N, Chen H, Li Y, Shi Z, Qin S, Yang J. Neural habituation during acute stress signals a blunted endocrine response and poor resilience. Psychol Med 2023; 53:7735-7745. [PMID: 37309913 DOI: 10.1017/s0033291723001666] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
BACKGROUND A blunted hypothalamic-pituitary-adrenal (HPA) axis response to acute stress is associated with psychiatric symptoms. Although the prefrontal cortex and limbic areas are important regulators of the HPA axis, whether the neural habituation of these regions during stress signals both blunted HPA axis responses and psychiatric symptoms remains unclear. In this study, neural habituation during acute stress and its associations with the stress cortisol response, resilience, and depression were evaluated. METHODS Seventy-seven participants (17-22 years old, 37 women) were recruited for a ScanSTRESS brain imaging study, and the activation changes between the first and last stress blocks were used as the neural habituation index. Meanwhile, participants' salivary cortisol during test was collected. Individual-level resilience and depression were measured using questionnaires. Correlation and moderation analyses were conducted to investigate the association between neural habituation and endocrine data and mental symptoms. Validated analyses were conducted using a Montreal Image Stress Test dataset in another independent sample (48 participants; 17-22 years old, 24 women). RESULTS Neural habituation of the prefrontal cortex and limbic area was negatively correlated with cortisol responses in both datasets. In the ScanSTRESS paradigm, neural habituation was both positively correlated with depression and negatively correlated with resilience. Moreover, resilience moderated the relationship between neural habituation in the ventromedial prefrontal cortex and cortisol response. CONCLUSIONS This study suggested that neural habituation of the prefrontal cortex and limbic area could reflect motivation dysregulation during repeated failures and negative feedback, which might further lead to maladaptive mental states.
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Affiliation(s)
- Yadong Liu
- Faculty of Psychology, Southwest University, Chongqing 400715, China
- Key Laboratory of Cognition and Personality, Ministry of Education, Southwest University, Chongqing 400715, China
| | - Xiaolin Zhao
- Faculty of Psychology, Southwest University, Chongqing 400715, China
- Key Laboratory of Cognition and Personality, Ministry of Education, Southwest University, Chongqing 400715, China
| | - Weiyu Hu
- Faculty of Psychology, Southwest University, Chongqing 400715, China
- Key Laboratory of Cognition and Personality, Ministry of Education, Southwest University, Chongqing 400715, China
| | - Yipeng Ren
- Faculty of Psychology, Southwest University, Chongqing 400715, China
- Key Laboratory of Cognition and Personality, Ministry of Education, Southwest University, Chongqing 400715, China
| | - Zhenni Wei
- Faculty of Psychology, Southwest University, Chongqing 400715, China
- Key Laboratory of Cognition and Personality, Ministry of Education, Southwest University, Chongqing 400715, China
| | - Xi Ren
- Faculty of Psychology, Southwest University, Chongqing 400715, China
- Key Laboratory of Cognition and Personality, Ministry of Education, Southwest University, Chongqing 400715, China
| | - Zihan Tang
- Faculty of Psychology, Southwest University, Chongqing 400715, China
- Key Laboratory of Cognition and Personality, Ministry of Education, Southwest University, Chongqing 400715, China
| | - Nan Wang
- Faculty of Psychology, Southwest University, Chongqing 400715, China
- Key Laboratory of Cognition and Personality, Ministry of Education, Southwest University, Chongqing 400715, China
| | - Haopeng Chen
- Faculty of Psychology, Southwest University, Chongqing 400715, China
- Key Laboratory of Cognition and Personality, Ministry of Education, Southwest University, Chongqing 400715, China
| | - Yizhuo Li
- Faculty of Psychology, Southwest University, Chongqing 400715, China
- Key Laboratory of Cognition and Personality, Ministry of Education, Southwest University, Chongqing 400715, China
| | - Zhenhao Shi
- Center for Studies of Addiction, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Shaozheng Qin
- State Key Laboratory of Cognitive Neuroscience and Learning, McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Juan Yang
- Faculty of Psychology, Southwest University, Chongqing 400715, China
- Key Laboratory of Cognition and Personality, Ministry of Education, Southwest University, Chongqing 400715, China
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Liu Q, Zhou B, Zhang X, Qing P, Zhou X, Zhou F, Xu X, Zhu S, Dai J, Huang Y, Wang J, Zou Z, Kendrick KM, Becker B, Zhao W. Abnormal multi-layered dynamic cortico-subcortical functional connectivity in major depressive disorder and generalized anxiety disorder. J Psychiatr Res 2023; 167:23-31. [PMID: 37820447 DOI: 10.1016/j.jpsychires.2023.10.004] [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: 05/23/2023] [Revised: 08/16/2023] [Accepted: 10/05/2023] [Indexed: 10/13/2023]
Abstract
Comorbidity has been frequently observed between generalized anxiety disorder (GAD) and major depressive disorder (MDD), however, common and distinguishable alterations in the topological organization of functional brain networks remain poorly understood. We sought to determine a robust and sensitive functional connectivity marker for diagnostic classification and symptom severity prediction. Multi-layered dynamic functional connectivity including whole brain, network-node and node-node layers via graph theory and gradient analyses were applied to functional MRI resting-state data obtained from 31 unmedicated GAD and 34 unmedicated MDD patients as well as 33 age and education matched healthy controls (HC). GAD and MDD symptoms were assessed using Penn State Worry Questionnaire and Beck Depression Inventory II, respectively. Three network measures including global properties (i.e., global efficiency, characteristic path length), regional nodal property (i.e., degree) and connectivity gradients were computed. Results showed that both patient groups exhibited abnormal dynamic cortico-subcortical topological organization compared to healthy controls, with MDD > GAD > HC in degree of randomization. Furthermore, our multi-layered dynamic functional connectivity network model reached 77% diagnostic accuracy between GAD and MDD and was highly predictive of symptom severity, respectively. Gradients of functional connectivity for superior frontal cortex-subcortical regions, middle temporal gyrus-subcortical regions and amygdala-cortical regions contributed more in this model compared to other gradients. We found shared and distinct cortico-subcortical connectivity features in dynamic functional brain networks between GAD and MDD, which together can promote the understanding of common and disorder-specific topological organization dysregulations and facilitate early neuroimaging-based diagnosis.
