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Gruzman R, Hempel M, Domke AK, Hartling C, Stippl A, Carstens L, Bajbouj M, Gärtner M, Grimm S. Investigating the impact of rumination and adverse childhood experiences on resting-state neural activity and connectivity in depression. J Affect Disord 2024; 358:283-291. [PMID: 38387672 DOI: 10.1016/j.jad.2024.02.068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 02/15/2024] [Accepted: 02/17/2024] [Indexed: 02/24/2024]
Abstract
BACKGROUND Both ruminative thought processes and adverse childhood experiences (ACEs) are well-established risk factors for the emergence and maintenance of depression. However, the neurobiological mechanisms underlying these associations remain poorly understood. METHODS We examined resting-state functional magnetic resonance imaging data (3 T Tim Trio MR scanner; Siemens, Erlangen) of 44 individuals diagnosed with an acute depressive episode. Specifically, we focused on investigating functional brain activity and connectivity within and between three large-scale neural networks associated with processes affected in depression: the default mode network (DMN), the salience network (SN), and the central executive network (CEN). Correlational and regression-based analyses were performed. RESULTS Our regions of interest analyses revealed that region-specific spontaneous neural activity in the anterior DMN was associated with self-reported trait rumination, specifically, the pregenual anterior cingulate cortex (pgACC). Furthermore, using a liberal statistical threshold, we found that spontaneous neural activity of the ventromedial prefrontal cortex and the pgACC were associated with depression symptom severity. Neither spontaneous neural activity in the SN and CEN nor functional connectivity within and across the investigated networks was associated with depression severity or rumination. Furthermore, there was no association between ACEs and brain activity and connectivity. LIMITATIONS Lack of a formal control group or low-risk group for comparison. CONCLUSIONS Overall, our results indicate network-specific changes in spontaneous brain activity, that are linked to both depression severity and rumination. Findings underscore the crucial role of the pgACC in depression and contribute to a dimensional and symptom-based understanding of depression-related network imbalances.
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Affiliation(s)
- Rebecca Gruzman
- Department of Psychology, MSB Medical School Berlin, Rüdesheimer Straße 50, 14197 Berlin, Germany.
| | - Moritz Hempel
- Department of Psychology, MSB Medical School Berlin, Rüdesheimer Straße 50, 14197 Berlin, Germany
| | - Ann-Kathrin Domke
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt - Universität zu Berlin, Berlin Institute of Health, Campus Benjamin Franklin, Hindenburgdamm 30, 12203 Berlin, Germany
| | - Corinna Hartling
- Department of Psychology, MSB Medical School Berlin, Rüdesheimer Straße 50, 14197 Berlin, Germany; Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt - Universität zu Berlin, Berlin Institute of Health, Campus Benjamin Franklin, Hindenburgdamm 30, 12203 Berlin, Germany
| | - Anna Stippl
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt - Universität zu Berlin, Berlin Institute of Health, Campus Benjamin Franklin, Hindenburgdamm 30, 12203 Berlin, Germany
| | - Luisa Carstens
- Department of Psychology, MSB Medical School Berlin, Rüdesheimer Straße 50, 14197 Berlin, Germany
| | - Malek Bajbouj
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt - Universität zu Berlin, Berlin Institute of Health, Campus Benjamin Franklin, Hindenburgdamm 30, 12203 Berlin, Germany
| | - Matti Gärtner
- Department of Psychology, MSB Medical School Berlin, Rüdesheimer Straße 50, 14197 Berlin, Germany; Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt - Universität zu Berlin, Berlin Institute of Health, Campus Benjamin Franklin, Hindenburgdamm 30, 12203 Berlin, Germany
| | - Simone Grimm
- Department of Psychology, MSB Medical School Berlin, Rüdesheimer Straße 50, 14197 Berlin, Germany; Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt - Universität zu Berlin, Berlin Institute of Health, Campus Benjamin Franklin, Hindenburgdamm 30, 12203 Berlin, Germany; Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Lenggstrasse 31, 8032 Zurich, Switzerland
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2
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Jin MX, Qin PP, Xia AWL, Kan RLD, Zhang BBB, Tang AHP, Li ASM, Lin TTZ, Giron CG, Pei JJ, Kranz GS. Neurophysiological and neuroimaging markers of repetitive transcranial magnetic stimulation treatment response in major depressive disorder: A systematic review and meta-analysis of predictive modeling studies. Neurosci Biobehav Rev 2024; 162:105695. [PMID: 38710424 DOI: 10.1016/j.neubiorev.2024.105695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 04/10/2024] [Accepted: 04/26/2024] [Indexed: 05/08/2024]
Abstract
Predicting repetitive transcranial magnetic stimulation (rTMS) treatment outcomes in major depressive disorder (MDD) could reduce the financial and psychological risks of treatment failure. We systematically reviewed and meta-analyzed studies that leveraged neurophysiological and neuroimaging markers to predict rTMS response in MDD. Five databases were searched from inception to May 25, 2023. The primary meta-analytic outcome was predictive accuracy pooled from classification models. Regression models were summarized qualitatively. A promising marker was identified if it showed a sensitivity and specificity of 80% or higher in at least two independent studies. Searching yielded 36 studies. Twenty-two classification modeling studies produced an estimated area under the summary receiver operating characteristic curve of 0.87 (95% CI = 0.83-0.92), with 86.8% sensitivity (95% CI = 80.6-91.2%) and 81.9% specificity (95% CI = 76.1-86.4%). Frontal theta cordance measured by electroencephalography is closest to proof of concept. Predicting rTMS response using neurophysiological and neuroimaging markers is promising for clinical decision-making. However, replications by different research groups are needed to establish rigorous markers.
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Affiliation(s)
- Min Xia Jin
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, Special Administrative Region of China; Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Medicine, Tongji University, Shanghai, China
| | - Penny Ping Qin
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, Special Administrative Region of China
| | - Adam Wei Li Xia
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, Special Administrative Region of China
| | - Rebecca Lai Di Kan
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, Special Administrative Region of China
| | - Bella Bing Bing Zhang
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, Special Administrative Region of China
| | - Alvin Hong Pui Tang
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, Special Administrative Region of China
| | - Ami Sin Man Li
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, Special Administrative Region of China
| | - Tim Tian Ze Lin
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, Special Administrative Region of China
| | - Cristian G Giron
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, Special Administrative Region of China
| | - Jun Jie Pei
- Department of Rehabilitation Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Zhejiang, China
| | - Georg S Kranz
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, Special Administrative Region of China; Mental Health Research Center, The Hong Kong Polytechnic University, Hong Kong, Special Administrative Region of China; Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Austria.
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Gärtner M, Weigand A, Meiering MS, Weigner D, Carstens L, Keicher C, Hertrampf R, Beckmann C, Mennes M, Wunder A, Grimm S. Negative emotionality shapes the modulatory effects of ketamine and lamotrigine in subregions of the anterior cingulate cortex. Transl Psychiatry 2024; 14:258. [PMID: 38890270 PMCID: PMC11189565 DOI: 10.1038/s41398-024-02977-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 05/31/2024] [Accepted: 06/10/2024] [Indexed: 06/20/2024] Open
Abstract
Neuroimaging studies have identified the anterior cingulate cortex (ACC) as one of the major targets of ketamine in the human brain, which may be related to ketamine's antidepressant (AD) mechanisms of action. However, due to different methodological approaches, different investigated populations, and varying measurement timepoints, results are not consistent, and the functional significance of the observed brain changes remains a matter of open debate. Inhibition of glutamate release during acute ketamine administration by lamotrigine provides the opportunity to gain additional insight into the functional significance of ketamine-induced brain changes. Furthermore, the assessment of trait negative emotionality holds promise to link findings in healthy participants to potential AD mechanisms of ketamine. In this double-blind, placebo-controlled, randomized, single dose, parallel-group study, we collected resting-state fMRI data before, during, and 24 h after ketamine administration in a sample of 75 healthy male and female participants who were randomly allocated to one of three treatment conditions (ketamine, ketamine with lamotrigine pre- treatment, placebo). Spontaneous brain activity was extracted from two ventral and one dorsal subregions of the ACC. Our results showed activity decreases during the administration of ketamine in all three ACC subregions. However, only in the ventral subregions of the ACC this effect was attenuated by lamotrigine. 24 h after administration, ACC activity returned to baseline levels, but group differences were observed between the lamotrigine and the ketamine group. Trait negative emotionality was closely linked to activity changes in the subgenual ACC after ketamine administration. These results contribute to an understanding of the functional significance of ketamine effects in different subregions of the ACC by combining an approach to modulate glutamate release with the assessment of multiple timepoints and associations with trait negative emotionality in healthy participants.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Andreas Wunder
- Translational Medicine and Clinical Pharmacology, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany
| | - Simone Grimm
- Medical School Berlin, Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Berlin, Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital of Psychiatry, University of Zurich, Zurich, Switzerland
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4
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Xia Z, Yang PY, Chen SL, Zhou HY, Yan C. Uncovering the power of neurofeedback: a meta-analysis of its effectiveness in treating major depressive disorders. Cereb Cortex 2024; 34:bhae252. [PMID: 38889442 DOI: 10.1093/cercor/bhae252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Revised: 05/25/2024] [Accepted: 06/04/2024] [Indexed: 06/20/2024] Open
Abstract
Neurofeedback, a non-invasive intervention, has been increasingly used as a potential treatment for major depressive disorders. However, the effectiveness of neurofeedback in alleviating depressive symptoms remains uncertain. To address this gap, we conducted a comprehensive meta-analysis to evaluate the efficacy of neurofeedback as a treatment for major depressive disorders. We conducted a comprehensive meta-analysis of 22 studies investigating the effects of neurofeedback interventions on depression symptoms, neurophysiological outcomes, and neuropsychological function. Our analysis included the calculation of Hedges' g effect sizes and explored various moderators like intervention settings, study designs, and demographics. Our findings revealed that neurofeedback intervention had a significant impact on depression symptoms (Hedges' g = -0.600) and neurophysiological outcomes (Hedges' g = -0.726). We also observed a moderate effect size for neurofeedback intervention on neuropsychological function (Hedges' g = -0.418). As expected, we observed that longer intervention length was associated with better outcomes for depressive symptoms (β = -4.36, P < 0.001) and neuropsychological function (β = -2.89, P = 0.003). Surprisingly, we found that shorter neurofeedback sessions were associated with improvements in neurophysiological outcomes (β = 3.34, P < 0.001). Our meta-analysis provides compelling evidence that neurofeedback holds promising potential as a non-pharmacological intervention option for effectively improving depressive symptoms, neurophysiological outcomes, and neuropsychological function in individuals with major depressive disorders.
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Affiliation(s)
- Zheng Xia
- Key Laboratory of Brain Functional Genomics (MOE&STCSM), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, 3663 North Zhongshan Road, Shanghai 200062, China
- Shanghai Changning Mental Health Center, 299 Xiehe Road, Shanghai 200335, China
| | - Peng-Yuan Yang
- Department of Methodology and Statistics, Faculty of Behavioral and Social Sciences, Tilburg University, Warandelaan 2, 5037 AB, Tilburg, The Netherlands
| | - Si-Lu Chen
- Shanghai Changning Mental Health Center, 299 Xiehe Road, Shanghai 200335, China
| | - Han-Yu Zhou
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, 3663 North Zhongshan Road, Shanghai 200062, China
| | - Chao Yan
- Key Laboratory of Brain Functional Genomics (MOE&STCSM), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, 3663 North Zhongshan Road, Shanghai 200062, China
- Shanghai Changning Mental Health Center, 299 Xiehe Road, Shanghai 200335, China
- Key Laboratory of Philosophy and Social Science of Anhui Province on Adolescent Mental Health and Crisis Intelligence Intervention, Hefei Normal University, 1688 Lianhua Road, Hefei 230601, China
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5
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Yang C, Zhou Z, Bao W, Zhong R, Tang M, Wang Y, Gao Y, Hu X, Zhang L, Qiu L, Kuang W, Huang X, Gong Q. Sex differences in aberrant functional connectivity of three core networks and subcortical networks in medication-free adolescent-onset major depressive disorder. Cereb Cortex 2024; 34:bhae225. [PMID: 38836288 DOI: 10.1093/cercor/bhae225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 05/02/2024] [Accepted: 05/04/2024] [Indexed: 06/06/2024] Open
Abstract
Major depressive disorder demonstrated sex differences in prevalence and symptoms, which were more pronounced during adolescence. Yet, research on sex-specific brain network characteristics in adolescent-onset major depressive disorder remains limited. This study investigated sex-specific and nonspecific alterations in resting-state functional connectivity of three core networks (frontoparietal network, salience network, and default mode network) and subcortical networks in adolescent-onset major depressive disorder, using seed-based resting-state functional connectivity in 50 medication-free patients with adolescent-onset major depressive disorder and 56 healthy controls. Irrespective of sex, compared with healthy controls, adolescent-onset major depressive disorder patients showed hypoconnectivity between bilateral hippocampus and right superior temporal gyrus (default mode network). More importantly, we further found that females with adolescent-onset major depressive disorder exhibited hypoconnectivity within the default mode network (medial prefrontal cortex), and between the subcortical regions (i.e. amygdala, striatum, and thalamus) with the default mode network (angular gyrus and posterior cingulate cortex) and the frontoparietal network (dorsal prefrontal cortex), while the opposite patterns of resting-state functional connectivity alterations were observed in males with adolescent-onset major depressive disorder, relative to their sex-matched healthy controls. Moreover, several sex-specific resting-state functional connectivity changes were correlated with age of onset, sleep disturbance, and anxiety in adolescent-onset major depressive disorder with different sex. These findings suggested that these sex-specific resting-state functional connectivity alterations may reflect the differences in brain development or processes related to early illness onset, underscoring the necessity for sex-tailored diagnostic and therapeutic approaches in adolescent-onset major depressive disorder.
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Affiliation(s)
- Chunyu Yang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, China
- Department of Radiology, The Second People's Hospital of Yibin, Yibin, 644000, China
| | - Zilin Zhou
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Weijie Bao
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Ruihan Zhong
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Mengyue Tang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Yidan Wang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Yingxue Gao
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Xinyue Hu
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Lianqing Zhang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Lihua Qiu
- Department of Radiology, The Second People's Hospital of Yibin, Yibin, 644000, China
| | - Weihong Kuang
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Xiaoqi Huang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, 610041, China
- The Xiamen Key Lab of Psychoradiology and Neuromodulation, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, 361022, China
| | - Qiyong Gong
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, 610041, China
- The Xiamen Key Lab of Psychoradiology and Neuromodulation, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, 361022, China
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Jüllig AK, Hebib S, Metzker H, Gruber E, Gruber O. Task-induced deactivation dysfunction during reward processing is associated with low self-esteem in a possible subtype of major depression. Brain Behav 2024; 14:e3545. [PMID: 38873863 DOI: 10.1002/brb3.3545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 04/10/2024] [Accepted: 05/02/2024] [Indexed: 06/15/2024] Open
Abstract
INTRODUCTION Low self-esteem is a frequent symptom in major depressive disorder (MDD). This functional magnetic resonance imaging study investigated whether MDD patients with low self-esteem show a distinct neural pathophysiology. Previous studies linked low self-esteem to reduced task-induced deactivation of the pregenual anterior cingulate cortex (pgACC) as a part of the default mode network, and to reduced connectivity between pgACC and reward system. Goya-Maldonado et al. identified an MDD subtype with pgACC and ventral striatal overactivations during reward processing. We hypothesized that this subtype might be characterized by low self-esteem. METHODS Eighty-three MDD patients performed the desire-reason dilemma task and completed the Rosenberg Self-Esteem Scale (RSES). Brain activity during bottom-up reward processing was regressed upon the RSES scores, controlling for depression severity measured by the Montgomery-Åsberg Depression Rating Scale. To corroborate the findings, we compared self-esteem scores between patient subgroups with impaired task-induced deactivation (n = 31) and with preserved task-induced deactivation (n = 31) of the pgACC. RESULTS Consistent with our a priori hypothesis, activity in a bilateral fronto-striatal network including pgACC and ventral striatum correlated negatively with RSES scores, also when controlling for depression severity. In the additional analysis, patients with impaired task-induced pgACC deactivation showed lower self-esteem (t (52.82) = -2.27; p = .027, d = 0.58) compared to those with preserved task-induced pgACC deactivation. CONCLUSIONS We conclude that low self-esteem in MDD patients is linked to a task-induced deactivation dysfunction of the pgACC. Our findings suggest that a previously described possible subtype of MDD with pgACC and ventral striatal overactivations during reward processing is clinically characterized by low self-esteem.
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Affiliation(s)
- Antonia K Jüllig
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, University Hospital Heidelberg, Heidelberg, Germany
| | - Sandi Hebib
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, University Hospital Heidelberg, Heidelberg, Germany
| | - Helena Metzker
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, University Hospital Heidelberg, Heidelberg, Germany
| | - Eva Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, University Hospital Heidelberg, Heidelberg, Germany
| | - Oliver Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, University Hospital Heidelberg, Heidelberg, Germany
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Qiu J, Gu W, Zhang Y, Wang L, Shen J. Alterations of the amplitude of low-frequency fluctuation induced by repetitive transcranial magnetic stimulation combined with antidepressants treatment for major depressive disorder. Psychiatry Res Neuroimaging 2024; 340:111792. [PMID: 38484532 DOI: 10.1016/j.pscychresns.2024.111792] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Revised: 02/02/2024] [Accepted: 02/07/2024] [Indexed: 04/13/2024]
Abstract
We investigated the neuroimaging changes and clinical efficacy of repetitive transcranial magnetic stimulation (rTMS) combined with antidepressants in major depressive disorder (MDD) patients. We scanned 35 patients with MDD and 27 healthy controls (HC) with resting-state functional magnetic resonance imaging (fMRI) before and after treatment. We analyzed amplitude of low-frequency fluctuation (ALFF) and the correlation with clinical variables. The rate of significant efficacy after treatment was higher in the combination treatment group than in the antidepressant group, although not statistically significant. At baseline, ALFF increased in the left middle temporal, brain stem, and left cerebellum and decreased in the right anterior cingulate (ACC), right orbital frontal cortex (OFC), and right caudate. ALFF increased in the left fusiform and decreased in the right lingual gyrus, left middle occipital gyrus, and left superior occipital gyrus after antidepressants. ALFF increased in the right ACC, right OFC, and right rectus after combination treatment. ALFF changes in the right ACC/OFC were negatively correlated with HAMD changes. After treatment, abnormal activity in some brain regions normalized, but these regions differed between the two treatment groups. rTMS combined with antidepressants therapy may improve MDD symptoms by improving neuronal activity levels in the right ACC and right OFC.
