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Ho SI, Lin IM, Hsieh JC, Yen CF. EEG coherences of the default mode network among patients comorbid with major depressive disorder and anxiety symptoms. J Affect Disord 2024; 361:728-738. [PMID: 38889861 DOI: 10.1016/j.jad.2024.06.041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 04/17/2024] [Accepted: 06/14/2024] [Indexed: 06/20/2024]
Abstract
BACKGROUND Higher functional connectivity within the default mode network (DMN) has been found in functional magnetic resonance imaging (fMRI) studies of major depressive disorder (MDD). We used electroencephalogram (EEG) coherence as an index of functional connectivity to examine group differences in DMN between the MDD and healthy control (HC) groups during the resting state. METHODS MDD patients with comorbid anxiety symptoms (n = 154) and healthy controls (n = 165) completed the questionnaires of depression, anxiety, and rumination. A 19-channel EEG recording was measured under resting state for all participants. EEG coherences of the delta, theta, alpha, beta, and high beta in the anterior DMN (aDMN), posterior DMN (pDMN), aDMN-pDMN, DMN-parahippocampal gyrus (PHG), and DMN-temporal gyrus were compared between the two groups. The correlations between rumination, anxiety, and DMN coherence were examined in the MDD group. RESULTS (1) No difference was found in the delta, theta, alpha, and beta within the DMN brain regions between the two groups; the MDD group showed higher high beta coherence within DMN brain regions than the HC group. (2) Rumination was negatively correlated with theta coherence of aDMN, and positively correlated with beta coherence of aDMN and with alpha coherence of pDMN and DMN-PHG. (3) Anxiety was positively correlated with high beta coherence of aDMN, pDMN, and DMN-PHG. CONCLUSIONS MDD patients with comorbid anxiety symptoms exhibited hypercoherence within the DMN brain regions. Hypercoherences were related to symptoms of rumination, and anxiety may be a biomarker for MDD patients with comorbid anxiety symptoms.
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Affiliation(s)
- Sok-In Ho
- Department of Psychology, College of Humanities and Social Sciences, Kaohsiung Medical University, Kaohsiung City, Taiwan
| | - I-Mei Lin
- Department of Psychology, College of Humanities and Social Sciences, Kaohsiung Medical University, Kaohsiung City, Taiwan; Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung City, Taiwan.
| | - Jen-Chuen Hsieh
- Integrated Brain Research Unit, Division of Clinical Research, Department of Medical Research, Taipei Veterans General Hospital, Taipei City, Taiwan; Brain Research Center, National Yang Ming Chiao Tung University, Taipei City, Taiwan; Department of Biological Science and Technology, College of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan; Center for Intelligent Drug Systems and Smart Bio-devices (IDS2B), National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Cheng-Fang Yen
- Department of Psychiatry, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung City, Taiwan; Graduate Institute of Medicine, Department of Psychiatry, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung City, Taiwan
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2
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Shang T, Chen Y, Ding Z, Qin W, Li S, Wei S, Ding Z, Yang X, Qi J, Qin X, Lv D, Li T, Pan Z, Zhan C, Xiao J, Sun Z, Wang N, Yu Z, Li C, Li P. Altered dynamic neural activities in individuals with obsessive-compulsive disorder and comorbid depressive symptoms. Front Psychiatry 2024; 15:1403933. [PMID: 39176228 PMCID: PMC11339690 DOI: 10.3389/fpsyt.2024.1403933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Accepted: 06/19/2024] [Indexed: 08/24/2024] Open
Abstract
Objectives Depressive symptoms are the most prevalent comorbidity in individuals with obsessive-compulsive disorder (OCD). The objective of this study was to investigate the dynamic characteristics of resting-state neural activities in OCD patients with depressive symptoms. Methods We recruited 29 OCD patients with depressive symptoms, 21 OCD patients without depressive symptoms, and 27 healthy controls, and collected data via structural and functional magnetic resonance imaging (fMRI). We analyzed the fMRI results using the dynamic amplitude of low-frequency fluctuation (dALFF) and support vector machine (SVM) techniques. Results Compared with OCD patients without depressive symptoms, OCD patients with depressive symptoms exhibited an increased dALFF in the left precuneus and decreased dALFF in the right medial frontal gyrus. The SVM indicated that the integration of aberrant dALFF values in the left precuneus and right medial frontal gyrus led to an overall accuracy of 80%, a sensitivity of 79%, and a specificity of 100% in detecting depressive symptoms among OCD patients. Conclusion Therefore, our study reveals that OCD patients with depressive symptoms display neural activities with unique dynamic characteristics in the resting state. Accordingly, abnormal dALFF values in the left precuneus and right medial frontal gyrus could be used to identify depressive symptoms in OCD patients.
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Affiliation(s)
- Tinghuizi Shang
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Yunhui Chen
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Zhenning Ding
- Medical Imaging Department, Qingdao Mental Health Center, Qingdao, Shandong, China
| | - Weiqi Qin
- The Second Affiliated Hospital, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Shancong Li
- The Second Affiliated Hospital, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Siyi Wei
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Zhipeng Ding
- Medical Technology Department, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Xu Yang
- Medical Technology Department, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Jiale Qi
- Medical Technology Department, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Xiaoqing Qin
- Medical Technology Department, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Dan Lv
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Tong Li
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Zan Pan
- Infection Control Department, Harbin Puning Hospital, Harbin, Heilongjiang, China
| | - Chuang Zhan
- Department of Psychiatry, Baiyupao Psychiatric Hospital of Harbin, Harbin, Heilongjiang, China
| | - Jian Xiao
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Zhenghai Sun
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Na Wang
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Zengyan Yu
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Chengchong Li
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Ping Li
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang, China
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3
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Laubacher C, Imhoff-Smith TP, Klaus DR, Frye CJ, Esnault S, Busse WW, Rosenkranz MA. Salience network resting state functional connectivity during airway inflammation in asthma: A feature of mental health resilience? Brain Behav Immun 2024; 122:9-17. [PMID: 39097203 DOI: 10.1016/j.bbi.2024.07.042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 07/07/2024] [Accepted: 07/28/2024] [Indexed: 08/05/2024] Open
Abstract
BACKGROUND Inflammation is an established contributor to the pathophysiology of depression and the prevalence of depression in those with chronic inflammatory disease is two- to four-fold higher than the general population. Yet little is known about the neurobiological changes that confer depression or resilience to depression, that occur when episodes of heightened inflammation are frequent or span many years. METHODS We used an innovative combination of longitudinal resting state functional magnetic resonance imaging coupled to segmental bronchial provocation with allergen (SBP-Ag) to assess changes in resting state functional connectivity (rsFC) of the salience network (SN) caused by an acute inflammatory exacerbation in twenty-six adults (15 female) with asthma and varying levels of depressive symptoms. Eosinophils measured in bronchoalveolar lavage fluid and blood provided an index of allergic inflammation and the Beck Depression Inventory provided an index of depressive symptoms. RESULTS We found that in those with the highest symptoms of depression at baseline, SN rsFC declined most from pre- to post-SBP-Ag in the context of a robust eosinophilic response to challenge, but in those with low depressive symptoms SN rsFC was maintained or increased, even in those with the most pronounced SBP-Ag response. CONCLUSIONS Thus, the maintenance of SN rsFC during inflammation may be a biomarker of resilience to depression, perhaps via more effective orchestration of large-scale brain network dynamics by the SN. These findings advance our understanding of the functional role of the SN during inflammation and inform treatment recommendations for those with comorbid inflammatory disease and depression.
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Affiliation(s)
- Claire Laubacher
- Center for Healthy Minds, University of Wisconsin-Madison, 625 W. Washington Ave, Madison, WI 53703, USA
| | - Theodore P Imhoff-Smith
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, 600 Highland Ave, Madison, WI 53792, USA
| | - Danika R Klaus
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, 600 Highland Ave, Madison, WI 53792, USA
| | - Corrina J Frye
- Waisman Center, University of Wisconsin-Madison, 1500 Highland Ave, Madison, WI 53705, USA
| | - Stephane Esnault
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, 600 Highland Ave, Madison, WI 53792, USA; University of Lille, INSERM, CHU Lille, U1286 - INFINITE - Institute for Translational Research in Inflammation, F-59000 Lille, France
| | - William W Busse
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, 600 Highland Ave, Madison, WI 53792, USA
| | - Melissa A Rosenkranz
- Center for Healthy Minds, University of Wisconsin-Madison, 625 W. Washington Ave, Madison, WI 53703, USA; Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Blvd, Madison, WI 53719, USA.
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Ironside M, Duda JM, Moser AD, Holsen LM, Zuo CS, Du F, Perlo S, Richards CE, Chen X, Nickerson LD, Null KE, Esfand SM, Alexander MM, Crowley DJ, Lauze M, Misra M, Goldstein JM, Pizzagalli DA. Association of Lower Rostral Anterior Cingulate GABA+ and Dysregulated Cortisol Stress Response With Altered Functional Connectivity in Young Adults With Lifetime Depression: A Multimodal Imaging Investigation of Trait and State Effects. Am J Psychiatry 2024; 181:639-650. [PMID: 38685857 PMCID: PMC11216878 DOI: 10.1176/appi.ajp.20230382] [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] [Indexed: 05/02/2024]
Abstract
OBJECTIVE Preclinical work suggests that excess glucocorticoids and reduced cortical γ-aminobutyric acid (GABA) may affect sex-dependent differences in brain regions implicated in stress regulation and depressive phenotypes. The authors sought to address a critical gap in knowledge, namely, how stress circuitry is functionally affected by glucocorticoids and GABA in current or remitted major depressive disorder (MDD). METHODS Multimodal imaging data were collected from 130 young adults (ages 18-25), of whom 44 had current MDD, 42 had remitted MDD, and 44 were healthy comparison subjects. GABA+ (γ-aminobutyric acid and macromolecules) was assessed using magnetic resonance spectroscopy, and task-related functional MRI data were collected under acute stress and analyzed using data-driven network modeling. RESULTS Across modalities, trait-related abnormalities emerged. Relative to healthy comparison subjects, both clinical groups were characterized by lower rostral anterior cingulate cortex (rACC) GABA+ and frontoparietal network amplitude but higher amplitude in salience and stress-related networks. For the remitted MDD group, differences from the healthy comparison group emerged in the context of elevated cortisol levels, whereas the MDD group had lower cortisol levels than the healthy comparison group. In the comparison group, frontoparietal and stress-related network connectivity was positively associated with cortisol level (highlighting putative top-down regulation of stress), but the opposite relationship emerged in the MDD and remitted MDD groups. Finally, rACC GABA+ was associated with stress-induced changes in connectivity between overlapping default mode and salience networks. CONCLUSIONS Lifetime MDD was characterized by reduced rACC GABA+ as well as dysregulated cortisol-related interactions between top-down control (frontoparietal) and threat (task-related) networks. These findings warrant further investigation of the role of GABA in the vulnerability to and treatment of MDD.
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Affiliation(s)
- Maria Ironside
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, Massachusetts, USA
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
| | - Jessica M. Duda
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, Massachusetts, USA
| | - Amelia D. Moser
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, Massachusetts, USA
| | - Laura M. Holsen
- Harvard Medical School, Boston, Massachusetts, USA
- Divison of Women’s Health, Department of Medicine, Brigham & Women’s Hospital, Boston, Massachusetts, USA
- Department of Psychiatry, Brigham & Women’s Hospital, Boston, Massachusetts, USA
- Innovation Center on Sex Differences in Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Chun S. Zuo
- Harvard Medical School, Boston, Massachusetts, USA
- McLean Imaging Center, McLean Hospital, Belmont, Massachusetts, USA
| | - Fei Du
- Harvard Medical School, Boston, Massachusetts, USA
- McLean Imaging Center, McLean Hospital, Belmont, Massachusetts, USA
| | - Sarah Perlo
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, Massachusetts, USA
| | - Christine E. Richards
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, Massachusetts, USA
| | - Xi Chen
- Harvard Medical School, Boston, Massachusetts, USA
- McLean Imaging Center, McLean Hospital, Belmont, Massachusetts, USA
| | - Lisa D. Nickerson
- Harvard Medical School, Boston, Massachusetts, USA
- McLean Imaging Center, McLean Hospital, Belmont, Massachusetts, USA
| | - Kaylee E. Null
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, Massachusetts, USA
| | - Shiba M. Esfand
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, Massachusetts, USA
| | - Madeline M. Alexander
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, Massachusetts, USA
| | - David J. Crowley
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, Massachusetts, USA
| | - Meghan Lauze
- Division of Pediatric Endocrinology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Madhusmita Misra
- Harvard Medical School, Boston, Massachusetts, USA
- Division of Pediatric Endocrinology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Innovation Center on Sex Differences in Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Jill M. Goldstein
- Harvard Medical School, Boston, Massachusetts, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA
- Innovation Center on Sex Differences in Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Diego A. Pizzagalli
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- McLean Imaging Center, McLean Hospital, Belmont, Massachusetts, USA
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5
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Sacchet MD, Keshava P, Walsh SW, Potash RM, Li M, Liu H, Pizzagalli DA. Individualized Functional Brain System Topologies and Major Depression: Relationships Among Patch Sizes and Clinical Profiles and Behavior. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024; 9:616-625. [PMID: 38417786 PMCID: PMC11156548 DOI: 10.1016/j.bpsc.2024.02.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 02/10/2024] [Accepted: 02/19/2024] [Indexed: 03/01/2024]
Abstract
BACKGROUND Neuroimaging studies of major depression have typically been conducted using group-level approaches. However, given interindividual differences in brain systems, there is a need for individualized approaches to brain systems mapping and putative links toward diagnosis, symptoms, and behavior. METHODS We used an iterative parcellation approach to map individualized brain systems in 328 participants from a multisite, placebo-controlled clinical trial. We hypothesized that participants with depression would show abnormalities in salience, control, default, and affective systems, which would be associated with higher levels of self-reported anhedonia, anxious arousal, and worse cognitive performance. Within hypothesized brain systems, we compared patch sizes (number of vertices) between depressed and healthy control groups. Within depressed groups, abnormal patches were correlated with hypothesized clinical and behavioral measures. RESULTS Significant group differences emerged in hypothesized patches of 1) the lateral salience system (parietal operculum; t326 = -3.11, p = .002) and 2) the control system (left medial posterior prefrontal cortex region; z = -3.63, p < .001), with significantly smaller patches in these regions in participants with depression than in healthy control participants. Results suggest that participants with depression with significantly smaller patch sizes in the lateral salience system and control system regions experience greater anxious arousal and cognitive deficits. CONCLUSIONS The findings imply that neural features mapped at the individual level may relate meaningfully to diagnosis, symptoms, and behavior. There is strong clinical relevance in taking an individualized brain systems approach to mapping neural functional connectivity because these associated region patch sizes may help advance our understanding of neural features linked to psychopathology and foster future patient-specific clinical decision making.