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Affiliation(s)
- Qi Liu
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - Bo Zhou
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - Xiaodong Zhang
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - Peng Qing
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - Xinqi Zhou
- Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu, 610066, China
| | - Feng Zhou
- Faculty of Psychology, Key Laboratory of Cognition and Personality, Ministry of Education, Southwest University, Chongqing, 400715, China
| | - Xiaolei Xu
- School of Psychology, Shandong Normal University, Jinan, 250014, China
| | - Siyu Zhu
- School of Sport Training, Chengdu Sport University, Chengdu, 610041, China
| | - Jing Dai
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China
| | - Yulan Huang
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - Jinyu Wang
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - Zhili Zou
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - Keith M Kendrick
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China
| | - Benjamin Becker
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China; State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, Pokfulam, Hong Kong; Department of Psychology, The University of Hong Kong, Hong Kong, Pokfulam, Hong Kong; The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China.
| | - Weihua Zhao
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China; The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China.
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Zugman A, Jett L, Antonacci C, Winkler AM, Pine DS. A systematic review and meta-analysis of resting-state fMRI in anxiety disorders: Need for data sharing to move the field forward. J Anxiety Disord 2023; 99:102773. [PMID: 37741177 PMCID: PMC10753861 DOI: 10.1016/j.janxdis.2023.102773] [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: 08/31/2022] [Revised: 09/11/2023] [Accepted: 09/12/2023] [Indexed: 09/25/2023]
Abstract
Anxiety disorders are among the most prevalent psychiatric disorders. Neuroimaging findings remain uncertain, and resting state functional magnetic resonance (rs-fMRI) connectivity is of particular interest since it is a scalable functional imaging modality. Given heterogeneous past findings for rs-fMRI in anxious individuals, we characterize patterns across anxiety disorders by conducting a systematic review and meta-analysis. Studies were included if they contained at the time of scanning both a healthy group and a patient group. Due to insufficient study numbers, the quantitative meta-analysis only included seed-based studies. We performed an activation likelihood estimation (ALE) analysis that compared patients and healthy volunteers. All analyses were corrected for family-wise error with a cluster-level threshold of p < .05. Patients exhibited hypo-connectivity between the amygdala and the medial frontal gyrus, anterior cingulate cortex, and cingulate gyrus. This finding, however, was not robust to potential file-drawer effects. Though limited by strict inclusion criteria, our results highlight the heterogeneous nature of reported findings. This underscores the need for data sharing when attempting to detect reliable patterns of disruption in brain activity across anxiety disorders.
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Affiliation(s)
- André Zugman
- Section on Development and Affective Neuroscience (SDAN), Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States.
| | - Laura Jett
- Section on Development and Affective Neuroscience (SDAN), Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States; Child Emotion Lab, University of Wisconsin, Madison, Madison, WI, United States.
| | - Chase Antonacci
- Section on Development and Affective Neuroscience (SDAN), Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States; Department of Psychology, Stanford University, Stanford, CA, United States.
| | - Anderson M Winkler
- Section on Development and Affective Neuroscience (SDAN), Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States; Division of Human Genetics, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, Texas, United States.
| | - Daniel S Pine
- Section on Development and Affective Neuroscience (SDAN), Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States.
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10
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Huang H, Rong B, Chen C, Wan Q, Liu Z, Zhou Y, Wang G, Wang H. Common and Distinct Functional Connectivity of the Orbitofrontal Cortex in Depression and Schizophrenia. Brain Sci 2023; 13:997. [PMID: 37508929 PMCID: PMC10377532 DOI: 10.3390/brainsci13070997] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 06/12/2023] [Accepted: 06/22/2023] [Indexed: 07/30/2023] Open
Abstract
Schizophrenia and depression are psychiatric disorders with overlapping clinical and biological features. This study aimed to identify common and distinct neuropathological mechanisms in schizophrenia and depression patients using resting-state functional magnetic resonance imaging (fMRI). The study included 28 patients with depression (DEP), 29 patients with schizophrenia (SCH), and 30 healthy control subjects (HC). Intrinsic connectivity contrast (ICC) was used to identify functional connectivity (FC) changes at the whole-brain level, and significant ICC differences were found in the bilateral orbitofrontal cortex (OFC) across all three groups. Further seed-based FC analysis indicated that compared to the DEP and HC groups, the FC between bilateral OFC and medial prefrontal cortex (MPFC), right anterior insula, and right middle frontal gyrus were significantly lower in the SCH group. Additionally, the FC between right OFC and left thalamus was decreased in both patient groups compared to the HC group. Correlation analysis showed that the FC between OFC and MPFC was positively correlated with cognitive function in the SCH group. These findings suggest that OFC connectivity plays a critical role in the pathophysiology of schizophrenia and depression and may provide new insights into the potential neural mechanisms underlying these two disorders.