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Affiliation(s)
- Jing Qiu
- Department of Radiology, Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, China; Department of Radiology, Soochow University Affiliated Guangji Hospital, Suzhou, Jiangsu Province, China
| | - Weiguo Gu
- Department of Radiology, Soochow University Affiliated Guangji Hospital, Suzhou, Jiangsu Province, China
| | - Yuan Zhang
- Department of Radiology, Soochow University Affiliated Guangji Hospital, Suzhou, Jiangsu Province, China
| | - Lei Wang
- Department of Radiology, Soochow University Affiliated Guangji Hospital, Suzhou, Jiangsu Province, China
| | - Junkang Shen
- Department of Radiology, Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, China; Institute of Imaging Medicine, Soochow University, Suzhou, Jiangsu Province, China.
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Ge Q, Lock M, Yang X, Ding Y, Yue J, Zhao N, Hu YS, Zhang Y, Yao M, Zang YF. Utilizing fMRI to Guide TMS Targets: the Reliability and Sensitivity of fMRI Metrics at 3 T and 1.5 T. Neuroinformatics 2024:10.1007/s12021-024-09667-5. [PMID: 38780699 DOI: 10.1007/s12021-024-09667-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/30/2024] [Indexed: 05/25/2024]
Abstract
US Food and Drug Administration (FDA) cleared a Transcranial Magnetic Stimulation (TMS) system with functional Magnetic Resonance Imaging-guided (fMRI) individualized treatment protocol for major depressive disorder, which employs resting state-fMRI (RS-fMRI) functional connectivity (FC) to pinpoint the target individually to increase the accuracy and effeteness of the stimulation. Furthermore, task activation-guided TMS, as well as the use of RS-fMRI local metrics for targeted the specific abnormal brain regions, are considered a precise scheme for TMS targeting. Since 1.5 T MRI is more available in hospitals, systematic evaluation of the test-retest reliability and sensitivity of fMRI metrics on 1.5 T and 3 T MRI may provide reference for the application of fMRI-guided individualized-precise TMS stimulation. Twenty participants underwent three RS-fMRI scans and one scan of finger-tapping task fMRI with self-initiated (SI) and visual-guided (VG) conditions at both 3 T and 1.5 T. Then the location reliability derived by FC (with three seed regions) and peak activation were assessed by intra-individual distance. The test-retest reliability and sensitivity of five RS-fMRI local metrics were evaluated using intra-class correlation and effect size, separately. The intra-individual distance of peak activation location between 1.5 T and 3 T was 15.8 mm and 19 mm for two conditions, respectively. The intra-individual distance for the FC derived targets at 1.5 T was 9.6-31.2 mm, compared to that of 3 T (7.6-31.1 mm). The test-retest reliability and sensitivity of RS-fMRI local metrics showed similar trends on 1.5 T and 3 T. These findings hasten the application of fMRI-guided individualized TMS treatment in clinical practice.
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Affiliation(s)
- Qiu Ge
- Center for Cognition and Brain Disorders, the Affiliated Hospital of Hangzhou Normal University, Zhejiang, Hangzhou, China
- Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Zhejiang, Hangzhou, China
- Institute of Psychological Sciences, Hangzhou Normal University, Zhejiang, Hangzhou, China
| | - Matthew Lock
- Center for Cognition and Brain Disorders, the Affiliated Hospital of Hangzhou Normal University, Zhejiang, Hangzhou, China
| | - Xue Yang
- Center for Cognition and Brain Disorders, the Affiliated Hospital of Hangzhou Normal University, Zhejiang, Hangzhou, China
- Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Zhejiang, Hangzhou, China
- Institute of Psychological Sciences, Hangzhou Normal University, Zhejiang, Hangzhou, China
| | - Yuejiao Ding
- Center for Cognition and Brain Disorders, the Affiliated Hospital of Hangzhou Normal University, Zhejiang, Hangzhou, China
- Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Zhejiang, Hangzhou, China
- Institute of Psychological Sciences, Hangzhou Normal University, Zhejiang, Hangzhou, China
| | - Juan Yue
- Hangzhou Normal University Affiliated Deqing Hospital, TMS Center, Zhejiang Province, Hangzhou, China
| | - Na Zhao
- Center for Cognition and Brain Disorders, the Affiliated Hospital of Hangzhou Normal University, Zhejiang, Hangzhou, China
- Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Zhejiang, Hangzhou, China
- Institute of Psychological Sciences, Hangzhou Normal University, Zhejiang, Hangzhou, China
| | - Yun-Song Hu
- Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China
| | | | - Minliang Yao
- Hangzhou Normal University Affiliated Deqing Hospital, TMS Center, Zhejiang Province, Hangzhou, China
| | - Yu-Feng Zang
- Center for Cognition and Brain Disorders, the Affiliated Hospital of Hangzhou Normal University, Zhejiang, Hangzhou, China.
- Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Zhejiang, Hangzhou, China.
- Institute of Psychological Sciences, Hangzhou Normal University, Zhejiang, Hangzhou, China.
- Hangzhou Normal University Affiliated Deqing Hospital, TMS Center, Zhejiang Province, Hangzhou, China.
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Hernández-Sauret A, Martin de la Torre O, Redolar-Ripoll D. Use of transcranial magnetic stimulation (TMS) for studying cognitive control in depressed patients: A systematic review. COGNITIVE, AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2024:10.3758/s13415-024-01193-w. [PMID: 38773020 DOI: 10.3758/s13415-024-01193-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 04/22/2024] [Indexed: 05/23/2024]
Abstract
Major depressive disorder (MDD) is a debilitating mental disorder and the leading cause of disease burden. Major depressive disorder is associated with emotional impairment and cognitive deficit. Cognitive control, which is the ability to use perceptions, knowledge, and information about goals and motivations to shape the selection of goal-directed actions or thoughts, is a primary function of the prefrontal cortex (PFC). Psychotropic medications are one of the main treatments for MDD, but they are not effective for all patients. An alternative treatment is transcranial magnetic stimulation (TMS). Previous studies have provided mixed results on the cognitive-enhancing effects of TMS treatment in patients with MDD. Some studies have found significant improvement, while others have not. There is a lack of understanding of the specific effects of different TMS protocols and stimulation parameters on cognitive control in MDD. Thus, this review aims to synthesize the effectiveness of the TMS methods and a qualitative assessment of their potential benefits in improving cognitive functioning in patients with MDD. We reviewed 21 studies in which participants underwent a treatment of any transcranial magnetic stimulation protocol, such as repetitive TMS or theta-burst stimulation. One of the primary outcome measures was any change in the cognitive control process. Overall, the findings indicate that transcranial magnetic stimulation (TMS) may enhance cognitive function in patients with MDD. Most of the reviewed studies supported the notion of cognitive improvement following TMS treatment. Notably, improvements were predominantly observed in inhibition, attention, set shifting/flexibility, and memory domains. However, fewer significant improvements were detected in evaluations of visuospatial function and recognition, executive function, phonemic fluency, and speed of information processing. This review found evidence supporting the use of TMS as a treatment for cognitive deficits in patients with MDD. The results are promising, but further research is needed to clarify the specific TMS protocol and stimulation locations that are most effective.
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Affiliation(s)
- Ana Hernández-Sauret
- Cognitive Neurolab, Faculty of Health Sciences, Universitat Oberta de Catalunya (UOC), Rambla del Poblenou 156, Barcelona, Spain.
- Instituto Brain360, Unidad Neuromodulación y Neuroimagen, Calle Maó 9, Barcelona, Spain.
| | - Ona Martin de la Torre
- Cognitive Neurolab, Faculty of Health Sciences, Universitat Oberta de Catalunya (UOC), Rambla del Poblenou 156, Barcelona, Spain
- Instituto Brain360, Unidad Neuromodulación y Neuroimagen, Calle Maó 9, Barcelona, Spain
| | - Diego Redolar-Ripoll
- Cognitive Neurolab, Faculty of Health Sciences, Universitat Oberta de Catalunya (UOC), Rambla del Poblenou 156, Barcelona, Spain
- Instituto Brain360, Unidad Neuromodulación y Neuroimagen, Calle Maó 9, Barcelona, Spain
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10
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Amemori S, Graybiel AM, Amemori KI. Cingulate microstimulation induces negative decision-making via reduced top-down influence on primate fronto-cingulo-striatal network. Nat Commun 2024; 15:4201. [PMID: 38760337 PMCID: PMC11101474 DOI: 10.1038/s41467-024-48375-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 04/26/2024] [Indexed: 05/19/2024] Open
Abstract
The dorsolateral prefrontal cortex (dlPFC) is crucial for regulation of emotion that is known to aid prevention of depression. The broader fronto-cingulo-striatal (FCS) network, including cognitive dlPFC and limbic cingulo-striatal regions, has been associated with a negative evaluation bias often seen in depression. The mechanism by which dlPFC regulates the limbic system remains largely unclear. Here we have successfully induced a negative bias in decision-making in female primates performing a conflict decision-making task, by directly microstimulating the subgenual cingulate cortex while simultaneously recording FCS local field potentials (LFPs). The artificially induced negative bias in decision-making was associated with a significant decrease in functional connectivity from cognitive to limbic FCS regions, represented by a reduction in Granger causality in beta-range LFPs from the dlPFC to the other regions. The loss of top-down directional influence from cognitive to limbic regions, we suggest, could underlie negative biases in decision-making as observed in depressive states.
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Affiliation(s)
- Satoko Amemori
- Institute for the Advanced Study of Human Biology (ASHBi), Kyoto University, Kyoto, Japan
- Japan Society for the Promotion of Science, Tokyo, Japan
| | - Ann M Graybiel
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ken-Ichi Amemori
- Institute for the Advanced Study of Human Biology (ASHBi), Kyoto University, Kyoto, Japan.
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11
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Fennema D, Barker GJ, O'Daly O, Duan S, Godlewska BR, Goldsmith K, Young AH, Moll J, Zahn R. Neural responses to facial emotions and subsequent clinical outcomes in difficult-to-treat depression. Psychol Med 2024:1-9. [PMID: 38757184 DOI: 10.1017/s0033291724001144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/18/2024]
Abstract
BACKGROUND Amygdala and dorsal anterior cingulate cortex responses to facial emotions have shown promise in predicting treatment response in medication-free major depressive disorder (MDD). Here, we examined their role in the pathophysiology of clinical outcomes in more chronic, difficult-to-treat forms of MDD. METHODS Forty-five people with current MDD who had not responded to ⩾2 serotonergic antidepressants (n = 42, meeting pre-defined fMRI minimum quality thresholds) were enrolled and followed up over four months of standard primary care. Prior to medication review, subliminal facial emotion fMRI was used to extract blood-oxygen level-dependent effects for sad v. happy faces from two pre-registered a priori defined regions: bilateral amygdala and dorsal/pregenual anterior cingulate cortex. Clinical outcome was the percentage change on the self-reported Quick Inventory of Depressive Symptomatology (16-item). RESULTS We corroborated our pre-registered hypothesis (NCT04342299) that lower bilateral amygdala activation for sad v. happy faces predicted favorable clinical outcomes (rs[38] = 0.40, p = 0.01). In contrast, there was no effect for dorsal/pregenual anterior cingulate cortex activation (rs[38] = 0.18, p = 0.29), nor when using voxel-based whole-brain analyses (voxel-based Family-Wise Error-corrected p < 0.05). Predictive effects were mainly driven by the right amygdala whose response to happy faces was reduced in patients with higher anxiety levels. CONCLUSIONS We confirmed the prediction that a lower amygdala response to negative v. positive facial expressions might be an adaptive neural signature, which predicts subsequent symptom improvement also in difficult-to-treat MDD. Anxiety reduced adaptive amygdala responses.
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Affiliation(s)
- Diede Fennema
- Centre of Affective Disorders, Institute of Psychiatry, Psychology & Neuroscience, Centre for Affective Disorders, King's College London, London, UK
| | - Gareth J Barker
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Owen O'Daly
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Suqian Duan
- Centre of Affective Disorders, Institute of Psychiatry, Psychology & Neuroscience, Centre for Affective Disorders, King's College London, London, UK
| | - Beata R Godlewska
- Psychopharmacology Research Unit, University Department of Psychiatry, University of Oxford, Oxford, UK
- Oxford Health NHS Foundation Trust, Warneford Hospital, Oxford, UK
| | - Kimberley Goldsmith
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Allan H Young
- Centre of Affective Disorders, Institute of Psychiatry, Psychology & Neuroscience, Centre for Affective Disorders, King's College London, London, UK
- National Service for Affective Disorders, South London and Maudsley NHS Foundation Trust, London, UK
| | - Jorge Moll
- Cognitive and Behavioural Neuroscience Unit, D'Or Institute for Research and Education (IDOR), Pioneer Science Program, Rio de Janeiro, Brazil
| | - Roland Zahn
- Centre of Affective Disorders, Institute of Psychiatry, Psychology & Neuroscience, Centre for Affective Disorders, King's College London, London, UK
- National Service for Affective Disorders, South London and Maudsley NHS Foundation Trust, London, UK
- Cognitive and Behavioural Neuroscience Unit, D'Or Institute for Research and Education (IDOR), Pioneer Science Program, Rio de Janeiro, Brazil
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Ruffini G, Salvador R, Castaldo F, Baleeiro T, Camprodon JA, Chopra M, Cappon D, Pascual-Leone A. Multichannel tDCS with Advanced Targeting for Major Depressive Disorder: A Tele-Supervised At-Home Pilot Study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.04.24303508. [PMID: 38496607 PMCID: PMC10942536 DOI: 10.1101/2024.03.04.24303508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Introduction Proof-of-principle human studies suggest that transcranial direct current stimulation (tDCS) over the dorsolateral prefrontal cortex (DLPFC) may improve depression severity. This open-label multicenter study tested remotely supervised multichannel tDCS delivered at home in patients (N=35) with major depressive disorder (MDD). The primary aim was to assess the feasibility and safety of our protocol. As an exploratory aim, we evaluated therapeutic efficacy: the primary efficacy measure was the median percent change from baseline to the end of the 4-week post-treatment follow-up period in the observer-rated Montgomery-Asberg Depression Mood Rating Scale (MADRS). Methods Participants received 37 at-home stimulation sessions (30 minutes each) of specifically designed multichannel tDCS targeting the left DLPFC administered over eight weeks (4 weeks of daily treatments plus 4 weeks of taper), with a follow-up period of 4 weeks following the final stimulation session. The stimulation montage (electrode positions and currents) was optimized by employing computational models of the electric field generated by multichannel tDCS using available structural data from a similar population (group optimization). Conducted entirely remotely, the study employed the MADRS for assessment at baseline, at weeks 4 and 8 during treatment, and at 4-week follow-up visits. Results 34 patients (85.3% women) with a mean age of 59 years, a diagnosis of MDD according to DSM-5 criteria, and a MADRS score ≥20 at the time of study enrolment completed all study visits. At baseline, the mean time since MDD diagnosis was 24.0 (SD 19.1) months. Concerning compliance, 85% of the participants (n=29) completed the complete course of 37 stimulation sessions at home, while 97% completed at least 36 sessions. No detrimental effects were observed, including suicidal ideation and/or behavior. The study observed a median MADRS score reduction of 64.5% (48.6, 72.4) 4 weeks post-treatment (Hedge's g = -3.1). We observed a response rate (≥ 50% improvement in MADRS scores) of 72.7% (n=24) from baseline to the last visit 4 weeks post-treatment. Secondary measures reflected similar improvements. Conclusions These results suggest that remotely supervised and supported multichannel home-based tDCS is safe and feasible, and antidepressant efficacy motivates further appropriately controlled clinical studies.
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Poggi G, Klaus F, Pryce CR. Pathophysiology in cortico-amygdala circuits and excessive aversion processing: the role of oligodendrocytes and myelination. Brain Commun 2024; 6:fcae140. [PMID: 38712320 PMCID: PMC11073757 DOI: 10.1093/braincomms/fcae140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 12/27/2023] [Accepted: 04/16/2024] [Indexed: 05/08/2024] Open
Abstract
Stress-related psychiatric illnesses, such as major depressive disorder, anxiety and post-traumatic stress disorder, present with alterations in emotional processing, including excessive processing of negative/aversive stimuli and events. The bidirectional human/primate brain circuit comprising anterior cingulate cortex and amygdala is of fundamental importance in processing emotional stimuli, and in rodents the medial prefrontal cortex-amygdala circuit is to some extent analogous in structure and function. Here, we assess the comparative evidence for: (i) Anterior cingulate/medial prefrontal cortex<->amygdala bidirectional neural circuits as major contributors to aversive stimulus processing; (ii) Structural and functional changes in anterior cingulate cortex<->amygdala circuit associated with excessive aversion processing in stress-related neuropsychiatric disorders, and in medial prefrontal cortex<->amygdala circuit in rodent models of chronic stress-induced increased aversion reactivity; and (iii) Altered status of oligodendrocytes and their oligodendrocyte lineage cells and myelination in anterior cingulate/medial prefrontal cortex<->amygdala circuits in stress-related neuropsychiatric disorders and stress models. The comparative evidence from humans and rodents is that their respective anterior cingulate/medial prefrontal cortex<->amygdala circuits are integral to adaptive aversion processing. However, at the sub-regional level, the anterior cingulate/medial prefrontal cortex structure-function analogy is incomplete, and differences as well as similarities need to be taken into account. Structure-function imaging studies demonstrate that these neural circuits are altered in both human stress-related neuropsychiatric disorders and rodent models of stress-induced increased aversion processing. In both cases, the changes include altered white matter integrity, albeit the current evidence indicates that this is decreased in humans and increased in rodent models. At the cellular-molecular level, in both humans and rodents, the current evidence is that stress disorders do present with changes in oligodendrocyte lineage, oligodendrocytes and/or myelin in these neural circuits, but these changes are often discordant between and even within species. Nonetheless, by integrating the current comparative evidence, this review provides a timely insight into this field and should function to inform future studies-human, monkey and rodent-to ascertain whether or not the oligodendrocyte lineage and myelination are causally involved in the pathophysiology of stress-related neuropsychiatric disorders.