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Affiliation(s)
- Matthew D Sacchet
- Meditation Research Program, Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts; Department of Psychiatry, Harvard Medical School, Boston, Massachusetts.
| | - Poorvi Keshava
- Meditation Research Program, Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts; Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
| | - Shane W Walsh
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, Massachusetts
| | - Ruby M Potash
- Meditation Research Program, Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts
| | - Meiling Li
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts
| | - Hesheng Liu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts; Department of Neuroscience, Medical University of South Carolina, Charleston, South Carolina
| | - Diego A Pizzagalli
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts; Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, Massachusetts; McLean Imaging Center, McLean Hospital, Belmont, Massachusetts
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Copa D, Erritzoe D, Giribaldi B, Nutt D, Carhart-Harris R, Tagliazucchi E. Predicting the outcome of psilocybin treatment for depression from baseline fMRI functional connectivity. J Affect Disord 2024; 353:60-69. [PMID: 38423367 DOI: 10.1016/j.jad.2024.02.089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2023] [Revised: 02/14/2024] [Accepted: 02/26/2024] [Indexed: 03/02/2024]
Abstract
BACKGROUND Psilocybin is a serotonergic psychedelic drug under assessment as a potential therapy for treatment-resistant and major depression. Heterogeneous treatment responses raise interest in predicting the outcome from baseline data. METHODS A machine learning pipeline was implemented to investigate baseline resting-state functional connectivity measured with functional magnetic resonance imaging (fMRI) as a predictor of symptom severity in psilocybin monotherapy for treatment-resistant depression (16 patients administered two 5 mg capsules followed by 25 mg, separated by one week). Generalizability was tested in a sample of 22 patients who participated in a psilocybin vs. escitalopram trial for moderate-to-severe major depression (two separate doses of 25 mg of psilocybin 3 weeks apart plus 6 weeks of daily placebo vs. two separate doses of 1 mg of psilocybin 3 weeks apart plus 6 weeks of daily oral escitalopram). The analysis was repeated using both samples combined. RESULTS Functional connectivity of visual, default mode and executive networks predicted early symptom improvement, while the salience network predicted responders up to 24 weeks after treatment (accuracy≈0.9). Generalization performance was borderline significant. Consistent results were obtained from the combined sample analysis. Fronto-occipital and fronto-temporal coupling predicted early and late symptom reduction, respectively. LIMITATIONS The number of participants and differences between the two datasets limit the generalizability of the findings, while the lack of a placebo arm limits their specificity. CONCLUSIONS Baseline neurophysiological measurements can predict the outcome of psilocybin treatment for depression. Future research based on larger datasets should strive to assess the generalizability of these predictions.
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Affiliation(s)
- Débora Copa
- Universidad de Buenos Aires, Facultad de Ingeniería, Instituto de Bioingeniería, Buenos Aires, Argentina.
| | - David Erritzoe
- Centre for Psychedelic Research, Division of Academic Psychiatry, Imperial College London, London, United Kingdom
| | - Bruna Giribaldi
- Centre for Psychedelic Research, Division of Academic Psychiatry, Imperial College London, London, United Kingdom
| | - David Nutt
- Centre for Psychedelic Research, Division of Academic Psychiatry, Imperial College London, London, United Kingdom
| | - Robin Carhart-Harris
- Centre for Psychedelic Research, Division of Academic Psychiatry, Imperial College London, London, United Kingdom; Psychedelics Division, Neuroscape, Department of Neurology, University of California, San Francisco, USA
| | - Enzo Tagliazucchi
- Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Física, Ciudad Universitaria, Buenos Aires, Argentina; CONICET - Universidad de Buenos Aires, Instituto de Física Interdisciplinaria y Aplicada (INFINA), Ciudad Universitaria, Buenos Aires, Argentina; Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago, Chile
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7
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Li J, Kuang S, Liu Y, Wu Y, Li H. Structural and functional brain alterations in subthreshold depression: A multimodal coordinate-based meta-analysis. Hum Brain Mapp 2024; 45:e26702. [PMID: 38726998 PMCID: PMC11083971 DOI: 10.1002/hbm.26702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 04/09/2024] [Accepted: 04/17/2024] [Indexed: 05/13/2024] Open
Abstract
Imaging studies of subthreshold depression (StD) have reported structural and functional abnormalities in a variety of spatially diverse brain regions. However, there is no consensus among different studies. In the present study, we applied a multimodal meta-analytic approach, the Activation Likelihood Estimation (ALE), to test the hypothesis that StD exhibits spatially convergent structural and functional brain abnormalities compared to healthy controls. A total of 31 articles with 25 experiments were included, collectively representing 1001 subjects with StD. We found consistent differences between StD and healthy controls mainly in the left insula across studies with various neuroimaging methods. Further exploratory analyses found structural atrophy and decreased functional activities in the right pallidum and thalamus in StD, and abnormal spontaneous activity converged to the middle frontal gyrus. Coordinate-based meta-analysis found spatially convergent structural and functional impairments in StD. These findings provide novel insights for understanding the neural underpinnings of subthreshold depression and enlighten the potential targets for its early screening and therapeutic interventions in the future.
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Affiliation(s)
- Jingyu Li
- School of PsychologyShanghai Normal UniversityShanghaiChina
- Lab for Educational Big Data and Policymaking, Ministry of EducationShanghai Normal UniversityShanghaiChina
| | - Shunrong Kuang
- School of PsychologyShanghai Normal UniversityShanghaiChina
- Lab for Educational Big Data and Policymaking, Ministry of EducationShanghai Normal UniversityShanghaiChina
| | - Yang Liu
- School of PsychologyShanghai Normal UniversityShanghaiChina
- Department of PsychologyUniversity of WashingtonSeattleWashingtonUSA
| | - Yuedong Wu
- Lab for Educational Big Data and Policymaking, Ministry of EducationShanghai Normal UniversityShanghaiChina
| | - Haijiang Li
- School of PsychologyShanghai Normal UniversityShanghaiChina
- Lab for Educational Big Data and Policymaking, Ministry of EducationShanghai Normal UniversityShanghaiChina
- The Research Base of Online Education for Shanghai Middle and Primary SchoolsShanghaiChina
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8
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Shan X, Uddin LQ, Ma R, Xu P, Xiao J, Li L, Huang X, Feng Y, He C, Chen H, Duan X. Disentangling the Individual-Shared and Individual-Specific Subspace of Altered Brain Functional Connectivity in Autism Spectrum Disorder. Biol Psychiatry 2024; 95:870-880. [PMID: 37741308 DOI: 10.1016/j.biopsych.2023.09.012] [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: 04/21/2023] [Revised: 08/25/2023] [Accepted: 09/15/2023] [Indexed: 09/25/2023]
Abstract
BACKGROUND Despite considerable effort toward understanding the neural basis of autism spectrum disorder (ASD) using case-control analyses of resting-state functional magnetic resonance imaging data, findings are often not reproducible, largely due to biological and clinical heterogeneity among individuals with ASD. Thus, exploring the individual-shared and individual-specific altered functional connectivity (AFC) in ASD is important to understand this complex, heterogeneous disorder. METHODS We considered 254 individuals with ASD and 295 typically developing individuals from the Autism Brain Imaging Data Exchange to explore the individual-shared and individual-specific subspaces of AFC. First, we computed AFC matrices of individuals with ASD compared with typically developing individuals. Then, common orthogonal basis extraction was used to project AFC of ASD onto 2 subspaces: an individual-shared subspace, which represents altered connectivity patterns shared across ASD, and an individual-specific subspace, which represents the remaining individual characteristics after eliminating the individual-shared altered connectivity patterns. RESULTS Analysis yielded 3 common components spanning the individual-shared subspace. Common components were associated with differences of functional connectivity at the group level. AFC in the individual-specific subspace improved the prediction of clinical symptoms. The default mode network-related and cingulo-opercular network-related magnitudes of AFC in the individual-specific subspace were significantly correlated with symptom severity in social communication deficits and restricted, repetitive behaviors in ASD. CONCLUSIONS Our study decomposed AFC of ASD into individual-shared and individual-specific subspaces, highlighting the importance of capturing and capitalizing on individual-specific brain connectivity features for dissecting heterogeneity. Our analysis framework provides a blueprint for parsing heterogeneity in other prevalent neurodevelopmental conditions.
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Affiliation(s)
- Xiaolong Shan
- Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; Ministry of Education Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Lucina Q Uddin
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California
| | - Rui Ma
- Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; Ministry of Education Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Pengfei Xu
- Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; Ministry of Education Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Jinming Xiao
- Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; Ministry of Education Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Lei Li
- Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; Ministry of Education Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Xinyue Huang
- Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; Ministry of Education Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Yu Feng
- Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; Ministry of Education Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Changchun He
- College of Blockchain Industry, Chengdu University of Information Technology, Chengdu, China
| | - Huafu Chen
- Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; Ministry of Education Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China.
| | - Xujun Duan
- Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; Ministry of Education Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China.
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9
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Beckmann FE, Gruber H, Seidenbecher S, Schirmer ST, Metzger CD, Tozzi L, Frodl T. Specific alterations of resting-state functional connectivity in the triple network related to comorbid anxiety in major depressive disorder. Eur J Neurosci 2024; 59:1819-1832. [PMID: 38217400 DOI: 10.1111/ejn.16249] [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: 09/28/2023] [Revised: 12/08/2023] [Accepted: 12/17/2023] [Indexed: 01/15/2024]
Abstract
The brain's default mode network (DMN) and the executive control network (ECN) switch engagement are influenced by the ventral attention network (VAN). Alterations in resting-state functional connectivity (RSFC) within this so-called triple network have been demonstrated in patients with major depressive disorder (MDD) or anxiety disorders (ADs). This study investigated alterations in the RSFC in patients with comorbid MDD and ADs to better understand the pathophysiology of this prevalent group of patients. Sixty-eight participants (52.9% male, mean age 35.3 years), consisting of 25 patients with comorbid MDD and ADs (MDD + AD), 20 patients with MDD only (MDD) and 23 healthy controls (HCs) were investigated clinically and with 3T resting-state fMRI. RSFC utilizing a seed-based approach within the three networks belonging to the triple network was compared between the groups. Compared with HC, MDD + AD showed significantly reduced RSFC between the ECN and the VAN, the DMN and the VAN and within the ECN. No differences could be found for the MDD group compared with both other groups. Furthermore, symptom severity and medication status did not affect RSFC values. The results of this study show a distinct set of alterations of RSFC for patients with comorbid MDD and AD compared with HCs. This set of dysfunctions might be related to less adequate switching between the DMN and the ECN as well as poorer functioning of the ECN. This might contribute to additional difficulties in engaging and utilizing consciously controlled emotional regulation strategies.
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Affiliation(s)
- Fienne-Elisa Beckmann
- Department of Psychiatry and Psychotherapy, Otto von Guericke University Magdeburg, Magdeburg, Germany
| | - Hanna Gruber
- Department of Psychiatry and Psychotherapy, Otto von Guericke University Magdeburg, Magdeburg, Germany
| | - Stephanie Seidenbecher
- Department of Psychiatry and Psychotherapy, Otto von Guericke University Magdeburg, Magdeburg, Germany
| | - Saskia Thérèse Schirmer
- Department of Psychiatry and Psychotherapy, Otto von Guericke University Magdeburg, Magdeburg, Germany
| | - Coraline D Metzger
- Department of Psychiatry and Psychotherapy, Otto von Guericke University Magdeburg, Magdeburg, Germany
| | - Leonardo Tozzi
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, USA
| | - Thomas Frodl
- Department of Psychiatry and Psychotherapy, Otto von Guericke University Magdeburg, Magdeburg, Germany
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, USA
- Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
- Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital RWTH, Aachen, Germany
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10
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Yin X, Yang J, Xiang Q, Peng L, Song J, Liang S, Wu J. Brain network hierarchy reorganization in subthreshold depression. Neuroimage Clin 2024; 42:103594. [PMID: 38518552 PMCID: PMC10973537 DOI: 10.1016/j.nicl.2024.103594] [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: 02/14/2024] [Revised: 03/12/2024] [Accepted: 03/17/2024] [Indexed: 03/24/2024]
Abstract
BACKGROUND Hierarchy is the organizing principle of human brain network. How network hierarchy changes in subthreshold depression (StD) is unclear. The aim of this study was to investigate the altered brain network hierarchy and its clinical significance in patients with StD. METHODS A total of 43 patients with StD and 43 healthy controls matched for age, gender and years of education participated in this study. Alterations in the hierarchy of StD brain networks were depicted by connectome gradient analysis. We assessed changes in network hierarchy by comparing gradient scores in each network in patients with StD and healthy controls. The study compared different brain subdivisions if there was a different network. Finally, we analysed the relationship between the altered gradient scores and clinical characteristics. RESULTS Patients with StD had contracted network hierarchy and suppressed cortical range gradients. In the principal gradient, the gradient scores of default mode network were significantly reduced in patients with StD compared to controls. In the default network, the subdivisions of reduced gradient scores were mainly located in the precuneus, superior temporal gyrus, and anterior and posterior cingulate gyrus. Reduced gradient scores in the default mode network, the anterior and posterior cingulate gyrus were correlated with severity of depression. CONCLUSIONS The network hierarchy of the StD changed and was significantly correlated with depressive symptoms and severity. These results provided new insights into further understanding of the neural mechanisms of StD.
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Affiliation(s)
- Xiaolong Yin
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China; Rehabilitation Industry Institute, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China
| | - Junchao Yang
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China
| | - Qing Xiang
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China; Rehabilitation Industry Institute, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China
| | - Lixin Peng
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China
| | - Jian Song
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China
| | - Shengxiang Liang
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China; Rehabilitation Industry Institute, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China; Traditional Chinese Medicine Rehabilitation Research Center of State Administration of Traditional Chinese Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China.
| | - Jingsong Wu
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China.
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11
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Sacu S, Aggensteiner PM, Monninger M, Kaiser A, Brandeis D, Banaschewski T, Holz NE. Lifespan adversities affect neural correlates of behavioral inhibition in adults. Front Psychiatry 2024; 15:1298695. [PMID: 38317765 PMCID: PMC10840329 DOI: 10.3389/fpsyt.2024.1298695] [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: 09/22/2023] [Accepted: 01/03/2024] [Indexed: 02/07/2024] Open
Abstract
Introduction Growing evidence suggests that adverse experiences have long-term effects on executive functioning and underlying neural circuits. Previous work has identified functional abnormalities during inhibitory control in frontal brain regions in individuals exposed to adversities. However, these findings were mostly limited to specific adversity types such as maltreatment and prenatal substance abuse. Methods We used data from a longitudinal birth cohort study (n = 121, 70 females) to investigate the association between adversities and brain responses during inhibitory control. At the age of 33 years, all participants completed a stop-signal task during fMRI and an Adult Self-Report scale. We collected seven prenatal and postnatal adversity measures across development and performed a principal component analysis to capture common variations across those adversities, which resulted in a three-factor solution. Multiple regression analysis was performed to identify links between adversities and brain responses during inhibitory control using the identified adversity factors to show the common effect and single adversity measures to show the specific contribution of each adversity. To find neural correlates of current psychopathology during inhibitory control, we performed additional regression analyses using Adult Self-Report subscales. Results The first adversity factor reflecting prenatal maternal smoking and postnatal psychosocial adversities was related to higher activation during inhibitory control in bilateral inferior frontal gyri, insula, anterior cingulate cortex, and middle temporal gyri. Similar results were found for the specific contribution of the adversities linked to the first adversity factor. In contrast, we did not identify any significant association between brain responses during inhibitory control and the second adversity factor reflecting prenatal maternal stress and obstetric risk or the third adversity factor reflecting lower maternal sensitivity. Higher current depressive symptoms were associated with higher activation in the bilateral insula and anterior cingulate cortex during inhibitory control. Conclusion Our findings extended previous work and showed that early adverse experiences have a long-term effect on the neural circuitry of inhibitory control in adulthood. Furthermore, the overlap between neural correlates of adversity and depressive symptomatology suggests that adverse experiences might increase vulnerability via neural alterations, which needs to be investigated by future longitudinal research.