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Affiliation(s)
- Huan Huang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Bei Rong
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Cheng Chen
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Qirong Wan
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Zhongchun Liu
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Yuan Zhou
- Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
| | - Gaohua Wang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Hubei Institute of Neurology and Psychiatry Research, Wuhan 430060, China
| | - Huiling Wang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Department of Psychiatry, Zhongxiang Hospital of Renmin Hospital of Wuhan University, Zhongxiang 431900, China
- Hubei Provincial Key Laboratory of Developmentally Originated Disease, Wuhan 430071, China
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11
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Wang H, Song P, Hou Y, Liu J, Hao W, Hu S, Dai X, Zhan S, Li N, Peng M, Wang H, Lin H, Wang Y. 820-nm Transcranial Near-infrared Stimulation on the Left DLPFC Relieved Anxiety: A Randomized, Double-blind, Sham-controlled Study. Brain Res Bull 2023:110682. [PMID: 37301483 DOI: 10.1016/j.brainresbull.2023.110682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 05/13/2023] [Accepted: 06/05/2023] [Indexed: 06/12/2023]
Abstract
OBJECTIVE Generalized anxiety disorder (GAD) is a chronic mood disease associated with abnormal brain network connections, including decreased activity in the left dorsolateral prefrontal cortex (DLPFC). Cortical excitability can be increased with 820-nm transcranial near-infrared stimulation (tNIRS), while transcranial magnetic stimulation with electroencephalography (TMS-EEG) can help evaluate time-varying brain network connectivity. A randomized, double-blind, sham-controlled trial was conducted to assess the efficacy of tNIRS on the left DLPFC and the impact on time-varying brain network connections in GAD patients. METHODS A total of 36 GAD patients were randomized to receive active or sham tNIRS for 2 weeks. Clinical psychological scales were assessed before, after, and at the 2-, 4-, and 8-week follow-ups. TMS-EEG was performed for 20minutes before and immediately after tNIRS treatment. The healthy controls did not receive tNIRS and only had TMS-EEG data collected once in the resting state. RESULTS The Hamilton Anxiety Scale (HAMA) scores of the active stimulation group decreased post-treatment compared with the sham group (P=0.021). The HAMA scores of the active stimulation group at the 2-, 4-, and 8-week follow-up assessments were lower than those before treatment (P<0.05). The time-varying EEG network pattern showed an information outflow from the left DLPFC and the left posterior temporal region after active treatment. CONCLUSION Herein, 820-nm tNIRS targeting the left DLPFC had significant positive effects on therapy for GAD that lasted at least 2 months. tNIRS may reverse the abnormality of time-varying brain network connections in GAD.
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Affiliation(s)
- Huicong Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Beijing Key Laboratory of Neuromodulation, Beijing 100053, China; Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China; Center for sleep and consciousness disorders, Beijing Institute for Brain Disorders, Beijing 100053, China; Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing 100053, China
| | - Penghui Song
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Beijing Key Laboratory of Neuromodulation, Beijing 100053, China; Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China; Center for sleep and consciousness disorders, Beijing Institute for Brain Disorders, Beijing 100053, China; Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing 100053, China.
| | - Yue Hou
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Beijing Key Laboratory of Neuromodulation, Beijing 100053, China; Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China; Center for sleep and consciousness disorders, Beijing Institute for Brain Disorders, Beijing 100053, China; Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing 100053, China; Hebei Hospital of Xuanwu Hospital, Capital Medical University, Shijiazhuang, 050000 China; Neuromedical Technology Innovation Center of Hebei Province, 050000 China
| | - Jianghong Liu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Beijing Key Laboratory of Neuromodulation, Beijing 100053, China; Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China; Center for sleep and consciousness disorders, Beijing Institute for Brain Disorders, Beijing 100053, China; Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing 100053, China
| | - Wensi Hao
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Beijing Key Laboratory of Neuromodulation, Beijing 100053, China; Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China
| | - Shimin Hu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Beijing Key Laboratory of Neuromodulation, Beijing 100053, China; Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China
| | - Xiaona Dai
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Beijing Key Laboratory of Neuromodulation, Beijing 100053, China; Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China
| | - Shuqin Zhan
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Beijing Key Laboratory of Neuromodulation, Beijing 100053, China; Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China; Center for sleep and consciousness disorders, Beijing Institute for Brain Disorders, Beijing 100053, China; Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing 100053, China
| | - Ning Li
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Beijing Key Laboratory of Neuromodulation, Beijing 100053, China; Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China; Center for sleep and consciousness disorders, Beijing Institute for Brain Disorders, Beijing 100053, China; Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing 100053, China
| | - Mao Peng
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Beijing Key Laboratory of Neuromodulation, Beijing 100053, China; Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China; Center for sleep and consciousness disorders, Beijing Institute for Brain Disorders, Beijing 100053, China; Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing 100053, China
| | - Hongxing Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Beijing Key Laboratory of Neuromodulation, Beijing 100053, China; Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China; Center for sleep and consciousness disorders, Beijing Institute for Brain Disorders, Beijing 100053, China; Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing 100053, China
| | - Hua Lin
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Beijing Key Laboratory of Neuromodulation, Beijing 100053, China; Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China; Center for sleep and consciousness disorders, Beijing Institute for Brain Disorders, Beijing 100053, China; Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing 100053, China
| | - Yuping Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Beijing Key Laboratory of Neuromodulation, Beijing 100053, China; Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China; Center for sleep and consciousness disorders, Beijing Institute for Brain Disorders, Beijing 100053, China; Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing 100053, China; Hebei Hospital of Xuanwu Hospital, Capital Medical University, Shijiazhuang, 050000 China; Neuromedical Technology Innovation Center of Hebei Province, 050000 China.