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Affiliation(s)
- Giulia Poggi
- Preclinical Laboratory for Translational Research into Affective Disorders, Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, CH-8008 Zurich, Switzerland
| | - Federica Klaus
- Department of Psychiatry, University of California San Diego, San Diego, CA 92093, USA
- Desert-Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, CA 92093, USA
| | - Christopher R Pryce
- Preclinical Laboratory for Translational Research into Affective Disorders, Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, CH-8008 Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, 8057 Zurich, Switzerland
- URPP Adaptive Brain Circuits in Development and Learning (AdaBD), University of Zurich, 8057 Zurich, Switzerland
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Zhou Z, Gao Y, Bao W, Liang K, Cao L, Tang M, Li H, Hu X, Zhang L, Sun H, Roberts N, Gong Q, Huang X. Distinctive intrinsic functional connectivity alterations of anterior cingulate cortex subdivisions in major depressive disorder: A systematic review and meta-analysis. Neurosci Biobehav Rev 2024; 159:105583. [PMID: 38365137 DOI: 10.1016/j.neubiorev.2024.105583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 01/22/2024] [Accepted: 02/11/2024] [Indexed: 02/18/2024]
Abstract
Evidence of whether the intrinsic functional connectivity of anterior cingulate cortex (ACC) and its subregions is altered in major depressive disorder (MDD) remains inconclusive. A systematic review and meta-analysis were therefore performed on the whole-brain resting-state functional connectivity (rsFC) studies using the ACC and its subregions as seed regions in MDD, in order to draw more reliable conclusions. Forty-four ACC-based rsFC studies were included, comprising 25 subgenual ACC-based studies, 11 pregenual ACC-based studies, and 17 dorsal ACC-based studies. Specific alterations of rsFC were identified for each ACC subregion in patients with MDD, with altered rsFC of subgenual ACC in emotion-related brain regions, of pregenual ACC in sensorimotor-related regions, and of dorsal ACC in cognition-related regions. Furthermore, meta-regression analysis revealed a significant negative correlation between the pgACC-caudate hypoconnectivity and percentage of female patients in the study cohort. This meta-analysis provides robust evidence of altered intrinsic functional connectivity of the ACC subregions in MDD, which may hold relevance to understanding the origin of, and treating, the emotional, sensorimotor and cognitive dysfunctions that are often observed in these patients.
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Affiliation(s)
- Zilin Zhou
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Yingxue Gao
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Weijie Bao
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Kaili Liang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Lingxiao Cao
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Mengyue Tang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Hailong Li
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Xinyue Hu
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Lianqing Zhang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Huaiqiang Sun
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Science, Chengdu, China
| | - Neil Roberts
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Centre for Reproductive Health (CRH), School of Clinical Sciences, University of Edinburgh, Edinburgh, UK
| | - Qiyong Gong
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Science, Chengdu, China; The Xiaman Key Lab of psychoradiology and neuromodulation, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China
| | - Xiaoqi Huang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Science, Chengdu, China; The Xiaman Key Lab of psychoradiology and neuromodulation, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China.
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15
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Danyeli LV, Sen ZD, Colic L, Opel N, Refisch A, Blekic N, Macharadze T, Kretzschmar M, Munk MJ, Gaser C, Speck O, Walter M, Li M. Cortical thickness of the posterior cingulate cortex is associated with the ketamine-induced altered sense of self: An ultra-high field MRI study. J Psychiatr Res 2024; 172:136-143. [PMID: 38382237 DOI: 10.1016/j.jpsychires.2024.02.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 01/31/2024] [Accepted: 02/07/2024] [Indexed: 02/23/2024]
Abstract
Subanesthetic doses of ketamine induce an antidepressant effect within hours in individuals with treatment-resistant depression while it furthermore induces immediate but transient psychotomimetic effects. Among these psychotomimetic effects, an altered sense of self has specifically been associated with the antidepressant response to ketamine as well as psychedelics. However, there is plenty of variation in the extent of the drug-induced altered sense of self experience that might be explained by differences in basal morphological characteristics, such as cortical thickness. Regions that have been previously associated with a psychedelics-induced sense of self and with ketamine's mechanism of action, are the posterior cingulate cortex (PCC) and the pregenual anterior cingulate cortex (pgACC). In this randomized, placebo-controlled, double-blind cross-over magnetic resonance imaging study, thirty-five healthy male participants (mean age ± standard deviation (SD) = 25.1 ± 4.2 years) were scanned at 7 T. We investigated whether the cortical thickness of two DMN regions, the PCC and the pgACC, are associated with disembodiment and experience of unity scores, which were used to index the ketamine-induced altered sense of self. We observed a negative correlation between the PCC cortical thickness and the disembodiment scores (R = -0.54, p < 0.001). In contrast, no significant association was found between the pgACC cortical thickness and the ketamine-induced altered sense of self. In the context of the existing literature, our findings highlight the importance of the PCC as a structure involved in the mechanism of ketamine-induced altered sense of self that seems to be shared with different antidepressant agents with psychotomimetic effects operating on different classes of transmitter systems.
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Affiliation(s)
- Lena Vera Danyeli
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany; Clinical Affective Neuroimaging Laboratory (CANLAB), Magdeburg, Germany; Department of Psychiatry and Psychotherapy, University Tübingen, Tübingen, Germany; Center for Intervention and Research on adaptive and maladaptive brain Circuits underlying mental health (C-I-R-C), Halle-Jena-Magdeburg, Germany
| | - Zümrüt Duygu Sen
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany; Clinical Affective Neuroimaging Laboratory (CANLAB), Magdeburg, Germany; Center for Intervention and Research on adaptive and maladaptive brain Circuits underlying mental health (C-I-R-C), Halle-Jena-Magdeburg, Germany
| | - Lejla Colic
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany; Center for Intervention and Research on adaptive and maladaptive brain Circuits underlying mental health (C-I-R-C), Halle-Jena-Magdeburg, Germany; German Center for Mental Health (DZPG), partner site Halle-Jena-Magdeburg, Germany
| | - Nils Opel
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany; Center for Intervention and Research on adaptive and maladaptive brain Circuits underlying mental health (C-I-R-C), Halle-Jena-Magdeburg, Germany; German Center for Mental Health (DZPG), partner site Halle-Jena-Magdeburg, Germany
| | - Alexander Refisch
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany; Center for Intervention and Research on adaptive and maladaptive brain Circuits underlying mental health (C-I-R-C), Halle-Jena-Magdeburg, Germany
| | - Nikolai Blekic
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany; Clinical Affective Neuroimaging Laboratory (CANLAB), Magdeburg, Germany
| | - Tamar Macharadze
- Department of Anesthesiology and Intensive Care Medicine, Medical Faculty, Otto-von-Guericke University Magdeburg, Magdeburg, Germany; Department Systems Physiology of Learning, Leibniz Institute for Neurobiology, Magdeburg, Germany; Center for Behavioral Brain Sciences, Magdeburg, Germany; Department of Behavioral Neurology, Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Moritz Kretzschmar
- Department of Anesthesiology and Intensive Care Medicine, Medical Faculty, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
| | - MatthiasH J Munk
- Department of Psychiatry and Psychotherapy, University Tübingen, Tübingen, Germany; Systems Neurophysiology, Department of Biology, Darmstadt University of Technology, Darmstadt, Germany
| | - Christian Gaser
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany; Center for Intervention and Research on adaptive and maladaptive brain Circuits underlying mental health (C-I-R-C), Halle-Jena-Magdeburg, Germany; German Center for Mental Health (DZPG), partner site Halle-Jena-Magdeburg, Germany; Department of Neurology, Jena University Hospital, Jena, Germany
| | - Oliver Speck
- Center for Intervention and Research on adaptive and maladaptive brain Circuits underlying mental health (C-I-R-C), Halle-Jena-Magdeburg, Germany; German Center for Mental Health (DZPG), partner site Halle-Jena-Magdeburg, Germany; Center for Behavioral Brain Sciences, Magdeburg, Germany; Department of Behavioral Neurology, Leibniz Institute for Neurobiology, Magdeburg, Germany; Department of Biomedical Magnetic Resonance, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
| | - Martin Walter
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany; Clinical Affective Neuroimaging Laboratory (CANLAB), Magdeburg, Germany; Department of Psychiatry and Psychotherapy, University Tübingen, Tübingen, Germany; Center for Intervention and Research on adaptive and maladaptive brain Circuits underlying mental health (C-I-R-C), Halle-Jena-Magdeburg, Germany; German Center for Mental Health (DZPG), partner site Halle-Jena-Magdeburg, Germany; Center for Behavioral Brain Sciences, Magdeburg, Germany; Department of Behavioral Neurology, Leibniz Institute for Neurobiology, Magdeburg, Germany.
| | - Meng Li
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany; Clinical Affective Neuroimaging Laboratory (CANLAB), Magdeburg, Germany; Center for Intervention and Research on adaptive and maladaptive brain Circuits underlying mental health (C-I-R-C), Halle-Jena-Magdeburg, Germany.
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16
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Klooster D, Voetterl H, Baeken C, Arns M. Evaluating Robustness of Brain Stimulation Biomarkers for Depression: A Systematic Review of Magnetic Resonance Imaging and Electroencephalography Studies. Biol Psychiatry 2024; 95:553-563. [PMID: 37734515 DOI: 10.1016/j.biopsych.2023.09.009] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 08/30/2023] [Accepted: 09/06/2023] [Indexed: 09/23/2023]
Abstract
Noninvasive brain stimulation (NIBS) treatments have gained considerable attention as potential therapeutic intervention for psychiatric disorders. The identification of reliable biomarkers for predicting clinical response to NIBS has been a major focus of research in recent years. Neuroimaging techniques, such as electroencephalography (EEG) and functional magnetic resonance imaging (MRI), have been used to identify potential biomarkers that could predict response to NIBS. However, identifying clinically actionable brain biomarkers requires robustness. In this systematic review, we aimed to summarize the current state of brain biomarker research for NIBS in depression, focusing only on well-powered studies (N ≥ 88) and/or studies that aimed at independently replicating previous findings, either successfully or unsuccessfully. A total of 220 studies were initially identified, of which 18 MRI studies and 18 EEG studies met the inclusion criteria. All focused on repetitive transcranial magnetic stimulation treatment in depression. After reviewing the included studies, we found the following MRI and EEG biomarkers to be most robust: 1) functional MRI-based functional connectivity between the dorsolateral prefrontal cortex and subgenual anterior cingulate cortex, 2) functional MRI-based network connectivity, 3) task-induced EEG frontal-midline theta, and 4) EEG individual alpha frequency. Future prospective studies should further investigate the clinical actionability of these specific EEG and MRI biomarkers to bring biomarkers closer to clinical reality.
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Affiliation(s)
- Debby Klooster
- Ghent Experimental Psychiatry Laboratory, Department of Head and Skin, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium; 4BRAIN Team, Department of Head and Skin, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium; Center for Care and Cure, Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - Helena Voetterl
- Research Institute Brainclinics, Brainclinics Foundation, Nijmegen, the Netherlands; Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Chris Baeken
- Ghent Experimental Psychiatry Laboratory, Department of Head and Skin, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium; Center for Care and Cure, Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands; Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Department of Psychiatry, Brussels, Belgium
| | - Martijn Arns
- Research Institute Brainclinics, Brainclinics Foundation, Nijmegen, the Netherlands; Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands.
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Poirot MG, Ruhe HG, Mutsaerts HJMM, Maximov II, Groote IR, Bjørnerud A, Marquering HA, Reneman L, Caan MWA. Treatment Response Prediction in Major Depressive Disorder Using Multimodal MRI and Clinical Data: Secondary Analysis of a Randomized Clinical Trial. Am J Psychiatry 2024; 181:223-233. [PMID: 38321916 DOI: 10.1176/appi.ajp.20230206] [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] [Indexed: 02/08/2024]
Abstract
OBJECTIVE Response to antidepressant treatment in major depressive disorder varies substantially between individuals, which lengthens the process of finding effective treatment. The authors sought to determine whether a multimodal machine learning approach could predict early sertraline response in patients with major depressive disorder. They assessed the predictive contribution of MR neuroimaging and clinical assessments at baseline and after 1 week of treatment. METHODS This was a preregistered secondary analysis of data from the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study, a multisite double-blind, placebo-controlled randomized clinical trial that included 296 adult outpatients with unmedicated recurrent or chronic major depressive disorder. MR neuroimaging and clinical data were collected before and after 1 week of treatment. Performance in predicting response and remission, collected after 8 weeks, was quantified using balanced accuracy (bAcc) and area under the receiver operating characteristic curve (AUROC) scores. RESULTS A total of 229 patients were included in the analyses (mean age, 38 years [SD=13]; 66% female). Internal cross-validation performance in predicting response to sertraline (bAcc=68% [SD=10], AUROC=0.73 [SD=0.03]) was significantly better than chance. External cross-validation on data from placebo nonresponders (bAcc=62%, AUROC=0.66) and placebo nonresponders who were switched to sertraline (bAcc=65%, AUROC=0.68) resulted in differences that suggest specificity for sertraline treatment compared with placebo treatment. Finally, multimodal models outperformed unimodal models. CONCLUSIONS The study results confirm that early sertraline treatment response can be predicted; that the models are sertraline specific compared with placebo; that prediction benefits from integrating multimodal MRI data with clinical data; and that perfusion imaging contributes most to these predictions. Using this approach, a lean and effective protocol could individualize sertraline treatment planning to improve psychiatric care.