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Affiliation(s)
- Seda Sacu
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Pascal-M. Aggensteiner
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Maximilian Monninger
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Anna Kaiser
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Daniel Brandeis
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Nathalie E. Holz
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
- Donders Center for Brain, Cognition and Behavior, Radboud University Nijmegen, Nijmegen, Netherlands
- Department for Cognitive Neuroscience, Radboud University Medical Center Nijmegen, Nijmegen, Netherlands
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12
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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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13
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Zhang S, Yang W, Li M, Wen X, Shao Z, Li J, Liu J, Zhang J, Yu D, Liu J, Yuan K. Reconfigurations of Dynamic Functional Network Connectivity in Large-scale Brain Network after Prolonged Abstinence in Heroin Users. Curr Neuropharmacol 2024; 22:1144-1153. [PMID: 36453493 PMCID: PMC10964104 DOI: 10.2174/1570159x21666221129105408] [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: 06/20/2022] [Revised: 11/01/2022] [Accepted: 11/02/2022] [Indexed: 12/04/2022] Open
Abstract
BACKGROUND Brain recovery phenomenon after long-term abstinence had been reported in substance use disorders. Yet, few longitudinal studies have been conducted to observe the abnormal dynamic functional connectivity (dFNC) of large-scale brain networks and recovery after prolonged abstinence in heroin users. OBJECTIVE The current study will explore the brain network dynamic connection reconfigurations after prolonged abstinence in heroin users (HUs). METHODS The 10-month longitudinal design was carried out for 40 HUs. The 40 healthy controls (HCs) were also enrolled. Group independent component analysis (GICA) and dFNC analysis were employed to detect the different dFNC patterns of addiction-related ICNs between HUs and HCs. The temporal properties and the graph-theoretical properties were calculated. Whether the abnormalities would be reconfigured in HUs after prolonged abstinence was then investigated. RESULTS Based on eight functional networks extracted from GICA, four states were identified by the dFNC analysis. Lower mean dwell time and fraction rate in state4 were found for HUs, which were increased toward HCs after prolonged abstinence. In this state, HUs at baseline showed higher dFNC of RECN-aSN, aSN- aSN and dDMN-pSN, which decreased after protracted abstinence. A similar recovery phenomenon was found for the global efficiency and path length in abstinence HUs. Mean while, the abnormal dFNC strength was correlated with craving both at baseline and after abstinence. CONCLUSION Our longitudinal study observed the large-scale brain network reconfiguration from the dynamic perspective in HUs after prolonged abstinence and improved the understanding of the neurobiology of prolonged abstinence in HUs.
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Affiliation(s)
- Shan Zhang
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710126, China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, 710071, China
| | - Wenhan Yang
- Department of Radiology, Second Xiangya Hospital, Central South University, Changsha, 410011, China
| | - Minpeng Li
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710126, China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, 710071, China
| | - Xinwen Wen
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710126, China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, 710071, China
| | - Ziqiang Shao
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710126, China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, 710071, China
| | - Jun Li
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710126, China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, 710071, China
| | - Jixin Liu
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710126, China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, 710071, China
| | - Jun Zhang
- Hunan Judicial Police Academy, Changsha, 410000, China
| | - Dahua Yu
- Information Processing Laboratory, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, 014010, China
| | - Jun Liu
- Department of Radiology, Second Xiangya Hospital, Central South University, Changsha, 410011, China
| | - Kai Yuan
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710126, China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, 710071, China
- Information Processing Laboratory, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, 014010, China
- International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of Trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710126, China
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14
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van der Horn HJ, de Koning ME, Visser K, Kok MGJ, Spikman JM, Scheenen ME, Renken RJ, Calhoun VD, Vergara VM, Cabral J, Mayer AR, van der Naalt J. Dynamic phase-locking states and personality in sub-acute mild traumatic brain injury: An exploratory study. PLoS One 2023; 18:e0295984. [PMID: 38100479 PMCID: PMC10723684 DOI: 10.1371/journal.pone.0295984] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 12/01/2023] [Indexed: 12/17/2023] Open
Abstract
Research has shown that maladaptive personality characteristics, such as Neuroticism, are associated with poor outcome after mild traumatic brain injury (mTBI). The current exploratory study investigated the neural underpinnings of this process using dynamic functional network connectivity (dFNC) analyses of resting-state (rs) fMRI, and diffusion MRI (dMRI). Twenty-seven mTBI patients and 21 healthy controls (HC) were included. After measuring the Big Five personality dimensions, principal component analysis (PCA) was used to obtain a superordinate factor representing emotional instability, consisting of high Neuroticism, moderate Openness, and low Extraversion, Agreeableness, and Conscientiousness. Persistent symptoms were measured using the head injury symptom checklist at six months post-injury; symptom severity (i.e., sum of all items) was used for further analyses. For patients, brain MRI was performed in the sub-acute phase (~1 month) post-injury. Following parcellation of rs-fMRI using independent component analysis, leading eigenvector dynamic analysis (LEiDA) was performed to compute dynamic phase-locking brain states. Main patterns of brain diffusion were computed using tract-based spatial statistics followed by PCA. No differences in phase-locking state measures were found between patients and HC. Regarding dMRI, a trend significant decrease in fractional anisotropy was found in patients relative to HC, particularly in the fornix, genu of the corpus callosum, anterior and posterior corona radiata. Visiting one specific phase-locking state was associated with lower symptom severity after mTBI. This state was characterized by two clearly delineated communities (each community consisting of areas with synchronized phases): one representing an executive/saliency system, with a strong contribution of the insulae and basal ganglia; the other representing the canonical default mode network. In patients who scored high on emotional instability, this relationship was even more pronounced. Dynamic phase-locking states were not related to findings on dMRI. Altogether, our results provide preliminary evidence for the coupling between personality and dFNC in the development of long-term symptoms after mTBI.
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Affiliation(s)
- Harm J. van der Horn
- Department of Neurology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- The Mind Research Network/Lovelace Biomedical Research Institute, Pete & Nancy Domenici Hall, Albuquerque, NM, United States of America
| | | | - Koen Visser
- Department of Neurology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Marius G. J. Kok
- Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Jacoba M. Spikman
- Department of Neuropsychology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Myrthe E. Scheenen
- Department of Neuropsychology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Remco J. Renken
- Department of Neuroscience, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Vince D. Calhoun
- Tri-institutional Center for Translational Research (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, United States of America
| | - Victor M. Vergara
- Tri-institutional Center for Translational Research (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, United States of America
| | - Joana Cabral
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
| | - Andrew R. Mayer
- The Mind Research Network/Lovelace Biomedical Research Institute, Pete & Nancy Domenici Hall, Albuquerque, NM, United States of America
- Department of Neurology, University of New Mexico School of Medicine, Albuquerque, NM, United States of America
- Department of Psychiatry, University of New Mexico School of Medicine, Albuquerque, NM, United States of America
- Department of Psychology, University of New Mexico School of Medicine, Albuquerque, NM, United States of America
| | - Joukje van der Naalt
- Department of Neurology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
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15
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Hirata R, Yoshimura S, Kobayashi K, Aki M, Shibata M, Ueno T, Miyagi T, Oishi N, Murai T, Fujiwara H. Differences between subclinical attention-deficit/hyperactivity and autistic traits in default mode, salience, and frontoparietal network connectivities in young adult Japanese. Sci Rep 2023; 13:19724. [PMID: 37957246 PMCID: PMC10643712 DOI: 10.1038/s41598-023-47034-7] [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: 02/28/2023] [Accepted: 11/08/2023] [Indexed: 11/15/2023] Open
Abstract
Attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are associated with attentional impairments, with both commonalities and differences in the nature of their attention deficits. This study aimed to investigate the neural correlates of ADHD and ASD traits in healthy individuals, focusing on the functional connectivity (FC) of attention-related large-scale brain networks (LSBNs). The participants were 61 healthy individuals (30 men; age, 21.9 ± 1.9 years). The Adult ADHD Self-Report Scale (ASRS) and Autism Spectrum Quotient (AQ) were administered as indicators of ADHD and ASD traits, respectively. Performance in the continuous performance test (CPT) was used as a behavioural measure of sustained attentional function. Functional magnetic resonance imaging scans were performed during the resting state (Rest) and auditory oddball task (Odd). Considering the critical role in attention processing, we focused our analyses on the default mode (DMN), frontoparietal (FPN), and salience (SN) networks. Region of interest (ROI)-to-ROI analyses (false discovery rate < 0.05) were performed to determine relationships between psychological measures with within-network FC (DMN, FPN, and SN) as well as with between-network FC (DMN-FPN, DMN-SN, and FPN-SN). ASRS scores, but not AQ scores, were correlated with less frequent commission errors and shorter reaction times in the CPT. During Odd, significant positive correlations with ASRS were demonstrated in multiple FCs within DMN, while significant positive correlations with AQ were demonstrated in multiple FCs within FPN. AQs were negatively correlated with FPN-SN FCs. During Rest, AQs were negatively and positively correlated with one FC within the SN and multiple FCs between the DMN and SN, respectively. These findings of the ROI-to-ROI analysis were only partially replicated in a split-half replication analysis, a replication analysis with open-access data sets, and a replication analysis with a structure-based atlas. The better CPT performance by individuals with subclinical ADHD traits suggests positive effects of these traits on sustained attention. Differential associations between LSBN FCs and ASD/ADHD traits corroborate the notion of differences in sustained and selective attention between clinical ADHD and ASD.
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Affiliation(s)
- Risa Hirata
- Department of Neuropsychiatry, Kyoto University Hospital, 54 Shogoinkawaracho, Sakyo-ku, Kyoto, 6068397, Japan
| | - Sayaka Yoshimura
- Faculty of Human Health Science, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Organization for Promotion of Neurodevelopmental Disorder Research, Kyoto, Japan
| | - Key Kobayashi
- Department of Neuropsychiatry, Graduate School of Medicine, University of Kyoto, Kyoto, Japan
| | - Morio Aki
- Department of Neuropsychiatry, Graduate School of Medicine, University of Kyoto, Kyoto, Japan
| | - Mami Shibata
- Department of Neuropsychiatry, Graduate School of Medicine, University of Kyoto, Kyoto, Japan
| | - Tsukasa Ueno
- Department of Neuropsychiatry, Graduate School of Medicine, University of Kyoto, Kyoto, Japan
- Integrated Clinical Education Center, Kyoto University Hospital, Kyoto, Japan
| | - Takashi Miyagi
- Department of Neuropsychiatry, Graduate School of Medicine, University of Kyoto, Kyoto, Japan
| | - Naoya Oishi
- Medical Innovation Center, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Toshiya Murai
- Department of Neuropsychiatry, Kyoto University Hospital, 54 Shogoinkawaracho, Sakyo-ku, Kyoto, 6068397, Japan
- Department of Neuropsychiatry, Graduate School of Medicine, University of Kyoto, Kyoto, Japan
| | - Hironobu Fujiwara
- Department of Neuropsychiatry, Kyoto University Hospital, 54 Shogoinkawaracho, Sakyo-ku, Kyoto, 6068397, Japan.
- Department of Neuropsychiatry, Graduate School of Medicine, University of Kyoto, Kyoto, Japan.
- Artificial Intelligence Ethics and Society Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan.
- The General Research Division, Osaka University Research Center on Ethical, Legal and Social Issues, Kyoto, Japan.
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16
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Feng L, Wu D, Ma S, Dong L, Yue Y, Li T, Tang Y, Ye Z, Mao G. Resting-state functional connectivity of the cerebellum-cerebrum in older women with depressive symptoms. BMC Psychiatry 2023; 23:732. [PMID: 37817133 PMCID: PMC10566116 DOI: 10.1186/s12888-023-05232-7] [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: 04/19/2023] [Accepted: 09/28/2023] [Indexed: 10/12/2023] Open
Abstract
BACKGROUND Although there has been much neurobiological research on major depressive disorder, research on the neurological function of depressive symptoms (DS) or subclinical depression is still scarce, especially in older women with DS. OBJECTIVES Resting-state functional magnetic resonance imaging (rs-fMRI) was used to compare functional connectivity (FC) between the cerebellum and cerebral in older women with DS and normal controls (NC), to explore unique changes in cerebellar FC in older women with DS. METHODS In all, 16 older women with DS and 17 NC were recruited. All subjects completed rs-fMRI. The 26 sub-regions of the cerebellum divided by the AAL3 map were used as regions of interest (ROI) to analyze the difference in FC strength of cerebellar seeds from other cerebral regions between the two groups. Finally, partial correlation analysis between abnormal FC strength and Geriatric Depression Scale (GDS) score and Reminiscence Functions Scale (RFS) score in the DS group. RESULTS Compared with NC group, the DS group showed significantly reduced FC between Crus I, II and the left frontoparietal region, and reduced FC between Crus I and the left temporal gyrus. Reduced FC between right insula (INS), right rolandic operculum (ROL), right precentral gyrus (PreCG) and the Lobule IX, X. Moreover, the negative FC between Crus I, II, Lobule IX and visual regions was reduced in the DS group. The DS group correlation analysis showed a positive correlation between the left Crus I and the right cuneus (CUN) FC and GDS. In addition, the abnormal FC strength correlated with the scores in different dimensions of the RFS, such as the negative FC between the Crus I and the left middle temporal gyrus (MTG) was positively associated with intimacy maintenance, and so on. CONCLUSION Older women with DS have anomalous FC between the cerebellum and several regions of the cerebrum, which may be related to the neuropathophysiological mechanism of DS in the DS group.
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Affiliation(s)
- Lanling Feng
- Nursing Department, The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Dongmei Wu
- Nursing Department, The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.
| | - Shaolun Ma
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Li Dong
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Yuchuan Yue
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Tao Li
- Nursing Department, The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Yixun Tang
- Nursing Department, The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Zixiang Ye
- Nursing Department, The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Guoju Mao
- Nursing Department, The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
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17
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Amiri S, Arbabi M, Rahimi M, Parvaresh-Rizi M, Mirbagheri MM. Effective connectivity between deep brain stimulation targets in individuals with treatment-resistant depression. Brain Commun 2023; 5:fcad256. [PMID: 37901039 PMCID: PMC10600572 DOI: 10.1093/braincomms/fcad256] [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: 01/06/2023] [Revised: 06/27/2023] [Accepted: 10/06/2023] [Indexed: 10/31/2023] Open
Abstract
The therapeutic effect of deep brain stimulation on patients with treatment-resistant depression is strongly dependent on the connectivity of the stimulation region with other regions associated with depression. The aims of this study are to characterize the effective connectivity between the brain regions playing important roles in depression and further investigate the underlying pathophysiological mechanisms of treatment-resistant depression and the mechanisms involving deep brain stimulation. Thirty-three individuals with treatment-resistant depression and 29 healthy control subjects were examined. All subjects underwent resting-state functional MRI scanning. The coupling parameters reflecting the causal interactions among deep brain stimulation targets and medial prefrontal cortex were estimated using spectral dynamic causal modelling. Our results showed that compared to the healthy control subjects, in the left hemisphere of treatment-resistant depression patients, the nucleus accumbens was inhibited by the inferior thalamic peduncle and excited the ventral caudate and the subcallosal cingulate gyrus, which in turn excited the lateral habenula. In the right hemisphere, the lateral habenula inhibited the ventral caudate and the nucleus accumbens, both of which inhibited the inferior thalamic peduncle, which in turn inhibited the cingulate gyrus. The ventral caudate excited the lateral habenula and the cingulate gyrus, which excited the medial prefrontal cortex. Furthermore, these effective connectivity links varied between males and females, and the left and right hemispheres. Our findings suggest that intrinsic excitatory/inhibitory connections between deep brain stimulation targets are impaired in treatment-resistant depression patients, and that these connections are sex dependent and hemispherically lateralized. This knowledge can help to better understand the underlying mechanisms of treatment-resistant depression, and along with tractography, structural imaging, and other relevant clinical information, may assist to determine the appropriate region for deep brain stimulation therapy in each treatment-resistant depression patient.
