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Calabro FJ, Parr AC, Sydnor VJ, Hetherington H, Prasad KM, Ibrahim TS, Sarpal DK, Famalette A, Verma P, Luna B. Leveraging ultra-high field (7T) MRI in psychiatric research. Neuropsychopharmacology 2024:10.1038/s41386-024-01980-6. [PMID: 39251774 DOI: 10.1038/s41386-024-01980-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Revised: 06/21/2024] [Accepted: 07/23/2024] [Indexed: 09/11/2024]
Abstract
Non-invasive brain imaging has played a critical role in establishing our understanding of the neural properties that contribute to the emergence of psychiatric disorders. However, characterizing core neurobiological mechanisms of psychiatric symptomatology requires greater structural, functional, and neurochemical specificity than is typically obtainable with standard field strength MRI acquisitions (e.g., 3T). Ultra-high field (UHF) imaging at 7 Tesla (7T) provides the opportunity to identify neurobiological systems that confer risk, determine etiology, and characterize disease progression and treatment outcomes of major mental illnesses. Increases in scanner availability, regulatory approval, and sequence availability have made the application of UHF to clinical cohorts more feasible than ever before, yet the application of UHF approaches to the study of mental health remains nascent. In this technical review, we describe core neuroimaging methodologies which benefit from UHF acquisition, including high resolution structural and functional imaging, single (1H) and multi-nuclear (e.g., 31P) MR spectroscopy, and quantitative MR techniques for assessing brain tissue iron and myelin. We discuss advantages provided by 7T MRI, including higher signal- and contrast-to-noise ratio, enhanced spatial resolution, increased test-retest reliability, and molecular and neurochemical specificity, and how these have begun to uncover mechanisms of psychiatric disorders. Finally, we consider current limitations of UHF in its application to clinical cohorts, and point to ongoing work that aims to overcome technical hurdles through the continued development of UHF hardware, software, and protocols.
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Affiliation(s)
- Finnegan J Calabro
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Ashley C Parr
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Valerie J Sydnor
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Konasale M Prasad
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA, USA
| | - Tamer S Ibrahim
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Deepak K Sarpal
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Alyssa Famalette
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Piya Verma
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beatriz Luna
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
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Saberi A, Ebneabbasi A, Rahimi S, Sarebannejad S, Sen ZD, Graf H, Walter M, Sorg C, Camilleri JA, Laird AR, Fox PT, Valk SL, Eickhoff SB, Tahmasian M. Convergent functional effects of antidepressants in major depressive disorder: a neuroimaging meta-analysis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.11.24.23298991. [PMID: 38076878 PMCID: PMC10705609 DOI: 10.1101/2023.11.24.23298991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/27/2024]
Abstract
Background Neuroimaging studies have provided valuable insights into the macroscale impacts of antidepressants on brain functions in patients with major depressive disorder. However, the findings of individual studies are inconsistent. Here, we aimed to provide a quantitative synthesis of the literature to identify convergence of the reported findings at both regional and network levels and to examine their associations with neurotransmitter systems. Methods Through a comprehensive search in PubMed and Scopus databases, we reviewed 5,258 abstracts and identified 36 eligible functional neuroimaging studies on antidepressant effects in major depressive disorder. Activation likelihood estimation was used to investigate regional convergence of the reported foci of consistent antidepressant effects, followed by functional decoding and connectivity mapping of the convergent clusters. Additionally, utilizing group-averaged data from the Human Connectome Project, we assessed convergent resting-state functional connectivity patterns of the reported foci. Next, we compared the convergent circuit with the circuits targeted by transcranial magnetic stimulation (TMS) therapy. Last, we studied the association of regional and network-level convergence maps with selected neurotransmitter receptors/transporters maps. Results No regional convergence was found across foci of treatment-associated alterations in functional imaging. Subgroup analysis across the Treated > Untreated contrast revealed a convergent cluster in the left dorsolateral prefrontal cortex, which was associated with working memory and attention behavioral domains. Moreover, we found network-level convergence of the treatment-associated alterations in a circuit more prominent in the frontoparietal areas. This circuit was co-aligned with circuits targeted by "anti-subgenual" and "Beam F3" TMS therapy. We observed no significant correlations between our meta-analytic findings with the maps of neurotransmitter receptors/transporters. Conclusion Our findings highlight the importance of the frontoparietal network and the left dorsolateral prefrontal cortex in the therapeutic effects of antidepressants, which may relate to their role in improving executive functions and emotional processing.
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Tschentscher N, Tafelmaier JC, Woll CFJ, Pogarell O, Maywald M, Vierl L, Breitenstein K, Karch S. The Clinical Impact of Real-Time fMRI Neurofeedback on Emotion Regulation: A Systematic Review. Brain Sci 2024; 14:700. [PMID: 39061440 PMCID: PMC11274904 DOI: 10.3390/brainsci14070700] [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: 06/14/2024] [Revised: 07/05/2024] [Accepted: 07/09/2024] [Indexed: 07/28/2024] Open
Abstract
Emotion dysregulation has long been considered a key symptom in multiple psychiatric disorders. Difficulties in emotion regulation have been associated with neural dysregulation in fronto-limbic circuits. Real-time fMRI-based neurofeedback (rt-fMRI-NFB) has become increasingly popular as a potential treatment for emotional dysregulation in psychiatric disorders, as it is able to directly target the impaired neural circuits. However, the clinical impact of these rt-fMRI-NFB protocols in psychiatric populations is still largely unknown. Here we provide a comprehensive overview of primary studies from 2010 to 2023 that used rt-fMRI-NFB to target emotion regulation. We assessed 41 out of 4001 original studies for methodological quality and risk of bias and synthesised concerning the frequency of significant rt-fMRI-NFB-related effects on the neural and behaviour level. Successful modulation of brain activity was reported in between 25 and 50 percent of study samples, while neural effects in clinical samples were more diverse than in healthy samples. Interestingly, the frequency of rt-fMRI-NFB-related behavioural improvement was over 75 percent in clinical samples, while healthy samples showed behavioural improvements between 0 and 25 percent. Concerning clinical subsamples, rt-fMRI-NFB-related behavioural improvement was observed in up to 100 percent of major depressive disorder (MDD) and post-traumatic stress disorder (PTSD) samples. Substance use samples showed behavioural benefits ranging between 50 and 75 percent. Neural effects appeared to be less frequent than behavioural improvements: most neural outcomes ranged between 25 and 50 percent for MDD and substance use and between 0 and 25 percent for PTSD. Using multiple individualised regions of interest (ROIs) for rt-fMRI-NFB training resulted in more frequent behavioural benefits than rt-fMRI-NFB solely based on the amygdala or the prefrontal cortex. While a significant improvement in behavioural outcomes was reported in most clinical studies, the study protocols were heterogeneous, which limits the current evaluation of rt-fMRI-NFB as a putative treatment for emotional dysregulation.
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Affiliation(s)
- Nadja Tschentscher
- Section of Clinical Psychology and Psychophysiology, Department of Psychiatry and Psychotherapy, LMU University Hospital, LMU Munich, Nußbaumstr. 7, 80336 Munich, Germany; (N.T.); (J.C.T.); (O.P.)
| | - Julia C. Tafelmaier
- Section of Clinical Psychology and Psychophysiology, Department of Psychiatry and Psychotherapy, LMU University Hospital, LMU Munich, Nußbaumstr. 7, 80336 Munich, Germany; (N.T.); (J.C.T.); (O.P.)
| | - Christian F. J. Woll
- Section of Clinical Psychology of Children and Adolescents, Department of Psychology and Educational Sciences, Ludwig Maximilian University of Munich, Leopoldstr. 13, 80802 Munich, Germany;
| | - Oliver Pogarell
- Section of Clinical Psychology and Psychophysiology, Department of Psychiatry and Psychotherapy, LMU University Hospital, LMU Munich, Nußbaumstr. 7, 80336 Munich, Germany; (N.T.); (J.C.T.); (O.P.)
| | - Maximilian Maywald
- Section of Clinical Psychology and Psychophysiology, Department of Psychiatry and Psychotherapy, LMU University Hospital, LMU Munich, Nußbaumstr. 7, 80336 Munich, Germany; (N.T.); (J.C.T.); (O.P.)
| | - Larissa Vierl
- Section of Clinical Psychology and Psychophysiology, Department of Psychiatry and Psychotherapy, LMU University Hospital, LMU Munich, Nußbaumstr. 7, 80336 Munich, Germany; (N.T.); (J.C.T.); (O.P.)
- Section of Clinical Psychology and Psychological Treatment, Department of Psychology and Educational Sciences, Ludwig Maximilian University of Munich, Leopoldstr. 13, 80802 Munich, Germany
| | - Katrin Breitenstein
- Section of Clinical Psychology and Psychophysiology, Department of Psychiatry and Psychotherapy, LMU University Hospital, LMU Munich, Nußbaumstr. 7, 80336 Munich, Germany; (N.T.); (J.C.T.); (O.P.)
| | - Susanne Karch
- Section of Clinical Psychology and Psychophysiology, Department of Psychiatry and Psychotherapy, LMU University Hospital, LMU Munich, Nußbaumstr. 7, 80336 Munich, Germany; (N.T.); (J.C.T.); (O.P.)