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Affiliation(s)
- Maarten G Poirot
- Department of Radiology and Nuclear Medicine (Poirot, Ruhe, Marquering, Reneman) and Department of Biomedical Engineering and Physics (Poirot, Marquering, Reneman, Caan), Amsterdam UMC Location AMC, University of Amsterdam, Amsterdam; Brain Imaging, Amsterdam Neuroscience, Amsterdam (Poirot, Mutsaerts, Reneman, Caan); Department of Psychiatry, Radboudumc, Nijmegen, the Netherlands (Ruhe); Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, the Netherlands (Ruhe); Department of Radiology and Nuclear Medicine, Amsterdam UMC location, Vrije Universiteit Amsterdam, Amsterdam (Mutsaerts); Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen (Maximov, Bjørnerud); Division of Radiology, Vestfold Hospital Trust, Tønsberg, Norway (Groote, Caan); Computational Radiology and Artificial Intelligence, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo (Groote, Bjørnerud); Department of Psychology, University of Oslo, Oslo (Bjørnerud)
| | - Henricus G Ruhe
- Department of Radiology and Nuclear Medicine (Poirot, Ruhe, Marquering, Reneman) and Department of Biomedical Engineering and Physics (Poirot, Marquering, Reneman, Caan), Amsterdam UMC Location AMC, University of Amsterdam, Amsterdam; Brain Imaging, Amsterdam Neuroscience, Amsterdam (Poirot, Mutsaerts, Reneman, Caan); Department of Psychiatry, Radboudumc, Nijmegen, the Netherlands (Ruhe); Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, the Netherlands (Ruhe); Department of Radiology and Nuclear Medicine, Amsterdam UMC location, Vrije Universiteit Amsterdam, Amsterdam (Mutsaerts); Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen (Maximov, Bjørnerud); Division of Radiology, Vestfold Hospital Trust, Tønsberg, Norway (Groote, Caan); Computational Radiology and Artificial Intelligence, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo (Groote, Bjørnerud); Department of Psychology, University of Oslo, Oslo (Bjørnerud)
| | - Henk-Jan M M Mutsaerts
- Department of Radiology and Nuclear Medicine (Poirot, Ruhe, Marquering, Reneman) and Department of Biomedical Engineering and Physics (Poirot, Marquering, Reneman, Caan), Amsterdam UMC Location AMC, University of Amsterdam, Amsterdam; Brain Imaging, Amsterdam Neuroscience, Amsterdam (Poirot, Mutsaerts, Reneman, Caan); Department of Psychiatry, Radboudumc, Nijmegen, the Netherlands (Ruhe); Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, the Netherlands (Ruhe); Department of Radiology and Nuclear Medicine, Amsterdam UMC location, Vrije Universiteit Amsterdam, Amsterdam (Mutsaerts); Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen (Maximov, Bjørnerud); Division of Radiology, Vestfold Hospital Trust, Tønsberg, Norway (Groote, Caan); Computational Radiology and Artificial Intelligence, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo (Groote, Bjørnerud); Department of Psychology, University of Oslo, Oslo (Bjørnerud)
| | - Ivan I Maximov
- Department of Radiology and Nuclear Medicine (Poirot, Ruhe, Marquering, Reneman) and Department of Biomedical Engineering and Physics (Poirot, Marquering, Reneman, Caan), Amsterdam UMC Location AMC, University of Amsterdam, Amsterdam; Brain Imaging, Amsterdam Neuroscience, Amsterdam (Poirot, Mutsaerts, Reneman, Caan); Department of Psychiatry, Radboudumc, Nijmegen, the Netherlands (Ruhe); Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, the Netherlands (Ruhe); Department of Radiology and Nuclear Medicine, Amsterdam UMC location, Vrije Universiteit Amsterdam, Amsterdam (Mutsaerts); Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen (Maximov, Bjørnerud); Division of Radiology, Vestfold Hospital Trust, Tønsberg, Norway (Groote, Caan); Computational Radiology and Artificial Intelligence, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo (Groote, Bjørnerud); Department of Psychology, University of Oslo, Oslo (Bjørnerud)
| | - Inge R Groote
- Department of Radiology and Nuclear Medicine (Poirot, Ruhe, Marquering, Reneman) and Department of Biomedical Engineering and Physics (Poirot, Marquering, Reneman, Caan), Amsterdam UMC Location AMC, University of Amsterdam, Amsterdam; Brain Imaging, Amsterdam Neuroscience, Amsterdam (Poirot, Mutsaerts, Reneman, Caan); Department of Psychiatry, Radboudumc, Nijmegen, the Netherlands (Ruhe); Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, the Netherlands (Ruhe); Department of Radiology and Nuclear Medicine, Amsterdam UMC location, Vrije Universiteit Amsterdam, Amsterdam (Mutsaerts); Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen (Maximov, Bjørnerud); Division of Radiology, Vestfold Hospital Trust, Tønsberg, Norway (Groote, Caan); Computational Radiology and Artificial Intelligence, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo (Groote, Bjørnerud); Department of Psychology, University of Oslo, Oslo (Bjørnerud)
| | - Atle Bjørnerud
- Department of Radiology and Nuclear Medicine (Poirot, Ruhe, Marquering, Reneman) and Department of Biomedical Engineering and Physics (Poirot, Marquering, Reneman, Caan), Amsterdam UMC Location AMC, University of Amsterdam, Amsterdam; Brain Imaging, Amsterdam Neuroscience, Amsterdam (Poirot, Mutsaerts, Reneman, Caan); Department of Psychiatry, Radboudumc, Nijmegen, the Netherlands (Ruhe); Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, the Netherlands (Ruhe); Department of Radiology and Nuclear Medicine, Amsterdam UMC location, Vrije Universiteit Amsterdam, Amsterdam (Mutsaerts); Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen (Maximov, Bjørnerud); Division of Radiology, Vestfold Hospital Trust, Tønsberg, Norway (Groote, Caan); Computational Radiology and Artificial Intelligence, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo (Groote, Bjørnerud); Department of Psychology, University of Oslo, Oslo (Bjørnerud)
| | - Henk A Marquering
- Department of Radiology and Nuclear Medicine (Poirot, Ruhe, Marquering, Reneman) and Department of Biomedical Engineering and Physics (Poirot, Marquering, Reneman, Caan), Amsterdam UMC Location AMC, University of Amsterdam, Amsterdam; Brain Imaging, Amsterdam Neuroscience, Amsterdam (Poirot, Mutsaerts, Reneman, Caan); Department of Psychiatry, Radboudumc, Nijmegen, the Netherlands (Ruhe); Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, the Netherlands (Ruhe); Department of Radiology and Nuclear Medicine, Amsterdam UMC location, Vrije Universiteit Amsterdam, Amsterdam (Mutsaerts); Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen (Maximov, Bjørnerud); Division of Radiology, Vestfold Hospital Trust, Tønsberg, Norway (Groote, Caan); Computational Radiology and Artificial Intelligence, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo (Groote, Bjørnerud); Department of Psychology, University of Oslo, Oslo (Bjørnerud)
| | - Liesbeth Reneman
- Department of Radiology and Nuclear Medicine (Poirot, Ruhe, Marquering, Reneman) and Department of Biomedical Engineering and Physics (Poirot, Marquering, Reneman, Caan), Amsterdam UMC Location AMC, University of Amsterdam, Amsterdam; Brain Imaging, Amsterdam Neuroscience, Amsterdam (Poirot, Mutsaerts, Reneman, Caan); Department of Psychiatry, Radboudumc, Nijmegen, the Netherlands (Ruhe); Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, the Netherlands (Ruhe); Department of Radiology and Nuclear Medicine, Amsterdam UMC location, Vrije Universiteit Amsterdam, Amsterdam (Mutsaerts); Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen (Maximov, Bjørnerud); Division of Radiology, Vestfold Hospital Trust, Tønsberg, Norway (Groote, Caan); Computational Radiology and Artificial Intelligence, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo (Groote, Bjørnerud); Department of Psychology, University of Oslo, Oslo (Bjørnerud)
| | - Matthan W A Caan
- Department of Radiology and Nuclear Medicine (Poirot, Ruhe, Marquering, Reneman) and Department of Biomedical Engineering and Physics (Poirot, Marquering, Reneman, Caan), Amsterdam UMC Location AMC, University of Amsterdam, Amsterdam; Brain Imaging, Amsterdam Neuroscience, Amsterdam (Poirot, Mutsaerts, Reneman, Caan); Department of Psychiatry, Radboudumc, Nijmegen, the Netherlands (Ruhe); Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, the Netherlands (Ruhe); Department of Radiology and Nuclear Medicine, Amsterdam UMC location, Vrije Universiteit Amsterdam, Amsterdam (Mutsaerts); Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen (Maximov, Bjørnerud); Division of Radiology, Vestfold Hospital Trust, Tønsberg, Norway (Groote, Caan); Computational Radiology and Artificial Intelligence, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo (Groote, Bjørnerud); Department of Psychology, University of Oslo, Oslo (Bjørnerud)
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18
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Schantell M, Taylor BK, Mansouri A, Arif Y, Coutant AT, Rice DL, Wang YP, Calhoun VD, Stephen JM, Wilson TW. Theta oscillatory dynamics serving cognitive control index psychosocial distress in youth. Neurobiol Stress 2024; 29:100599. [PMID: 38213830 PMCID: PMC10776433 DOI: 10.1016/j.ynstr.2023.100599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 11/09/2023] [Accepted: 12/10/2023] [Indexed: 01/13/2024] Open
Abstract
Background Psychosocial distress among youth is a major public health issue characterized by disruptions in cognitive control processing. Using the National Institute of Mental Health's Research Domain Criteria (RDoC) framework, we quantified multidimensional neural oscillatory markers of psychosocial distress serving cognitive control in youth. Methods The sample consisted of 39 peri-adolescent participants who completed the NIH Toolbox Emotion Battery (NIHTB-EB) and the Eriksen flanker task during magnetoencephalography (MEG). A psychosocial distress index was computed with exploratory factor analysis using assessments from the NIHTB-EB. MEG data were analyzed in the time-frequency domain and peak voxels from oscillatory maps depicting the neural cognitive interference effect were extracted for voxel time series analyses to identify spontaneous and oscillatory aberrations in dynamics serving cognitive control as a function of psychosocial distress. Further, we quantified the relationship between psychosocial distress and dynamic functional connectivity between regions supporting cognitive control. Results The continuous psychosocial distress index was strongly associated with validated measures of pediatric psychopathology. Theta-band neural cognitive interference was identified in the left dorsolateral prefrontal cortex (dlPFC) and middle cingulate cortex (MCC). Time series analyses of these regions indicated that greater psychosocial distress was associated with elevated spontaneous activity in both the dlPFC and MCC and blunted theta oscillations in the MCC. Finally, we found that stronger phase coherence between the dlPFC and MCC was associated with greater psychosocial distress. Conclusions Greater psychosocial distress was marked by alterations in spontaneous and oscillatory theta activity serving cognitive control, along with hyperconnectivity between the dlPFC and MCC.
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Affiliation(s)
- Mikki Schantell
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
- College of Medicine, University of Nebraska Medical Center, Omaha, NE, USA
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Brittany K. Taylor
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
- Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, USA
| | - Amirsalar Mansouri
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Yasra Arif
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Anna T. Coutant
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Danielle L. Rice
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Yu-Ping Wang
- Department of Biomedical Engineering, Tulane University, New Orleans, LA, USA
| | - Vince D. Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging & Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | | | - Tony W. Wilson
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
- College of Medicine, University of Nebraska Medical Center, Omaha, NE, USA
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
- Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, USA
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19
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Phillips ML. Multimodal Predictors of Treatment Response in Major Depressive Disorder: Advancing Personalized Medicine in Psychiatry. Am J Psychiatry 2024; 181:180-182. [PMID: 38425254 DOI: 10.1176/appi.ajp.20231025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/02/2024]
Affiliation(s)
- Mary L Phillips
- Department of Psychiatry, University of Pittsburgh, Pittsburgh
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20
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Liu X, Zhang H, Cui Y, Zhao T, Wang B, Xie X, Liang S, Sha S, Yan Y, Zhao X, Zhang L. EEG-based major depressive disorder recognition by neural oscillation and asymmetry. Front Neurosci 2024; 18:1362111. [PMID: 38419668 PMCID: PMC10899403 DOI: 10.3389/fnins.2024.1362111] [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: 12/27/2023] [Accepted: 01/30/2024] [Indexed: 03/02/2024] Open
Abstract
Background Major Depressive Disorder (MDD) is a pervasive mental health issue with significant diagnostic challenges. Electroencephalography (EEG) offers a non-invasive window into the neural dynamics associated with MDD, yet the diagnostic efficacy is contingent upon the appropriate selection of EEG features and brain regions. Methods In this study, resting-state EEG signals from both eyes-closed and eyes-open conditions were analyzed. We examined band power across various brain regions, assessed the asymmetry of band power between the hemispheres, and integrated these features with clinical characteristics of MDD into a diagnostic regression model. Results Regression analysis found significant predictors of MDD to be beta2 (16-24 Hz) power in the Prefrontal Cortex (PFC) with eyes open (B = 20.092, p = 0.011), beta3 (24-40 Hz) power in the Medial Occipital Cortex (MOC) (B = -12.050, p < 0.001), and beta2 power in the Right Medial Frontal Cortex (RMFC) with eyes closed (B = 24.227, p < 0.001). Asymmetries in beta1 (12-16 Hz) power with eyes open (B = 28.047, p = 0.018), and in alpha (8-12 Hz, B = 9.004, p = 0.013) and theta (4-8 Hz, B = -13.582, p = 0.008) with eyes closed were also significant predictors. Conclusion The study confirms the potential of multi-region EEG analysis in improving the diagnostic precision for MDD. By including both neurophysiological and clinical data, we present a more robust approach to understanding and identifying this complex disorder. Limitations The research is limited by the sample size and the inherent variability in EEG signal interpretation. Future studies with larger cohorts and advanced analytical techniques are warranted to validate and refine these findings.
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Affiliation(s)
- Xinyu Liu
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Haoran Zhang
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Yi Cui
- Gnosis Healthineer Co. Ltd., Beijing, China
| | - Tong Zhao
- Gnosis Healthineer Co. Ltd., Beijing, China
| | - Bin Wang
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Xiaomeng Xie
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Sixiang Liang
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Sha Sha
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | | | - Xixi Zhao
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Ling Zhang
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
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21
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Jamieson AJ, Leonards CA, Davey CG, Harrison BJ. Major depressive disorder associated alterations in the effective connectivity of the face processing network: a systematic review. Transl Psychiatry 2024; 14:62. [PMID: 38272868 PMCID: PMC10810788 DOI: 10.1038/s41398-024-02734-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 12/19/2023] [Accepted: 01/02/2024] [Indexed: 01/27/2024] Open
Abstract
Major depressive disorder (MDD) is marked by altered processing of emotional stimuli, including facial expressions. Recent neuroimaging research has attempted to investigate how these stimuli alter the directional interactions between brain regions in those with MDD; however, methodological heterogeneity has made identifying consistent effects difficult. To address this, we systematically examined studies investigating MDD-associated differences present in effective connectivity during the processing of emotional facial expressions. We searched five databases: PsycINFO, EMBASE, PubMed, Scopus, and Web of Science, using a preregistered protocol (registration number: CRD42021271586). Of the 510 unique studies screened, 17 met our inclusion criteria. These studies identified that compared with healthy controls, participants with MDD demonstrated (1) reduced connectivity from the dorsolateral prefrontal cortex to the amygdala during the processing of negatively valenced expressions, and (2) increased inhibitory connectivity from the ventromedial prefrontal cortex to amygdala during the processing of happy facial expressions. Most studies investigating the amygdala and anterior cingulate cortex noted differences in their connectivity; however, the precise nature of these differences was inconsistent between studies. As such, commonalities observed across neuroimaging modalities warrant careful investigation to determine the specificity of these effects to particular subregions and emotional expressions. Future research examining longitudinal connectivity changes associated with treatment response may provide important insights into mechanisms underpinning therapeutic interventions, thus enabling more targeted treatment strategies.
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Affiliation(s)
- Alec J Jamieson
- Department of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia.
| | - Christine A Leonards
- Department of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia
| | - Christopher G Davey
- Department of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia
| | - Ben J Harrison
- Department of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia.
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22
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Leonards CA, Harrison BJ, Jamieson AJ, Agathos J, Steward T, Davey CG. Altered task-related decoupling of the rostral anterior cingulate cortex in depression. Neuroimage Clin 2024; 41:103564. [PMID: 38218081 PMCID: PMC10821626 DOI: 10.1016/j.nicl.2024.103564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 12/08/2023] [Accepted: 01/07/2024] [Indexed: 01/15/2024]
Abstract
Dysfunctional activity of the rostral anterior cingulate cortex (rACC) - an extensively connected hub region of the default mode network - has been broadly linked to cognitive and affective impairments in depression. However, the nature of aberrant task-related rACC suppression in depression is incompletely understood. In this study, we sought to characterize functional connectivity of rACC activity suppression ('deactivation') - an essential feature of rACC function - during external task engagement in depression. Specifically, we aimed to explore neural patterns of functional decoupling and coupling with the rACC during its task-driven suppression. We enrolled 81 15- to 25-year-old young people with moderate-to-severe major depressive disorder (MDD) before they commenced a 12-week clinical trial that assessed the effectiveness of cognitive behavioral therapy plus either fluoxetine or placebo. Ninety-four matched healthy controls were also recruited. Participants completed a functional magnetic resonance imaging face matching task known to elicit rACC suppression. To identify brain regions associated with the rACC during its task-driven suppression, we employed a seed-based functional connectivity analysis. We found MDD participants, compared to controls, showed significantly reduced 'decoupling' of the rACC with extended task-specific regions during task performance. Specifically, less decoupling was observed in the occipital and fusiform gyrus, dorsal ACC, medial prefrontal cortex, cuneus, amygdala, thalamus, and hippocampus. Notably, impaired decoupling was apparent in participants who did not remit to treatment, but not treatment remitters. Further, we found MDD participants showed significant increased coupling with the anterior insula cortex during task engagement. Our findings indicate that aberrant task-related rACC suppression is associated with disruptions in adaptive neural communication and dynamic switching between internal and external cognitive modes that may underpin maladaptive cognitions and biased emotional processing in depression.
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Affiliation(s)
- Christine A Leonards
- Department of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia
| | - Ben J Harrison
- Department of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia
| | - Alec J Jamieson
- Department of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia
| | - James Agathos
- Department of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia
| | - Trevor Steward
- Department of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia; Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, Victoria, Australia
| | - Christopher G Davey
- Department of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia.
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23
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Gonsalves MA, White TL, Barredo J, DeMayo MM, DeLuca E, Harris AD, Carpenter LL. Cortical glutamate, Glx, and total N-acetylaspartate: potential biomarkers of repetitive transcranial magnetic stimulation treatment response and outcomes in major depression. Transl Psychiatry 2024; 14:5. [PMID: 38184652 PMCID: PMC10771455 DOI: 10.1038/s41398-023-02715-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 12/06/2023] [Accepted: 12/13/2023] [Indexed: 01/08/2024] Open
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for individuals with major depressive disorder (MDD) who have not improved with standard therapies. However, only 30-45% of patients respond to rTMS. Predicting response to rTMS will benefit both patients and providers in terms of prescribing and targeting treatment for maximum efficacy and directing resources, as individuals with lower likelihood of response could be redirected to more suitable treatment alternatives. In this exploratory study, our goal was to use proton magnetic resonance spectroscopy to examine how glutamate (Glu), Glx, and total N-acetylaspartate (tNAA) predict post-rTMS changes in overall MDD severity and symptoms, and treatment response. Metabolites were measured in a right dorsal anterior cingulate cortex voxel prior to a standard course of 10 Hz rTMS to the left DLPFC in 25 individuals with MDD. MDD severity and symptoms were evaluated via the Inventory of Depression Symptomatology Self-Report (IDS-SR). rTMS response was defined as ≥50% change in full-scale IDS-SR scores post treatment. Percent change in IDS-SR symptom domains were evaluated using principal component analysis and established subscales. Generalized linear and logistic regression models were used to evaluate the relationship between baseline Glu, Glx, and tNAA and outcomes while controlling for age and sex. Participants with baseline Glu and Glx levels in the lower range had greater percent change in full scale IDS-SR scores post-treatment (p < 0.001), as did tNAA (p = 0.007). Low glutamatergic metabolite levels also predicted greater percent change in mood/cognition symptoms (p ≤ 0.001). Low-range Glu, Glx, and tNAA were associated with greater improvement on the immuno-metabolic subscale (p ≤ 0.003). Baseline Glu predicted rTMS responder status (p = 0.025) and had an area under the receiving operating characteristic curve of 0.81 (p = 0.009), demonstrating excellent discriminative ability. Baseline Glu, Glx, and tNAA significantly predicted MDD improvement after rTMS; preliminary evidence also demonstrates metabolite association with symptom subdomain improvement post-rTMS. This work provides feasibility for a personalized medicine approach to rTMS treatment selection, with individuals with Glu levels in the lower range potentially being the best candidates.
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Affiliation(s)
- Meghan A Gonsalves
- Neuroscience Graduate Program, Brown University, Providence, RI, USA.
- Butler Hospital Neuromodulation Research Facility, Providence, RI, USA.
- Center of Biomedical Research Excellence (COBRE) for Neuromodulation, Butler Hospital, Providence, RI, USA.
| | - Tara L White
- Center for Alcohol and Addiction Studies, Brown University, Providence, RI, USA
- Department of Behavioral and Social Sciences, School of Public Health, Brown University, Providence, RI, USA
- Carney Institute for Brain Sciences, Brown University, Providence, RI, USA
| | - Jennifer Barredo
- Department of Psychiatry and Human Behavior, Alpert Medical School, Brown University, Providence, RI, USA
- Providence VA Medical Center, Providence, RI, USA
- Clinical Neuroimaging Research Core, Brown University, Providence, RI, USA
| | - Marilena M DeMayo
- Department of Radiology, University of Calgary, Calgary, AB, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Emily DeLuca
- Clinical Neuroimaging Research Core, Brown University, Providence, RI, USA
| | - Ashley D Harris
- Department of Radiology, University of Calgary, Calgary, AB, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Linda L Carpenter
- Butler Hospital Neuromodulation Research Facility, Providence, RI, USA
- Center of Biomedical Research Excellence (COBRE) for Neuromodulation, Butler Hospital, Providence, RI, USA
- Department of Psychiatry and Human Behavior, Alpert Medical School, Brown University, Providence, RI, USA
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Liang L, Wang LL, Jiang XD, Chen DJ, Huang TA, Ding WB. Hippocampal volume and resting-state functional connectivity on magnetic resonance imaging in patients with Parkinson and depression. Quant Imaging Med Surg 2024; 14:824-836. [PMID: 38223081 PMCID: PMC10784022 DOI: 10.21037/qims-23-919] [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: 06/26/2023] [Accepted: 11/07/2023] [Indexed: 01/16/2024]
Abstract
Background Recent structural and functional imaging studies of depression in Parkinson disease (DPD) have failed to reveal the relevant mechanism, and relatively few studies have been conducted on limbic systems such as the hippocampus. This study thus aimed to gain new insights into the pathogenesis of DPD by detecting the changes in the hippocampal structure and the resting-state functional connectivity (FC) of patients with DPD. Methods This study included 30 patients with DPD (DPD group), 30 patients with nondepressed Parkinson disease (NDPD; NDPD group), and 30 normal controls (NCs; NC group) with no significant age or gender differences with the DPD group. The Hamilton Depression Rating Scale (HAMD) and three-dimensional T1-weighted imaging and blood oxygen level-dependent imaging data of all patients were collected. The hippocampal volumes were measured using MATLAB software (MathWorks). The correlation between hippocampal volume and the HAMD score in the DPD group was analyzed with Pearson correlation coefficient. The bilateral hippocampi were used as the regions of interest and as the seed points for FC. FC analysis was performed between the preprocessed functional data of the whole brain and the two seed points with Data Processing Assistant for Resting-State and Statistical Parametric Mapping 8 software, respectively. The correlation between FC and HAMD scores in the patients with DPD was determined using partial correlation analysis. Results Compared with those in the NC group and the NDPD group, the bilateral hippocampal volumes in the DPD group were significantly decreased (P<0.05). There was a negative correlation between the bilateral hippocampal volume and the HAMD score in the DPD group (P<0.05). Compared with that of the NDPD group, the FC of the right hippocampus with the right occipital lobe and left precuneus was reduced in the DPD group. In the DPD group, the FC values of the right hippocampus, right occipital lobe, and left anterior cuneiform lobe were negatively correlated with HAMD scores. Conclusions The volume of bilateral hippocampi in patients with DPD is significantly decreased and negatively correlated with the severity of depressive disorder. The weakened FC of the right hippocampus to the right occipital lobe and the left precuneus may play an important role in the neurological basis of DPD.