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Affiliation(s)
- Saba Amiri
- Neuroscience Research Center, Shahid Beheshti University of Medical Science, Tehran 1983969367, Iran
| | - Mohammad Arbabi
- Psychiatry, Psychosomatic Medicine Research Center Department, Tehran University of Medical Sciences, Tehran 1419733141, Iran
| | - Milad Rahimi
- Medical Physics and Biomedical Engineering Group, Faculty of Medicine, Tehran University of Medical Sciences (TUMS), Tehran 1461884513, Iran
| | - Mansour Parvaresh-Rizi
- Neurosurgery Department, Iran University of Medical Sciences (IUMS), Tehran 02166509120, Iran
| | - Mehdi M Mirbagheri
- Medical Physics and Biomedical Engineering Group, Faculty of Medicine, Tehran University of Medical Sciences (TUMS), Tehran 1461884513, Iran
- Physical Medicine and Rehabilitation Department, Northwestern University, Chicago IL 60611, USA
- Neural Engineering and Rehabilitation Research Center, Tehran 1146733711, Iran
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18
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Metzger BA, Kalva P, Mocchi MM, Cui B, Adkinson JA, Wang Z, Mathura R, Kanja K, Gavvala J, Krishnan V, Lin L, Maheshwari A, Shofty B, Magnotti JF, Willie JT, Sheth SA, Bijanki KR. Intracranial stimulation and EEG feature analysis reveal affective salience network specialization. Brain 2023; 146:4366-4377. [PMID: 37293814 PMCID: PMC10545499 DOI: 10.1093/brain/awad200] [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: 09/13/2022] [Revised: 05/04/2023] [Accepted: 05/11/2023] [Indexed: 06/10/2023] Open
Abstract
Emotion is represented in limbic and prefrontal brain areas, herein termed the affective salience network (ASN). Within the ASN, there are substantial unknowns about how valence and emotional intensity are processed-specifically, which nodes are associated with affective bias (a phenomenon in which participants interpret emotions in a manner consistent with their own mood). A recently developed feature detection approach ('specparam') was used to select dominant spectral features from human intracranial electrophysiological data, revealing affective specialization within specific nodes of the ASN. Spectral analysis of dominant features at the channel level suggests that dorsal anterior cingulate (dACC), anterior insula and ventral-medial prefrontal cortex (vmPFC) are sensitive to valence and intensity, while the amygdala is primarily sensitive to intensity. Akaike information criterion model comparisons corroborated the spectral analysis findings, suggesting all four nodes are more sensitive to intensity compared to valence. The data also revealed that activity in dACC and vmPFC were predictive of the extent of affective bias in the ratings of facial expressions-a proxy measure of instantaneous mood. To examine causality of the dACC in affective experience, 130 Hz continuous stimulation was applied to dACC while patients viewed and rated emotional faces. Faces were rated significantly happier during stimulation, even after accounting for differences in baseline ratings. Together the data suggest a causal role for dACC during the processing of external affective stimuli.
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Affiliation(s)
- Brian A Metzger
- Department of Psychology, Swarthmore College, Swarthmore, PA 19081, USA
| | - Prathik Kalva
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX 77030, USA
| | - Madaline M Mocchi
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX 77030, USA
| | - Brian Cui
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX 77030, USA
| | - Joshua A Adkinson
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX 77030, USA
| | - Zhengjia Wang
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Raissa Mathura
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX 77030, USA
| | - Kourtney Kanja
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX 77030, USA
| | - Jay Gavvala
- Department of Neurology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Vaishnav Krishnan
- Department of Neurology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Lu Lin
- Department of Neurology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Atul Maheshwari
- Department of Neurology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Ben Shofty
- Department of Neurosurgery, University of Utah Health, Salt Lake City, UT 84132, USA
| | - John F Magnotti
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jon T Willie
- Department of Neurosurgery, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX 77030, USA
| | - Kelly R Bijanki
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX 77030, USA
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19
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Ghaderi AH, Brown EC, Clark DL, Ramasubbu R, Kiss ZHT, Protzner AB. Functional brain network features specify DBS outcome for patients with treatment resistant depression. Mol Psychiatry 2023; 28:3888-3899. [PMID: 37474591 DOI: 10.1038/s41380-023-02181-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 06/29/2023] [Accepted: 07/05/2023] [Indexed: 07/22/2023]
Abstract
Deep brain stimulation (DBS) has shown therapeutic benefits for treatment resistant depression (TRD). Stimulation of the subcallosal cingulate gyrus (SCG) aims to alter dysregulation between subcortical and cortex. However, the 50% response rates for SCG-DBS indicates that selection of appropriate patients is challenging. Since stimulation influences large-scale network function, we hypothesized that network features can be used as biomarkers to inform outcome. In this pilot project, we used resting-state EEG recorded longitudinally from 10 TRD patients with SCG-DBS (11 at baseline). EEGs were recorded before DBS-surgery, 1-3 months, and 6 months post surgery. We used graph theoretical analysis to calculate clustering coefficient, global efficiency, eigenvector centrality, energy, and entropy of source-localized EEG networks to determine their topological/dynamical features. Patients were classified as responders based on achieving a 50% or greater reduction in Hamilton Depression (HAM-D) scores from baseline to 12 months post surgery. In the delta band, false discovery rate analysis revealed that global brain network features (segregation, integration, synchronization, and complexity) were significantly lower and centrality of subgenual anterior cingulate cortex (ACC) was higher in responders than in non-responders. Accordingly, longitudinal analysis showed SCG-DBS increased global network features and decreased centrality of subgenual ACC. Similarly, a clustering method separated two groups by network features and significant correlations were identified longitudinally between network changes and depression symptoms. Despite recent speculation that certain subtypes of TRD are more likely to respond to DBS, in the SCG it seems that underlying brain network features are associated with ability to respond to DBS. SCG-DBS increased segregation, integration, and synchronizability of brain networks, suggesting that information processing became faster and more efficient, in those patients in whom it was lower at baseline. Centrality results suggest these changes may occur via altered connectivity in specific brain regions especially ACC. We highlight potential mechanisms of therapeutic effect for SCG-DBS.
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Affiliation(s)
- Amir Hossein Ghaderi
- Department of Psychology, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Clinical Neuroscience, University of Calgary, Calgary, AB, Canada
| | - Elliot C Brown
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Clinical Neuroscience, University of Calgary, Calgary, AB, Canada
- Mathison Centre for Mental Health, University of Calgary, Calgary, AB, Canada
- Arden University Berlin, 10963, Berlin, Germany
- Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Berlin, Germany
- Berlin Institute of Health, 10117, Berlin, Germany
| | - Darren Laree Clark
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Clinical Neuroscience, University of Calgary, Calgary, AB, Canada
- Mathison Centre for Mental Health, University of Calgary, Calgary, AB, Canada
| | - Rajamannar Ramasubbu
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Clinical Neuroscience, University of Calgary, Calgary, AB, Canada
- Mathison Centre for Mental Health, University of Calgary, Calgary, AB, Canada
| | - Zelma H T Kiss
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.
- Department of Clinical Neuroscience, University of Calgary, Calgary, AB, Canada.
- Mathison Centre for Mental Health, University of Calgary, Calgary, AB, Canada.
| | - Andrea B Protzner
- Department of Psychology, University of Calgary, Calgary, AB, Canada.
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.
- Mathison Centre for Mental Health, University of Calgary, Calgary, AB, Canada.
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20
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Bainter SA, McCauley TG, Fahmy MM, Goodman ZT, Kupis LB, Rao JS. Comparing Bayesian Variable Selection to Lasso Approaches for Applications in Psychology. PSYCHOMETRIKA 2023; 88:1032-1055. [PMID: 37217762 PMCID: PMC10202760 DOI: 10.1007/s11336-023-09914-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Indexed: 05/24/2023]
Abstract
In the current paper, we review existing tools for solving variable selection problems in psychology. Modern regularization methods such as lasso regression have recently been introduced in the field and are incorporated into popular methodologies, such as network analysis. However, several recognized limitations of lasso regularization may limit its suitability for psychological research. In this paper, we compare the properties of lasso approaches used for variable selection to Bayesian variable selection approaches. In particular we highlight advantages of stochastic search variable selection (SSVS), that make it well suited for variable selection applications in psychology. We demonstrate these advantages and contrast SSVS with lasso type penalization in an application to predict depression symptoms in a large sample and an accompanying simulation study. We investigate the effects of sample size, effect size, and patterns of correlation among predictors on rates of correct and false inclusion and bias in the estimates. SSVS as investigated here is reasonably computationally efficient and powerful to detect moderate effects in small sample sizes (or small effects in moderate sample sizes), while protecting against false inclusion and without over-penalizing true effects. We recommend SSVS as a flexible framework that is well-suited for the field, discuss limitations, and suggest directions for future development.
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Affiliation(s)
- Sierra A Bainter
- Department of Psychology, University of Miami, 5665 Ponce de Leon Blvd, Coral Gables, FL, 33146, USA.
| | - Thomas G McCauley
- Department of Psychology, University of California San Diego, San Diego, USA
| | - Mahmoud M Fahmy
- Department of Industrial Engineering, University of Miami, Coral Gables, USA
| | - Zachary T Goodman
- Department of Psychology, University of Miami, 5665 Ponce de Leon Blvd, Coral Gables, FL, 33146, USA
| | - Lauren B Kupis
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, USA
| | - J Sunil Rao
- Division of Biostatistics, University of Miami, Coral Gables, USA
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21
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Kent L. Mental Gravity: Depression as Spacetime Curvature of the Self, Mind, and Brain. ENTROPY (BASEL, SWITZERLAND) 2023; 25:1275. [PMID: 37761574 PMCID: PMC10528036 DOI: 10.3390/e25091275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 08/09/2023] [Accepted: 08/18/2023] [Indexed: 09/29/2023]
Abstract
The principle of mental gravity contends that the mind uses physical gravity as a mental model or simulacrum to express the relation between the inner self and the outer world in terms of "UP"-ness and "DOWN"-ness. The simulation of increased gravity characterises a continuum of mental gravity which states includes depression as the paradigmatic example of being down, low, heavy, and slow. The physics of gravity can also be used to model spacetime curvature in depression, particularly gravitational time dilation as a property of MG analogous to subjective time dilation (i.e., the slowing of temporal flow in conscious experience). The principle has profound implications for the Temporo-spatial Theory of Consciousness (TTC) with regard to temporo-spatial alignment that establishes a "world-brain relation" that is centred on embodiment and the socialisation of conscious states. The principle of mental gravity provides the TTC with a way to incorporate the structure of the world into the structure of the brain, conscious experience, and thought. In concert with other theories of cognitive and neurobiological spacetime, the TTC can also work towards the "common currency" approach that also potentially connects the TTC to predictive processing frameworks such as free energy, neuronal gauge theories, and active inference accounts of depression. It gives the up/down dimension of space, as defined by the gravitational field, a unique status that is connected to both our embodied interaction with the physical world, and also the inverse, reflective, emotional but still embodied experience of ourselves.
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Affiliation(s)
- Lachlan Kent
- Mental Wellbeing Initiatives, Royal Melbourne Institute of Technology, Melbourne, VIC 3001, Australia
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22
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Zhong J, Xu J, Wang Z, Yang H, Li J, Yu H, Huang W, Wan C, Ma H, Zhang N. Changes in brain functional networks in remitted major depressive disorder: a six-month follow-up study. BMC Psychiatry 2023; 23:628. [PMID: 37641013 PMCID: PMC10464087 DOI: 10.1186/s12888-023-05082-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 08/06/2023] [Indexed: 08/31/2023] Open
Abstract
BACKGROUND Patients with remitted major depressive disorder (rMDD) show abnormal functional connectivity of the central executive network (CEN), salience networks (SN) and default mode network (DMN). It is unclear how these change during remission, or whether changes are related to function. METHODS Three spatial networks in 17 patients with rMDD were compared between baseline and the six-month follow-up, and to 22 healthy controls. Correlations between these changes and psychosocial functioning were also assessed. RESULTS In the CEN, patients at baseline had abnormal functional connectivity in the right anterior cingulate, right dorsolateral prefrontal cortex (DLPFC) and inferior parietal lobule (IPL) compare with HCs. There were functional connection differences in the right DLPFC and left IPL at baseline during follow-up. Abnormal connectivity in the right DLPFC and medial prefrontal cortex (mPFC) were found at follow-up. In the SN, patients at baseline had abnormal functional connectivity in the insula, left anterior cingulate, left IPL, and right precuneus; compared with baseline, patients had higher connectivity in the right DLPFC at follow-up. In the DMN, patients at baseline had abnormal functional connectivity in the right mPFC. Resting-state functional connectivity of the IPL and DLPFC in the CEN correlated with psychosocial functioning. CONCLUSIONS At six-month follow-up, the CEN still showed abnormal functional connectivity in those with rMDD, while anomalies in the SN and DMN has disappeared. Resting-state functional connectivity of the CEN during early rMDD is associated with psychosocial function. CLINICAL TRIALS REGISTRATION Pharmacotherapy and Psychotherapy for MDD after Remission on Psychology and Neuroimaging. https://www. CLINICALTRIALS gov/ , registration number: NCT01831440 (15/4/2013).
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Affiliation(s)
- Jiaqi Zhong
- Affiliated Nanjing Brain Hospital of Nanjing Medical University, No.264 Guangzhou Street, Gulou District, Nanjing, 210029, Jiangsu, China
- Cognitive Behavioral Therapy Institute of Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Jingren Xu
- Affiliated Nanjing Brain Hospital of Nanjing Medical University, No.264 Guangzhou Street, Gulou District, Nanjing, 210029, Jiangsu, China
| | - Zhenzhen Wang
- Affiliated Nanjing Brain Hospital of Nanjing Medical University, No.264 Guangzhou Street, Gulou District, Nanjing, 210029, Jiangsu, China
- School of psychological and cognitive sciences, Peking University, Beijing, 100871, China
| | - Hao Yang
- Affiliated Nanjing Brain Hospital of Nanjing Medical University, No.264 Guangzhou Street, Gulou District, Nanjing, 210029, Jiangsu, China
| | - Jiawei Li
- Affiliated Nanjing Brain Hospital of Nanjing Medical University, No.264 Guangzhou Street, Gulou District, Nanjing, 210029, Jiangsu, China
| | - Haoran Yu
- Affiliated Nanjing Brain Hospital of Nanjing Medical University, No.264 Guangzhou Street, Gulou District, Nanjing, 210029, Jiangsu, China
| | - Wenyan Huang
- Affiliated Nanjing Brain Hospital of Nanjing Medical University, No.264 Guangzhou Street, Gulou District, Nanjing, 210029, Jiangsu, China
| | - Cheng Wan
- Department of Medical Informatic, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Hui Ma
- Affiliated Nanjing Brain Hospital of Nanjing Medical University, No.264 Guangzhou Street, Gulou District, Nanjing, 210029, Jiangsu, China.
| | - Ning Zhang
- Affiliated Nanjing Brain Hospital of Nanjing Medical University, No.264 Guangzhou Street, Gulou District, Nanjing, 210029, Jiangsu, China.
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, 210029, Jiangsu, China.
- Cognitive Behavioral Therapy Institute of Nanjing Medical University, Nanjing, 210029, Jiangsu, China.