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Wang Y, Lin H, Liu X, Zhu B, He M, Chen C. Associations between capacity of cognitive control and sleep quality: a two-wave longitudinal study. Front Psychol 2024; 15:1391761. [PMID: 38952828 PMCID: PMC11216015 DOI: 10.3389/fpsyg.2024.1391761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Accepted: 06/05/2024] [Indexed: 07/03/2024] Open
Abstract
This longitudinal study explored the impact of the upper limit of cognitive control on the sleep quality of high school students. We collected data in two waves to examine four main variables: capacity of cognitive control (CCC), trait mindfulness, emotional distress and sleep quality. At the first time point (T1), trait mindfulness and emotional distress were measured by rating scales, and the CCC was evaluated by revised backward masking majority function task. Sleep quality was rated 5 months later (T2). The results indicated that: (1) the CCC was negatively correlated with trait mindfulness, and trait mindfulness was negatively correlated with emotional stress; (2) there was no simple mediation of either trait mindfulness or emotional distress in the relationship between CCC and sleep quality; (3) instead, the CCC was associated with poor sleep quality in a sequential mediation through trait mindfulness and then emotional stress. The research highlights the importance of trait mindfulness and emotional distress for addressing sleep problems in adolescents.
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Affiliation(s)
- Yongchun Wang
- School of Psychology, South China Normal University, Guangzhou, China
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, South China Normal University, Guangzhou, China
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, China
- Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
| | - Huanping Lin
- School of Psychology, South China Normal University, Guangzhou, China
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, South China Normal University, Guangzhou, China
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, China
- Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
| | - Xiqin Liu
- School of Foreign Languages, South China University of Technology, Guangzhou, China
| | - Bojia Zhu
- Department of Human Resource, Guangzhou Branch of China Mobile Group Guangdong Company Limited, Guangzhou, China
| | - Meihui He
- School of Psychology, South China Normal University, Guangzhou, China
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, South China Normal University, Guangzhou, China
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, China
- Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
| | - Caiqi Chen
- School of Psychology, South China Normal University, Guangzhou, China
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, South China Normal University, Guangzhou, China
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, China
- Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
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Costa T, Ferraro M, Manuello J, Camasio A, Nani A, Mancuso L, Cauda F, Fox PT, Liloia D. Activation Likelihood Estimation Neuroimaging Meta-Analysis: a Powerful Tool for Emotion Research. Psychol Res Behav Manag 2024; 17:2331-2345. [PMID: 38882233 PMCID: PMC11179639 DOI: 10.2147/prbm.s453035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 05/31/2024] [Indexed: 06/18/2024] Open
Abstract
Over the past two decades, functional magnetic resonance imaging (fMRI) has become the primary tool for exploring neural correlates of emotion. To enhance the reliability of results in understanding the complex nature of emotional experiences, researchers combine findings from multiple fMRI studies using coordinate-based meta-analysis (CBMA). As one of the most widely employed CBMA methods worldwide, activation likelihood estimation (ALE) is of great importance in affective neuroscience and neuropsychology. This comprehensive review provides an introductory guide for implementing the ALE method in emotion research, outlining the experimental steps involved. By presenting a case study about the emotion of disgust, with regard to both its core and social processing, we offer insightful commentary as to how ALE can enable researchers to produce consistent results and, consequently, fruitfully investigate the neural mechanisms underpinning emotions, facilitating further progress in this field.
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Affiliation(s)
- Tommaso Costa
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
- FOCUS Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Mario Ferraro
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
- FOCUS Laboratory, Department of Psychology, University of Turin, Turin, Italy
- Department of Physics, University of Turin, Turin, Italy
| | - Jordi Manuello
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
- FOCUS Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Alessia Camasio
- FOCUS Laboratory, Department of Psychology, University of Turin, Turin, Italy
- Department of Physics, University of Turin, Turin, Italy
| | - Andrea Nani
- FOCUS Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Lorenzo Mancuso
- FOCUS Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Franco Cauda
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
- FOCUS Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Donato Liloia
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
- FOCUS Laboratory, Department of Psychology, University of Turin, Turin, Italy
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Camacho-Téllez V, Castro MN, Wainsztein AE, Goldberg X, De Pino G, Costanzo EY, Cardoner N, Menchón JM, Soriano-Mas C, Guinjoan SM, Villarreal MF. Childhood adversity modulates structural brain changes in borderline personality but not in major depression disorder. Psychiatry Res Neuroimaging 2024; 340:111803. [PMID: 38460393 DOI: 10.1016/j.pscychresns.2024.111803] [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: 07/08/2023] [Revised: 11/24/2023] [Accepted: 02/20/2024] [Indexed: 03/11/2024]
Abstract
Adverse childhood experiences (ACEs) negatively affect the function and structure of emotion brain circuits, increasing the risk of various psychiatric disorders. It is unclear if ACEs show disorder specificity with respect to their effects on brain structure. We aimed to investigate whether the structural brain effects of ACEs differ between patients with major depression (MDD) and borderline personality disorder (BPD). These disorders share many symptoms but likely have different etiologies. To achieve our goal, we obtained structural 3T-MRI images from 20 healthy controls (HC), 19 MDD patients, and 18 BPD patients, and measured cortical thickness and subcortical gray matter volumes. We utilized the Adverse Childhood Experiences (ACE) questionnaire to quantify self-reported exposure to childhood trauma. Our findings suggest that individuals with MDD exhibit a smaller cortical thickness when compared to those with BPD. However, ACEs showed a significantly affected relationship with cortical thickness in BPD but not in MDD. ACEs were found to be associated with thinning in cortical regions involved in emotional behavior in BPD, whereas HC showed an opposite association. Our results suggest a potential mechanism of ACE effects on psychopathology involving changes in brain structure. These findings highlight the importance of early detection and intervention strategies.
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Affiliation(s)
- Vicente Camacho-Téllez
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta (Grupo INAAC), Instituto de Neurociencias Fleni-CONICET (INEU), Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina; Departamento de Salud Mental, Facultad de Medicina, Universidad de Buenos Aires (UBA), Argentina
| | - Mariana N Castro
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta (Grupo INAAC), Instituto de Neurociencias Fleni-CONICET (INEU), Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina; Departamento de Salud Mental, Facultad de Medicina, Universidad de Buenos Aires (UBA), Argentina.
| | - Agustina E Wainsztein
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta (Grupo INAAC), Instituto de Neurociencias Fleni-CONICET (INEU), Argentina; Servicio de Psiquiatría, Fleni, Argentina
| | - Ximena Goldberg
- Mental Health Department, Institut d'Investigació i Innovació Parc Taulí I3PT, Universitat Autònoma de Barcelona, Sabadell, Spain; CIBERSAM, Carlos III Health Institute, Madrid, Spain; ISGlobal, Barcelona, Spain
| | - Gabriela De Pino
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta (Grupo INAAC), Instituto de Neurociencias Fleni-CONICET (INEU), Argentina; Laboratorio de Neuroimágenes, Departamento de Imágenes, Fleni, Argentina; Escuela de Ciencia y Tecnología, Universidad Nacional de San Martín, Argentina
| | - Elsa Y Costanzo
- Departamento de Salud Mental, Facultad de Medicina, Universidad de Buenos Aires (UBA), Argentina; Servicio de Psiquiatría, Fleni, Argentina
| | - Narcís Cardoner
- CIBERSAM, Carlos III Health Institute, Madrid, Spain; Sant Pau Mental Health Research Group, Institut d'Investigació Biomèdica Sant Pau (IIB-Sant Pau), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain; Department of Psychiatry and Forensic Medicine, School of Medicine Bellaterra, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - José M Menchón
- CIBERSAM, Carlos III Health Institute, Madrid, Spain; Bellvitge Biomedical Research Institute-IDIBELL, Department of Psychiatry, Bellvitge University Hospital, Barcelona, Spain; Department of Clinical Sciences, Bellvitge Campus, University of Barcelona, Barcelona, Spain
| | - Carles Soriano-Mas
- CIBERSAM, Carlos III Health Institute, Madrid, Spain; Bellvitge Biomedical Research Institute-IDIBELL, Department of Psychiatry, Bellvitge University Hospital, Barcelona, Spain; Department of Social Psychology and Quantitative Psychology, Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | - Salvador M Guinjoan
- Laureate Institute for Brain Research, Tulsa, USA; Department of Psychiatry, Health Sciences Center, Oklahoma University, and Oxley College, Tulsa University, Tulsa, Oklahoma, USA
| | - Mirta F Villarreal
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta (Grupo INAAC), Instituto de Neurociencias Fleni-CONICET (INEU), Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina; Departamento de Física, Facultad de Ciencias Exactas y Naturales, UBA, Argentina
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Dai P, Shi Y, Lu D, Zhou Y, Luo J, He Z, Chen Z, Zou B, Tang H, Huang Z, Liao S. Classification of recurrent major depressive disorder using a residual denoising autoencoder framework: Insights from large-scale multisite fMRI data. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 247:108114. [PMID: 38447315 DOI: 10.1016/j.cmpb.2024.108114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 02/14/2024] [Accepted: 03/01/2024] [Indexed: 03/08/2024]
Abstract
BACKGROUND AND OBJECTIVE Recurrent major depressive disorder (rMDD) has a high recurrence rate, and symptoms often worsen with each episode. Classifying rMDD using functional magnetic resonance imaging (fMRI) can enhance understanding of brain activity and aid diagnosis and treatment of this disorder. METHODS We developed a Residual Denoising Autoencoder (Res-DAE) framework for the classification of rMDD. The functional connectivity (FC) was extracted from fMRI data as features. The framework addresses site heterogeneity by employing the Combat method to harmonize feature distribution differences. A feature selection method based on Fisher scores was used to reduce redundant information in the features. A data augmentation strategy using a Synthetic Minority Over-sampling Technique algorithm based on Extended Frobenius Norm measure was incorporated to increase the sample size. Furthermore, a residual module was integrated into the autoencoder network to preserve important features and improve the classification accuracy. RESULTS We tested our framework on a large-scale, multisite fMRI dataset, which includes 189 rMDD patients and 427 healthy controls. The Res-DAE achieved an average accuracy of 75.1 % (sensitivity = 69 %, specificity = 77.8 %) in cross-validation, thereby outperforming comparison methods. In a larger dataset that also includes first-episode depression (comprising 832 MDD patients and 779 healthy controls), the accuracy reached 70 %. CONCLUSIONS We proposed a deep learning framework that can effectively classify rMDD and 33 identify the altered FC associated with rMDD. Our study may reveal changes in brain function 34 associated with rMDD and provide assistance for the diagnosis and treatment of rMDD.