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12
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Opposing and emotion-specific associations between frontal activation with depression and anxiety symptoms during facial emotion processing in generalized anxiety and depression. Prog Neuropsychopharmacol Biol Psychiatry 2023; 123:110716. [PMID: 36623581 DOI: 10.1016/j.pnpbp.2023.110716] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 11/06/2022] [Accepted: 01/04/2023] [Indexed: 01/09/2023]
Abstract
Major depression (MDD) and generalized anxiety disorder (GAD) have become one of the leading global causes of disability and both are characterized by marked interpersonal and social impairments. However, despite high comorbidity and overlapping social-emotional deficits, it remains unclear whether MDD and GAD share a common neural basis during interpersonal processing. In the present study, we combined an emotional face processing paradigm with fMRI and dimensional and categorical analyses in a sample of unmedicated MDD and GAD patients (N = 72) as well as healthy controls (N = 35). No group differences were found in categorical analyses. However, the dimensional analyses revealed that dorsolateral prefrontal cortex (dlPFC) reactivity to sad facial expressions was positively associated with depression symptom load, yet negatively associated with anxiety symptom load in the entire sample. On the network level depression symptom load was positively associated with functional connectivity between the bilateral amygdala and a widespread network including the anterior cingulate and insular cortex. Together, these findings suggest that the dlPFC - engaged in cognitive and emotional processing - exhibits symptom- and emotion-specific alteration during interpersonal processing. Dysregulated communication between the amygdala and core regions of the salience network may represent depression-specific neural dysregulations.
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13
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Xu S, Zhang Z, Li L, Zhou Y, Lin D, Zhang M, Zhang L, Huang G, Liu X, Becker B, Liang Z. Functional connectivity profiles of the default mode and visual networks reflect temporal accumulative effects of sustained naturalistic emotional experience. Neuroimage 2023; 269:119941. [PMID: 36791897 DOI: 10.1016/j.neuroimage.2023.119941] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 01/30/2023] [Accepted: 02/11/2023] [Indexed: 02/15/2023] Open
Abstract
Determining and decoding emotional brain processes under ecologically valid conditions remains a key challenge in affective neuroscience. The current functional Magnetic Resonance Imaging (fMRI) based emotion decoding studies are mainly based on brief and isolated episodes of emotion induction, while sustained emotional experience in naturalistic environments that mirror daily life experiences are scarce. Here we used 12 different 10-minute movie clips as ecologically valid emotion-evoking procedures in n = 52 individuals to explore emotion-specific fMRI functional connectivity (FC) profiles on the whole-brain level at high spatial resolution (432 parcellations including cortical and subcortical structures). Employing machine-learning based decoding and cross validation procedures allowed to investigate FC profiles contributing to classification that can accurately distinguish sustained happiness and sadness and that generalize across subjects, movie clips, and parcellations. Both functional brain network-based and subnetwork-based emotion classification results suggested that emotion manifests as distributed representation of multiple networks, rather than a single functional network or subnetwork. Further, the results showed that the Visual Network (VN) and Default Mode Network (DMN) associated functional networks, especially VN-DMN, exhibited a strong contribution to emotion classification. To further estimate the temporal accumulative effect of naturalistic long-term movie-based video-evoking emotions, we divided the 10-min episode into three stages: early stimulation (1∼200 s), middle stimulation (201∼400 s), and late stimulation (401∼600 s) and examined the emotion classification performance at different stimulation stages. We found that the late stimulation contributes most to the classification (accuracy=85.32%, F1-score=85.62%) compared to early and middle stimulation stages, implying that continuous exposure to emotional stimulation can lead to more intense emotions and further enhance emotion-specific distinguishable representations. The present work demonstrated that sustained happiness and sadness under naturalistic conditions are presented in emotion-specific network profiles and these expressions may play different roles in the generation and modulation of emotions. These findings elucidated the importance of network level adaptations for sustained emotional experiences during naturalistic contexts and open new venues for imaging network level contributions under naturalistic conditions.