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23
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Wang Z, Baeken C, Wu GR. Metabolic Covariance Connectivity of Posterior Cingulate Cortex Associated with Depression Symptomatology Level in Healthy Young Adults. Metabolites 2023; 13:920. [PMID: 37623864 PMCID: PMC10456574 DOI: 10.3390/metabo13080920] [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: 07/10/2023] [Revised: 08/01/2023] [Accepted: 08/02/2023] [Indexed: 08/26/2023] Open
Abstract
Early detection in the development of a Major Depressive Disorder (MDD) could guide earlier clinical interventions. Although MDD can begin at a younger age, most people have their first episode in young adulthood. The underlying pathophysiological mechanisms relating to such an increased risk are not clear. The posterior cingulate cortex (PCC), exhibiting high levels of brain connectivity and metabolic activity, plays a pivotal role in the pathological mechanism underlying MDD. In the current study, we used the (F-18) fluorodeoxyglucose (FDG) positron emission tomography (PET) to measure metabolic covariance connectivity of the PCC and investigated its association with depression symptomatology evaluated by the Centre for Epidemiological Studies Depression Inventory-Revised (CESD-R) among 27 healthy individuals aged between 18 and 23 years. A significant negative correlation has been observed between CESD-R scale scores and the PCC metabolic connectivity with the anterior cingulate, medial prefrontal cortex, inferior and middle frontal gyrus, as well as the insula. Overall, our findings suggest that the neural correlates of depressive symptomatology in healthy young adults without a formal diagnosis involve the metabolic connectivity of the PCC. Our findings may have potential implications for early identification and intervention in people at risk of developing depression.
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Affiliation(s)
- Zhixin Wang
- Key Laboratory of Cognition and Personality, Faculty of Psychology, Southwest University, Chongqing 400715, China;
| | - Chris Baeken
- Faculty of Medicine and Health Sciences, Department of Head and Skin, Ghent Experimental Psychiatry (GHEP) Lab, Ghent University, 9000 Ghent, Belgium;
| | - Guo-Rong Wu
- Key Laboratory of Cognition and Personality, Faculty of Psychology, Southwest University, Chongqing 400715, China;
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24
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Ten Doesschate F, Bruin W, Zeidman P, Abbott CC, Argyelan M, Dols A, Emsell L, van Eijndhoven PFP, van Exel E, Mulders PCR, Narr K, Tendolkar I, Rhebergen D, Sienaert P, Vandenbulcke M, Verdijk J, van Verseveld M, Bartsch H, Oltedal L, van Waarde JA, van Wingen GA. Effective resting-state connectivity in severe unipolar depression before and after electroconvulsive therapy. Brain Stimul 2023; 16:1128-1134. [PMID: 37517467 DOI: 10.1016/j.brs.2023.07.054] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 07/06/2023] [Accepted: 07/27/2023] [Indexed: 08/01/2023] Open
Abstract
BACKGROUND Electroconvulsive therapy (ECT) is one of the most effective treatments for severe depressive disorders. A recent multi-center study found no consistent changes in correlation-based (undirected) resting-state connectivity after ECT. Effective (directed) connectivity may provide more insight into the working mechanism of ECT. OBJECTIVE We investigated whether there are consistent changes in effective resting-state connectivity. METHODS This multi-center study included data from 189 patients suffering from severe unipolar depression and 59 healthy control participants. Longitudinal data were available for 81 patients and 24 healthy controls. We used dynamic causal modeling for resting-state functional magnetic resonance imaging to determine effective connectivity in the default mode, salience and central executive networks before and after a course of ECT. Bayesian general linear models were used to examine differences in baseline and longitudinal effective connectivity effects associated with ECT and its effectiveness. RESULTS Compared to controls, depressed patients showed many differences in effective connectivity at baseline, which varied according to the presence of psychotic features and later treatment outcome. Additionally, effective connectivity changed after ECT, which was related to ECT effectiveness. Notably, treatment effectiveness was associated with decreasing and increasing effective connectivity from the posterior default mode network to the left and right insula, respectively. No effects were found using correlation-based (undirected) connectivity. CONCLUSIONS A beneficial response to ECT may depend on how brain regions influence each other in networks important for emotion and cognition. These findings further elucidate the working mechanisms of ECT and may provide directions for future non-invasive brain stimulation research.
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Affiliation(s)
- Freek Ten Doesschate
- Department of Psychiatry, Rijnstate Hospital, Arnhem, the Netherlands; Amsterdam UMC Location University of Amsterdam, Department of Psychiatry, Amsterdam, the Netherlands; Amsterdam Neuroscience, Amsterdam, the Netherlands.
| | - Willem Bruin
- Amsterdam UMC Location University of Amsterdam, Department of Psychiatry, Amsterdam, the Netherlands; Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Peter Zeidman
- Wellcome Centre for Human Neuroimaging, 12 Queen Square, London, WC1N 3AR, UK
| | - Christopher C Abbott
- Department of Psychiatry, University of New Mexico School of Medicine, Albuquerque, NM, USA
| | - Miklos Argyelan
- Center for Psychiatric Neuroscience at the Feinstein Institute for Medical Research, New York, NY, USA
| | - Annemieke Dols
- GGZ inGeest Specialized Mental Health Care, Department of Old Age Psychiatry, Oldenaller 1, 1081 HJ, Amsterdam, the Netherlands; Amsterdam UMC, Vrije Universiteit, Psychiatry, Amsterdam Public Health Research Institute, the Netherlands; Amsterdam UMC, Vrije Universiteit, Psychiatry, Amsterdam Neuroscience, the Netherlands
| | - Louise Emsell
- Katholieke Universiteit Leuven, University Psychiatric Center Katholieke Universiteit Leuven, Leuven, Belgium
| | - Philip F P van Eijndhoven
- Donders Institute for Brain, Cognition and Behavior, Department of Psychiatry, Nijmegen, the Netherlands; Department of Psychiatry, Radboud University Medical Centre, Huispost 961, P.O. Box 9101, 6500 HB, Nijmegen, the Netherlands
| | - Eric van Exel
- GGZ inGeest Specialized Mental Health Care, Department of Old Age Psychiatry, Oldenaller 1, 1081 HJ, Amsterdam, the Netherlands; Amsterdam UMC, Vrije Universiteit, Psychiatry, Amsterdam Public Health Research Institute, the Netherlands; Amsterdam UMC, Vrije Universiteit, Psychiatry, Amsterdam Neuroscience, the Netherlands
| | - Peter C R Mulders
- Donders Institute for Brain, Cognition and Behavior, Department of Psychiatry, Nijmegen, the Netherlands; Department of Psychiatry, Radboud University Medical Centre, Huispost 961, P.O. Box 9101, 6500 HB, Nijmegen, the Netherlands
| | - Katherine Narr
- Departments of Neurology, Psychiatry, and Biobehavioral Sciences, University of California, Los Angeles, CA, USA
| | - Indira Tendolkar
- Donders Institute for Brain, Cognition and Behavior, Department of Psychiatry, Nijmegen, the Netherlands; Department of Psychiatry, Radboud University Medical Centre, Huispost 961, P.O. Box 9101, 6500 HB, Nijmegen, the Netherlands
| | - Didi Rhebergen
- Amsterdam UMC, Vrije Universiteit, Psychiatry, Amsterdam Public Health Research Institute, the Netherlands; Amsterdam UMC, Vrije Universiteit, Psychiatry, Amsterdam Neuroscience, the Netherlands
| | - Pascal Sienaert
- Academic Center for ECT and Neuromodulation (AcCENT), University Psychiatric Center KU Leuven (Catholic University of Leuven), Leuven, Belgium
| | - Mathieu Vandenbulcke
- Katholieke Universiteit Leuven, University Psychiatric Center Katholieke Universiteit Leuven, Leuven, Belgium
| | - Joey Verdijk
- Department of Psychiatry, Rijnstate Hospital, Arnhem, the Netherlands
| | | | - Hauke Bartsch
- Mohn Medical Imaging and Visualization Center, Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Leif Oltedal
- Mohn Medical Imaging and Visualization Center, Department of Radiology, Haukeland University Hospital, Bergen, Norway; Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | | | - Guido A van Wingen
- Amsterdam UMC Location University of Amsterdam, Department of Psychiatry, Amsterdam, the Netherlands; Amsterdam Neuroscience, Amsterdam, the Netherlands
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Mitra A, Raichle ME, Geoly AD, Kratter IH, Williams NR. Targeted neurostimulation reverses a spatiotemporal biomarker of treatment-resistant depression. Proc Natl Acad Sci U S A 2023; 120:e2218958120. [PMID: 37186863 PMCID: PMC10214160 DOI: 10.1073/pnas.2218958120] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 03/26/2023] [Indexed: 05/17/2023] Open
Abstract
Major depressive disorder (MDD) is widely hypothesized to result from disordered communication across brain-wide networks. Yet, prior resting-state-functional MRI (rs-fMRI) studies of MDD have studied zero-lag temporal synchrony (functional connectivity) in brain activity absent directional information. We utilize the recent discovery of stereotyped brain-wide directed signaling patterns in humans to investigate the relationship between directed rs-fMRI activity, MDD, and treatment response to FDA-approved neurostimulation paradigm termed Stanford neuromodulation therapy (SNT). We find that SNT over the left dorsolateral prefrontal cortex (DLPFC) induces directed signaling shifts in the left DLPFC and bilateral anterior cingulate cortex (ACC). Directional signaling shifts in the ACC, but not the DLPFC, predict improvement in depression symptoms, and moreover, pretreatment ACC signaling predicts both depression severity and the likelihood of SNT treatment response. Taken together, our findings suggest that ACC-based directed signaling patterns in rs-fMRI are a potential biomarker of MDD.
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Affiliation(s)
- Anish Mitra
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA94305
| | - Marcus E. Raichle
- Department of Radiology, Washington University, Saint Louis, MO63110
- Department of Neurology, Washington University, Saint Louis, MO63110
| | - Andrew D. Geoly
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA94305
| | - Ian H. Kratter
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA94305
| | - Nolan R. Williams
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA94305
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Immediate modulatory effects of transcutaneous auricular vagus nerve stimulation on the resting state of major depressive disorder. J Affect Disord 2023; 325:513-521. [PMID: 36642310 DOI: 10.1016/j.jad.2023.01.035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 12/13/2022] [Accepted: 01/08/2023] [Indexed: 01/15/2023]
Abstract
BACKGROUND Previous studies have found that transcutaneous auricular vagus nerve stimulation (taVNS) is clinically effective in the treatment of major depressive disorder (MDD), and its efficacy mechanism is related to modulation of the default mode network (DMN) and cognitive control network (CCN). However, the mechanism of the immediate effect of taVNS for MDD remains to be elucidated. METHODS A total of 58 patients with MDD and 54 healthy controls(HCs) were included in this study. The MDD group was treated with taVNS for 30 min (20 Hz, 4-6 mA) immediately, and we observed amplitude of low-frequency fluctuations (ALFF) abnormalities in the MDD group and changes in ALFF and functional connectivity (FC) before and after immediate treatment. The ALFF brain regions altered by taVNS induction were used as regions of interest to analyze whole-brain FC changes in the MDD group. RESULTS After taVNS treatment, ALFF in the right precuneus was decreased in the MDD group. The FC of the right precuneus with the left middle frontal gyrus, the left posterior cingulate gyrus and the left angular gyrus were decreased in the MDD group. Correlation analysis showed that the FC values between the right precuneus and the left posterior cingulate gyrus in the pre-treatment MDD group was negatively correlated with the 17-item Hamilton depression rating scale scores. CONCLUSION TaVNS has an immediate modulatory effect on DMN and CCN. It would be proposed that these functional networks may be effective targets for the long-term treatment of MDD patients with taVNS.
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Radoman M, Gorka SM. Intolerance of uncertainty and functional connectivity of the anterior insula during anticipation of unpredictable reward. Int J Psychophysiol 2023; 183:1-8. [PMID: 36122824 PMCID: PMC11062179 DOI: 10.1016/j.ijpsycho.2022.09.003] [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: 12/31/2021] [Revised: 09/04/2022] [Accepted: 09/11/2022] [Indexed: 01/04/2023]
Abstract
Individuals with high intolerance of uncertainty (IU) tend to display maladaptive cognitive, behavioral, physiological, and/or neural responses during anticipation of uncertain or ambiguous outcomes, both positive and negative in valence. Importantly, high IU has been proposed as a key transdiagnostic phenotypic risk factor for the onset and maintenance of several psychiatric disorders. Within the context of reward processing, high IU has been related to dysfunctional reward anticipation, which may be mediated by hyperactive anterior insula (AIC) response to uncertainty. The present study further investigated the relationship between the AIC and IU by examining the association between individual differences in IU and task-based functional connectivity of the right AIC using functional magnetic resonance imaging (fMRI). Participants (N = 171) completed a self-report measure of IU and a reward anticipation task during fMRI. Generalized psychophysiological interaction (gPPI) analyses were performed with a seed in the right AIC. In the U-threat model, we found that greater self-reported levels of IU were correlated with increased functional connectivity between the right AIC and the dorsal anterior cingulate cortex (dACC) and the right dorsolateral prefrontal cortex (dlPFC). In the P-threat model, we did not find these associations, perhaps indicating that they may be more robust during uncertainty. These preliminary findings suggest that parts of salience and central executive control networks may be impacted by and underlie the expression of IU. Future studies should examine the generalizability of these findings to clinical populations and investigate how disruption of these functional networks may contribute to psychopathology.
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Affiliation(s)
- Milena Radoman
- Department of Psychiatry, University of Illinois at Chicago, 1601 W Taylor Street, Chicago, IL 60612, USA; Department of Anatomy and Cell Biology, University of Illinois at Chicago, 840 S Wood Street, Chicago, IL 60612, USA; The Graduate Program in Neuroscience, University of Illinois at Chicago, 840 S Wood Street, Chicago, IL 60612, USA.
| | - Stephanie M Gorka
- Department of Psychiatry and Behavioral Health, Ohio State University, 1670 Upham Drive, Columbus, OH 43205, USA
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A systematic review on the potential use of machine learning to classify major depressive disorder from healthy controls using resting state fMRI measures. Neurosci Biobehav Rev 2023; 144:104972. [PMID: 36436736 DOI: 10.1016/j.neubiorev.2022.104972] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 09/08/2022] [Accepted: 11/21/2022] [Indexed: 11/27/2022]
Abstract
BACKGROUND Major Depressive Disorder (MDD) is a psychiatric disorder characterized by functional brain deficits, as documented by resting-state functional magnetic resonance imaging (rs-fMRI) studies. AIMS In recent years, some studies used machine learning (ML) approaches, based on rs-fMRI features, for classifying MDD from healthy controls (HC). In this context, this review aims to provide a comprehensive overview of the results of these studies. DESIGN The studies research was performed on 3 online databases, examining English-written articles published before August 5, 2022, that performed a two-class ML classification using rs-fMRI features. The search resulted in 20 eligible studies. RESULTS The reviewed studies showed good performance metrics, with better performance achieved when the dataset was restricted to a more homogeneous group in terms of disease severity. Regions within the default mode network, salience network, and central executive network were reported as the most important features in the classification algorithms. LIMITATIONS The small sample size together with the methodological and clinical heterogeneity limited the generalizability of the findings. CONCLUSIONS In conclusion, ML applied to rs-fMRI features can be a valid approach to classify MDD and HC subjects and to discover features that can be used for additional investigation of the pathophysiology of the disease.