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Affiliation(s)
- Peishan Dai
- School of Computer Science and Engineering, Central South University, Changsha, Hunan 410083, China.
| | - Yun Shi
- School of Computer Science and Engineering, Central South University, Changsha, Hunan 410083, China
| | - Da Lu
- School of Computer Science and Engineering, Central South University, Changsha, Hunan 410083, China
| | - Ying Zhou
- School of Computer Science and Engineering, Central South University, Changsha, Hunan 410083, China
| | - Jialin Luo
- School of Computer Science and Engineering, Central South University, Changsha, Hunan 410083, China
| | - Zhuang He
- School of Computer Science and Engineering, Central South University, Changsha, Hunan 410083, China
| | - Zailiang Chen
- School of Computer Science and Engineering, Central South University, Changsha, Hunan 410083, China
| | - Beiji Zou
- School of Computer Science and Engineering, Central South University, Changsha, Hunan 410083, China
| | - Hui Tang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410083, China
| | - Zhongchao Huang
- Department of Biomedical Engineering, School of Basic Medical Science, Central South University, Changsha, Hunan 410083, China
| | - Shenghui Liao
- School of Computer Science and Engineering, Central South University, Changsha, Hunan 410083, China
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Pilmeyer J, Lamerichs R, Ramsaransing F, Jansen JFA, Breeuwer M, Zinger S. Improved clinical outcome prediction in depression using neurodynamics in an emotional face-matching functional MRI task. Front Psychiatry 2024; 15:1255370. [PMID: 38585483 PMCID: PMC10996064 DOI: 10.3389/fpsyt.2024.1255370] [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: 07/08/2023] [Accepted: 03/06/2024] [Indexed: 04/09/2024] Open
Abstract
Introduction Approximately one in six people will experience an episode of major depressive disorder (MDD) in their lifetime. Effective treatment is hindered by subjective clinical decision-making and a lack of objective prognostic biomarkers. Functional MRI (fMRI) could provide such an objective measure but the majority of MDD studies has focused on static approaches, disregarding the rapidly changing nature of the brain. In this study, we aim to predict depression severity changes at 3 and 6 months using dynamic fMRI features. Methods For our research, we acquired a longitudinal dataset of 32 MDD patients with fMRI scans acquired at baseline and clinical follow-ups 3 and 6 months later. Several measures were derived from an emotion face-matching fMRI dataset: activity in brain regions, static and dynamic functional connectivity between functional brain networks (FBNs) and two measures from a wavelet coherence analysis approach. All fMRI features were evaluated independently, with and without demographic and clinical parameters. Patients were divided into two classes based on changes in depression severity at both follow-ups. Results The number of coherence clusters (nCC) between FBNs, reflecting the total number of interactions (either synchronous, anti-synchronous or causal), resulted in the highest predictive performance. The nCC-based classifier achieved 87.5% and 77.4% accuracy for the 3- and 6-months change in severity, respectively. Furthermore, regression analyses supported the potential of nCC for predicting depression severity on a continuous scale. The posterior default mode network (DMN), dorsal attention network (DAN) and two visual networks were the most important networks in the optimal nCC models. Reduced nCC was associated with a poorer depression course, suggesting deficits in sustained attention to and coping with emotion-related faces. An ensemble of classifiers with demographic, clinical and lead coherence features, a measure of dynamic causality, resulted in a 3-months clinical outcome prediction accuracy of 81.2%. Discussion The dynamic wavelet features demonstrated high accuracy in predicting individual depression severity change. Features describing brain dynamics could enhance understanding of depression and support clinical decision-making. Further studies are required to evaluate their robustness and replicability in larger cohorts.
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Affiliation(s)
- Jesper Pilmeyer
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Department of Research and Development, Epilepsy Centre Kempenhaeghe, Heeze, Netherlands
| | - Rolf Lamerichs
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Department of Research and Development, Epilepsy Centre Kempenhaeghe, Heeze, Netherlands
- Department of Medical Image Acquisitions, Philips Research, Eindhoven, Netherlands
| | - Faroeq Ramsaransing
- Department of Research and Development, Epilepsy Centre Kempenhaeghe, Heeze, Netherlands
- Department of Psychiatry, Amsterdam University Medical Center, Amsterdam, Netherlands
| | - Jacobus F. A. Jansen
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Department of Radiology and Nuclear Medicine, Maastricht University, Maastricht, Netherlands
- Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
| | - Marcel Breeuwer
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Department of Magnetic Resonance Research & Development - Clinical Science, Philips Healthcare, Best, Netherlands
| | - Svitlana Zinger
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Department of Research and Development, Epilepsy Centre Kempenhaeghe, Heeze, Netherlands
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Reyes-Lizaola S, Luna-Zarate U, Tendilla-Beltrán H, Morales-Medina JC, Flores G. Structural and biochemical alterations in dendritic spines as key mechanisms for severe mental illnesses. Prog Neuropsychopharmacol Biol Psychiatry 2024; 129:110876. [PMID: 37863171 DOI: 10.1016/j.pnpbp.2023.110876] [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: 08/01/2023] [Revised: 10/11/2023] [Accepted: 10/12/2023] [Indexed: 10/22/2023]
Abstract
Severe mental illnesses (SMI) collectively affect approximately 20% of the global population, as estimated by the World Health Organization (WHO). Despite having diverse etiologies, clinical symptoms, and pharmacotherapies, these diseases share a common pathophysiological characteristic: the misconnection of brain areas involved in reality perception, executive control, and cognition, including the corticolimbic system. Dendritic spines play a crucial role in excitatory neurotransmission within the central nervous system. These small structures exhibit remarkable plasticity, regulated by factors such as neurotransmitter tone, neurotrophic factors, and innate immunity-related molecules, and other mechanisms - all of which are associated with the pathophysiology of SMI. However, studying dendritic spine mechanisms in both healthy and pathological conditions in patients is fraught with technical limitations. This is where animal models related to these diseases become indispensable. They have played a pivotal role in elucidating the significance of dendritic spines in SMI. In this review, the information regarding the potential role of dendritic spines in SMI was summarized, drawing from clinical and animal model reports. Also, the implications of targeting dendritic spine-related molecules for SMI treatment were explored. Specifically, our focus is on major depressive disorder and the neurodevelopmental disorders schizophrenia and autism spectrum disorder. Abundant clinical and basic research has studied the functional and structural plasticity of dendritic spines in these diseases, along with potential pharmacological targets that modulate the dynamics of these structures. These targets may be associated with the clinical efficacy of the pharmacotherapy.