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Affiliation(s)
- Li Liang
- Department of Intervention, Nantong First People’s Hospital, Nantong, China
| | - Ling-Ling Wang
- Clinical Laboratory, Nantong First People’s Hospital, Nantong, China
- Department of Medical Immunology, Nantong University, Nantong, China
| | - Xiao-Dong Jiang
- Department of Intervention, Nantong First People’s Hospital, Nantong, China
| | - Dong-Jian Chen
- Department of Intervention, Nantong First People’s Hospital, Nantong, China
| | - Tian-An Huang
- Department of Intervention, Nantong First People’s Hospital, Nantong, China
| | - Wen-Bin Ding
- Department of Intervention, Nantong First People’s Hospital, Nantong, China
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25
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Long Z, Du L, Marino M. Individual resting-state network functional connectivity predicts treatment improvement of repetitive transcranial magnetic stimulation in major depressive disorder: A pilot study. Psychiatry Res 2024; 331:115616. [PMID: 38039648 DOI: 10.1016/j.psychres.2023.115616] [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: 09/01/2023] [Revised: 11/16/2023] [Accepted: 11/18/2023] [Indexed: 12/03/2023]
Abstract
The current pilot study aimed to exploratively investigate whether individual functional connectivity (FC) of the rTMS stimulation site with resting-state networks could predict the individual efficacy of rTMS treatment. We found that rTMS induced an increase of the FC between the stimulation site and the limbic network (LN) in healthy participants, and that this individualized FC was negatively correlated with the rTMS treatment improvement in MDD patients. Moreover, the LN successfully guided the personalized rTMS therapy. These findings highlighted the crucial role of the LN in understanding the mechanisms underlying rTMS treatment improvement, and the personalized therapy in MDD patients.
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Affiliation(s)
- Zhiliang Long
- Sleep and NeuroImaging Center, Faculty of Psychology, Southwest University, Chongqing, PR China.
| | - Lian Du
- Department of Psychiatry, The First Affliated Hospital of Chongqing Medical University, Chongqing, PR China
| | - Marco Marino
- KU Leuven, Movement Control & Neuroplasticity Research Group, Leuven, Belgium; Department of General Psychology, University of Padua, Italy
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26
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Deng ZD, Robins PL, Regenold W, Rohde P, Dannhauer M, Lisanby SH. How electroconvulsive therapy works in the treatment of depression: is it the seizure, the electricity, or both? Neuropsychopharmacology 2024; 49:150-162. [PMID: 37488281 PMCID: PMC10700353 DOI: 10.1038/s41386-023-01677-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 06/27/2023] [Accepted: 07/14/2023] [Indexed: 07/26/2023]
Abstract
We have known for nearly a century that triggering seizures can treat serious mental illness, but what we do not know is why. Electroconvulsive Therapy (ECT) works faster and better than conventional pharmacological interventions; however, those benefits come with a burden of side effects, most notably memory loss. Disentangling the mechanisms by which ECT exerts rapid therapeutic benefit from the mechanisms driving adverse effects could enable the development of the next generation of seizure therapies that lack the downside of ECT. The latest research suggests that this goal may be attainable because modifications of ECT technique have already yielded improvements in cognitive outcomes without sacrificing efficacy. These modifications involve changes in how the electricity is administered (both where in the brain, and how much), which in turn impacts the characteristics of the resulting seizure. What we do not completely understand is whether it is the changes in the applied electricity, or in the resulting seizure, or both, that are responsible for improved safety. Answering this question may be key to developing the next generation of seizure therapies that lack these adverse side effects, and ushering in novel interventions that are better, faster, and safer than ECT.
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Affiliation(s)
- Zhi-De Deng
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Pei L Robins
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - William Regenold
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Paul Rohde
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Moritz Dannhauer
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Sarah H Lisanby
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, Bethesda, MD, USA.
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27
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Runyan A, Cassani A, Reyna L, Walsh EC, Hoks RM, Birn RM, Abercrombie HC, Philippi CL. Effects of Cortisol Administration on Resting-State Functional Connectivity in Women with Depression. Psychiatry Res Neuroimaging 2024; 337:111760. [PMID: 38039780 PMCID: PMC10843737 DOI: 10.1016/j.pscychresns.2023.111760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 11/01/2023] [Accepted: 11/20/2023] [Indexed: 12/03/2023]
Abstract
Previous resting-state functional connectivity (rsFC) research has identified several brain networks impacted by depression and cortisol, including default mode (DMN), frontoparietal (FPN), and salience networks (SN). In the present study, we examined the effects of cortisol administration on rsFC of these networks in individuals varying in depression history and severity. We collected resting-state fMRI scans and self-reported depression symptom severity for 74 women with and without a history of depression after cortisol and placebo administration using a double-blind, crossover design. We conducted seed-based rsFC analyses for DMN, FPN, and SN seeds to examine rsFC changes after cortisol vs. placebo administration in relation to depression history group and severity. Results revealed a main effect of depression group, with lower left amygdala (SN)-middle temporal gyrus connectivity in women with a history of depression. Cortisol administration increased insula (SN)-inferior frontal gyrus and superior temporal gyrus connectivity. We also found that greater depression severity was associated with increased PCC (DMN)-cerebellum connectivity after cortisol. These results did not survive Bonferroni correction for seed ROIs and should be interpreted with caution. Our findings indicate that acute cortisol elevation may normalize aberrant connectivity of DMN and SN regions, which could help inform clinical treatments for depression.
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Affiliation(s)
- Adam Runyan
- Department of Psychological Sciences, University of Central Missouri, 116 West S. St., Warrensburg, MO 64093, USA
| | - Alexis Cassani
- Department of Psychological Sciences, University of Missouri-St. Louis, 1 University Blvd., St. Louis, Missouri, MO 63121, USA
| | - Leah Reyna
- Department of Psychological Sciences, University of Missouri-St. Louis, 1 University Blvd., St. Louis, Missouri, MO 63121, USA
| | - Erin C Walsh
- Department of Psychiatry, University of North Carolina at Chapel Hill School of Medicine, CB# 7167, Chapel Hill, NC 27599, USA
| | - Roxanne M Hoks
- Center for Healthy Minds, University of Wisconsin-Madison, 625W. Washington Ave., Madison, WI 53703, USA
| | - Rasmus M Birn
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Blvd., Madison, Wisconsin, 53719, USA
| | - Heather C Abercrombie
- Center for Healthy Minds, University of Wisconsin-Madison, 625W. Washington Ave., Madison, WI 53703, USA
| | - Carissa L Philippi
- Department of Psychological Sciences, University of Missouri-St. Louis, 1 University Blvd., St. Louis, Missouri, MO 63121, USA.
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28
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Wang H, Zhang T, Zu M, Fan S, Kai Y, Zhang J, Ji Y, Pang X, Tian Y. Electroconvulsive therapy enhances degree centrality in the orbitofrontal cortex in depressive rumination. Psychiatry Res Neuroimaging 2024; 337:111765. [PMID: 38104485 DOI: 10.1016/j.pscychresns.2023.111765] [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: 09/30/2023] [Revised: 11/13/2023] [Accepted: 12/02/2023] [Indexed: 12/19/2023]
Abstract
Depressive rumination has been implicated in the onset, duration, and treatment response of refractory depression. Electroconvulsive therapy (ECT) is remarkably effective in treatment of refractory depression by modulating the functional coordination between brain hubs. However, the mechanisms by which ECT regulates depressive rumination remain unsolved. We investigated degree centrality (DC) in 32 pre- and post-ECT depression patients as well as 38 matched healthy controls. An identified brain region was defined as the seed to calculate functional connectivity (FC) in whole brains. Rumination was measured by the Ruminative Response Scale (RRS) and its relationships with identified DC and FC alterations were examined. We found a significant negative correlation between DC of the right orbitofrontal cortex (rOFC) before ECT and brooding level before and after treatment. Moreover, rOFC DC increased after ECT. DC of the left superior temporal gyrus (lSTG) was positively correlated with reflective level before intervention, while lSTG DC decreased after ECT. Patients showed elevated FC in the rOFC with default mode network. No significant association was found between decreased RRS scores and changes in DC and FC. Our findings suggest that functional changes in rOFC and lSTG may be associated with the beneficial effects of ECT on depressive rumination.
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Affiliation(s)
- Hongping Wang
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Ting Zhang
- Department of Psychiatry, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Meidan Zu
- Department of Neurology, Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Siyu Fan
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Yiao Kai
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Jiahua Zhang
- School of Mental Health and Psychological Science, Anhui Medical University, Hefei, Anhui, China
| | - Yang Ji
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Xiaonan Pang
- Department of Neurology, Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
| | - Yanghua Tian
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China; Department of Neurology, Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
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29
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Berkovitch L, Lee K, Ji JL, Helmer M, Rahmati M, Demšar J, Kraljič A, Matkovič A, Tamayo Z, Murray JD, Repovš G, Krystal JH, Martin WJ, Fonteneau C, Anticevic A. A common symptom geometry of mood improvement under sertraline and placebo associated with distinct neural patterns. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.15.23300019. [PMID: 38168378 PMCID: PMC10760263 DOI: 10.1101/2023.12.15.23300019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Importance Understanding the mechanisms of major depressive disorder (MDD) improvement is a key challenge to determine effective personalized treatments. Objective To perform a secondary analysis quantifying neural-to-symptom relationships in MDD as a function of antidepressant treatment. Design Double blind randomized controlled trial. Setting Multicenter. Participants Patients with early onset recurrent depression from the public Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study. Interventions Either sertraline or placebo during 8 weeks (stage 1), and according to response a second line of treatment for 8 additional weeks (stage 2). Main Outcomes and Measures To identify a data-driven pattern of symptom variations during these two stages, we performed a Principal Component Analysis (PCA) on the variations of individual items of four clinical scales measuring depression, anxiety, suicidal ideas and manic-like symptoms, resulting in a univariate measure of clinical improvement. We then investigated how initial clinical and neural factors predicted this measure during stage 1. To do so, we extracted resting-state global brain connectivity (GBC) at baseline at the individual level using a whole-brain functional network parcellation. In turn, we computed a linear model for each brain parcel with individual data-driven clinical improvement scores during stage 1 for each group. Results 192 patients (127 women), age 37.7 years old (standard deviation: 13.5), were included. The first PC (PC1) capturing 20% of clinical variation was similar across treatment groups at stage 1 and stage 2, suggesting a reproducible pattern of symptom improvement. PC1 patients' scores significantly differed according to treatment during stage 1, whereas no difference of response was evidenced between groups with the Clinical Global Impressions (CGI). Baseline GBC correlated to stage 1 PC1 scores in the sertraline, but not in the placebo group. Conclusions and Relevance Using data-driven reduction of symptoms scales, we identified a common profile of symptom improvement across placebo and sertraline. However, the neural patterns of baseline that mapped onto symptom improvement distinguished between treatment and placebo. Our results underscore that mapping from data-driven symptom improvement onto neural circuits is vital to detect treatment-responsive neural profiles that may aid in optimal patient selection for future trials.
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Affiliation(s)
- Lucie Berkovitch
- Department of Psychiatry, Neuroscience, and Psychology, Yale University School of Medicine, New Haven, CT, USA
- Division of Neurocognition, Neurocomputation, Neurogenetics (N3), Yale University School of Medicine, New Haven, Connecticut, USA
- Université Paris Cité, Paris, France
- Department of Psychiatry, GHU Paris Psychiatrie et Neurosciences, Service Hospitalo-Universitaire, Paris, France
- Unicog, Saclay CEA Centre, Neurospin, Gif-Sur-Yvette Cedex, France
| | - Kangjoo Lee
- Department of Psychiatry, Neuroscience, and Psychology, Yale University School of Medicine, New Haven, CT, USA
- Division of Neurocognition, Neurocomputation, Neurogenetics (N3), Yale University School of Medicine, New Haven, Connecticut, USA
| | - Jie Lisa Ji
- Manifest Technologies, Inc. New Haven, CT, USA
| | | | | | - Jure Demšar
- Department of Psychology, University of Ljubljana, Ljubljana, Slovenia
- Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia
| | - Aleksij Kraljič
- Department of Psychology, University of Ljubljana, Ljubljana, Slovenia
| | - Andraž Matkovič
- Department of Psychology, University of Ljubljana, Ljubljana, Slovenia
| | - Zailyn Tamayo
- Department of Psychiatry, Neuroscience, and Psychology, Yale University School of Medicine, New Haven, CT, USA
- Division of Neurocognition, Neurocomputation, Neurogenetics (N3), Yale University School of Medicine, New Haven, Connecticut, USA
| | - John D Murray
- Department of Psychological and Brain Science, Dartmouth College, Hanover, NH, USA
| | - Grega Repovš
- Department of Psychology, University of Ljubljana, Ljubljana, Slovenia
| | - John H Krystal
- Department of Psychiatry, Neuroscience, and Psychology, Yale University School of Medicine, New Haven, CT, USA
- Division of Neurocognition, Neurocomputation, Neurogenetics (N3), Yale University School of Medicine, New Haven, Connecticut, USA
| | | | - Clara Fonteneau
- Department of Psychiatry, Neuroscience, and Psychology, Yale University School of Medicine, New Haven, CT, USA
- Division of Neurocognition, Neurocomputation, Neurogenetics (N3), Yale University School of Medicine, New Haven, Connecticut, USA
| | - Alan Anticevic
- Department of Psychiatry, Neuroscience, and Psychology, Yale University School of Medicine, New Haven, CT, USA
- Division of Neurocognition, Neurocomputation, Neurogenetics (N3), Yale University School of Medicine, New Haven, Connecticut, USA
- Department of Psychology, Yale University School of Medicine, New Haven, CT, USA
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30
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Li CT, Chen CS, Cheng CM, Chen CP, Chen JP, Chen MH, Bai YM, Tsai SJ. Prediction of antidepressant responses to non-invasive brain stimulation using frontal electroencephalogram signals: Cross-dataset comparisons and validation. J Affect Disord 2023; 343:86-95. [PMID: 37579885 DOI: 10.1016/j.jad.2023.08.059] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2023] [Revised: 08/10/2023] [Accepted: 08/11/2023] [Indexed: 08/16/2023]
Abstract
BACKGROUND 10-Hz repetitive transcranial magnetic stimulation(rTMS) and intermittent theta-burst stimulation(iTBS) over left prefrontal cortex are FDA-approved, effective options for treatment-resistant depression (TRD). Optimal prediction models for iTBS and rTMS remain elusive. Therefore, our primary objective was to compare prediction accuracy between classification by frontal theta activity alone and machine learning(ML) models by linear and non-linear frontal signals. The second objective was to study an optimal ML model for predicting responses to rTMS and iTBS. METHODS Two rTMS and iTBS datasets (n = 163) were used: one randomized controlled trial dataset (RCTD; n = 96) and one outpatient dataset (OPD; n = 67). Frontal theta and non-linear EEG features that reflect trend, stability, and complexity were extracted. Pretreatment frontal EEG and ML algorithms, including classical support vector machine(SVM), random forest(RF), XGBoost, and CatBoost, were analyzed. Responses were defined as ≥50 % depression improvement after treatment. Response rates between those with and without pretreatment prediction in another independent outpatient cohort (n = 208) were compared. RESULTS Prediction accuracy using combined EEG features by SVM was better than frontal theta by logistic regression. The accuracy for OPD patients significantly dropped using the RCTD-trained SVM model. Modern ML models, especially RF (rTMS = 83.3 %, iTBS = 88.9 %, p-value(ACC > NIR) < 0.05 for iTBS), performed significantly above chance and had higher accuracy than SVM using both selected features (p < 0.05, FDR corrected for multiple comparisons) or all EEG features. Response rates among those receiving prediction before treatment were significantly higher than those without prediction (p = 0.035). CONCLUSION The first study combining linear and non-linear EEG features could accurately predict responses to left PFC iTBS. The bootstraps-based ML model (i.e., RF) had the best predictive accuracy for rTMS and iTBS.