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Affiliation(s)
- Shuyue Xu
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China
| | - Zhiguo Zhang
- Institute of Computing and Intelligence, Harbin Institute of Technology, Shenzhen, China; Peng Cheng Laboratory, Shenzhen 518055, China; Marshall Laboratory of Biomedical Engineering, Shenzhen 518060, China
| | - Linling Li
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China
| | - Yongjie Zhou
- Department of Psychiatric Rehabilitation, Shenzhen Kangning Hospital, Shenzhen, China
| | - Danyi Lin
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China
| | - Min Zhang
- Institute of Computing and Intelligence, Harbin Institute of Technology, Shenzhen, China
| | - Li Zhang
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China
| | - Gan Huang
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China
| | - Xiqin Liu
- Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, MOE Key Laboratory for Neuroinformation, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Benjamin Becker
- Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, MOE Key Laboratory for Neuroinformation, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China.
| | - Zhen Liang
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China; Marshall Laboratory of Biomedical Engineering, Shenzhen 518060, China.
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14
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Acute TMS/fMRI response explains offline TMS network effects - An interleaved TMS-fMRI study. Neuroimage 2023; 267:119833. [PMID: 36572133 DOI: 10.1016/j.neuroimage.2022.119833] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 11/22/2022] [Accepted: 12/22/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Transcranial magnetic stimulation (TMS) is an FDA-approved therapeutic option for treatment resistant depression. However, exact mechanisms-of-action are not fully understood and individual responses are variable. Moreover, although previously suggested, the exact network effects underlying TMS' efficacy are poorly understood as of today. Although, it is supposed that DLPFC stimulation indirectly modulates the sgACC, recent evidence is sparse. METHODS Here, we used concurrent interleaved TMS/fMRI and state-of-the-science purpose-designed MRI head coils to delineate networks and downstream regions activated by DLPFC-TMS. RESULTS We show that regions of increased acute BOLD signal activation during TMS resemble a resting-state brain network previously shown to be modulated by offline TMS. There was a topographical overlap in wide spread cortical and sub-cortical areas within this specific RSN#17 derived from the 1000 functional connectomes project. CONCLUSION These data imply a causal relation between DLPFC-TMS and activation of the ACC and a broader network that has been implicated in MDD. In the broader context of our recent work, these data imply a direct relation between initial changes in BOLD activity mediated by connectivity to the DLPFC target site, and later consolidation of connectivity between these regions. These insights advance our understanding of the mechanistic targets of DLPFC-TMS and may provide novel opportunities to characterize and optimize TMS therapy in other neurological and psychiatric disorders.
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15
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Cheng B, Wang X, Roberts N, Zhou Y, Wang S, Deng P, Meng Y, Deng W, Wang J. Abnormal dynamics of resting-state functional activity and couplings in postpartum depression with and without anxiety. Cereb Cortex 2022; 32:5597-5608. [PMID: 35174863 DOI: 10.1093/cercor/bhac038] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Revised: 01/18/2022] [Accepted: 01/19/2022] [Indexed: 02/05/2023] Open
Abstract
Postpartum depression (PPD) and PPD comorbid with anxiety (PPD-A) are highly prevalent and severe mental health problems in postnatal women. PPD and PPD-A share similar pathopsychological features, leading to ongoing debates regarding the diagnostic and neurobiological uniqueness. This paper aims to delineate common and disorder-specific neural underpinnings and potential treatment targets for PPD and PPD-A by characterizing functional dynamics with resting-state functional magnetic resonance imaging in 138 participants (45 first-episode, treatment-naïve PPD; 31 PDD-A patients; and 62 healthy postnatal women [HPW]). PPD-A group showed specifically increased dynamic amplitude of low-frequency fluctuation in the subgenual anterior cingulate cortex (sgACC) and increased dynamic functional connectivity (dFC) between the sgACC and superior temporal sulcus. PPD group exhibited specifically increased static FC (sFC) between the sgACC and ventral anterior insula. Common disrupted sFC between the sgACC and middle temporal gyrus was found in both PPD and PPD-A patients. Interestingly, dynamic changes in dFC between the sgACC and superior temporal gyrus could differentiate PPD, PPD-A, and HPW. Our study presents initial evidence on specifically abnormal functional dynamics of limbic, emotion regulation, and social cognition systems in patients with PDD and PPD-A, which may facilitate understanding neurophysiological mechanisms, diagnosis, and treatment for PPD and PPD-A.