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Affiliation(s)
- Sebastian Reyes-Lizaola
- Departamento de Ciencias de la Salud, Licenciatura en Medicina, Universidad Popular del Estado de Puebla (UPAEP), Puebla, Mexico
| | - Ulises Luna-Zarate
- Departamento de Ciencias de la Salud, Licenciatura en Medicina, Universidad de las Américas Puebla (UDLAP), Puebla, Mexico
| | - Hiram Tendilla-Beltrán
- Laboratorio de Neuropsiquiatría, Instituto de Fisiología, Benemérita Universidad Autónoma de Puebla (BUAP), Puebla, Mexico
| | - Julio César Morales-Medina
- Centro de Investigación en Reproducción Animal, CINVESTAV-Universidad Autónoma de Tlaxcala, Tlaxcala, Mexico
| | - Gonzalo Flores
- Laboratorio de Neuropsiquiatría, Instituto de Fisiología, Benemérita Universidad Autónoma de Puebla (BUAP), Puebla, Mexico.
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Wen X, Han B, Li H, Dou F, Wei G, Hou G, Wu X. Unbalanced amygdala communication in major depressive disorder. J Affect Disord 2023; 329:192-206. [PMID: 36841299 DOI: 10.1016/j.jad.2023.02.091] [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: 08/19/2022] [Revised: 02/06/2023] [Accepted: 02/19/2023] [Indexed: 02/27/2023]
Abstract
BACKGROUND Previous studies suggested an association between functional alteration of the amygdala and typical major depressive disorder (MDD) symptoms. Examining whether and how the interaction between the amygdala and regions/functional networks is altered in patients with MDD is important for understanding its neural basis. METHODS Resting-state functional magnetic resonance imaging data were recorded from 67 patients with MDD and 74 age- and sex-matched healthy controls (HCs). A framework for large-scale network analysis based on seed mappings of amygdala sub-regions, using a multi-connectivity-indicator strategy (cross-correlation, total interdependencies (TI), Granger causality (GC), and machine learning), was employed. Multiple indicators were compared between the two groups. The altered indicators were ranked in a supporting-vector machine-based procedure and associated with the Hamilton Rating Scale for Depression scores. RESULTS The amygdala connectivity with the default mode network and ventral attention network regions was enhanced and that with the somatomotor network, dorsal frontoparietal network, and putamen regions in patients with MDD was reduced. The machine learning analysis highlighted altered indicators that were most conducive to the classification between the two groups. LIMITATIONS Most patients with MDD received different pharmacological treatments. It is difficult to illustrate the medication state's effect on the alteration model because of its complex situation. CONCLUSION The results indicate an unbalanced interaction model between the amygdala and functional networks and regions essential for various emotional and cognitive functions. The model can help explain potential aberrancy in the neural mechanisms that underlie the functional impairments observed across various domains in patients with MDD.
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Affiliation(s)
- Xiaotong Wen
- Department of Psychology, Renmin University of China, Beijing 100872, China; Laboratory of the Department of Psychology, Renmin University of China, Beijing 100872, China; Interdisciplinary Platform of Philosophy and Cognitive Science, Renmin University of China, 100872, China.
| | - Bukui Han
- Department of Psychology, Renmin University of China, Beijing 100872, China; Laboratory of the Department of Psychology, Renmin University of China, Beijing 100872, China
| | - Huanhuan Li
- Department of Psychology, Renmin University of China, Beijing 100872, China; Laboratory of the Department of Psychology, Renmin University of China, Beijing 100872, China; Interdisciplinary Platform of Philosophy and Cognitive Science, Renmin University of China, 100872, China.
| | - Fengyu Dou
- Department of Psychology, Renmin University of China, Beijing 100872, China
| | - Guodong Wei
- Department of Psychology, Renmin University of China, Beijing 100872, China
| | - Gangqiang Hou
- Shenzhen Mental Health Center, Shenzhen Kangning Hospital, Shenzhen 518020, China
| | - Xia Wu
- School of Artificial Intelligence, Beijing Normal University, Beijing 100093, China
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Yan Y, Li M, Jia H, Fu L, Qiu J, Yang W. Amygdala-based functional connectivity mediates the relationship between thought control ability and trait anxiety. Brain Cogn 2023; 168:105976. [PMID: 37086555 DOI: 10.1016/j.bandc.2023.105976] [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: 01/12/2023] [Revised: 04/02/2023] [Accepted: 04/04/2023] [Indexed: 04/24/2023]
Abstract
Thought control ability (TCA) refers to the ability to exclude unwanted thoughts. There has been consistent evidence on the protective effect of TCA on anxiety, that higher TCA is associated with lower anxiety. However, the underlying neural mechanism remains unclear. In this study, with a large sample (N = 495), we investigated how seed-based resting-state functional connectivity (RSFC) mediates the relationship between TCA and anxiety. Our behaviour results replicated previous findings that TCA is negatively associated with trait anxiety after controlling for gender, age, and depression. More importantly, the RSFC results revealed that TCA is negatively associated with the left amygdala - left frontal pole (LA-LFP), left amygdala - left inferior temporal gyrus (LA-LITG), and left hippocampus - left inferior frontal gyrus (LH-LIFG) connectivity. In addition, a mediation analysis demonstrated that the LA-LFP and LA-LITG connectivity in particular mediated the influence of TCA on trait anxiety. Overall, our study extends previous research by revealing the neural bases underlying the protective effect of TCA on anxiety and pinpointing specific mediating RSFC pathways. Future studies could explore whether targeted TCA training (behavioural or neural) can help alleviate anxiety.
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Affiliation(s)
- Yuchi Yan
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University (SWU), Chongqing 400715, China
| | - Min Li
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University (SWU), Chongqing 400715, China
| | - Hui Jia
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University (SWU), Chongqing 400715, China
| | - Lei Fu
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University (SWU), Chongqing 400715, China
| | - Jiang Qiu
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University (SWU), Chongqing 400715, China.
| | - Wenjing Yang
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University (SWU), Chongqing 400715, China.
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Brain function changes reveal rapid antidepressant effects of nitrous oxide for treatment-resistant depression:Evidence from task-state EEG. Psychiatry Res 2023; 322:115072. [PMID: 36791487 DOI: 10.1016/j.psychres.2023.115072] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 01/15/2023] [Accepted: 01/22/2023] [Indexed: 01/28/2023]
Abstract
Nitrous oxide has rapid antidepressant effects in patients with treatment-resistant depression (TRD), but its underlying mechanisms of therapeutic actions are not well understood. Moreover, most of the current studies lack objective biological indicators to evaluate the changes of nitrous oxide-induced brain function for TRD. Therefore, this study assessed the effect of nitrous oxide on brain function for TRD based on event-related potential (ERP) components and functional connectivity networks (FCNs) methods. In this randomized, longitudinal, placebo-controlled trial, all TRD participants were divided into two groups to receive either a 1-hour inhalation of nitrous oxide or a placebo treatment, and they took part in the same task-state electroencephalogram (EEG) experiment before and after treatment. The experimental results showed that nitrous oxide improved depressive symptoms better than placebo in terms of 17-Hamilton Depression Rating Scale score (HAMD-17). Statistical analysis based on ERP components showed that nitrous oxide-induced significant differences in amplitude and latency of N1, P1, N2, P2. In addition, increased brain functional connectivity was found after nitrous oxide treatment. And the change of network metrics has a significant correlation with decreased depressive symptoms. These findings may suggest that nitrous oxide improves depression symptoms for TRD by modifying brain function.
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13
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Li K, Yang J, Becker B, Li X. Functional near-infrared spectroscopy neurofeedback of dorsolateral prefrontal cortex enhances human spatial working memory. NEUROPHOTONICS 2023; 10:025011. [PMID: 37275655 PMCID: PMC10234406 DOI: 10.1117/1.nph.10.2.025011] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 04/06/2023] [Accepted: 05/11/2023] [Indexed: 06/07/2023]
Abstract
Significance Spatial working memory (SWM) is essential for daily life and deficits in this domain represent a common impairment across aging and several mental disorders. Impaired SWM has been closely linked to dysregulations in dorsolateral prefrontal cortex (DLPFC) activation. Aim The present study evaluates the feasibility and maintenance of functional near-infrared spectroscopy neurofeedback (fNIRS-NF) training of the DLPFC to enhance SWM in healthy individuals using a real-time fNIRS-NF platform developed by the authors. Approach We used a randomized sham-controlled between-subject fNIRS-NF design with 60 healthy subjects as a sample. Training-induced changes in the DLPFC, SWM, and attention performance served as primary outcomes. Results Feedback from the target channel significantly increased regional-specific DLPFC activation over the fNIRS-NF training compared to sham NF. A significant group difference in NF-induced frontoparietal connectivity was observed. Compared to the control group, the experimental group demonstrated significantly improved SWM and attention performance that were maintained for 1 week. Furthermore, a mediation analysis demonstrated that increased DLPFC activation mediated the effects of fNIRS-NF treatment on better SWM performance. Conclusions The present results demonstrated that successful self-regulation of DLPFC activation may represent a long-lasting intervention to improve human SWM and has the potential for further applications.