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Affiliation(s)
- Cheng-Ta Li
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan; Division of Psychiatry, School of Medicine, National Yang-Ming Chiao-Tung University, Taipei, Taiwan; Institute of Brain Science and Brain Research Center, School of Medicine, National Yang-Ming Chiao-Tung University, Taipei, Taiwan; Institute of Cognitive Neuroscience, National Central University, Jhongli, Taiwan.
| | - Chi-Sheng Chen
- Graduate Institute of Biomedical Electronics and Bioinformatics College of Electrical Engineering and Computer Science, National Taiwan University, Taipei, Taiwan
| | - Chih-Ming Cheng
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Chung-Ping Chen
- Graduate Institute of Biomedical Electronics and Bioinformatics College of Electrical Engineering and Computer Science, National Taiwan University, Taipei, Taiwan
| | - Jen-Ping Chen
- Division of Psychiatry, School of Medicine, National Yang-Ming Chiao-Tung University, Taipei, Taiwan
| | - Mu-Hong Chen
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan; Division of Psychiatry, School of Medicine, National Yang-Ming Chiao-Tung University, Taipei, Taiwan; Institute of Brain Science and Brain Research Center, School of Medicine, National Yang-Ming Chiao-Tung University, Taipei, Taiwan
| | - Ya-Mei Bai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan; Division of Psychiatry, School of Medicine, National Yang-Ming Chiao-Tung University, Taipei, Taiwan; Institute of Brain Science and Brain Research Center, School of Medicine, National Yang-Ming Chiao-Tung University, Taipei, Taiwan
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan; Division of Psychiatry, School of Medicine, National Yang-Ming Chiao-Tung University, Taipei, Taiwan; Institute of Brain Science and Brain Research Center, School of Medicine, National Yang-Ming Chiao-Tung University, Taipei, Taiwan
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31
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Lu F, Cui Q, Zou Y, Guo Y, Luo W, Yu Y, Gao J, Cai X, Fu L, Yuan S, Huang J, Zhang Y, Xie J, Sheng W, Tang Q, Gao Q, He Z, Chen H. Effects of rTMS Intervention on Functional Neuroimaging Activities in Adolescents with Major Depressive Disorder Measured Using Resting-State fMRI. Bioengineering (Basel) 2023; 10:1374. [PMID: 38135965 PMCID: PMC10740826 DOI: 10.3390/bioengineering10121374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 11/10/2023] [Accepted: 11/22/2023] [Indexed: 12/24/2023] Open
Abstract
Repetitive transcranial magnetic stimulation (rTMS) to the left dorsolateral prefrontal cortex (L-DLPFC) is commonly used for the clinical treatment of major depressive disorder (MDD). The neuroimaging biomarkers and mechanisms of rTMS are still not completely understood. This study aimed to explore the functional neuroimaging changes induced by rTMS in adolescents with MDD. A total of ten sessions of rTMS were administrated to the L-DLPFC in thirteen adolescents with MDD once a day for two weeks. All of them were scanned using resting-state functional magnetic resonance imaging at baseline and after rTMS treatment. The regional homogeneity (ReHo), amplitude of low-frequency fluctuation (ALFF), and the subgenual anterior cingulate cortex (sgACC)-based functional connectivity (FC) were computed as neuroimaging indicators. The correlation between changes in the sgACC-based FC and the improvement in depressive symptoms was also analyzed. After rTMS treatment, ReHo and ALFF were significantly increased in the L-DLPFC, the left medial prefrontal cortex, bilateral medial orbital frontal cortex, and the left ACC. ReHo and ALFF decreased mainly in the left middle occipital gyrus, the right middle cingulate cortex (MCC), bilateral calcarine, the left cuneus, and the left superior occipital gyrus. Furthermore, the FCs between the left sgACC and the L-DLPFC, the right IFGoper, the left MCC, the left precuneus, bilateral post-central gyrus, the left supplementary motor area, and the left superior marginal gyrus were enhanced after rTMS treatment. Moreover, the changes in the left sgACC-left MCC FC were associated with an improvement in depressive symptoms in early improvers. This study showed that rTMS treatment in adolescents with MDD causes changes in brain activities and sgACC-based FC, which may provide basic neural biomarkers for rTMS clinical trials.
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Affiliation(s)
- Fengmei Lu
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Qian Cui
- School of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Yang Zou
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Yuanhong Guo
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Wei Luo
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Yue Yu
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Jingjing Gao
- School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China;
| | - Xiao Cai
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Linna Fu
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Shuai Yuan
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Juan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Yajun Zhang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Jing Xie
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Wei Sheng
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Qin Tang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Qing Gao
- School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Zongling He
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
- MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 611731, China
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Duan J, Li Y, Zhang X, Dong S, Zhao P, Liu J, Zheng J, Zhu R, Kong Y, Wang F. Predicting treatment response in adolescents and young adults with major depressive episodes from fMRI using graph isomorphism network. Neuroimage Clin 2023; 40:103534. [PMID: 37939442 PMCID: PMC10665904 DOI: 10.1016/j.nicl.2023.103534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 10/30/2023] [Accepted: 10/30/2023] [Indexed: 11/10/2023]
Abstract
BACKGROUND Major depressive episode (MDE) is the main clinical feature of mood disorders (major depressive disorder and bipolar disorder) in adolescents and young adults and accounts for most of the disease course. However, 30%-40% of MDE patients not responding to clinical first-line interventions. It is crucial to predict treatment response in the early stages and identify biomarkers associated with treatment response. Graph Isomorphism Network (GIN), a deep learning method, is promising for predicting treatment response for individual MDE patients with more powerful representation ability to capture the features of brain functional connectivity. METHODS In this study, GIN was used to predict individual treatment response in 198 adolescents and young adults with MDE. The most discriminating regions were also identified for the treatment response prediction. RESULTS Using GIN approach, the baseline functional connectivity could predict 79.8% responders and 67.4% non-responders to treatment (accuracy 74.24%). Furthermore, the most discriminating brain regions were mainly involved in paralimbic and subcortical areas. CONCLUSIONS GIN has shown potential in predicting treatment response for individual patients, which may enable personalized treatment decisions. Furthermore, targeted interventions focused on modulating the activity and connectivity within paralimbic and subcortical regions could potentially improve treatment outcomes and enable personalized interventions for adolescents and young adults with MDE.
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Affiliation(s)
- Jia Duan
- Department of Mental Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yueying Li
- Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing, School of Computer Science and Engineering, Southeast University, Nanjing, China
| | - Xiaotong Zhang
- Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing, School of Computer Science and Engineering, Southeast University, Nanjing, China
| | - Shuai Dong
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Pengfei Zhao
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Jie Liu
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Junjie Zheng
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Rongxin Zhu
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Youyong Kong
- Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing, School of Computer Science and Engineering, Southeast University, Nanjing, China; Key Laboratory of Computer Network and Information Integration, Southeast University, Ministry of Education, Nanjing, China.
| | - Fei Wang
- Department of Mental Health, School of Public Health, Nanjing Medical University, Nanjing, China; Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
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Gärtner M, Weigand A, Meiering MS, Weigner D, Carstens L, Keicher C, Hertrampf R, Beckmann C, Mennes M, Wunder A, Grimm S. Region- and time- specific effects of ketamine on cerebral blood flow: a randomized controlled trial. Neuropsychopharmacology 2023; 48:1735-1741. [PMID: 37231079 PMCID: PMC10579356 DOI: 10.1038/s41386-023-01605-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 05/04/2023] [Accepted: 05/07/2023] [Indexed: 05/27/2023]
Abstract
There is intriguing evidence suggesting that ketamine might have distinct acute and delayed neurofunctional effects, as its acute administration transiently induces schizophrenia-like symptoms, while antidepressant effects slowly emerge and are most pronounced 24 h after administration. Studies attempting to characterize ketamine's mechanism of action by using blood oxygen level dependent (BOLD) imaging have yielded inconsistent results regarding implicated brain regions and direction of effects. This may be due to intrinsic properties of the BOLD contrast, while cerebral blood flow (CBF), as measured with arterial spin labeling, is a single physiological marker more directly related to neural activity. As effects of acute ketamine challenge are sensitive to modulation by pretreatment with lamotrigine, which inhibits glutamate release, a combination of these approaches should be particularly suited to offer novel insights. In total, 75 healthy participants were investigated in a double blind, placebo-controlled, randomized, parallel-group study and underwent two scanning sessions (acute/post 24 h.). Acute ketamine administration was associated with higher perfusion in interior frontal gyrus (IFG) and dorsolateral prefrontal cortex (DLPFC), but no other investigated brain region. Inhibition of glutamate release by pretreatment with lamotrigine abolished ketamine's effect on perfusion. At the delayed time point, pretreatment with lamotrigine was associated with lower perfusion in IFG. These findings underscore the idea that regionally selective patterns of CBF changes reflect proximate effects of modulated glutamate release on neuronal activity. Furthermore, region- specific sustained effects indicate both a swift restoration of disturbed homeostasis in DLPFC as well changes occurring beyond the immediate effects on glutamate signaling in IFG.
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Affiliation(s)
- Matti Gärtner
- Medical School Berlin, Berlin, Germany.
- Department of Psychiatry and Psychotherapy, Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Berlin, Germany.
| | | | | | | | | | | | | | | | | | - Andreas Wunder
- Translational Medicine and Clinical Pharmacology, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany
| | - Simone Grimm
- Medical School Berlin, Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Berlin, Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital of Psychiatry, University of Zurich, Zurich, Switzerland
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Chibaatar E, Watanabe K, Quinn PM, Okamoto N, Shinkai T, Natsuyama T, Hayasaki G, Ikenouchi A, Kakeda S, Yoshimura R. Triple network connectivity changes in patients with major depressive disorder versus healthy controls via structural network imaging after electroconvulsive therapy treatment. J Affect Disord 2023; 340:923-929. [PMID: 37598718 DOI: 10.1016/j.jad.2023.08.020] [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: 04/13/2023] [Revised: 07/06/2023] [Accepted: 08/03/2023] [Indexed: 08/22/2023]
Abstract
OBJECTIVE To investigate the effect of electroconvulsive treatment (ECT) on dynamic structural network connectivity in major depressive disorder (MDD), based on the triple-network model. METHODS Twenty-one first-episode, drug-naïve patients with MDD and 21 age- and sex-matched healthy subjects were recruited. Bilateral electrical stimulation was performed thrice a week for a total of 4-5 weeks in the MDD group. MRI data were obtained, and triple-network structural connectivity was evaluated using source-based morphometry (SBM) analysis. A paired t-test was used to analyze structural connectivity differences between pre- and post-ECT MDD groups, one-way analysis was used to calculate three intrinsic network differences between HCs, pre- and post-ECT groups, and partial least squares structural equation modelling was used to investigate dynamic structural network connectivity (dSNC) across groups. RESULTS Pre-ECT patients with MDD exhibited significantly lower salience network (SN) structural connectivity (p = 0.010) than the healthy control (HC) group and after ECT therapy SN structural connectivity was significantly elevated (p = 0.002) in post-ECT group compared with pre-ECT. PLS-SEM analysis conducted on inter-network connectivity in the triple-network model indicated a significant difference between SN and central executive network (CEN) in all three groups. The HC and post-ECT MDD groups showed notable direct connectivity between the SN and default mode network (DMN), while the pre-ECT MDD group showed consequential pathological connectivity between the CEN and DMN. A mediation analysis revealed a significant indirect effect of the SN on the DMN through the CEN (β = 0.363, p = 0.008) only in the pre-ECT MDD group. CONCLUSIONS ECT may be an effective and minimally invasive treatment for addressing structural changes in the SN and direct communication abnormalities between the three core brain networks in patients with MDD, with possible beneficial correction of indirect connections.
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Affiliation(s)
- Enkmurun Chibaatar
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Keita Watanabe
- Department of Radiology, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Patrick M Quinn
- Wakamatsu Hospital, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Naomichi Okamoto
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Takahiro Shinkai
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Tomoya Natsuyama
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Gaku Hayasaki
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Atsuko Ikenouchi
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Shingo Kakeda
- Department of Radiology, Graduate School of Medicine, Hirosaki University, Hirosaki, Japan
| | - Reiji Yoshimura
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan.
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Gao M, Sang W, Mi K, Liu J, Liu Y, Zhen W, An B. The Relationship Between Theta Power, Theta Asymmetry and the Effect of Escitalopram in the Treatment of Depression. Neuropsychiatr Dis Treat 2023; 19:2241-2249. [PMID: 37900670 PMCID: PMC10612517 DOI: 10.2147/ndt.s425506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 10/05/2023] [Indexed: 10/31/2023] Open
Abstract
Objective Only about one-third of depressed patients respond to initial antidepressant treatment. Therefore, it is crucial to find effective predictors of antidepressants. The purpose of our study was to learn the relationship between EEG theta power, theta asymmetry, and the efficacy of escitalopram. Methods The study included 34 patients with depression. Before and after each patient's course of treatment, EEG data was gathered. Both the Hamilton Anxiety Scale (HAMA) and the 17-item Hamilton Depression Scale (HAMD-17) were evaluated simultaneously. The natural logarithm of right frontal theta power minus left frontal theta power was used to calculate inter-electrode theta asymmetry (AT). Results First, our study found no statistically significant difference between intra-electrode theta power and inter-electrode AT before and after treatment (P ≥ 0.05). When we later looked at the data regarding treatment effects, the findings revealed that patients (n = 9) who did not respond to treatment had lower baseline theta power at C4 [6.190 (2.000, 12.990) vs 15.800 (7.255, 22.330), z = -2.166, P = 0.030]. The two groups had no difference in other electrodes (P ≥ 0.05). The AT of C3/C4 in non-responders (n = 9) was lower [0.012 (0.795) vs 0.733 (0.539), t = -3.224, P = 0.005]. However, there was no difference in inter-electrode AT between the two groups in F3/F4 and F7/F8 (P ≥ 0.05). We finally show that the theta power at C4 was negatively correlated with HAMD scores before treatment (r = -0.346, P = 0.045). Conclusion Our findings determined that increased theta power and positive asymmetry in the right frontal-central area correlate with favourable escitalopram treatment, providing a basis for finding predictive markers for antidepressants.
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Affiliation(s)
- Min Gao
- Department of Affective Disorders II, Hebei Provincial Mental Health Center, Baoding, People’s Republic of China
- Xianyang Central Hospital, Xianyang Mental Health Center, Xianyang, People’s Republic of China
| | - Wenhua Sang
- Department of Affective Disorders II, Hebei Provincial Mental Health Center, Baoding, People’s Republic of China
- Hebei Key Laboratory of Major Mental and Behavioral Disorders, Baoding, People's Republic of China
- The Sixth Clinical Medical College of Hebei University, Baoding, People's Republic of China
| | - Kun Mi
- Department of Affective Disorders II, Hebei Provincial Mental Health Center, Baoding, People’s Republic of China
- Hebei Key Laboratory of Major Mental and Behavioral Disorders, Baoding, People's Republic of China
- The Sixth Clinical Medical College of Hebei University, Baoding, People's Republic of China
| | - Jiancong Liu
- Department of Affective Disorders II, Hebei Provincial Mental Health Center, Baoding, People’s Republic of China
- Hebei Key Laboratory of Major Mental and Behavioral Disorders, Baoding, People's Republic of China
- The Sixth Clinical Medical College of Hebei University, Baoding, People's Republic of China
| | - Yudong Liu
- Department of Affective Disorders II, Hebei Provincial Mental Health Center, Baoding, People’s Republic of China
- Hebei Key Laboratory of Major Mental and Behavioral Disorders, Baoding, People's Republic of China
- The Sixth Clinical Medical College of Hebei University, Baoding, People's Republic of China
| | - Wenge Zhen
- Department of Affective Disorders II, Hebei Provincial Mental Health Center, Baoding, People’s Republic of China
- Hebei Key Laboratory of Major Mental and Behavioral Disorders, Baoding, People's Republic of China
- The Sixth Clinical Medical College of Hebei University, Baoding, People's Republic of China
| | - Bang An
- Xianyang Central Hospital, Xianyang Mental Health Center, Xianyang, People’s Republic of China
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Wunram HL, Kasparbauer AM, Oberste M, Bender S. [Movement as a Neuromodulator: How Physical Activity Influences the Physiology of Adolescent Depression]. ZEITSCHRIFT FUR KINDER- UND JUGENDPSYCHIATRIE UND PSYCHOTHERAPIE 2023; 52:77-93. [PMID: 37851436 DOI: 10.1024/1422-4917/a000954] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2023]
Abstract
Movement as a Neuromodulator: How Physical Activity Influences the Physiology of Adolescent Depression Abstract: In the context of adolescent depression, physical activity is becoming increasingly recognized for its positive effects on neuropathology. Current scientific findings indicate that physical training affects the biological effects of depression during adolescence. Yet the pathophysiology of adolescent depression is not yet fully understood. Besides psychosocial and genetic influences, various neurobiological factors are being discussed. One explanation model describes a dysfunction of the hypothalamus-pituitary-adrenal axis (HPA axis) with a sustained elevation in cortisol concentration. Recent studies highlight neuroimmunological processes and a reduced concentration of growth factors as causative factors. These changes appear to lead to a dysregulation of the excitation and inhibition balance of the cerebral cortex as well as to cerebral morphological alterations. Regular physical training can potentially counteract the dysregulation of the HPA axis and normalize cortisol levels. The release of proinflammatory cytokines is inhibited, and the expression of growth factors involved in adult neurogenesis is stimulated. One should ensure the synergistic interaction of biological and psychosocial factors when designing the exercise schedule (endurance or strength training, group or individual sports, frequency, duration, and intensity). Addressing these open questions is essential when integrating physical activity into the guidelines for treating depressive disorders in children and adolescents.
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Affiliation(s)
- Heidrun Lioba Wunram
- Klinik und Poliklinik für Psychiatrie, Psychosomatik und Psychotherapie des Kindes- und Jugendalters, Uniklinik Köln, Medizinische Fakultät der Universität zu Köln, Deutschland
- Kinderklinik Uniklinik Köln, Medizinische Fakultät der Universität zu Köln, Deutschland
- Geteilte Erstautorenschaft
| | - Anna-Maria Kasparbauer
- Klinik und Poliklinik für Psychiatrie, Psychosomatik und Psychotherapie des Kindes- und Jugendalters, Uniklinik Köln, Medizinische Fakultät der Universität zu Köln, Deutschland
- Geteilte Erstautorenschaft
| | - Max Oberste
- Institut für Medizinische Statistik und Bioinformatik, Universität zu Köln, Deutschland
| | - Stephan Bender
- Klinik und Poliklinik für Psychiatrie, Psychosomatik und Psychotherapie des Kindes- und Jugendalters, Uniklinik Köln, Medizinische Fakultät der Universität zu Köln, Deutschland
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Prentice A, Barreiros AR, van der Vinne N, Stuiver S, van Dijk H, van Waarde JA, Korgaonkar M, Sack AT, Arns M. Rostral Anterior Cingulate Cortex Oscillatory Power Indexes Treatment-Resistance to Multiple Therapies in Major Depressive Disorder. Neuropsychobiology 2023; 82:373-383. [PMID: 37848013 DOI: 10.1159/000533853] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 08/22/2023] [Indexed: 10/19/2023]
Abstract
INTRODUCTION High rostral anterior cingulate cortex (rACC) activity is proposed as a nonspecific prognostic marker for treatment response in major depressive disorder, independent of treatment modality. However, other studies report a negative association between baseline high rACC activation and treatment response. Interestingly, these contradictory findings were also found when focusing on oscillatory markers, specifically rACC-theta power. An explanation could be that rACC-theta activity dynamically changes according to number of previous treatment attempts and thus is mediated by level of treatment-resistance. METHODS Primarily, we analyzed differences in rACC- and frontal-theta activity in large national cross-sectional samples representing various levels of treatment-resistance and resistance to multimodal treatments in depressed patients (psychotherapy [n = 175], antidepressant medication [AD; n = 106], repetitive transcranial magnetic stimulation [rTMS; n = 196], and electroconvulsive therapy [ECT; n = 41]), and the respective difference between remitters and non-remitters. For exploratory purposes, we also investigated other frequency bands (delta, alpha, beta, gamma). RESULTS rACC-theta activity was higher (p < 0.001) in the more resistant rTMS and ECT patients relative to the less resistant psychotherapy and AD patients (psychotherapy-rTMS: d = 0.315; AD-rTMS: d = 0.320; psychotherapy-ECT: d = 1.031; AD-ECT: d = 1.034), with no difference between psychotherapy and AD patients. This association was even more pronounced after controlling for frontal-theta. Post hoc analyses also yielded effects for delta, beta, and gamma bands. CONCLUSION Our findings suggest that by factoring in degree of treatment-resistance during interpretation of the rACC-theta biomarker, its usefulness in treatment selection and prognosis could potentially be improved substantially in future real-world practice. Future research should however also investigate specificity of the theta band.