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Affiliation(s)
- Bochao Cheng
- Department of Radiology, West China Second University Hospital of Sichuan University, Chengdu 610041, China.,Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu 610041, China
| | - Xiuli Wang
- Department of Psychiatry, The Fourth People's Hospital of Chengdu, University of Electronic Science and Technology of China, Chengdu 610041, China
| | - Neil Roberts
- Edinburgh Imaging facility, The Queen's Medical Research Institute (QMRI), School of Clinical Sciences, University of Edinburgh, Edinburgh EH16 4TJ, United Kingdom
| | - Yushan Zhou
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu 610041, China.,Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Song Wang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Pengcheng Deng
- Department of Radiology, West China Second University Hospital of Sichuan University, Chengdu 610041, China
| | - Yajing Meng
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Wei Deng
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Jiaojian Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
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Disorder-specific impaired neurocognitive function in major depression and generalized anxiety disorder. J Affect Disord 2022; 318:123-129. [PMID: 36057290 DOI: 10.1016/j.jad.2022.08.129] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 06/02/2022] [Accepted: 08/28/2022] [Indexed: 11/21/2022]
Abstract
BACKGROUND Generalized anxiety disorder (GAD) and major depressive disorder (MDD) are both highly prevalent and comorbid psychiatric disorders. Neurocognitive dysfunction has been commonly found in MDD, but the findings in GAD are inconsistent. Few studies have directly compared cognitive performance between GAD and MDD. Therefore, the present study aimed to reveal the similar and distinct cognitive impairments between both disorders. METHODS Three non-overlapping and non-comorbid groups were enrolled in the current study including patients with GAD (n = 37), MDD (n = 107) and healthy controls (n = 74). Levels of anxiety and depression were assessed using the Hamilton Anxiety Rating Scale (HAMA) and the Hamilton Depression Rating Scale (HAMD) respectively. The Cambridge Neuropsychological Test Automated Battery (CANTAB) was used to compare the cognitive performance, including sustained attention, visual memory, executive functions and learning. RESULTS Both MDD and GAD groups demonstrated common significant deficits in sustained attention, visual memory, working memory and learning when compared to healthy controls. Despite the similarities, the MDD group had significantly greater impairment in learning, particularly generalization, while the GAD group demonstrated more pronounced deficits in visual memory. LIMITATIONS Patients involved were medicated and the sample size for GAD was relatively small. CONCLUSIONS The significant differences in visual memory and learning between MDD and GAD groups might be indicators to distinguishing both disorders. These results confirm that cognitive function is of great importance as a future target for treatment in order to improve wellbeing, quality of life and functionality in both GAD and MDD.
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17
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Sun J, Du Z, Ma Y, Guo C, Gao S, Luo Y, Chen Q, Hong Y, Xiao X, Yu X, Fang J. Characterization of Resting-State Striatal Differences in First-Episode Depression and Recurrent Depression. Brain Sci 2022; 12:brainsci12121603. [PMID: 36552063 PMCID: PMC9776048 DOI: 10.3390/brainsci12121603] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 11/19/2022] [Accepted: 11/19/2022] [Indexed: 11/24/2022] Open
Abstract
The presence of reward deficits in major depressive disorder is associated with abnormal striatal function. However, differences in striatal whole-brain functional between recurrent depressive episode (RDE) and first-episode depression (FDE) have not been elucidated. Thirty-three patients with RDE, 27 with FDE, and 35 healthy controls (HCs) were recruited for this study. A seed-based functional connectivity (FC) method was used to analyze abnormalities in six predefined striatal subregion circuits among the three groups of subjects and to further explore the correlation between abnormal FC and clinical symptoms. The results revealed that compared with the FDE group, the RDE group showed higher FC of the striatal subregion with the left middle occipital gyrus, left orbital area of the middle frontal gyrus, and bilateral posterior cerebellar gyrus, while showing lower FC of the striatal subregion with the right thalamus, left inferior parietal lobule, left middle cingulate gyrus, right angular gyrus, right cerebellum anterior lobe, and right caudate nucleus. In the RDE group, the HAMD-17 scores were positively correlated with the FC between the left dorsal rostral putamen and the left cerebellum posterior lobe. This study provides new insights into understanding the specificity of striatal circuits in the RDE group.
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Affiliation(s)
- Jifei Sun
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Zhongming Du
- Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing 100700, China
| | - Yue Ma
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Chunlei Guo
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Shanshan Gao
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Yi Luo
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Qingyan Chen
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Yang Hong
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Xue Xiao
- Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing 100026, China
| | - Xue Yu
- Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing 100026, China
| | - Jiliang Fang
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
- Correspondence: ; Tel.: +86-010-88001493
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18
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Xu X, Xin F, Liu C, Chen Y, Yao S, Zhou X, Zhou F, Huang Y, Dai J, Wang J, Zou Z, Kendrick KM, Zhou B, Becker B. Disorder- and cognitive demand-specific neurofunctional alterations during social emotional working memory in generalized anxiety disorder and major depressive disorder. J Affect Disord 2022; 308:98-105. [PMID: 35427713 DOI: 10.1016/j.jad.2022.04.023] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 04/03/2022] [Accepted: 04/08/2022] [Indexed: 02/06/2023]
Abstract
BACKGROUND Generalized Anxiety Disorder (GAD) and Major Depressive Disorder (MDD) are both characterized by cognitive and social impairments. Determining disorder-specific neurobiological alterations in GAD and MDD by means of functional magnetic resonance imaging (fMRI) may promote determination of precise diagnostic markers. METHODS This study aimed to examine disorder-specific behavioral and neural alterations at the intersection of social and cognitive processing in treatment-naïve first-episode GAD (n = 35) and MDD (n = 37) patients compared to healthy controls (n = 35) by employing a social-emotional n-back fMRI paradigm. RESULTS No behavioral differences between patients and healthy controls were observed. However, GAD patients exhibited decreased bilateral dorsomedial prefrontal cortex (dmPFC) engagement during the 0-back condition yet increased dmPFC engagement during the 1-back condition compared to MDD and healthy participants. In contrast, MDD patients exhibited increased dmPFC-insula coupling during 0-back, yet decreased coupling during 1-back, compared to GAD and healthy participants. Dimensional symptom-load analysis confirmed that increased dmPFC-insula connectivity during 0-back was positively associated with depressive symptom load. LIMITATIONS The moderate sample size in the present study did not allow us to further explore gender differences. In addition, some patients exhibited GAD and MDD comorbidity according to the M.I.N.I. interview. Finally, the paradigm we used did not allow to further disentangle emotion-specific effects on working memory. CONCLUSIONS These findings suggest that the dmPFC engaged in integrating affective and cognitive components and self-other processing exhibits GAD-specific neurofunctional dysregulations whereas functional dmPFC communication with the insula, a region involved in salience processing, may represent an MDD-specific neurofunctional deficit.