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Rakesh D, Zalesky A, Whittle S. The Role of School Environment in Brain Structure, Connectivity, and Mental Health in Children: A Multimodal Investigation. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:32-41. [PMID: 35123109 DOI: 10.1016/j.bpsc.2022.01.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Revised: 01/05/2022] [Accepted: 01/20/2022] [Indexed: 02/07/2023]
Abstract
BACKGROUND Much work has been dedicated to understanding the effects of adverse home environments on brain development. While the school social and learning environment plays a role in child development, little work has been done to investigate the impact of the school environment on the developing brain. The goal of the present study was to examine associations between the school environment, brain structure and connectivity, and mental health. METHODS In this preregistered study we investigated these questions in a large sample of adolescents (9-10 years of age) from the Adolescent Brain Cognitive Development (ABCD) Study. We examined the association between school environment and gray matter (n = 10,435) and white matter (n = 10,770) structure and functional connectivity (n = 9528). We then investigated multivariate relationships between school-associated brain measures and mental health. RESULTS School environment was associated with connectivity of the auditory and retrosplenial temporal network as well as of higher-order cognitive networks like the cingulo-opercular, default mode, ventral attention, and frontoparietal networks. Multivariate analyses revealed that connectivity of the cingulo-opercular and default mode networks was also associated with mental health. CONCLUSIONS Findings shed light on the neural mechanisms through which favorable school environments may contribute to positive mental health outcomes in children. Our findings have implications for interventions targeted at promoting positive youth functioning through improving school environments.
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Affiliation(s)
- Divyangana Rakesh
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Victoria, Australia.
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Victoria, Australia; Melbourne School of Engineering, University of Melbourne, Melbourne, Victoria, Australia
| | - Sarah Whittle
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Victoria, Australia.
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Anticipatory cues in emotional processing shift the activation of a combined salience sensorimotor functional network in drug-naïve depressed patients. J Affect Disord 2023; 320:509-516. [PMID: 36206887 DOI: 10.1016/j.jad.2022.09.165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 09/26/2022] [Accepted: 09/30/2022] [Indexed: 11/05/2022]
Abstract
BACKGROUND Major depressive disorder is characterized by a large-scale brain network dysfunction, contributing to impairments in cognitive and affective functioning. Core regions of default mode, limbic and salience networks are also impaired in emotional processing and anticipation. This study aimed to explore default mode, salience, and limbic networks modulation during the processing of emotional stimuli with and without anticipatory cues in depression, and further investigate how these networks were functionally coupled with the rest of the brain. METHODS Twenty-one drug-naïve depressed patients and 15 matched controls were included in the study. All participants completed a psychological assessment and the affective pictures paradigm during an fMRI acquisition. Group independent component analysis and psychophysiological interactions analyses were performed. RESULTS A significant interaction between Cue, Valence and Group was found for the salience/sensorimotor network. When processing uncued emotional stimuli, patients showed increased activation of this network for negative vs. neutral pictures, whereas when anticipatory cues were displayed previously to the picture presentation, they invert this pattern of activation (hyperactivating the salience/sensorimotor network for positive vs. neutral pictures). Patients showed increased functional connectivity between the salience/sensorimotor network and the left amygdala as well as the right inferior parietal lobule compared to controls when processing uncued negative pictures. LIMITATIONS The sample size was modest, and the salience/sensorimotor network included regions not typically identified as part of salience network. Thus, this study should be replicated to further interpret the results. CONCLUSIONS Anticipatory cues shift the pattern of activation of the salience/sensorimotor network in drug-naïve depressed patients.
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Individual- and Connectivity-Based Real-Time fMRI Neurofeedback to Modulate Emotion-Related Brain Responses in Patients with Depression: A Pilot Study. Brain Sci 2022; 12:brainsci12121714. [PMID: 36552173 PMCID: PMC9775232 DOI: 10.3390/brainsci12121714] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 12/08/2022] [Accepted: 12/11/2022] [Indexed: 12/23/2022] Open
Abstract
INTRODUCTION Individual real-time functional magnetic resonance imaging neurofeedback (rtfMRI NF) might be a promising adjuvant in treating depressive symptoms. Further studies showed functional variations and connectivity-related changes in the dorsolateral prefrontal cortex (dlPFC) and the insular cortex. OBJECTIVES The aim of this pilot study was to investigate whether individualized connectivity-based rtfMRI NF training can improve symptoms in depressed patients as an adjunct to a psychotherapeutic programme. The novel strategy chosen for this was to increase connectivity between individualized regions of interest, namely the insula and the dlPFC. METHODS Sixteen patients diagnosed with major depressive disorder (MDD, ICD-10) and 19 matched healthy controls (HC) participated in a rtfMRI NF training consisting of two sessions with three runs each, within an interval of one week. RtfMRI NF was applied during a sequence of negative emotional pictures to modulate the connectivity between the dlPFC and the insula. The MDD REAL group was divided into a Responder and a Non-Responder group. Patients with an increased connectivity during the second NF session or during both the first and the second NF session were identified as "MDD REAL Responder" (N = 6). Patients that did not show any increase in connectivity and/or a decreased connectivity were identified as "MDD REAL Non-Responder" (N = 7). RESULTS Before the rtfMRI sessions, patients with MDD showed higher neural activation levels in ventromedial PFC and the insula than HC; by contrast, HC revealed increased hemodynamic activity in visual processing areas (primary visual cortex and visual association cortex) compared to patients with MDD. The comparison of hemodynamic responses during the first compared to during the last NF session demonstrated significantly increased BOLD-activation in the medial orbitofrontal cortex (mOFC) in patients and HC, and additionally in the lateral OFC in patients with MDD. These findings were particularly due to the MDD Responder group, as the MDD Non-Responder group showed no increase in this region during the last NF run. There was a decrease of neural activation in emotional processing brain regions in both groups in the last NF run compared to the first: HC showed differences in the insula, parahippocampal gyrus, basal ganglia, and cingulate gyrus. Patients with MDD demonstrated deceased responses in the parahippocampal gyrus. There was no significant reduction of BDI scores after NF training in patients. CONCLUSIONS Increased neural activation in the insula and vmPFC in MDD suggests an increased emotional reaction in patients with MDD. The activation of the mOFC could be associated with improved control-strategies and association-learning processes. The increased lOFC activation could indicate a stronger sensitivity to failed NF attempts in MDD. A stronger involvement of visual processing areas in HC may indicate better adaptation to negative emotional stimuli after repeated presentation. Overall, the rtfMRI NF had an impact on neurobiological mechanisms, but not on psychometric measures in patients with MDD.
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Resting state functional connectivity as a marker of internalizing disorder onset in high-risk youth. Sci Rep 2022; 12:21337. [PMID: 36494495 PMCID: PMC9734132 DOI: 10.1038/s41598-022-25805-y] [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: 08/26/2022] [Accepted: 12/05/2022] [Indexed: 12/13/2022] Open
Abstract
While research has linked alterations in functional connectivity of the default mode (DMN), cognitive control (CCN), and salience networks (SN) to depression and anxiety, little research has examined whether these alterations may be premorbid vulnerabilities. This study examined resting state functional connectivity (RSFC) of the CCN, DMN, and SN as markers of risk for developing an onset of a depressive or anxiety disorder in adolescents at high familial risk for these disorders. At baseline, 135 participants aged 11-17 completed resting-state functional magnetic resonance imaging, measures of internalizing symptoms, and diagnostic interviews to assess history of depressive and anxiety disorders. Diagnostic assessments were completed again at 9- or 18-month follow-up for 112 participants. At baseline, increased CCN connectivity to areas of the visual network, and decreased connectivity between the left SN and the precentral gyrus, predicted an increased likelihood of a new onset at follow-up. Increased connectivity between the right SN and postcentral gyrus at baseline predicted first episode onsets at follow-up. Altered connectivity between these regions may represent a risk factor for developing a clinically significant onset of an internalizing disorder. Results may have implications for understanding the neural bases of internalizing disorders for early identification and prevention efforts.
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Holt-Gosselin B, Cohodes EM, McCauley S, Foster JC, Odriozola P, Zacharek SJ, Kribakaran S, Haberman JT, Hodges HR, Gee DG. Lack of robust associations between prepandemic coping strategies and frontolimbic circuitry with depression and anxiety symptoms during the COVID-19 pandemic: A preregistered longitudinal study. Behav Neurosci 2022; 136:528-540. [PMID: 36395014 PMCID: PMC9884515 DOI: 10.1037/bne0000534] [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] [Indexed: 11/19/2022]
Abstract
The COVID-19 pandemic is an ongoing stressor that has resulted in the exacerbation of mental health problems worldwide. However, longitudinal studies that identify preexisting behavioral and neurobiological factors associated with mental health outcomes during the pandemic are lacking. Here, we examined associations between prepandemic coping strategy engagement and frontolimbic circuitry with internalizing symptoms during the pandemic. In 85 adults (71.8% female; age 18-30 years), we assessed prototypically adaptive coping strategies (Connor-Davidson Resilience Scale), resting-state functional magnetic resonance imaging functional connectivity (FC) of frontolimbic circuitry, and depression and anxiety symptoms (Beck Depression Inventory, Screen for Child Anxiety-Related Emotional Disorders-Adult, respectively). We conducted general linear models to test preregistered hypotheses that (1) lower coping engagement prepandemic and (2) weaker frontolimbic FC prepandemic would predict elevated symptoms during the pandemic; and (3) coping would interact with FC to predict symptoms during the pandemic. Depression and anxiety symptoms worsened during the pandemic (ps < .001). Prepandemic adaptive coping engagement and frontolimbic FC were not associated with depression or anxiety symptoms during the pandemic (uncorrected ps > .05). Coping interacted with insula-rostral anterior cingulate cortex (ACC) FC (p = .003, pFDR = .014) and with insula-ventral ACC FC (p < .001, pFDR < .001) to predict depression symptoms, but these findings did not survive FDR correction after removal of outliers. Findings from our preregistered study suggest that specific prepandemic factors, particularly adaptive coping and frontolimbic circuitry, are not robustly associated with emotional responses to the pandemic. Additional studies that identify preexisting neurobehavioral factors implicated in mental health outcomes during global health crises are needed. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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Affiliation(s)
- Bailey Holt-Gosselin
- Department of Psychology, Yale University, 2 Hillhouse Avenue, New Haven, CT 06520, United States
- Interdepartmental Neuroscience Graduate Program, Yale University, New Haven, CT 06520, United States
| | - Emily M. Cohodes
- Department of Psychology, Yale University, 2 Hillhouse Avenue, New Haven, CT 06520, United States
| | - Sarah McCauley
- Department of Psychology, Yale University, 2 Hillhouse Avenue, New Haven, CT 06520, United States
| | - Jordan C. Foster
- Department of Psychology, Yale University, 2 Hillhouse Avenue, New Haven, CT 06520, United States
| | - Paola Odriozola
- Department of Psychology, Yale University, 2 Hillhouse Avenue, New Haven, CT 06520, United States
| | - Sadie J. Zacharek
- Department of Psychology, Yale University, 2 Hillhouse Avenue, New Haven, CT 06520, United States
| | - Sahana Kribakaran
- Department of Psychology, Yale University, 2 Hillhouse Avenue, New Haven, CT 06520, United States
- Interdepartmental Neuroscience Graduate Program, Yale University, New Haven, CT 06520, United States
| | - Jason T. Haberman
- Department of Psychology, Yale University, 2 Hillhouse Avenue, New Haven, CT 06520, United States
| | - H. R. Hodges
- Department of Psychology, Yale University, 2 Hillhouse Avenue, New Haven, CT 06520, United States
| | - Dylan G. Gee
- Department of Psychology, Yale University, 2 Hillhouse Avenue, New Haven, CT 06520, United States
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Yu F, Fang H, Zhang J, Wang Z, Ai H, Kwok VPY, Fang Y, Guo Y, Wang X, Zhu C, Luo Y, Xu P, Wang K. Individualized prediction of consummatory anhedonia from functional connectome in major depressive disorder. Depress Anxiety 2022; 39:858-869. [PMID: 36325748 DOI: 10.1002/da.23292] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 10/12/2022] [Accepted: 10/22/2022] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND Anhedonia is a key symptom of major depressive disorder (MDD) and other psychiatric diseases. The neural basis of anhedonia has been widely examined, yet the interindividual variability in neuroimaging biomarkers underlying individual-specific symptom severity is not well understood. METHODS To establish an individualized prediction model of anhedonia, we applied connectome-based predictive modeling (CPM) to whole-brain resting-state functional connectivity profiles of MDD patients. RESULTS The CPM can successfully and reliably predict individual consummatory but not anticipatory anhedonia. The predictive model mainly included salience network (SN), frontoparietal network (FPN), default mode network (DMN), and motor network. Importantly, subsequent computational lesion prediction and consummatory-specific model prediction revealed that connectivity of the SN with DMN and FPN is essential and specific for the prediction of consummatory anhedonia. CONCLUSIONS This study shows that brain functional connectivity, especially the connectivity of SN-FPN and SN-DMN, can specifically predict individualized consummatory anhedonia in MDD. These findings suggest the potential of functional connectomes for the diagnosis and prognosis of anhedonia in MDD and other disorders.
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Affiliation(s)
- Fengqiong Yu
- Research Center for Translational Medicine, The Second Hospital of Anhui Medical University, Hefei, China.,School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China.,Department of Neurology, The First Affiliated Hospital of Anhui Medical University, The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, Anhui Province, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Huihua Fang
- Shenzhen Key Laboratory of Affective and Social Neuroscience, Magnetic Resonance Imaging Center, Center for Brain Disorders and Cognitive Sciences, Shenzhen University, Shenzhen, China.,Department of Psychology, University of Mannheim, Mannheim, Germany
| | - Junfeng Zhang
- Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education (BNU), Faculty of Psychology, Beijing Normal University, Beijing, China
| | - Zhihao Wang
- Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education (BNU), Faculty of Psychology, Beijing Normal University, Beijing, China
| | - Hui Ai
- Shenzhen Key Laboratory of Affective and Social Neuroscience, Magnetic Resonance Imaging Center, Center for Brain Disorders and Cognitive Sciences, Shenzhen University, Shenzhen, China
| | - Veronica P Y Kwok
- Center for Neuroimaging, Shenzhen Institute of Neuroscience, Shenzhen, China
| | - Ya Fang
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Anhui Province, China
| | - Yaru Guo
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Anhui Province, China
| | - Xin Wang
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Anhui Province, China
| | - Chunyan Zhu
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Anhui Province, China
| | - Yuejia Luo
- Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education (BNU), Faculty of Psychology, Beijing Normal University, Beijing, China
| | - Pengfei Xu
- Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education (BNU), Faculty of Psychology, Beijing Normal University, Beijing, China.,Center for Neuroimaging, Shenzhen Institute of Neuroscience, Shenzhen, China
| | - Kai Wang
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China.,Department of Neurology, The First Affiliated Hospital of Anhui Medical University, The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, Anhui Province, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Anhui Province, China
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Goldberg H. Growing Brains, Nurturing Minds-Neuroscience as an Educational Tool to Support Students' Development as Life-Long Learners. Brain Sci 2022; 12:1622. [PMID: 36552082 PMCID: PMC9775149 DOI: 10.3390/brainsci12121622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 11/19/2022] [Accepted: 11/23/2022] [Indexed: 11/29/2022] Open
Abstract
Compared to other primates, humans are late bloomers, with exceptionally long childhood and adolescence. The extensive developmental period of humans is thought to facilitate the learning processes required for the growth and maturation of the complex human brain. During the first two and a half decades of life, the human brain is a construction site, and learning processes direct its shaping through experience-dependent neuroplasticity. Formal and informal learning, which generates long-term and accessible knowledge, is mediated by neuroplasticity to create adaptive structural and functional changes in brain networks. Since experience-dependent neuroplasticity is at full force during school years, it holds a tremendous educational opportunity. In order to fulfill this developmental and learning potential, educational practices should be human-brain-friendly and "ride" the neuroplasticity wave. Neuroscience can inform educators about the natural learning mechanisms of the brain to support student learning. This review takes a neuroscientific lens to explore central concepts in education (e.g., mindset, motivation, meaning-making, and attention) and suggests two methods of using neuroscience as an educational tool: teaching students about their brain (content level) and considering the neuro-mechanisms of learning in educational design (design level).