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Affiliation(s)
- Amourie Prentice
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands,
- Research Institute Brainclinics, Brainclinics Foundation, Nijmegen, The Netherlands,
- Synaeda Research, Synaeda Psycho Medisch Centrum, Drachten, The Netherlands,
| | - Ana Rita Barreiros
- Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
- Brain Dynamics Centre, The Westmead Institute for Medical Research, Sydney, New South Wales, Australia
| | - Nikita van der Vinne
- Research Institute Brainclinics, Brainclinics Foundation, Nijmegen, The Netherlands
- Synaeda Research, Synaeda Psycho Medisch Centrum, Drachten, The Netherlands
| | - Sven Stuiver
- Department of Psychiatry, Rijnstate Depression Centre, Arnhem, The Netherlands
- Technical Medical Centre, University of Twente, Enschede, The Netherlands
| | - Hanneke van Dijk
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Research Institute Brainclinics, Brainclinics Foundation, Nijmegen, The Netherlands
| | | | - Mayuresh Korgaonkar
- Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
- Brain Dynamics Centre, The Westmead Institute for Medical Research, Sydney, New South Wales, Australia
| | - Alexander T Sack
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Martijn Arns
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Research Institute Brainclinics, Brainclinics Foundation, Nijmegen, The Netherlands
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Belanger HG, Lee C, Winsberg M. Symptom clustering of major depression in a national telehealth sample. J Affect Disord 2023; 338:129-134. [PMID: 37245550 DOI: 10.1016/j.jad.2023.05.026] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 03/30/2023] [Accepted: 05/11/2023] [Indexed: 05/30/2023]
Abstract
BACKGROUND Major depressive disorder (MDD) is a heterogeneous disorder whose possible symptom combinations have not been well delineated. The aim of this study was to explore the heterogeneity of symptoms experienced by those with MDD to characterize phenotypic presentations. METHODS Cross-sectional data (N = 10,158) from a large telemental health platform were used to identify subtypes of MDD. Symptom data, gathered from both clinically-validated surveys and intake questions, were analyzed via polychoric correlations, principal component analysis, and cluster analysis. RESULTS Principal components analysis (PCA) of baseline symptom data revealed 5 components, including anxious distress, core emotional, agitation/irritability, insomnia, and anergic/apathy components. PCA-based cluster analysis resulted in four MDD phenotypes, the largest of which was characterized by a prominent elevation on the anergic/apathy component, but also core emotional. The four clusters differed on demographic and clinical characteristics. LIMITATIONS The primary limitation of this study is that the phenotypes uncovered are limited by the questions asked. These phenotypes will need to be cross validated with other samples, potentially expanded to include biological/genetic variables, and followed longitudinally. CONCLUSIONS The heterogeneity in MDD, as illustrated by the phenotypes in this sample, may explain the heterogeneity of treatment response in large-scale treatment trials. These phenotypes can be used to study varying rates of recovery following treatment and to develop clinical decision support tools and artificial intelligence algorithms. Strengths of this study include its size, breadth of included symptoms, and novel use of a telehealth platform.
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Affiliation(s)
- Heather G Belanger
- Brightside Health Inc., 5241F Diamond Heights Blvd #3422, San Francisco CA 94131, United States of America; University of South Florida, Department of Psychiatry and Behavioral Neurosciences, 3515 E Fletcher Ave, Tampa, FL 33613, United States of America.
| | - Christine Lee
- Brightside Health Inc., 5241F Diamond Heights Blvd #3422, San Francisco CA 94131, United States of America
| | - Mirène Winsberg
- Brightside Health Inc., 5241F Diamond Heights Blvd #3422, San Francisco CA 94131, United States of America
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Boucherie DE, Reneman L, Ruhé HG, Schrantee A. Neurometabolite changes in response to antidepressant medication: A systematic review of 1H-MRS findings. Neuroimage Clin 2023; 40:103517. [PMID: 37812859 PMCID: PMC10563053 DOI: 10.1016/j.nicl.2023.103517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 09/22/2023] [Accepted: 09/23/2023] [Indexed: 10/11/2023]
Abstract
Selective serotonin reuptake inhibitors (SSRIs), serotonin and noradrenaline reuptake inhibitors (SNRIs), and (es)ketamine are used to treat major depressive disorder (MDD). These different types of medication may involve common neural pathways related to glutamatergic and GABAergic neurotransmitter systems, both of which have been implicated in MDD pathology. We conducted a systematic review of pharmacological proton Magnetic Resonance Spectroscopy (1H-MRS) studies in healthy volunteers and individuals with MDD to explore the potential impact of these medications on glutamatergic and GABAergic systems. We searched PubMed, Web of Science and Embase and included randomized controlled trials or cohort studies, which assessed the effects of SSRIs, SNRIs, or (es)ketamine on glutamate, glutamine, Glx or GABA using single-voxel 1H-MRS or Magnetic Resonance Spectroscopic Imaging (MRSI). Additionally, studies were included when they used a field strength > 1.5 T, and when a comparison of metabolite levels between antidepressant treatment and placebo or baseline with post-medication metabolite levels was done. We excluded animal studies, duplicate publications, or articles with 1H-MRS data already described in another included article. Twenty-nine studies were included in this review. Fifteen studies investigated the effect of administration or treatment with SSRIs or SNRIs, and fourteen studies investigated the effect of (es)ketamine on glutamatergic and GABAergic metabolite levels. Studies on SSRIs and SNRIs were highly variable, generally underpowered, and yielded no consistent findings across brain regions or specific populations. Although studies on (es)ketamine were also highly variable, some demonstrated an increase in glutamate levels in the anterior cingulate cortex in a time-dependent manner after administration. Our findings highlight the need for standardized study and acquisition protocols. Additionally, measuring metabolites dynamically over time or combining 1H-MRS with whole brain functional imaging techniques could provide valuable insights into the effects of these medications on glutamate and GABAergic neurometabolism.
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Affiliation(s)
- Daphne E Boucherie
- Amsterdam UMC, Location AMC, Department of Radiology and Nuclear Medicine, Meibergdreef 9, 1109 AZ Amsterdam, the Netherlands.
| | - Liesbeth Reneman
- Department of Psychiatry, Radboudumc, Radboud University, Reinier Postlaan 4, 6525 GC Nijmegen, the Netherlands
| | - Henricus G Ruhé
- Amsterdam UMC, Location AMC, Department of Radiology and Nuclear Medicine, Meibergdreef 9, 1109 AZ Amsterdam, the Netherlands; Department of Psychiatry, Radboudumc, Radboud University, Reinier Postlaan 4, 6525 GC Nijmegen, the Netherlands; Donders Institute for Brain Cognition and Behaviour, Radboud University, Kapittelweg 29, 6525 EN Nijmegen, the Netherlands
| | - Anouk Schrantee
- Amsterdam UMC, Location AMC, Department of Radiology and Nuclear Medicine, Meibergdreef 9, 1109 AZ Amsterdam, the Netherlands
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Guo W, Liu B, Wei X, Ju Y, Wang M, Dong Q, Lu X, Sun J, Zhang L, Guo H, Zhao F, Li W, Li Z, Liao M, Zhang L, Liu J, Zhang Y, Li L. The longitudinal change pattern of cognitive subtypes in medication-free patients with major depressive disorder: a cluster analysis. Psychiatry Res 2023; 327:115413. [PMID: 37579539 DOI: 10.1016/j.psychres.2023.115413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 07/24/2023] [Accepted: 08/11/2023] [Indexed: 08/16/2023]
Abstract
This study aimed to investigate whether there are different cognitive subtypes in patients with major depressive disorder (MDD) and the change pattern of cognitive clusters across the course of MDD. A battery of comprehensive cognitive tests was used to assess the executive function, processing speed, attention, and memory of 153 medication-free patients and 142 healthy controls (HCs). After 6 months of treatment with antidepressants, 87 patients completed cognitive tests again. K-means cluster analysis was performed to determine the cognitive subtypes. A preserved cognition cluster and an impaired cognition cluster were identified in the acute episode phase and the 6-month follow-up phase. 80.5% of the patients remained in their original subgroup after 6 months of treatment. The impaired cognition cluster during the 6-month follow-up period could be predicted by impaired cognition during the episode phase, disease state (remission or non-remission), current illness duration, and education level. This study supporting the heterogeneity of cognitive performance across the course of disease in patients with MDD using cluster analysis. It was found that cognitive impairment during depressive episodes was predictive of poorer cognitive performance even after treatment with antidepressants. Therefore, interventions targeting cognitive function from the early stages of MDD is essential.
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Affiliation(s)
- Weilong Guo
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Bangshan Liu
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Xiyu Wei
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Yumeng Ju
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Mi Wang
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Qiangli Dong
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Xiaowen Lu
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Jinrong Sun
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Liang Zhang
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Hua Guo
- Zhumadian Psychiatric Hospital, Zhumadian, Henan, 463000, China
| | - Futao Zhao
- Zhumadian Psychiatric Hospital, Zhumadian, Henan, 463000, China
| | - Weihui Li
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Zexuan Li
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Mei Liao
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Li Zhang
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Jin Liu
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China.
| | - Yan Zhang
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China.
| | - Lingjiang Li
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China.
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Umemoto A, Zhou Z, Millon EM, Koshy CS, Taylor SM, Spann MN, Monk C, Marsh R, Rosellini AJ, Auerbach RP. Intergenerational transmission of cognitive control capacity among children at risk for depression. Biol Psychol 2023; 182:108652. [PMID: 37516422 PMCID: PMC10528753 DOI: 10.1016/j.biopsycho.2023.108652] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 07/23/2023] [Accepted: 07/25/2023] [Indexed: 07/31/2023]
Abstract
A maternal history of major depressive disorder (MDD) is a well-known risk factor for depression in offspring. However, the mechanism through which familial risk is transmitted remains unclear. Cognitive control alterations are common in MDD, and thus, the current study investigated whether altered control capacity is transmitted intergenerationally, and whether it then contributes to the developmental pathways through which depression is passed from mothers to children. We recruited children (N = 65) ages 4-10-years-old, of which 47.7 % (n = 31) reported a maternal history of MDD, and their biological mother (N = 65). Children performed a child-friendly Go/NoGo task while electroencephalography (EEG) data were recorded, and mothers performed a Flanker task. Children exhibited heightened sensitivity to error versus correct responses, which was characterized by an error-related negativity (ERN), error positivity (Pe) as well as prominent delta and frontal midline theta (FMT) oscillations. Interestingly, worse maternal performance on the Flanker task associated with an increased Go/NoGo error rate and a smaller ERN and Pe in children. However, there was no association between maternal or child control indices with child depression symptoms. Our results suggest a familial influence of cognitive control capacity in mother-child dyads, but it remains unclear whether this confers risk for depressive symptoms in children. Further research is necessary to determine whether alterations in cognitive control over time may influence symptom development in at-risk children.
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Affiliation(s)
- Akina Umemoto
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - Zhixin Zhou
- Department of Counseling and Clinical Psychology, Teachers College, Columbia University, New York, NY, USA
| | - Emma M Millon
- Department of Psychiatry, Columbia University, New York, NY, USA; Division of Child and Adolescent Psychiatry, New York State Psychiatric Institute, New York, NY, USA
| | - Christina S Koshy
- Department of Counseling and Clinical Psychology, Teachers College, Columbia University, New York, NY, USA
| | - Sydney M Taylor
- Department of Psychiatry, Columbia University, New York, NY, USA; Division of Child and Adolescent Psychiatry, New York State Psychiatric Institute, New York, NY, USA
| | - Marisa N Spann
- Department of Psychiatry, Columbia University, New York, NY, USA; Division of Child and Adolescent Psychiatry, New York State Psychiatric Institute, New York, NY, USA
| | - Catherine Monk
- Department of Psychiatry, Columbia University, New York, NY, USA; Department of Obstetrics and Gynecology, Columbia University, New York, NY, USA; Division of Behavioral Medicine, New York State Psychiatric Institute, New York, NY, USA
| | - Rachel Marsh
- Department of Psychiatry, Columbia University, New York, NY, USA; Division of Child and Adolescent Psychiatry, New York State Psychiatric Institute, New York, NY, USA
| | | | - Randy P Auerbach
- Department of Psychiatry, Columbia University, New York, NY, USA; Division of Child and Adolescent Psychiatry, New York State Psychiatric Institute, New York, NY, USA; Division of Clinical Developmental Neuroscience, Sackler Institute, New York, NY, USA.
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Strege MV, Siegle GJ, Richey JA, Krawczak RA, Young K. Cingulate prediction of response to antidepressant and cognitive behavioral therapies for depression: Meta-analysis and empirical application. Brain Imaging Behav 2023; 17:450-460. [PMID: 36622532 PMCID: PMC10329727 DOI: 10.1007/s11682-022-00756-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Revised: 10/26/2022] [Accepted: 12/16/2022] [Indexed: 01/10/2023]
Abstract
We sought to identify baseline (pre-treatment) neural markers associated with treatment response in major depressive disorder (MDD), specific to treatment type, Cognitive Behavioral Therapy (CBT) or pharmacotherapy (selective serotonin reuptake inhibitors; SSRI). We conducted a meta-analysis of functional magnetic resonance imaging (fMRI) studies to identify neural prognostic indicators of response to CBT or SSRI. To verify the regions derived from literature, the meta-analytic regions were used to predict clinical change in a verification sample of participants with MDD who received either CBT (n = 60) or an SSRI (n = 19) as part of prior clinical trials. The meta-analysis consisted of 21 fMRI studies that used emotion-related tasks. It yielded prognostic regions of the perigenual (meta pgACC) and subgenual anterior cingulate cortex (meta sgACC), associated with SSRI and CBT response, respectively. When applying the meta-analytic regions to predict treatment response in the verification sample, reactivity of the meta pgACC was prognostic for SSRI response, yet the effect direction was opposite of most prior studies. Meta sgACC reactivity failed to be prognostic for CBT response. Results confirm the prognostic potential of neural reactivity of ACC subregions in MDD but further research is necessary for clinical translation.
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Affiliation(s)
- Marlene V Strege
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, United States.
| | - Greg J Siegle
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, United States
| | - John A Richey
- Department of Psychology, Virginia Polytechnic Institute and State University, Blacksburg, United States
| | | | - Kymberly Young
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, United States
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Hanuka S, Olson EA, Admon R, Webb CA, Killgore WDS, Rauch SL, Rosso IM, Pizzagalli DA. Reduced anhedonia following internet-based cognitive-behavioral therapy for depression is mediated by enhanced reward circuit activation. Psychol Med 2023; 53:4345-4354. [PMID: 35713110 DOI: 10.1017/s0033291722001106] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
BACKGROUND Major depressive disorder (MDD) is a highly prevalent psychiatric condition, yet many patients do not receive adequate treatment. Novel and highly scalable interventions such as internet-based cognitive-behavioral-therapy (iCBT) may help to address this treatment gap. Anhedonia, a hallmark symptom of MDD that refers to diminished interest and ability to experience pleasure, has been associated with reduced reactivity in a neural reward circuit that includes medial prefrontal and striatal brain regions. Whether iCBT can reduce anhedonia severity in MDD patients, and whether these therapeutic effects are accompanied by enhanced reward circuit reactivity has yet to be examined. METHODS Fifty-two MDD patients were randomly assigned to either 10-week iCBT (n = 26) or monitored attention control (MAC, n = 26) programs. All patients completed pre- and post-treatment assessments of anhedonia (Snaith-Hamilton Pleasure Scale; SHAPS) and reward circuit reactivity [monetary incentive delay (MID) task during functional magnetic resonance imaging (fMRI)]. Healthy control participants (n = 42) also underwent two fMRI scans while completing the MID task 10 weeks apart. RESULTS Both iCBT and MAC groups exhibited a reduction in anhedonia severity post-treatment. Nevertheless, only the iCBT group exhibited enhanced nucleus accumbens (Nacc) and subgenual anterior cingulate cortex (sgACC) activation and functional connectivity from pre- to post-treatment in response to reward feedback. Enhanced Nacc and sgACC activations were associated with reduced anhedonia severity following iCBT treatment, with enhanced Nacc activation also mediating the reduction in anhedonia severity post-treatment. CONCLUSIONS These findings suggest that increased reward circuit reactivity may contribute to a reduction in anhedonia severity following iCBT treatment for depression.
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Affiliation(s)
- Shir Hanuka
- School of Psychological Sciences, University of Haifa, Haifa, Israel
| | - Elizabeth A Olson
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Roee Admon
- School of Psychological Sciences, University of Haifa, Haifa, Israel
- The Integrated Brain and Behavior Research Center (IBBRC), University of Haifa, Haifa, Israel
| | - Christian A Webb
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | | | - Scott L Rauch
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Isabelle M Rosso
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Diego A Pizzagalli
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
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Sacu S, Wackerhagen C, Erk S, Romanczuk-Seiferth N, Schwarz K, Schweiger JI, Tost H, Meyer-Lindenberg A, Heinz A, Razi A, Walter H. Effective connectivity during face processing in major depression - distinguishing markers of pathology, risk, and resilience. Psychol Med 2023; 53:4139-4151. [PMID: 35393001 PMCID: PMC10317809 DOI: 10.1017/s0033291722000824] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Revised: 02/20/2022] [Accepted: 03/09/2022] [Indexed: 11/07/2022]
Abstract
BACKGROUND Aberrant brain connectivity during emotional processing, especially within the fronto-limbic pathway, is one of the hallmarks of major depressive disorder (MDD). However, the methodological heterogeneity of previous studies made it difficult to determine the functional and etiological implications of specific alterations in brain connectivity. We previously reported alterations in psychophysiological interaction measures during emotional face processing, distinguishing depressive pathology from at-risk/resilient and healthy states. Here, we extended these findings by effective connectivity analyses in the same sample to establish a refined neural model of emotion processing in depression. METHODS Thirty-seven patients with MDD, 45 first-degree relatives of patients with MDD and 97 healthy controls performed a face-matching task during functional magnetic resonance imaging. We used dynamic causal modeling to estimate task-dependent effective connectivity at the subject level. Parametric empirical Bayes was performed to quantify group differences in effective connectivity. RESULTS MDD patients showed decreased effective connectivity from the left amygdala and left lateral prefrontal cortex to the fusiform gyrus compared to relatives and controls, whereas patients and relatives showed decreased connectivity from the right orbitofrontal cortex to the left insula and from the left orbitofrontal cortex to the right fusiform gyrus compared to controls. Relatives showed increased connectivity from the anterior cingulate cortex to the left dorsolateral prefrontal cortex compared to patients and controls. CONCLUSIONS Our results suggest that the depressive state alters top-down control of higher visual regions during face processing. Alterations in connectivity within the cognitive control network present potential risk or resilience mechanisms.