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Affiliation(s)
- Xiaolei Xu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, Sichuan 610054, China; School of Psychology, Shandong Normal University, Jinan 250358, China
| | - Fei Xin
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, Sichuan 610054, China; School of Psychology, Shenzhen University, Shenzhen 518060, Guangdong, China
| | - Congcong Liu
- Department of Psychology, Xinxiang Medical University, Henan 453003, China
| | - Yuanshu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, Sichuan 610054, China
| | - Shuxia Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, Sichuan 610054, China
| | - Xinqi Zhou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, Sichuan 610054, China
| | - Feng Zhou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, Sichuan 610054, China
| | - Yulan Huang
- Department of Psychosomatic Medicine, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, Chengdu, Sichuan 610072, China
| | - Jing Dai
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, Sichuan 610054, China; Chengdu Mental Health Center, The Fourth People's Hospital of Chengdu, Chengdu, Sichuan 610036, China
| | - Jinyu Wang
- Department of Psychosomatic Medicine, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, Chengdu, Sichuan 610072, China
| | - Zhili Zou
- Department of Psychosomatic Medicine, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, Chengdu, Sichuan 610072, China
| | - Keith M Kendrick
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, Sichuan 610054, China
| | - Bo Zhou
- Department of Psychosomatic Medicine, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, Chengdu, Sichuan 610072, China.
| | - Benjamin Becker
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, Sichuan 610054, China.
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19
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Lan C, Liu C, Li K, Zhao Z, Yang J, Ma Y, Scheele D, Yao S, Kendrick KM, Becker B. Oxytocinergic Modulation of Stress-Associated Amygdala-Hippocampus Pathways in Humans Is Mediated by Serotonergic Mechanisms. Int J Neuropsychopharmacol 2022; 25:807-817. [PMID: 35723242 PMCID: PMC9593216 DOI: 10.1093/ijnp/pyac037] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 05/31/2022] [Accepted: 06/15/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND The hypothalamic neuropeptide oxytocin (OXT) may exert anxiolytic and stress-reducing actions via modulatory effects on amygdala circuits. Animal models and initial findings in humans suggest that some of these effects are mediated by interactions with other neurotransmitter systems, in particular the serotonin (5-HT) system. Against this background, the present pharmacological resting-state functional magnetic resonance imaging study aimed to determine whether effects of OXT on stress-associated amygdala intrinsic networks are mediated by 5-HT. METHODS We employed a randomized, placebo-controlled, double-blind parallel-group, pharmacological functional magnetic resonance imaging resting-state experiment with 4 treatment groups in n = 112 healthy male participants. Participants underwent a transient decrease in 5-HT signaling via acute tryptophan depletion (ATD) or a corresponding placebo-control protocol before the administration of intranasal OXT (24 IU) or placebo intranasal spray. RESULTS OXT and 5-HT modulation exerted interactive effects on the coupling of the left amygdala with the ipsilateral hippocampus and adjacent midbrain. OXT increased intrinsic coupling in this pathway, whereas this effect of OXT was significantly attenuated during transiently decreased central serotonergic signaling induced via acute tryptophan depletion. In the absence of OXT or 5-HT modulation, this pathway showed a trend for an association with self-reported stress perception in everyday life. No interactive effects were observed for the right amygdala. CONCLUSIONS Together, the findings provide the first evidence, to our knowledge, that the effects of OXT on stress-associated amygdala-hippocampal-midbrain pathways are critically mediated by the 5-HT system in humans.