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Affiliation(s)
- Keshuang Li
- East China Normal University, School of Psychology and Cognitive Science, Affiliated Mental Health Center, Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, Shanghai, China
| | - Jinhao Yang
- East China Normal University, School of Psychology and Cognitive Science, Affiliated Mental Health Center, Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, Shanghai, China
| | - Benjamin Becker
- University of Electronic Science and Technology of China, The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Chengdu, China
| | - Xianchun Li
- East China Normal University, School of Psychology and Cognitive Science, Affiliated Mental Health Center, Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, Shanghai, China
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14
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Zhang Q, Li X, Yan H, Wang Y, Ou Y, Yu Y, Liang J, Liao H, Wu W, Mai X, Xie G, Guo W. Associations between abnormal spontaneous neural activity and clinical variables, eye movements, and event-related potential indicators in major depressive disorder. Front Neurosci 2023; 16:1056868. [PMID: 36711124 PMCID: PMC9875062 DOI: 10.3389/fnins.2022.1056868] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 12/26/2022] [Indexed: 01/13/2023] Open
Abstract
Background This study aimed to investigate the correlations between abnormal spontaneous neural activity measured with fractional amplitude of low-frequency fluctuations (fALFF) and clinical variables, eye movements, and event-related potential indicators in patients with major depressive disorder (MDD). Methods We recruited 42 patients with MDD and 42 healthy controls (HCs) and collected their clinical variables, eye movement, event-related potential, and resting-state functional magnetic resonance imaging (rs-fMRI) data. The fALFF, support vector machine (SVM), and correlation analysis were used to analyze the data. Results The results of the study showed that the fALFF values of the sensorimotor network, including the right middle temporal gyrus, right cerebellar Crus2, left occipital gyrus, and left middle temporal gyrus, were significantly higher compared to HCs. Correlation analysis showed that the abnormal fALFF value of the right cerebellar Crus2 was inversely correlated with the active coping scores of the Simplified Coping Style Questionnaire in the patients (r = -0.307, p = 0.048). No correlation was observed between abnormal fALFF values and other clinical symptoms, neuropsychological tests, eye movements, and event-related potential-related indicators in patients with MDD. fALFF values in the left middle temporal gyrus could be used to distinguish patients with MDD from HCs with an accuracy of 78.57%. Conclusions Patients with MDD exhibited enhanced spontaneous neural activity in the sensorimotor network. No associations were found between abnormal spontaneous neural activity and clinical variables, eye movements, and event-related potential related indicators in MDD.
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Affiliation(s)
- Qinqin Zhang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Xiaoling Li
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Haohao Yan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Yun Wang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Yangpan Ou
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Yang Yu
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Jiaquan Liang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Hairong Liao
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Wanting Wu
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Xiancong Mai
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Guojun Xie
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China,*Correspondence: Guojun Xie ✉
| | - Wenbin Guo
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China,Wenbin Guo ✉
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15
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Altered Functional Connectivity and Complexity in Major Depressive Disorder after Musical Stimulation. Brain Sci 2022; 12:brainsci12121680. [PMID: 36552139 PMCID: PMC9775252 DOI: 10.3390/brainsci12121680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 11/24/2022] [Accepted: 11/30/2022] [Indexed: 12/13/2022] Open
Abstract
Major depressive disorder (MDD) is a common mental illness. This study used electroencephalography (EEG) to explore the effects of music therapy on brain networks in MDD patients and to elucidate changes in functional brain connectivity in subjects before and after musical stimulation. EEG signals were collected from eight MDD patients and eight healthy controls. The phase locking value was adopted to calculate the EEG correlation of different channels in different frequency bands. Correlation matrices and network topologies were studied to analyze changes in functional connectivity between brain regions. The results of the experimental analysis found that the connectivity of the delta and beta bands decreased, while the connectivity of the alpha band increased. Regarding the characteristics of the EEG functional network, the average clustering coefficient, characteristic path length and degree of each node in the delta band decreased significantly after musical stimulation, while the characteristic path length in the beta band increased significantly. Characterized by the average clustering coefficient and characteristic path length, the classification of depression and healthy controls reached 93.75% using a support vector machine.
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16
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Prediction of remission among patients with a major depressive disorder based on the resting-state functional connectivity of emotion regulation networks. Transl Psychiatry 2022; 12:391. [PMID: 36115833 PMCID: PMC9482642 DOI: 10.1038/s41398-022-02152-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 08/29/2022] [Accepted: 09/02/2022] [Indexed: 11/08/2022] Open
Abstract
The prediction of antidepressant response is critical for psychiatrists to select the initial antidepressant drug for patients with major depressive disorders (MDD). The implicated brain networks supporting emotion regulation (ER) are critical in the pathophysiology of MDD and the prediction of antidepressant response. Therefore, the primary aim of the current study was to identify the neuroimaging biomarkers for the prediction of remission in patients with MDD based on the resting-state functional connectivity (rsFC) of the ER networks. A total of 81 unmedicated adult MDD patients were investigated and they underwent resting-state functional magnetic resonance imagining (fMRI) scans. The patients were treated with escitalopram for 12 weeks. The 17-item Hamilton depression rating scale was used for assessing remission. The 36 seed regions from predefined ER networks were selected and the rsFC matrix was caculated for each participant. The support vector machine algorithm was employed to construct prediction model, which separated the patients with remission from those with non-remission. And leave-one-out cross-validation and the area under the curve (AUC) of the receiver operating characteristic were used for evaluating the performance of the model. The accuracy of the prediction model was 82.08% (sensitivity = 71.43%, specificity = 89.74%, AUC = 0.86). The rsFC between the left medial superior frontal gyrus and the right inferior frontal gyrus as well as the precuneus were the features with the highest discrimination ability in predicting remission from escitalopram among the MDD patients. Results from our study demonstrated that rsFC of the ER brain networks are potential predictors for the response of antidepressant drugs. The trial name: appropriate technology study of MDD diagnosis and treatment based on objective indicators and measurement. URL: http://www.chictr.org.cn/showproj.aspx?proj=21377 . Registration number: ChiCTR-OOC-17012566.
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17
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Pereira JA, Ray A, Rana M, Silva C, Salinas C, Zamorano F, Irani M, Opazo P, Sitaram R, Ruiz S. A real-time fMRI neurofeedback system for the clinical alleviation of depression with a subject-independent classification of brain states: A proof of principle study. Front Hum Neurosci 2022; 16:933559. [PMID: 36092645 PMCID: PMC9452730 DOI: 10.3389/fnhum.2022.933559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Accepted: 07/25/2022] [Indexed: 11/13/2022] Open
Abstract
Most clinical neurofeedback studies based on functional magnetic resonance imaging use the patient's own neural activity as feedback. The objective of this study was to create a subject-independent brain state classifier as part of a real-time fMRI neurofeedback (rt-fMRI NF) system that can guide patients with depression in achieving a healthy brain state, and then to examine subsequent clinical changes. In a first step, a brain classifier based on a support vector machine (SVM) was trained from the neural information of happy autobiographical imagery and motor imagery blocks received from a healthy female participant during an MRI session. In the second step, 7 right-handed female patients with mild or moderate depressive symptoms were trained to match their own neural activity with the neural activity corresponding to the “happiness emotional brain state” of the healthy participant. The training (4 training sessions over 2 weeks) was carried out using the rt-fMRI NF system guided by the brain-state classifier we had created. Thus, the informative voxels previously obtained in the first step, using SVM classification and Effect Mapping, were used to classify the Blood-Oxygen-Level Dependent (BOLD) activity of the patients and converted into real-time visual feedback during the neurofeedback training runs. Improvements in the classifier accuracy toward the end of the training were observed in all the patients [Session 4–1 Median = 6.563%; Range = 4.10–27.34; Wilcoxon Test (0), 2-tailed p = 0.031]. Clinical improvement also was observed in a blind standardized clinical evaluation [HDRS CE2-1 Median = 7; Range 2 to 15; Wilcoxon Test (0), 2-tailed p = 0.016], and in self-report assessments [BDI-II CE2-1 Median = 8; Range 1–15; Wilcoxon Test (0), 2-tailed p = 0.031]. In addition, the clinical improvement was still present 10 days after the intervention [BDI-II CE3-2_Median = 0; Range −1 to 2; Wilcoxon Test (0), 2-tailed p = 0.50/ HDRS CE3-2 Median = 0; Range −1 to 2; Wilcoxon Test (0), 2-tailed p = 0.625]. Although the number of participants needs to be increased and a control group included to confirm these findings, the results suggest a novel option for neural modulation and clinical alleviation in depression using noninvasive stimulation technologies.