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Affiliation(s)
- Hagar Goldberg
- Department of Psychology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
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36
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Vilgis V, Yee D, Silk TJ, Vance A. Distinct Neural Profiles of Frontoparietal Networks in Boys with ADHD and Boys with Persistent Depressive Disorder. COGNITIVE, AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2022; 22:1183-1198. [PMID: 35349053 PMCID: PMC10149107 DOI: 10.3758/s13415-022-00999-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 03/12/2022] [Indexed: 05/02/2023]
Abstract
Working memory deficits are common in attention-deficit/hyperactivity disorder (ADHD) and depression-two common neurodevelopmental disorders with overlapping cognitive profiles but distinct clinical presentation. Multivariate techniques have previously been utilized to understand working memory processes in functional brain networks in healthy adults but have not yet been applied to investigate how working memory processes within the same networks differ within typical and atypical developing populations. We used multivariate pattern analysis (MVPA) to identify whether brain networks discriminated between spatial versus verbal working memory processes in ADHD and Persistent Depressive Disorder (PDD). Thirty-six male clinical participants and 19 typically developing (TD) boys participated in a fMRI scan while completing a verbal and a spatial working memory task. Within a priori functional brain networks (frontoparietal, default mode, salience), the TD group demonstrated differential response patterns to verbal and spatial working memory. The PDD group showed weaker differentiation than TD, with lower classification accuracies observed in primarily the left frontoparietal network. The neural profiles of the ADHD and PDD differed specifically in the SN where the ADHD group's neural profile suggests significantly less specificity in neural representations of spatial and verbal working memory. We highlight within-group classification as an innovative tool for understanding the neural mechanisms of how cognitive processes may deviate in clinical disorders, an important intermediary step towards improving translational psychiatry.
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Affiliation(s)
- Veronika Vilgis
- Department of Paediatrics, University of Melbourne, Melbourne, Australia
| | - Debbie Yee
- Washington University in St. Louis, St. Louis, MO, USA.
- Cognitive, Linguistic & Psychological Sciences, Brown University, Box 182, Metcalf Research Building, 190 Thayer Street, Providence, RI, 02912, USA.
| | - Tim J Silk
- Department of Paediatrics, University of Melbourne, Melbourne, Australia
- Murdoch Children's Research Institute, Melbourne, Australia
- School of Psychology, Deakin University, Providence, Australia
| | - Alasdair Vance
- Department of Paediatrics, University of Melbourne, Melbourne, Australia
- School of Psychology, Deakin University, Providence, Australia
- Royal Children's Hospital, Parkville, Australia
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37
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Pessin S, Walsh EC, Hoks RM, Birn RM, Abercrombie HC, Philippi CL. Resting-state neural signal variability in women with depressive disorders. Behav Brain Res 2022; 433:113999. [PMID: 35811000 PMCID: PMC9559753 DOI: 10.1016/j.bbr.2022.113999] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 06/15/2022] [Accepted: 07/05/2022] [Indexed: 11/21/2022]
Abstract
Aberrant activity and connectivity in default mode (DMN), frontoparietal (FPN), and salience (SN) network regions is well-documented in depression. Recent neuroimaging research suggests that altered variability in the blood oxygen level-dependent (BOLD) signal may disrupt normal network integration and be an important novel predictor of psychopathology. However, no studies have yet determined the relationship between resting-state BOLD signal variability and depressive disorders nor applied BOLD signal variability features to the classification of depression history using machine learning (ML). We collected resting-state fMRI data for 79 women with different depression histories: no history, past history, and current depressive disorder. We tested voxelwise differences in BOLD signal variability related to depression group and severity. We also investigated whether BOLD signal variability of DMN, FPN, and SN regions could predict depression history group using a supervised random forest ML model. Results indicated that individuals with any history of depression had significantly decreased BOLD signal variability in the left and right cerebellum and right parietal cortex (pFWE <0.05). Furthermore, greater depression severity was also associated with reduced BOLD signal variability in the cerebellum. A random forest model classified participant depression history with 74% accuracy, with the ventral anterior cingulate cortex of the DMN as the most important variable in the model. These findings provide novel support for resting-state BOLD signal variability as a marker of neural dysfunction in depression and implicate decreased neural signal variability in the pathophysiology of depression.
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Affiliation(s)
- Sally Pessin
- Department of Psychological Sciences, University of Missouri-St. Louis, 1 University Blvd., St. Louis, 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, WI 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, MO 63121, USA.
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Belleau EL, Bolton TAW, Kaiser RH, Clegg R, Cárdenas E, Goer F, Pechtel P, Beltzer M, Vitaliano G, Olson DP, Teicher MH, Pizzagalli DA. Resting state brain dynamics: Associations with childhood sexual abuse and major depressive disorder. Neuroimage Clin 2022; 36:103164. [PMID: 36044792 PMCID: PMC9449675 DOI: 10.1016/j.nicl.2022.103164] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 07/23/2022] [Accepted: 08/22/2022] [Indexed: 01/07/2023]
Abstract
Early life stress (ELS) and major depressive disorder (MDD) share neural network abnormalities. However, it is unclear how ELS and MDD may separately and/or jointly relate to brain networks, and whether neural differences exist between depressed individuals with vs without ELS. Moreover, prior work evaluated static versus dynamic network properties, a critical gap considering brain networks show changes in coordinated activity over time. Seventy-one unmedicated females with and without childhood sexual abuse (CSA) histories and/or MDD completed a resting state scan and a stress task in which cortisol and affective ratings were collected. Recurring functional network co-activation patterns (CAPs) were examined and time in CAP (number of times each CAP is expressed) and transition frequencies (transitioning between different CAPs) were computed. The effects of MDD and CSA on CAP metrics were examined and CAP metrics were correlated with depression and stress-related variables. Results showed that MDD, but not CSA, related to CAP metrics. Specifically, individuals with MDD (N = 35) relative to HCs (N = 36), spent more time in a posterior default mode (DMN)-frontoparietal network (FPN) CAP and transitioned more frequently between posterior DMN-FPN and prototypical DMN CAPs. Across groups, more time spent in a posterior DMN-FPN CAP and greater DMN-FPN and prototypical DMN CAP transition frequencies were linked to higher rumination. Imbalances between the DMN and the FPN appear central to MDD and might contribute to MDD-related cognitive dysfunction, including rumination. Unexpectedly, CSA did not modulate such dysfunctions, a finding that needs to be replicated by future studies with larger sample sizes.
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Affiliation(s)
- Emily L Belleau
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
| | - Thomas A W Bolton
- Department of Clinical Neurosciences, Neurosurgery Service and Gamma Knife Center, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
| | - Roselinde H Kaiser
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, USA
| | - Rachel Clegg
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Emilia Cárdenas
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Franziska Goer
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Pia Pechtel
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Miranda Beltzer
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Gordana Vitaliano
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA; McLean Imaging Center, McLean Hospital, Belmont, MA, USA
| | - David P Olson
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA; McLean Imaging Center, McLean Hospital, Belmont, MA, USA
| | - Martin H Teicher
- 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; McLean Imaging Center, McLean Hospital, Belmont, MA, USA
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Matsui T, Yamashita KI. Static and Dynamic Functional Connectivity Alterations in Alzheimer's Disease and Neuropsychiatric Diseases. Brain Connect 2022. [PMID: 35994384 DOI: 10.1089/brain.2022.0044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
To date, numerous studies have documented various alterations in resting brain activity in Alzheimer's disease (AD) and other neuropsychiatric diseases. In particular, disease-related alterations of functional connectivity (FC) in the resting state networks (RSN) have been documented. Altered FC in RSN is useful not only for interpreting the phenotype of diseases but also for diagnosing the diseases. More recently, several studies proposed the dynamics of resting-brain activity as a useful marker for detecting altered RSNs related to AD and other diseases. In contrast to previous studies, which focused on FC calculated using an entire fMRI scan (static FC), these newer studies focused the on temporal dynamics of FC within the scan (dynamic FC) to provide more sensitive measures to characterize RSNs. However, despite the increasing popularity of dFC, several studies cautioned that the results obtained in commonly used analyses for dFC require careful interpretation. In this mini-review, we review recent studies exploring alterations of static and dynamic functional connectivity in AD and other neuropsychiatric diseases. We then discuss how to utilize and interpret dFC for studying resting brain activity in diseases.
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Affiliation(s)
- Teppei Matsui
- Okayama University - Tsushima Campus, Tsushima-kita 1-1-1, Okayama, Japan, 700-8530;
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Macêdo MA, Sato JR, Bressan RA, Pan PM. Adolescent depression and resting-state fMRI brain networks: a scoping review of longitudinal studies. REVISTA BRASILEIRA DE PSIQUIATRIA (SAO PAULO, BRAZIL : 1999) 2022; 44. [PMID: 35896034 PMCID: PMC9375668 DOI: 10.47626/1516-4446-2021-2032] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 12/02/2021] [Indexed: 11/24/2022]
Abstract
The neurobiological factors associated with the emergence of major depressive disorder (MDD) in adolescence are still unclear. Previous cross-sectional studies have documented aberrant connectivity in resting-state functional magnetic resonance imaging (rs-fMRI) networks. However, whether these findings precede MDD onset has not been established. This scoping review mapped key methodological aspects and main findings of longitudinal rs-fMRI studies of MDD in adolescence. Three sets of neuroimaging methods to analyze rs-fMRI data were identified: seed-based analysis, independent component analysis, and network-based approaches. Main findings involved aberrant connectivity within and between the default mode network (DMN), the cognitive control network (CCN), and the salience network (SN). Accordingly, we utilized Menon's (2011) triple-network model for neuropsychiatric disorders to summarize key results. Adolescent MDD was associated with hyperconnectivity within the SN and between DMN and SN, as well as hypoconectivity within the CCN. These findings suggested that dysfunctional connectivity among the three main large-scale brain networks preceded MDD onset. However, there was high heterogeneity in neuroimaging methods and sampling procedures, which may limit comparisons between studies. Future studies should consider some level of harmonization for clinical instruments and neuroimaging methods.
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Affiliation(s)
- Marcos Antônio Macêdo
- Laboratório Interdisciplinar de Neurociências Clínicas, Departamento de Psiquiatria, Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil
| | - João Ricardo Sato
- Centro de Matemática, Computação e Cognição, Universidade Federal do ABC, Santo André, SP, Brazil
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Rodrigo A. Bressan
- Laboratório Interdisciplinar de Neurociências Clínicas, Departamento de Psiquiatria, Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil
- Instituto Nacional de Psiquiatria do Desenvolvimento, São Paulo, SP, Brazil
| | - Pedro Mario Pan
- Laboratório Interdisciplinar de Neurociências Clínicas, Departamento de Psiquiatria, Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil
- Instituto Nacional de Psiquiatria do Desenvolvimento, São Paulo, SP, Brazil
- Programa Jovens Lideranças Médicas, Academia Nacional de Medicina, Rio de Janeiro, RJ, Brazil
- Departamento de Psiquiatria, UNIFESP, São Paulo, SP, Brazil
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41
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Resting-state functional connectivity of salience network in schizophrenia and depression. Sci Rep 2022; 12:11204. [PMID: 35778603 PMCID: PMC9249853 DOI: 10.1038/s41598-022-15489-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 06/24/2022] [Indexed: 11/08/2022] Open
Abstract
To explore the salience network (SN) functional alterations in schizophrenia and depression, resting-state functional magnetic resonance imaging (rs-fMRI) data from 29 patients with schizophrenia (SCH), 28 patients with depression (DEP) and 30 healthy controls (HC) were obtained. The SN was derived from data-driven group independent component analysis (gICA). ANCOVA and post hoc tests were performed to discover the FC differences of SN between groups. The ANCOVA demonstrated a significant group effect in FC with right inferior and middle temporal gyrus (ITG and MTG), left caudate, and right precentral gyrus. Post-hoc analyses revealed an opposite altered FC pattern between SN and right ITG and MTG for both patient groups. The DEP group showed a reduced FC between SN and right ITG and MTG compared with HC whereas the SCH group showed an increased FC. In addition, the SCH group showed decreased FC between SN and left caudate, and enhanced FC between SN and right precentral gyrus compared to the other two groups. Our findings suggest distinct FC of SN in schizophrenia and depression, supporting that the resting-state FC pattern of SN may be a transdiagnostic difference between depression and schizophrenia and may play a critical role in the pathogenesis of these two disorders.
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Pang Y, Wei Q, Zhao S, Li N, Li Z, Lu F, Pang J, Zhang R, Wang K, Chu C, Tian Y, Wang J. Enhanced default mode network functional connectivity links with electroconvulsive therapy response in major depressive disorder. J Affect Disord 2022; 306:47-54. [PMID: 35304230 DOI: 10.1016/j.jad.2022.03.035] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 01/16/2022] [Accepted: 03/10/2022] [Indexed: 12/22/2022]
Abstract
BACKGROUND Electroconvulsive therapy (ECT) is an effective neuromodulatory treatment for major depressive disorder (MDD), especially for cases resistant to antidepressant drugs. While the precise mechanisms underlying ECT efficacy are still unclear, it is speculated that ECT modulates brain connectivity. The current study aimed to investigate the longitudinal effects of ECT on resting-state functional connectivity (FC) in MDD patients and test if baseline FC can be used to predict therapeutic response. METHOD Resting-state functional magnetic resonance imaging data were collected at baseline and following ECT from 33 MDD patients. Whole-brain multi-voxel pattern analysis (MVPA) and region of interest-wise FC analysis were employed to fully investigate ECT effects on brain connectivity. Linear support vector regression was further utilized to predict the improvement in depressive symptoms based on baseline connectivity. RESULTS MVPA revealed a significant ECT effect on FC in the default mode network (DMN), central executive network (CEN), sensorimotor network (SMN), and cerebellar posterior lobe. The FCs within the DMN and between DMN and CEN were enhanced in patients after ECT, and the changed FC between the medial prefrontal cortex and ventrolateral prefrontal cortex was negatively correlated with depressive symptom improvement. Moreover, baseline FC within the DMN and between the DMN and CEN could effectively predict the improvement of depressive symptoms. CONCLUSIONS The findings suggest that the FCs within the DMN and between DMN and CEN may be critical therapeutic targets for effective antidepressant treatment as well as neuromarkers for predicting treatment response.
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Affiliation(s)
- Yajing Pang
- School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China
| | - Qiang Wei
- Department of Neurology, The First Hospital of Anhui Medical University, Hefei 230022, China
| | - Shanshan Zhao
- School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China
| | - Nan Li
- School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China
| | - Zhihui Li
- School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China
| | - 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 610054, China
| | - Jianyue Pang
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Rui Zhang
- School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China
| | - Kai Wang
- Department of Neurology, The First Hospital of Anhui Medical University, Hefei 230022, China
| | - Congying Chu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; China National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
| | - Yanghua Tian
- Department of Neurology, The First Hospital of Anhui Medical University, Hefei 230022, China.
| | - Jiaojian Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan, 650500, China.