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Affiliation(s)
| | | | - Keshuang Li
- The Clinical Hospital of the Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China,School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
| | - Zhiying Zhao
- The Clinical Hospital of the Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China,Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Jiaxin Yang
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute of Brain Research, Beijing Normal University, Beijing, China
| | - Yina Ma
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute of Brain Research, Beijing Normal University, Beijing, China
| | - Dirk Scheele
- Division of Medical Psychology, Department of Psychiatry and Psychotherapy, University HospitalBonn, Bonn, Germany,Department of Psychiatry, School of Medicine & Health Sciences, University of Oldenburg, Oldenburg, Germany
| | - Shuxia Yao
- The Clinical Hospital of the Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Keith M Kendrick
- The Clinical Hospital of the Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Benjamin Becker
- Correspondence: Benjamin Becker, PhD, University of Electronic Science and Technology, Xiyuan Avenue 2006, 611731 Chengdu, China ()
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Williamson JB, Jaffee MS, Jorge RE. Posttraumatic Stress Disorder and Anxiety-Related Conditions. Continuum (Minneap Minn) 2021; 27:1738-1763. [PMID: 34881734 DOI: 10.1212/con.0000000000001054] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
PURPOSE OF REVIEW This article provides a synopsis of current assessment and treatment considerations for posttraumatic stress disorder (PTSD) and related anxiety disorder characteristics. Epidemiologic and neurobiological data are reviewed as well as common associated symptoms, including sleep disruption, and treatment approaches to these conditions. RECENT FINDINGS PTSD is no longer considered an anxiety-related disorder in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition classification and instead is associated with trauma/stressor-related disorders. PTSD symptoms are clustered into four domains including intrusive experiences, avoidance, mood, and arousal symptoms. Despite this reclassification, similarities exist in consideration of diagnosis, treatment, and comorbidities with anxiety disorders. PTSD and anxiety-related disorders are heterogeneous, which is reflected by the neural circuits involved in the genesis of symptoms that may vary across symptom domains. Treatment is likely to benefit from consideration of this heterogeneity.Research in animal models of fear and anxiety, as well as in humans, suggests that patients with PTSD and generalized anxiety disorder have difficulty accurately determining safety from danger and struggle to suppress fear in the presence of safety cues.Empirically supported psychotherapies commonly involved exposure (fear extinction learning) and are recommended for PTSD. Cognitive-behavioral therapy has been shown to be effective in other anxiety-related disorders. Selective serotonin reuptake inhibitors (SSRIs) and serotonin norepinephrine reuptake inhibitors (SNRIs) are commonly used in the treatment of PTSD and anxiety disorders in which pharmacologic intervention is supported. Treating sleep disruption including sleep apnea (continuous positive airway pressure [CPAP]), nightmares, and insomnia (preferably via psychotherapy) may improve symptoms of PTSD, as well as improve mood in anxiety disorders. SUMMARY PTSD has a lifetime prevalence that is close to 10% and shares neurobiological features with anxiety disorders. Anxiety disorders are the most common class of mental conditions and are highly comorbid with other disorders; treatment considerations typically include cognitive-behavioral therapy and pharmacologic intervention. Developing technologies show some promise as treatment alternatives in the future.
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22
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McKibben LA, Dwivedi Y. Early-life stress induces genome-wide sex-dependent miRNA expression and correlation across limbic brain areas in rats. Epigenomics 2021; 13:1031-1056. [PMID: 34008410 PMCID: PMC8244583 DOI: 10.2217/epi-2021-0037] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Aims: The aim of this study was to assess regional- and sex-dependent changes in miRNA expression resulting from early-life stress (ELS). Materials and methods: Small RNA sequencing was used to determine sex-dependent changes in miRNAs after maternal separation, a rodent model of ELS, across the prefrontal cortex, amygdala and hippocampus. Results: Maternal separation induced anhedonia and altered miRNA expression in a sex-dependent manner, particularly in the prefrontal cortex and hippocampus. Gene ontology revealed that these miRNAs target genes with brain-specific biological functions. Conclusion: Using a network approach to explore miRNA signaling across the brain after ELS, regional differences were highlighted as key to studying the brain’s stress response, which indicates that sex is critical for understanding miRNA-mediated ELS-induced behavior.
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Affiliation(s)
- Lauren A McKibben
- Department of Psychiatry & Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL 35233, USA
| | - Yogesh Dwivedi
- Department of Psychiatry & Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL 35233, USA
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23
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Liu X, Lai H, Li J, Becker B, Zhao Y, Cheng B, Wang S. Gray matter structures associated with neuroticism: A meta-analysis of whole-brain voxel-based morphometry studies. Hum Brain Mapp 2021; 42:2706-2721. [PMID: 33704850 PMCID: PMC8127153 DOI: 10.1002/hbm.25395] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2020] [Revised: 01/28/2021] [Accepted: 02/22/2021] [Indexed: 02/05/2023] Open
Abstract
Neuroticism is major higher-order personality trait and has been robustly associated with mental and physical health outcomes. Although a growing body of studies have identified neurostructural markers of neuroticism, the results remained highly inconsistent. To characterize robust associations between neuroticism and variations in gray matter (GM) structures, the present meta-analysis investigated the concurrence across voxel-based morphometry (VBM) studies using the anisotropic effect size signed differential mapping (AES-SDM). A total of 13 studies comprising 2,278 healthy subjects (1,275 females, 29.20 ± 14.17 years old) were included. Our analysis revealed that neuroticism was consistently associated with the GM structure of a cluster spanning the bilateral dorsal anterior cingulate cortex and extending to the adjacent medial prefrontal cortex (dACC/mPFC). Meta-regression analyses indicated that the neuroticism-GM associations were not confounded by age and gender. Overall, our study is the first whole-brain meta-analysis exploring the brain structural correlates of neuroticism, and the findings may have implications for the intervention of high-neuroticism individuals, who are at risk of mental disorders, by targeting the dACC/mPFC.
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Affiliation(s)
- Xiqin Liu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Han Lai
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Jingguang Li
- College of Teacher Education, Dali University, Dali, China
| | - Benjamin Becker
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Yajun Zhao
- School of Education and Psychology, Southwest Minzu University, Chengdu, China
| | - Bochao Cheng
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu, China
| | - Song Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
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