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Affiliation(s)
- Seda Sacu
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Carolin Wackerhagen
- Division of Mind and Brain Research, Department of Psychiatry and Psychotherapy CCM, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Susanne Erk
- Division of Mind and Brain Research, Department of Psychiatry and Psychotherapy CCM, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Nina Romanczuk-Seiferth
- Division of Mind and Brain Research, Department of Psychiatry and Psychotherapy CCM, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Kristina Schwarz
- Systems Neuroscience in Psychiatry, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Janina I. Schweiger
- Systems Neuroscience in Psychiatry, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Heike Tost
- Systems Neuroscience in Psychiatry, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Andreas Meyer-Lindenberg
- Systems Neuroscience in Psychiatry, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Andreas Heinz
- Division of Mind and Brain Research, Department of Psychiatry and Psychotherapy CCM, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Adeel Razi
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London, UK
- Turner Institute for Brain and Mental Health & Monash Biomedical Imaging, Monash University, Clayton, Australia
| | - Henrik Walter
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
- Division of Mind and Brain Research, Department of Psychiatry and Psychotherapy CCM, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
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Chai Y, Gehrman P, Yu M, Mao T, Deng Y, Rao J, Shi H, Quan P, Xu J, Zhang X, Lei H, Fang Z, Xu S, Boland E, Goldschmied JR, Barilla H, Goel N, Basner M, Thase ME, Sheline YI, Dinges DF, Detre JA, Zhang X, Rao H. Enhanced amygdala-cingulate connectivity associates with better mood in both healthy and depressive individuals after sleep deprivation. Proc Natl Acad Sci U S A 2023; 120:e2214505120. [PMID: 37339227 PMCID: PMC10293819 DOI: 10.1073/pnas.2214505120] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 05/08/2023] [Indexed: 06/22/2023] Open
Abstract
Sleep loss robustly disrupts mood and emotion regulation in healthy individuals but can have a transient antidepressant effect in a subset of patients with depression. The neural mechanisms underlying this paradoxical effect remain unclear. Previous studies suggest that the amygdala and dorsal nexus (DN) play key roles in depressive mood regulation. Here, we used functional MRI to examine associations between amygdala- and DN-related resting-state connectivity alterations and mood changes after one night of total sleep deprivation (TSD) in both healthy adults and patients with major depressive disorder using strictly controlled in-laboratory studies. Behavioral data showed that TSD increased negative mood in healthy participants but reduced depressive symptoms in 43% of patients. Imaging data showed that TSD enhanced both amygdala- and DN-related connectivity in healthy participants. Moreover, enhanced amygdala connectivity to the anterior cingulate cortex (ACC) after TSD associated with better mood in healthy participants and antidepressant effects in depressed patients. These findings support the key role of the amygdala-cingulate circuit in mood regulation in both healthy and depressed populations and suggest that rapid antidepressant treatment may target the enhancement of amygdala-ACC connectivity.
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Affiliation(s)
- Ya Chai
- Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai201620, China
- Center for Functional Neuroimaging and Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
| | - Philip Gehrman
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
| | - Meichen Yu
- Indiana Alzheimer’s Disease Research Center, School of Medicine, Indiana University, Indianapolis, IN46202
- Indiana University Network Science Institute, Bloomington, IN47408
| | - Tianxin Mao
- Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai201620, China
- Center for Functional Neuroimaging and Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
| | - Yao Deng
- Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai201620, China
- Center for Functional Neuroimaging and Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
| | - Joy Rao
- Center for Functional Neuroimaging and Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
| | - Hui Shi
- Center for Functional Neuroimaging and Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
- Beijing An Zhen Hospital, Capital Medical University, Beijing100029, China
| | - Peng Quan
- Center for Functional Neuroimaging and Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
- Research Center for Quality of Life and Applied Psychology, Guangdong Medical University, Dongguan, Guangdong524023, China
| | - Jing Xu
- Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai201620, China
- Center for Functional Neuroimaging and Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
| | - Xiaocui Zhang
- Center for Functional Neuroimaging and Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan410017, China
| | - Hui Lei
- Center for Functional Neuroimaging and Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
- College of Education, Hunan Agricultural University, Changsha, Hunan410127, China
| | - Zhuo Fang
- Center for Functional Neuroimaging and Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
- Brain and Mind Research Institute, University of Ottawa, Ottawa, ON K1H 8M5, Canada
| | - Sihua Xu
- Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai201620, China
- Center for Functional Neuroimaging and Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
| | - Elaine Boland
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
- Mental Illness Research Education and Clinical Center, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA19104
| | - Jennifer R. Goldschmied
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
| | - Holly Barilla
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
| | - Namni Goel
- Biological Rhythms Research Laboratory, Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, IL60612
| | - Mathias Basner
- Division of Sleep and Chronobiology, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
| | - Michael E. Thase
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
- Mental Illness Research Education and Clinical Center, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA19104
| | - Yvette I. Sheline
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
- Center for Neuromodulation in Depression and Stress, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
| | - David F. Dinges
- Division of Sleep and Chronobiology, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
| | - John A. Detre
- Center for Functional Neuroimaging and Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
| | - Xiaochu Zhang
- Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai201620, China
- Department of Radiology, the First Affiliated Hospital of University of Science and Technology of China, School of Life Science, Division of Life Science and Medicine, University of Science and Technology of China, Hefei, Anhui230026, China
- Department of Psychology, School of Humanities and Social Science, University of Science and Technology of China, Anhui230026, China
| | - Hengyi Rao
- Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai201620, China
- Center for Functional Neuroimaging and Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
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Wade-Bohleber L, Zölch N, Lehmann M, Ernst J, Richter A, Seifritz E, Boeker H, Grimm S. Effects of Psychotherapy on Glutamatergic Neurotransmission. Neuropsychobiology 2023; 82:203-209. [PMID: 37321187 PMCID: PMC10614498 DOI: 10.1159/000530312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 03/14/2023] [Indexed: 06/17/2023]
Abstract
INTRODUCTION Psychodynamic psychotherapy is an effective and widely used treatment for major depressive disorder (MDD); however, little is known about neurobiological changes associated with induced symptom improvement. METHODS Proton magnetic resonance spectroscopy with a two-dimensional J-resolved sequence served to test the relationship between glutamate (Glu) and glutamine (Gln) levels, measured separately in pregenual anterior cingulate cortex (pgACC) and the anterior midcingulate cortex (aMCC) as a control region, with change in depression symptoms after 6 months of weekly psychodynamic psychotherapy sessions in MDD patients. Depressed (N = 45) and healthy (N = 30) subjects participated in a baseline proton magnetic resonance spectroscopy measurement and a subgroup of MDD subjects (N = 21) then received once-a-week psychodynamic psychotherapy and participated in a second proton magnetic resonance spectroscopy measurement after 6 months. Change in depression symptoms was assessed using the Hamilton Depression Rating Scale (HAMD). RESULTS Higher pretreatment pgACC Gln concentrations in MDD patients compared to healthy controls were associated with symptom severity. Patients and controls did not differ regarding Gln levels in aMCC nor regarding Glu levels in both regions. The association of pgACC Gln concentration and severity of depressive symptoms was reversed after 6 months of psychotherapy in MDD subjects. Regarding Gln in aMCC as well as Glu in both regions, there were no significant associations with improvement of depressive symptoms in the course of psychotherapy. DISCUSSION Findings indicate specific regional effects of psychodynamic psychotherapy on glutamatergic neurotransmission and thereby highlight the key role of the pgACC in both depression pathophysiology and recovery.
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Affiliation(s)
- Laura Wade-Bohleber
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Psychological Institute, Zurich University of Applied Sciences, Zurich, Switzerland
| | - Niklaus Zölch
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Forensic Medicine and Imaging, Institute of Forensic Medicine, University of Zurich, Zurich, Switzerland
| | - Mick Lehmann
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Jutta Ernst
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - André Richter
- Department of Consultation-Liaison-Psychiatry and Psychosomatic Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Erich Seifritz
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Heinz Boeker
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Simone Grimm
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Medical School Berlin, Berlin, Germany
- Department of Psychiatry, Charité Campus Benjamin Franklin, Berlin, Germany
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47
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Picó-Pérez M, Fullana MA, Albajes-Eizagirre A, Vega D, Marco-Pallarés J, Vilar A, Chamorro J, Felmingham KL, Harrison BJ, Radua J, Soriano-Mas C. Neural predictors of cognitive-behavior therapy outcome in anxiety-related disorders: a meta-analysis of task-based fMRI studies. Psychol Med 2023; 53:3387-3395. [PMID: 35916600 DOI: 10.1017/s0033291721005444] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
BACKGROUND Cognitive-behavior therapy (CBT) is a well-established first-line intervention for anxiety-related disorders, including specific phobia, social anxiety disorder, panic disorder/agoraphobia, generalized anxiety disorder, obsessive-compulsive disorder, and posttraumatic stress disorder. Several neural predictors of CBT outcome for anxiety-related disorders have been proposed, but previous results are inconsistent. METHODS We conducted a systematic review and meta-analysis of task-based functional magnetic resonance imaging (fMRI) studies investigating whole-brain predictors of CBT outcome in anxiety-related disorders (17 studies, n = 442). RESULTS Across different tasks, we observed that brain response in a network of regions involved in salience and interoception processing, encompassing fronto-insular (the right inferior frontal gyrus-anterior insular cortex) and fronto-limbic (the dorsomedial prefrontal cortex-dorsal anterior cingulate cortex) cortices was strongly associated with a positive CBT outcome. CONCLUSIONS Our results suggest that there are robust neural predictors of CBT outcome in anxiety-related disorders that may eventually lead (probably in combination with other data) to develop personalized approaches for the treatment of these mental disorders.
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Affiliation(s)
- Maria Picó-Pérez
- Life and Health Sciences Research Institute (ICVS), University of Minho, Braga, Portugal
- ICVS/3B's, PT Government Associate Laboratory, Braga/Guimarães, Portugal
- Clinical Academic Center - Braga, Braga, Portugal
| | - Miquel A Fullana
- Adult Psychiatry and Psychology Department, Institute of Neurosciences, Hospital Clinic, Barcelona, Spain
- Imaging of Mood- and Anxiety-Related Disorders (IMARD) Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), CIBERSAM, Barcelona, Spain
| | - Anton Albajes-Eizagirre
- Imaging of Mood- and Anxiety-Related Disorders (IMARD) Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), CIBERSAM, Barcelona, Spain
- Opticks Security, Barcelona, Spain
| | - Daniel Vega
- Psychiatry and Mental Health Department, Consorci Sanitari de l'Anoia & Fundació Sanitària d'Igualada, Igualada, Barcelona, Spain
- Unitat de Psicologia Mèdica, Departament de Psiquiatria i Medicina Legal & Institut de Neurociències, Universitat Autònoma de Barcelona, Bellaterra, Barcelona, Spain
| | - Josep Marco-Pallarés
- Department of Cognition, Development and Educational Psychology, Institute of Neurosciences, University of Barcelona, Barcelona, Spain
- Cognition and Brain Plasticity Unit, Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain
| | - Ana Vilar
- Institut de Neuropsiquiatria i Addiccions, Hospital de Dia Infanto Juvenil Litoral Mar, Parc de Salut Mar, Barcelona, Spain
| | - Jacobo Chamorro
- Anxiety Unit, Institute of Neuropsychiatry and Addictions, Parc de Salut Mar, Barcelona, Spain
| | - Kim L Felmingham
- School of Psychological Sciences, University of Melbourne, Melbourne, Australia
| | - Ben J Harrison
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, The University of Melbourne and Melbourne Health, Carlton, Victoria, Australia
| | - Joaquim Radua
- Imaging of Mood- and Anxiety-Related Disorders (IMARD) Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), CIBERSAM, Barcelona, Spain
- Department of Clinical Neuroscience, Centre for Psychiatric Research and Education, Karolinska Institutet, Stockholm, Sweden
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Carles Soriano-Mas
- Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain
- CIBERSAM, Barcelona, Spain
- Department of Psychobiology and Methodology of Health Sciences, Universitat Autònoma de Barcelona, Barcelona, Spain
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48
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Tsai YC, Li CT, Juan CH. A review of critical brain oscillations in depression and the efficacy of transcranial magnetic stimulation treatment. Front Psychiatry 2023; 14:1073984. [PMID: 37260762 PMCID: PMC10228658 DOI: 10.3389/fpsyt.2023.1073984] [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: 10/19/2022] [Accepted: 04/11/2023] [Indexed: 06/02/2023] Open
Abstract
Repetitive transcranial magnetic stimulation (rTMS) and intermittent theta burst stimulation (iTBS) have been proven effective non-invasive treatments for patients with drug-resistant major depressive disorder (MDD). However, some depressed patients do not respond to these treatments. Therefore, the investigation of reliable and valid brain oscillations as potential indices for facilitating the precision of diagnosis and treatment protocols has become a critical issue. The current review focuses on brain oscillations that, mostly based on EEG power analysis and connectivity, distinguish between MDD and controls, responders and non-responders, and potential depression severity indices, prognostic indicators, and potential biomarkers for rTMS or iTBS treatment. The possible roles of each biomarker and the potential reasons for heterogeneous results are discussed, and the directions of future studies are proposed.
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Affiliation(s)
- Yi-Chun Tsai
- Institute of Cognitive Neuroscience, College of Health Sciences and Technology, National Central University, Taoyuan City, Taiwan
| | - Cheng-Ta Li
- Institute of Cognitive Neuroscience, College of Health Sciences and Technology, National Central University, Taoyuan City, Taiwan
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
- Institute of Brain Science, National Yang-Ming Chiao-Tung University, Taipei, Taiwan
- Division of Psychiatry, Faculty of Medicine, National Yang-Ming Chiao-Tung University, Taipei, Taiwan
| | - Chi-Hung Juan
- Institute of Cognitive Neuroscience, College of Health Sciences and Technology, National Central University, Taoyuan City, Taiwan
- Cognitive Intelligence and Precision Healthcare Center, National Central University, Taoyuan City, Taiwan
- Department of Psychology, Kaohsiung Medical University, Kaohsiung, Taiwan
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49
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Alterations in EEG functional connectivity in individuals with depression: A systematic review. J Affect Disord 2023; 328:287-302. [PMID: 36801418 DOI: 10.1016/j.jad.2023.01.126] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 01/22/2023] [Accepted: 01/30/2023] [Indexed: 02/19/2023]
Abstract
The brain works as an organised, network-like structure of functionally interconnected regions. Disruptions to interconnectivity in certain networks have been linked to symptoms of depression and impairments in cognition. Electroencephalography (EEG) is a low-burden tool by which differences in functional connectivity (FC) can be assessed. This systematic review aims to provide a synthesis of evidence relating to EEG FC in depression. A comprehensive electronic literature search for terms relating to depression, EEG, and FC was conducted on studies published before the end of November 2021, according to PRISMA guidelines. Studies comparing EEG measures of FC of individuals with depression to that of healthy control groups were included. Data was extracted by two independent reviewers, and the quality of EEG FC methods was assessed. Fifty-two studies assessing EEG FC in depression were identified: 36 assessed resting-state FC, and 16 assessed task-related or other (i.e., sleep) FC. Somewhat consistent findings in resting-state studies suggest for no differences between depression and control groups in EEG FC in the delta and gamma frequencies. However, while most resting-state studies noted a difference in alpha, theta, and beta, no clear conclusions could be drawn about the direction of the difference, due to considerable inconsistencies between study design and methodology. This was also true for task-related and other EEG FC. More robust research is needed to understand the true differences in EEG FC in depression. Given that the FC between brain regions drives behaviour, cognition, and emotion, characterising how FC differs in depression is essential for understanding the aetiology of depression.
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50
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Ray KL, Griffin NR, Shumake J, Alario A, Allen JJB, Beevers CG, Schnyer DM. Altered electroencephalography resting state network coherence in remitted MDD. Brain Res 2023; 1806:148282. [PMID: 36792002 DOI: 10.1016/j.brainres.2023.148282] [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: 10/10/2022] [Revised: 02/10/2023] [Accepted: 02/11/2023] [Indexed: 02/16/2023]
Abstract
Individuals with remitted depression are at greater risk for subsequent depression and therefore may provide a unique opportunity to understand the neurophysiological correlates underlying the risk of depression. Research has identified abnormal resting-state electroencephalography (EEG) power metrics and functional connectivity patterns associated with major depression, however little is known about these neural signatures in individuals with remitted depression. We investigate the spectral dynamics of 64-channel EEG surface power and source-estimated network connectivity during resting states in 37 individuals with depression, 56 with remitted depression, and 49 healthy adults that did not differ on age, education, and cognitive ability across theta, alpha, and beta frequencies. Average reference spectral EEG surface power analyses identified greater left and midfrontal theta in remitted depression compared to healthy adults. Using Network Based Statistics, we also demonstrate within and between network alterations in LORETA transformed EEG source-space coherence across the default mode, fronto-parietal, and salience networks where individuals with remitted depression exhibited enhanced coherence compared to those with depression, and healthy adults. This work builds upon our currently limited understanding of resting EEG connectivity in depression, and helps bridge the gap between aberrant EEG power and brain network connectivity dynamics in this disorder. Further, our unique examination of remitted depression relative to both healthy and depressed adults may be key to identifying brain-based biomarkers for those at high risk for future, or subsequent depression.
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Affiliation(s)
| | | | | | - Alexandra Alario
- University of Texas, Austin, United States; University of Iowa, United States
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