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43
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Yamashita KI, Uehara T, Taniwaki Y, Tobimatsu S, Kira JI. Long-Term Effect of Acetylcholinesterase Inhibitors on the Dorsal Attention Network of Alzheimer’s Disease Patients: A Pilot Study Using Resting-State Functional Magnetic Resonance Imaging. Front Aging Neurosci 2022; 14:810206. [PMID: 35450059 PMCID: PMC9016195 DOI: 10.3389/fnagi.2022.810206] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Accepted: 03/11/2022] [Indexed: 11/16/2022] Open
Abstract
Background Alzheimer’s disease (AD) is the most common condition of all neurodegenerative diseases and is characterized by various cognitive dysfunctions. Recent resting-state functional magnetic resonance imaging (rs-fMRI) studies have revealed the physiological dynamics of functionally connected brain networks, which are called resting-state networks (RSNs). Associations between impairments of RSNs and various neuropsychiatric diseases, such as AD, have been reported. Acetylcholinesterase inhibitors (AChEIs) have been used as a pharmacological treatment for mild-to-moderate moderate AD, and short-term improvements in cognitive functions and RSNs in restricted areas have been reported. Objective We aimed to characterize AChEI-related RSN changes by acquiring two sets of rs-fMRI data separated by approximately 3 to 6 months. Methods Seventeen patients with AD and nine healthy subjects participated in this study. Independent component analysis was performed on the rs-fMRI data of AChEI-responsive and non-responsive AD patients, stratified according to change in Mini-Mental State Examination (MMSE) scores after 3 to 6 months of AChEI therapy. In addition, a region of interest-based analysis of the rs-fMRI data before therapy was performed to explore the functional connectivity (FC) changes associated with AchEI therapy. Results Responders showed a significantly greater increase in MMSE scores, especially for orientation for time, than that of non-responders following AChEI therapy. A subtraction map of MMSE score differences (responders minus non-responders) in the independent component analysis revealed higher FC of the dorsal attention network in responders compared with that in non-responders. Moreover, in the region of interest analysis of untreated status data, the dorsal attention network showed significant negative FC with the right planum temporale, which belongs to the ventral attention network, proportional to MMSE score change. Conclusion The negative correlation of the FC of the dorsal attention network and right planum temporale before AChEI therapy and MMSE score change may be a biomarker of the therapeutic effect of AChEIs for AD.
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Affiliation(s)
- Ken-ichiro Yamashita
- Translational Neuroscience Center, Graduate School of Medicine, International University of Health and Welfare, Otawara, Japan
- Department of Neurology, Brain and Nerve Center, Fukuoka Central Hospital, Fukuoka, Japan
- *Correspondence: Ken-ichiro Yamashita,
| | - Taira Uehara
- Department of Neurology, International University of Health and Welfare Narita Hospital, Chiba, Japan
| | | | - Shozo Tobimatsu
- Department of Orthoptics, Faculty of Medicine, Fukuoka International University of Health and Welfare, Fukuoka, Japan
| | - Jun-ichi Kira
- Translational Neuroscience Center, Graduate School of Medicine, International University of Health and Welfare, Otawara, Japan
- Department of Neurology, Brain and Nerve Center, Fukuoka Central Hospital, Fukuoka, Japan
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Keatch C, Lambert E, Woods W, Kameneva T. Measuring Brain Response to Transcutaneous Vagus Nerve Stimulation (tVNS) using Simultaneous Magnetoencephalography (MEG). J Neural Eng 2022; 19. [DOI: 10.1088/1741-2552/ac620c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 03/28/2022] [Indexed: 11/12/2022]
Abstract
Abstract
Objective: Transcutaneous vagus nerve stimulation (tVNS) is form of non-invasive brain stimulation that delivers a sequence of electrical pulses to the auricular branch of the vagus nerve, and is used increasingly in the treatment of a number of health conditions such as epilepsy and depression. Recent research has focused on the efficacy of tVNS to treat different medical conditions, but there is little conclusive evidence concerning the optimal stimulation parameters.There are relatively few studies that have combined tVNS with a neuroimaging modality, and none that have attempted simultaneous magnetoencephalography (MEG) and tVNS due to the presence of large stimulation artifacts produced by the electrical stimulation which are many orders of magnitude larger than underlying brain activity. Approach: The aim of this study is to investigate the utility of MEG to gain insight into the regions of the brain most strongly influenced by tVNS and how variation of the stimulation parameters can affect this response in healthy participants. Main Results: We have successfully demonstrated that MEG can be used to measure brain response to tVNS. We have also shown that varying the stimulation frequency can lead to a difference in brain response, with the brain also responding in different anatomical regions depending on the frequency. Significance: The main contribution of this paper is to demonstrate the feasibility of simultaneous pulsed tVNS and MEG recording, allowing direct investigation of the changes in brain activity that result from different stimulation parameters. This may lead to the development of customised therapeutic approaches for the targeted treatment of different conditions.
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Bauer LG, Hirsch F, Jones C, Hollander M, Grohs P, Anand A, Plant C, Wohlschläger A. Quantification of Kuramoto Coupling Between Intrinsic Brain Networks Applied to fMRI Data in Major Depressive Disorder. Front Comput Neurosci 2022; 16:729556. [PMID: 35311219 PMCID: PMC8929174 DOI: 10.3389/fncom.2022.729556] [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: 06/23/2021] [Accepted: 01/28/2022] [Indexed: 11/13/2022] Open
Abstract
Organized patterns of system-wide neural activity adapt fluently within the brain to adjust behavioral performance to environmental demands. In major depressive disorder (MD), markedly different co-activation patterns across the brain emerge from a rather similar structural substrate. Despite the application of advanced methods to describe the functional architecture, e.g., between intrinsic brain networks (IBNs), the underlying mechanisms mediating these differences remain elusive. Here we propose a novel complementary approach for quantifying the functional relations between IBNs based on the Kuramoto model. We directly estimate the Kuramoto coupling parameters (K) from IBN time courses derived from empirical fMRI data in 24 MD patients and 24 healthy controls. We find a large pattern with a significant number of Ks depending on the disease severity score Hamilton D, as assessed by permutation testing. We successfully reproduced the dependency in an independent test data set of 44 MD patients and 37 healthy controls. Comparing the results to functional connectivity from partial correlations (FC), to phase synchrony (PS) as well as to first order auto-regressive measures (AR) between the same IBNs did not show similar correlations. In subsequent validation experiments with artificial data we find that a ground truth of parametric dependencies on artificial regressors can be recovered. The results indicate that the calculation of Ks can be a useful addition to standard methods of quantifying the brain's functional architecture.
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Affiliation(s)
- Lena G. Bauer
- Research Network Data Science, University of Vienna, Vienna, Austria
| | - Fabian Hirsch
- Departement of Neuroradiology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
- TUMNIC, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Corey Jones
- Departement of Neuroradiology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
- TUMNIC, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Matthew Hollander
- Departement of Neuroradiology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
- TUMNIC, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Philipp Grohs
- Research Network Data Science, University of Vienna, Vienna, Austria
- Faculty of Mathematics, University of Vienna, Vienna, Austria
| | - Amit Anand
- Center for Behavioral Health, Cleveland Clinic, Cleveland, OH, United States
| | - Claudia Plant
- Research Network Data Science, University of Vienna, Vienna, Austria
- Faculty of Computer Science, University of Vienna, Vienna, Austria
| | - Afra Wohlschläger
- Departement of Neuroradiology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
- TUMNIC, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
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MVS-GCN: A prior brain structure learning-guided multi-view graph convolution network for autism spectrum disorder diagnosis. Comput Biol Med 2022; 142:105239. [DOI: 10.1016/j.compbiomed.2022.105239] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 01/13/2022] [Accepted: 01/16/2022] [Indexed: 11/22/2022]
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Stress and its sequelae: An active inference account of the etiological pathway from allostatic overload to depression. Neurosci Biobehav Rev 2022; 135:104590. [DOI: 10.1016/j.neubiorev.2022.104590] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 01/06/2022] [Accepted: 02/16/2022] [Indexed: 12/28/2022]
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48
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Tang S, Wu Z, Cao H, Chen X, Wu G, Tan W, Liu D, Yang J, Long Y, Liu Z. Age-Related Decrease in Default-Mode Network Functional Connectivity Is Accelerated in Patients With Major Depressive Disorder. Front Aging Neurosci 2022; 13:809853. [PMID: 35082661 PMCID: PMC8785895 DOI: 10.3389/fnagi.2021.809853] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 12/20/2021] [Indexed: 12/14/2022] Open
Abstract
Major depressive disorder (MDD) is a common psychiatric disorder which is associated with an accelerated biological aging. However, little is known whether such process would be reflected by a more rapid aging of the brain function. In this study, we tested the hypothesis that MDD would be characterized by accelerated aging of the brain's default-mode network (DMN) functions. Resting-state functional magnetic resonance imaging data of 971 MDD patients and 902 healthy controls (HCs) was analyzed, which was drawn from a publicly accessible, multicenter dataset in China. Strength of functional connectivity (FC) and temporal variability of dynamic functional connectivity (dFC) within the DMN were calculated. Age-related effects on FC/dFC were estimated by linear regression models with age, diagnosis, and diagnosis-by-age interaction as variables of interest, controlling for sex, education, site, and head motion effects. The regression models revealed (1) a significant main effect of age in the predictions of both FC strength and dFC variability; and (2) a significant main effect of diagnosis and a significant diagnosis-by-age interaction in the prediction of FC strength, which was driven by stronger negative correlation between age and FC strength in MDD patients. Our results suggest that (1) both healthy participants and MDD patients experience decrease in DMN FC strength and increase in DMN dFC variability along age; and (2) age-related decrease in DMN FC strength may occur at a faster rate in MDD patients than in HCs. However, further longitudinal studies are still needed to understand the causation between MDD and accelerated aging of brain.
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Affiliation(s)
- Shixiong Tang
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
- Clinical Research Center for Medical Imaging in Hunan Province, Changsha, China
| | - Zhipeng Wu
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Hengyi Cao
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, United States
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, United States
| | - Xudong Chen
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Guowei Wu
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Wenjian Tan
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Dayi Liu
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Jie Yang
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Yicheng Long
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Zhening Liu
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
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49
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Foo H, Thalamuthu A, Jiang J, Koch F, Mather KA, Wen W, Sachdev PS. Age- and Sex-Related Topological Organization of Human Brain Functional Networks and Their Relationship to Cognition. Front Aging Neurosci 2022; 13:758817. [PMID: 34975453 PMCID: PMC8718995 DOI: 10.3389/fnagi.2021.758817] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Accepted: 11/25/2021] [Indexed: 11/23/2022] Open
Abstract
Age and sex associated with changes in the functional brain network topology and cognition in large population of older adults have been poorly understood. We explored this question further by examining differences in 11 resting-state graph theory measures with respect to age, sex, and their relationships with cognitive performance in 17,127 United Kingdom Biobank participants (mean = 62.83 ± 7.41 years). Age was associated with an overall decrease in the effectiveness of network communication (i.e., integration) and loss of functional specialization (i.e., segregation) of specific brain regions. Sex differences were also observed, with women showing more efficient networks, which were less segregated than in men (FDR adjusted p < 0.05). The age-related changes were also more apparent in men than in women, which suggests that men may be more vulnerable to cognitive decline with age. Interestingly, while network segregation and strength of limbic network were only nominally associated with cognitive performance, the network measures collectively were significantly associated with cognition (FDR adjusted p ≤ 0.002). This may imply that individual measures may be inadequate to capture much of the variance in the neural activity or its output and need further refinement. The complexity of the organization of the functional brain may be shaped by the age and sex of an individual, which ultimately may influence the cognitive performance of older adults. Age and sex stratification may be used to inform clinical neuroscience research to identify older adults at risk of cognitive dysfunction.
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Affiliation(s)
- Heidi Foo
- Centre for Healthy Brain Aging, CHeBA, School of Psychiatry, University of New South Wales Medicine, Kensington, NSW, Australia
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Aging, CHeBA, School of Psychiatry, University of New South Wales Medicine, Kensington, NSW, Australia
| | - Jiyang Jiang
- Centre for Healthy Brain Aging, CHeBA, School of Psychiatry, University of New South Wales Medicine, Kensington, NSW, Australia
| | - Forrest Koch
- Centre for Healthy Brain Aging, CHeBA, School of Psychiatry, University of New South Wales Medicine, Kensington, NSW, Australia
| | - Karen A Mather
- Centre for Healthy Brain Aging, CHeBA, School of Psychiatry, University of New South Wales Medicine, Kensington, NSW, Australia.,Neuroscience Research Australia, Randwick, NSW, Australia
| | - Wei Wen
- Centre for Healthy Brain Aging, CHeBA, School of Psychiatry, University of New South Wales Medicine, Kensington, NSW, Australia
| | - Perminder S Sachdev
- Centre for Healthy Brain Aging, CHeBA, School of Psychiatry, University of New South Wales Medicine, Kensington, NSW, Australia.,Neuropsychiatric Institute, Euroa Centre, Prince of Wales Hospital, Randwick, NSW, Australia
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50
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Zilcha‐Mano S, Zhu X, Lazarov A, Suarez‐Jimenez B, Helpman L, Kim Y, Maitlin C, Neria Y, Rutherford BR. Structural brain features signaling trauma, PTSD, or resilience? A systematic exploration. Depress Anxiety 2022; 39:695-705. [PMID: 35708133 PMCID: PMC9588504 DOI: 10.1002/da.23275] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Revised: 04/15/2022] [Accepted: 05/30/2022] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND Studies have searched for neurobiological markers of trauma exposure, posttraumatic stress disorder (PTSD) diagnosis, and resilience to trauma to identify therapeutic targets for PTSD. Despite some promising results, findings are inconsistent. AIMS The present study adopted a data-driven approach to systematically explore whether structural brain markers of trauma, PTSD, or resilience emerge when all are explored. MATERIALS & METHODS Differences between clusters in the proportion of PTSD, healthy controls (HC), and trauma-exposed healthy controls (TEHC) served to indicate the presence of PTSD, trauma, and resilience markers, respectively. A total of 129 individuals, including 46 with PTSD, 49 TEHCs, and 34 HCs not exposed to trauma were scanned. Volumes, cortical thickness, and surface areas of interest were obtained from T1 structural MRI and used to identify data-driven clusters. RESULTS Two clusters were identified, differing in the proportion of TEHCs but not of PTSDs or HCs. The cluster with the higher proportion of TEHCs, referred to as the resilience cluster, was characterized by higher volume in brain regions implicated in trauma exposure, especially the thalamus and rostral middle frontal gyrus. Cross-validation established the robustness and consistency of the identified clusters. DISCUSSION & CONCLUSION Findings support the existence of structural brain markers of resilience.
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Affiliation(s)
| | - Xi Zhu
- Department of PsychiatryColumbia UniversityNew YorkNew YorkUSA,New York State Psychiatric Institute, Columbia University Medical CenterNew YorkNew YorkUSA
| | - Amit Lazarov
- School of Psychological SciencesTel‐Aviv UniversityTel‐AvivIsrael,Department of PsychiatryColumbia University Medical CenterNew YorkNew YorkUSA
| | - Benjamin Suarez‐Jimenez
- New York State Psychiatric Institute, Columbia University Medical CenterNew YorkNew YorkUSA,Department of NeuroscienceUniversity of RochesterRochesterNew YorkUSA
| | - Liat Helpman
- Department of Counseling and Human DevelopmentUniversity of HaifaMount CarmelHaifaIsrael,Tel Aviv Sourasky Medical CenterTel AvivIsrael
| | - Yoojean Kim
- Department of PsychiatryColumbia UniversityNew YorkNew YorkUSA,New York State Psychiatric Institute, Columbia University Medical CenterNew YorkNew YorkUSA
| | - Carly Maitlin
- Department of PsychiatryColumbia UniversityNew YorkNew YorkUSA,New York State Psychiatric Institute, Columbia University Medical CenterNew YorkNew YorkUSA
| | - Yuval Neria
- Department of PsychiatryColumbia UniversityNew YorkNew YorkUSA,New York State Psychiatric Institute, Columbia University Medical CenterNew YorkNew YorkUSA
| | - Bret R. Rutherford
- Columbia University College of Physicians and Surgeons, New York State Psychiatric InstituteNew York CityNew YorkUSA
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