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Affiliation(s)
- Jaime A. Pereira
- Departamento de Psiquiatría, Facultad de Medicina, Centro Interdisciplinario de Neurociencias, Pontificia Universidad Católica de Chile, Santiago, Chile
- Laboratory for Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Andreas Ray
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Mohit Rana
- Laboratory for Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica de Chile, Santiago, Chile
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Claudio Silva
- Unidad de Imágenes Cuantitativas Avanzadas, Departamento de Imágenes, Facultad de Medicina, Clínica Alemana- Universidad del Desarrollo, Santiago, Chile
| | - Cesar Salinas
- Unidad de Imágenes Cuantitativas Avanzadas, Departamento de Imágenes, Facultad de Medicina, Clínica Alemana- Universidad del Desarrollo, Santiago, Chile
| | - Francisco Zamorano
- Unidad de Imágenes Cuantitativas Avanzadas, Departamento de Imágenes, Facultad de Medicina, Clínica Alemana- Universidad del Desarrollo, Santiago, Chile
- Laboratorio de Neurociencia Social y Neuromodulación, Centro de Investigación en Complejidad Social (neuroCICS), Facultad de Gobierno, Universidad del Desarrollo, Santiago, Chile
| | - Martin Irani
- Departamento de Psiquiatría, Facultad de Medicina, Centro Interdisciplinario de Neurociencias, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Patricia Opazo
- Departamento de Psiquiatría, Facultad de Medicina, Centro Interdisciplinario de Neurociencias, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Ranganatha Sitaram
- Departamento de Psiquiatría, Facultad de Medicina, Centro Interdisciplinario de Neurociencias, Pontificia Universidad Católica de Chile, Santiago, Chile
- Laboratory for Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica de Chile, Santiago, Chile
- Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, TN, United States
- *Correspondence: Ranganatha Sitaram
| | - Sergio Ruiz
- Departamento de Psiquiatría, Facultad de Medicina, Centro Interdisciplinario de Neurociencias, Pontificia Universidad Católica de Chile, Santiago, Chile
- Laboratory for Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica de Chile, Santiago, Chile
- Sergio Ruiz
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Chen J, Luo Q, Li Y, Wu Z, Lin X, Yao J, Yu H, Nie H, Du Y, Peng H, Wu H. Intrinsic brain abnormalities in female major depressive disorder patients with childhood trauma: A resting-state functional magnetic resonance imaging study. Front Neurosci 2022; 16:930997. [PMID: 36017185 PMCID: PMC9395929 DOI: 10.3389/fnins.2022.930997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 07/11/2022] [Indexed: 11/29/2022] Open
Abstract
Objective Childhood trauma is a strong predictor of major depressive disorder (MDD). Women are more likely to develop MDD than men. However, the neural basis of female MDD patients with childhood trauma remains unclear. We aimed to identify the specific brain regions that are associated with female MDD patients with childhood trauma. Methods We recruited 16 female MDD patients with childhood trauma, 16 female MDD patients without childhood trauma, and 20 age- and education level-matched healthy controls. All participants underwent resting-state functional magnetic resonance imaging (MRI). Regional brain activity was evaluated as the amplitude of low-frequency fluctuation (ALFF). Furthermore, functional connectivity (FC) analyses were performed on areas with altered ALFF to explore alterations in FC patterns. Results There was increased ALFF in the left middle frontal gyrus (MFG) and the right postcentral gyrus (PoCG) in MDD with childhood trauma compared with MDD without childhood trauma. The areas with significant ALFF discrepancies were selected as seeds for the FC analyses. There was increased FC between the left MFG and the bilateral putamen gyrus. Moreover, ALFF values were correlated with childhood trauma severity. Conclusion Our findings revealed abnormal intrinsic brain activity and FC patterns in female MDD patients with childhood trauma, which provides new possibilities for exploring the pathophysiology of this disorder in women.
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Affiliation(s)
- Juran Chen
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Qianyi Luo
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yuhong Li
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Zhiyao Wu
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Xinyi Lin
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jiazheng Yao
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Huiwen Yu
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Huiqin Nie
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yingying Du
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Hongjun Peng
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- *Correspondence: Hongjun Peng,
| | - Huawang Wu
- Department of Radiology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Huawang Wu,
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19
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Pilmeyer J, Huijbers W, Lamerichs R, Jansen JFA, Breeuwer M, Zinger S. Functional MRI in major depressive disorder: A review of findings, limitations, and future prospects. J Neuroimaging 2022; 32:582-595. [PMID: 35598083 PMCID: PMC9540243 DOI: 10.1111/jon.13011] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 05/04/2022] [Accepted: 05/04/2022] [Indexed: 02/02/2023] Open
Abstract
Objective diagnosis and prognosis in major depressive disorder (MDD) remains a challenge due to the absence of biomarkers based on physiological parameters or medical tests. Numerous studies have been conducted to identify functional magnetic resonance imaging‐based biomarkers of depression that either objectively differentiate patients with depression from healthy subjects, predict personalized treatment outcome, or characterize biological subtypes of depression. While there are some findings of consistent functional biomarkers, there is still lack of robust data acquisition and analysis methodology. According to current findings, primarily, the anterior cingulate cortex, prefrontal cortex, and default mode network play a crucial role in MDD. Yet, there are also less consistent results and the involvement of other regions or networks remains ambiguous. We further discuss image acquisition, processing, and analysis limitations that might underlie these inconsistencies. Finally, the current review aims to address and discuss possible remedies and future opportunities that could improve the search for consistent functional imaging biomarkers of depression. Novel acquisition techniques, such as multiband and multiecho imaging, and neural network‐based cleaning approaches can enhance the signal quality in limbic and frontal regions. More comprehensive analyses, such as directed or dynamic functional features or the identification of biological depression subtypes, can improve objective diagnosis or treatment outcome prediction and mitigate the heterogeneity of MDD. Overall, these improvements in functional MRI imaging techniques, processing, and analysis could advance the search for biomarkers and ultimately aid patients with MDD and their treatment course.
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Affiliation(s)
- Jesper Pilmeyer
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.,Department of Research and Development, Epilepsy Centre Kempenhaeghe, Heeze, The Netherlands
| | - Willem Huijbers
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.,Philips Research, Eindhoven, The Netherlands
| | - Rolf Lamerichs
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.,Department of Research and Development, Epilepsy Centre Kempenhaeghe, Heeze, The Netherlands.,Philips Research, Eindhoven, The Netherlands
| | - Jacobus F A Jansen
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.,Department of Radiology and Nuclear Medicine, Maastricht University Medical Centre, Maastricht, The Netherlands.,School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Marcel Breeuwer
- Philips Healthcare, Best, The Netherlands.,Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Svitlana Zinger
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.,Department of Research and Development, Epilepsy Centre Kempenhaeghe, Heeze, The Netherlands
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20
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Luo Q, Yu H, Chen J, Lin X, Wu Z, Yao J, Li Y, Wu H, Peng H. Altered Variability and Concordance of Dynamic Resting-State Functional Magnetic Resonance Imaging Indices in Patients With Major Depressive Disorder and Childhood Trauma. Front Neurosci 2022; 16:852799. [PMID: 35615286 PMCID: PMC9124829 DOI: 10.3389/fnins.2022.852799] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 03/18/2022] [Indexed: 11/13/2022] Open
Abstract
Childhood trauma is a non-specific risk factor for major depressive disorder (MDD). resting-state functional magnetic resonance imaging (R-fMRI) studies have demonstrated changes in regional brain activity in patients with MDD who experienced childhood trauma. However, previous studies have mainly focused on static characteristics of regional brain activity. This study aimed to determine the specific brain regions associated with MDD with childhood trauma by performing temporal dynamic analysis of R-fMRI data in three groups of patients: patients with childhood trauma-associated MDD (n = 48), patients without childhood trauma-associated MDD (n = 30), and healthy controls (n = 103). Dynamics and concordance of R-fMRI indices were calculated and analyzed. In patients with childhood trauma-associated MDD, a lower dynamic amplitude of low-frequency fluctuations was found in the left lingual gyrus, whereas a lower dynamic degree of centrality was observed in the right lingual gyrus and right calcarine cortex. Patients with childhood trauma-associated MDD showed a lower voxel-wise concordance in the left middle temporal and bilateral calcarine cortices. Moreover, group differences (depressed or not) significantly moderated the relationship between voxel-wise concordance in the right calcarine cortex and childhood trauma history. Overall, patients with childhood trauma-associated MDD demonstrated aberrant variability and concordance in intrinsic brain activity. These aberrances may be an underlying neurobiological mechanism that explains MDD from the perspective of temporal dynamics.
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Affiliation(s)
- Qianyi Luo
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Huiwen Yu
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Juran Chen
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Xinyi Lin
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Zhiyao Wu
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jiazheng Yao
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yuhong Li
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Huawang Wu
- Department of Radiology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Hongjun Peng
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
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21
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Luo Q, Chen J, Li Y, Wu Z, Lin X, Yao J, Yu H, Peng H, Wu H. Altered regional brain activity and functional connectivity patterns in major depressive disorder: A function of childhood trauma or diagnosis? J Psychiatr Res 2022; 147:237-247. [PMID: 35066292 DOI: 10.1016/j.jpsychires.2022.01.038] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 01/10/2022] [Accepted: 01/13/2022] [Indexed: 12/26/2022]
Abstract
Childhood trauma (CT) is a non-specific risk factor for major depressive disorder (MDD). However, the neurobiological mechanisms of MDD with CT remain unclear. In the present study, we sought to determine the specific brain regions associated with CT and MDD etiology. Fractional amplitude of low-frequency fluctuation (fALFF) and functional connectivity (FC) analyses were performed to assess alterations of intrinsic brain activity in MDD with CT, MDD without CT, healthy controls with CT, and healthy controls without CT. Two-by-two factorial analyses were performed to examine the effects of the factors "MDD" and "CT" on fALFF and FC. Moderator analysis was used to explore whether the severity of depression moderated the relationship between CT and aberrant fALFF. We found that the etiological effects of MDD and CT exhibited negative impacts on brain dysfunction including altered fALFF in the left postcentral gyrus, left lingual gyrus, left paracentral lobule (PCL), and left cuneus. Decreased FC was observed in the following regions: (i) the left lingual gyrus seed and the left fusiform gyrus as well as the right calcarine cortex; (ii) the left PCL seed and the left supplementary motor area, left calcarine cortex, left precentral gyrus, and right cuneus; (iii) the left postcentral gyrus seed and left superior parietal lobule, right postcentral gyrus, and left precentral gyrus. Furthermore, the severity of depression acted as a moderator in the relationship between CT and aberrant fALFF in the left PCL. These data indicate that MDD patients with and without trauma exposure are clinically and neurobiologically distinct.
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Affiliation(s)
- Qianyi Luo
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510370, China
| | - Juran Chen
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510370, China
| | - Yuhong Li
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510370, China
| | - Zhiyao Wu
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510370, China
| | - Xinyi Lin
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510370, China
| | - Jiazheng Yao
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510370, China
| | - Huiwen Yu
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510370, China
| | - Hongjun Peng
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510370, China.
| | - Huawang Wu
- Department of Radiology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510370, China.
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22
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Current and Future Perspectives of the Cerebellum in Affective Neuroscience. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1378:303-313. [DOI: 10.1007/978-3-030-99550-8_19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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23
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Khodadadifar T, Soltaninejad Z, Ebneabbasi A, Eickhoff CR, Sorg C, Van Eimeren T, Vogeley K, Zarei M, Eickhoff SB, Tahmasian M. In search of convergent regional brain abnormality in cognitive emotion regulation: A transdiagnostic neuroimaging meta-analysis. Hum Brain Mapp 2021; 43:1309-1325. [PMID: 34826162 PMCID: PMC8837597 DOI: 10.1002/hbm.25722] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 10/29/2021] [Accepted: 11/01/2021] [Indexed: 01/28/2023] Open
Abstract
Ineffective use of adaptive cognitive strategies (e.g., reappraisal) to regulate emotional states is often reported in a wide variety of psychiatric disorders, suggesting a common characteristic across different diagnostic categories. However, the extent of shared neurobiological impairments is incompletely understood. This study, therefore, aimed to identify the transdiagnostic neural signature of disturbed reappraisal using the coordinate‐based meta‐analysis (CBMA) approach. Following the best‐practice guidelines for conducting neuroimaging meta‐analyses, we systematically searched PubMed, ScienceDirect, and Web of Science databases and tracked the references. Out of 1,608 identified publications, 32 whole‐brain neuroimaging studies were retrieved that compared brain activation in patients with psychiatric disorders and healthy controls during a reappraisal task. Then, the reported peak coordinates of group comparisons were extracted and several activation likelihood estimation (ALE) analyses were performed at three hierarchical levels to identify the potential spatial convergence: the global level (i.e., the pooled analysis and the analyses of increased/decreased activations), the experimental‐contrast level (i.e., the analyses of grouped data based on the regulation goal, stimulus valence, and instruction rule) and the disorder‐group level (i.e., the analyses across the experimental‐contrast level focused on increasing homogeneity of disorders). Surprisingly, none of our analyses provided significant convergent findings. This CBMA indicates a lack of transdiagnostic convergent regional abnormality related to reappraisal task, probably due to the complex nature of cognitive emotion regulation, heterogeneity of clinical populations, and/or experimental and statistical flexibility of individual studies.
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Affiliation(s)
- Tina Khodadadifar
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences, Tehran, Iran
| | - Zahra Soltaninejad
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran.,Cognitive and Brain Science Institute, Shahid Beheshti University, Tehran, Iran
| | - Amir Ebneabbasi
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
| | - Claudia R Eickhoff
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Center Jülich, Jülich, Germany.,Institute of Clinical Neuroscience and Medical Psychology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Institute of Neuroscience and Medicine, Structural and functional organization of the brain (INM-1), Research Center Jülich, Jülich, Germany
| | - Christian Sorg
- TUM-Neuroimaging Center (TUM-NIC), Klinikum Rechts der Isar, Technische Universität München, Munich, Germany.,Department of Neuroradiology, Klinikum Rechts der Isar, Technische Universität München, Munich, Germany.,Department of Psychiatry and Psychotherapy, Klinikum Rechts der Isar, Technische Universität München, Munich, Germany
| | - Thilo Van Eimeren
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany.,Department of Neurology, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
| | - Kai Vogeley
- Department of Psychiatry and Psychotherapy, University Hospital Cologne, Cologne, Germany.,Cognitive Neuroscience (INM-3), Institute of Neuroscience and Medicine, Research Center Jülich, Jülich, Germany
| | - Mojtaba Zarei
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Center Jülich, Jülich, Germany.,Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Masoud Tahmasian
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran.,Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Center Jülich, Jülich, Germany.,Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
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24
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Tang E, Jones C, Smith-MacDonald L, Brown MRG, Vermetten EHGJM, Brémault-Phillips S. Decreased Emotional Dysregulation Following Multi-Modal Motion-Assisted Memory Desensitization and Reconsolidation Therapy (3MDR): Identifying Possible Driving Factors in Remediation of Treatment-Resistant PTSD. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:12243. [PMID: 34831999 PMCID: PMC8621264 DOI: 10.3390/ijerph182212243] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 11/17/2021] [Accepted: 11/19/2021] [Indexed: 12/23/2022]
Abstract
Multi-modal motion-assisted memory desensitization and reconsolidation therapy (3MDR), an interactive, virtual reality-assisted, exposure-based intervention for PTSD, has shown promising results for treatment-resistant posttraumatic stress disorder (TR-PTSD) among military members (MMs) and veterans in randomized controlled trials (RCT). Previous research has suggested that emotional regulation (ER) and emotional dysregulation (ED) may be factors which are correlated with symptom severity and maintenance of TR-PTSD. This embedded mixed-methods pilot study (n = 9) sought to explore the impact of 3MDR on ER and ED of MMs and veterans. Difficulties in Emotional Regulation Scale (DERS-18) data were collected at baseline, prior to each session, and at one week, one month, and three months postintervention and analyzed. Qualitative data collected from sessions, debriefs, and follow-up interviews were transcribed and descriptively analyzed. Results demonstrated statistically significant decreases in DERS-18 scores from preintervention to postintervention at each timepoint. Qualitatively, participants perceived improvements in ER within specified DERS-18 domains. We describe how 3MDR's unique and novel approach addresses ED through cognitive-motor stimulation, narration, divergent thinking, reappraisal of aversive stimuli, dual-task processing, and reconsolidation of traumatic memories. More studies are needed to better understand the underlying neurobiological mechanisms by which 3MDR addresses ER and PTSD.
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Affiliation(s)
- Emily Tang
- Department of Occupational Therapy, Faculty of Rehabilitation Medicine, University of Alberta, Edmonton, AB T6G 2G4, Canada; (E.T.); (L.S.-M.)
- Heroes in Mind, Advocacy and Research Consortium (HiMARC), Faculty of Rehabilitation Medicine, University of Alberta, Edmonton, AB T6G 2G4, Canada; (C.J.); (M.R.G.B.)
- Neuroscience and Mental Health Institute (NMHI), University of Alberta, Edmonton, AB T6G 2E1, Canada
| | - Chelsea Jones
- Heroes in Mind, Advocacy and Research Consortium (HiMARC), Faculty of Rehabilitation Medicine, University of Alberta, Edmonton, AB T6G 2G4, Canada; (C.J.); (M.R.G.B.)
- Alberta Health Services, Edmonton, AB T5E 5R8, Canada
- Leiden University Medical Center, 2333 ZA Leiden, The Netherlands;
| | - Lorraine Smith-MacDonald
- Department of Occupational Therapy, Faculty of Rehabilitation Medicine, University of Alberta, Edmonton, AB T6G 2G4, Canada; (E.T.); (L.S.-M.)
- Heroes in Mind, Advocacy and Research Consortium (HiMARC), Faculty of Rehabilitation Medicine, University of Alberta, Edmonton, AB T6G 2G4, Canada; (C.J.); (M.R.G.B.)
| | - Matthew R. G. Brown
- Heroes in Mind, Advocacy and Research Consortium (HiMARC), Faculty of Rehabilitation Medicine, University of Alberta, Edmonton, AB T6G 2G4, Canada; (C.J.); (M.R.G.B.)
- Department of Computing Science, University of Alberta, Edmonton, AB T6G 2E8, Canada
| | - Eric H. G. J. M. Vermetten
- Leiden University Medical Center, 2333 ZA Leiden, The Netherlands;
- ARQ National Psychotrauma Center, 1112 XE Diemen, The Netherlands
- Military Mental Health, Dutch Ministry of Defense, 3584 EZ Utrecht, The Netherlands
| | - Suzette Brémault-Phillips
- Department of Occupational Therapy, Faculty of Rehabilitation Medicine, University of Alberta, Edmonton, AB T6G 2G4, Canada; (E.T.); (L.S.-M.)
- Heroes in Mind, Advocacy and Research Consortium (HiMARC), Faculty of Rehabilitation Medicine, University of Alberta, Edmonton, AB T6G 2G4, Canada; (C.J.); (M.R.G.B.)
- Neuroscience and Mental Health Institute (NMHI), University of Alberta, Edmonton, AB T6G 2E1, Canada
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25
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Saberi A, Mohammadi E, Zarei M, Eickhoff SB, Tahmasian M. Structural and functional neuroimaging of late-life depression: a coordinate-based meta-analysis. Brain Imaging Behav 2021; 16:518-531. [PMID: 34331655 DOI: 10.1007/s11682-021-00494-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Accepted: 06/28/2021] [Indexed: 10/20/2022]
Abstract
Several neuroimaging studies have investigated localized aberrations in brain structure, function or connectivity in late-life depression, but the ensuing results are equivocal and often conflicting. Here, we provide a quantitative consolidation of neuroimaging in late-life depression using coordinate-based meta-analysis by searching multiple databases up to March 2020. Our search revealed 3252 unique records, among which we identified 32 eligible whole-brain neuroimaging publications comparing 674 patients with 568 controls. The peak coordinates of group comparisons between the patients and the controls were extracted and then analyzed using activation likelihood estimation method. Our sufficiently powered analysis on all the experiments, and more homogenous subsections of the data (patients > controls, controls > patients, and functional imaging experiments) revealed no significant convergent regional abnormality in late-life depression. This inconsistency might be due to clinical and biological heterogeneity of LLD, as well as experimental (e.g., choice of tasks, image modalities) and analytic flexibility (e.g., preprocessing and analytic parameters), and distributed patterns of neural abnormalities. Our findings highlight the importance of clinical/biological heterogeneity of late-life depression, in addition to the need for more reproducible research by using pre-registered and standardized protocols on more homogenous populations to identify potential consistent brain abnormalities in late-life depression.
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Affiliation(s)
- Amin Saberi
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
| | - Esmaeil Mohammadi
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran.,Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mojtaba Zarei
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany.,Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Masoud Tahmasian
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran.
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26
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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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27
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Qin Y, Tong X, Li W, Zhang L, Zhang Y, Li X, Yang J, Qin K, Lei D, Gong Q, Zhou D, An D. Divergent Anatomical Correlates and Functional Network Connectivity Patterns in Temporal Lobe Epilepsy with and Without Depression. Brain Topogr 2021; 34:525-536. [PMID: 33973138 DOI: 10.1007/s10548-021-00848-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Accepted: 05/05/2021] [Indexed: 02/05/2023]
Abstract
Epilepsy and depression were proposed to facilitate each other reciprocally through common neurobiological anomalies, especially the prefrontal-limbic-subcortical abnormalities. Yet neuroimaging patterns of higher-order cognitive networks and neuroanatomical correlates were rarely compared in temporal lobe epilepsy patients with (TLE-D) and without depression (TLE-N). We collected T1-weighted structural and resting-state functional MRI data from 20 TLE-D, 31 TLE-N and 20 healthy controls (HCs) and performed analyses including hippocampal volume (HCV), cortical thickness, gray matter volume (GMV) and whole-brain functional network connectivity (FNC) across three groups. Imaging differences were related to clinical and psychological measurements. TLE-D demonstrated disrupted functional role of subcortical (SUB) and higher-order cognitive networks compared to TLE-N and HCs. In TLE-D, GMV in the right supplementary motor area (SMA) and FNC between the dorsal attention (DAN) and SUB were attenuated compared to TLE-N and HCs, FNC between SUB and the visual network (VIS) decreased compared to HCs. GMV in the right SMA was negatively correlated with depression severity and some symptoms. Combined, explicit emotion regulation may be impaired in TLE-D. Meanwhile, compared to HCs, TLE-N showed smaller HCVs, TLE-D and TLE-N showed smaller GMV in the medial orbital frontal gyrus and right hippocampus and hippocampal gyrus, possibly implying predisposition of epileptic activities to co-morbid depression. Our findings suggest distinct anatomical and FNC patterns in TLE-D and TLE-N. More than prefrontal-limbic-subcortical anomalies, disrupted higher-order cognitive network may contribute to depression in TLE, providing new potential treatment targets for depression and calling attention to relation between cognitive dysfunction and co-morbid depression.
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Affiliation(s)
- Yingjie Qin
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xin Tong
- Department of Neurology, West China Second Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Wei Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Le Zhang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yingying Zhang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xiuli Li
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jing Yang
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Kun Qin
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Du Lei
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Dong Zhou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Dongmei An
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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Ebneabbasi A, Mahdipour M, Nejati V, Li M, Liebe T, Colic L, Leutritz AL, Vogel M, Zarei M, Walter M, Tahmasian M. Emotion processing and regulation in major depressive disorder: A 7T resting-state fMRI study. Hum Brain Mapp 2021; 42:797-810. [PMID: 33151031 PMCID: PMC7814754 DOI: 10.1002/hbm.25263] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 09/18/2020] [Accepted: 10/14/2020] [Indexed: 12/23/2022] Open
Abstract
Dysfunctions in bottom-up emotion processing (EP), as well as top-down emotion regulation (ER) are prominent features in pathophysiology of major depressive disorder (MDD). Nonetheless, it is not clear whether EP- and ER-related areas are regionally and/or connectively disturbed in MDD. In addition, it is yet to be known how EP- and ER-related areas are interactively linked to regulatory behavior, and whether this interaction is disrupted in MDD. In our study, regional amplitude of low frequency fluctuations (ALFF) and whole-brain functional connectivity (FC) of meta-analytic-driven EP- and ER-related areas were compared between 32 healthy controls (HC) and 20 MDD patients. Then, we aimed to investigate whether the EP-related areas can predict the ER-related areas and regulatory behavior in both groups. Finally, the brain-behavior correlations between the EP- and ER-related areas and depression severity were assessed. We found that: (a) affective areas are regionally and/or connectively disturbed in MDD; (b) EP-ER interaction seems to be disrupted in MDD; overburden of emotional reactivity in amygdala may inversely affect cognitive control processes in prefrontal cortices, which leads to diminished regulatory actions. (c) Depression severity is correlated with FC of affective areas. Our findings shed new lights on the neural underpinning of affective dysfunctions in depression.
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Affiliation(s)
- Amir Ebneabbasi
- Institute of Medical Science and TechnologyShahid Beheshti UniversityTehranIran
- Department of Psychology, Faculty of Psychology and Educational SciencesShahid Beheshti UniversityTehranIran
| | - Mostafa Mahdipour
- Institute of Medical Science and TechnologyShahid Beheshti UniversityTehranIran
| | - Vahid Nejati
- Department of Psychology, Faculty of Psychology and Educational SciencesShahid Beheshti UniversityTehranIran
| | - Meng Li
- Clinical Affective Neuroimaging LaboratoryOtto von Guericke UniversityMagdeburgGermany
- Department of Psychiatry and PsychotherapyJena University HospitalJenaGermany
| | - Thomas Liebe
- Clinical Affective Neuroimaging LaboratoryOtto von Guericke UniversityMagdeburgGermany
| | - Lejla Colic
- Clinical Affective Neuroimaging LaboratoryOtto von Guericke UniversityMagdeburgGermany
| | - Anna Linda Leutritz
- Clinical Affective Neuroimaging LaboratoryOtto von Guericke UniversityMagdeburgGermany
- Department of Psychiatry, Psychosomatic Medicine and PsychotherapyUniversity Hospital, University of WürzburgWürzburgGermany
| | - Matthias Vogel
- Clinical Affective Neuroimaging LaboratoryOtto von Guericke UniversityMagdeburgGermany
- University Clinic for Psychosomatic Medicine and PsychotherapyMagdeburgGermany
| | - Mojtaba Zarei
- Institute of Medical Science and TechnologyShahid Beheshti UniversityTehranIran
| | - Martin Walter
- Clinical Affective Neuroimaging LaboratoryOtto von Guericke UniversityMagdeburgGermany
- Department of Psychiatry and PsychotherapyJena University HospitalJenaGermany
- Leibniz Institute for NeurobiologyMagdeburgGermany
| | - Masoud Tahmasian
- Institute of Medical Science and TechnologyShahid Beheshti UniversityTehranIran
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