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Buck Z, Michalchyshyn E, Nishat A, Lisi M, Huang Y, Liu H, Makarenka A, Plyngam CP, Windle A, Yang Z, Walther DB. Aesthetic processing in neurodiverse populations. Neurosci Biobehav Rev 2024; 166:105878. [PMID: 39260715 DOI: 10.1016/j.neubiorev.2024.105878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2024] [Revised: 08/07/2024] [Accepted: 09/05/2024] [Indexed: 09/13/2024]
Abstract
Neurodiversity is a perspective on cognition which suggests a non-pathological view of individual cognitive differences. Aesthetics research on neurodivergent brains has generally been limited to neuropsychological cases. Although this research has been integral to establishing the neurological correlates of aesthetic experience, it is crucial to expand this paradigm to more psychologically complex disorders. We offer a review of research on aesthetic preference in neurodivergent brains beyond neuropsychological cases: across populations with psychotic disorder, anhedonia and depression, anxiety disorder, and autism. We identify stable patterns of aesthetic bias in these populations, relate these biases to symptoms at perceptual, emotional, and evaluative levels of cognition, review relevant neurological correlates, and connect this evidence to current neuroaesthetics theory. Critically, we synthesize the reviewed evidence and discuss its relevance for three brain networks regularly implicated in aesthetic processing: the mesocorticolimbic reward circuit, frontolimbic connections, and the default mode network. Finally, we propose that broadening the subject populations for neuroaesthetics research to include neurodiverse populations is instrumental for yielding new insights into aesthetic processing in the brain.
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Affiliation(s)
- Zach Buck
- Department of Psychology, University of Toronto, Toronto, Canada
| | | | - Amna Nishat
- Department of Psychology, University of Toronto, Toronto, Canada
| | - Mikayla Lisi
- Department of Psychology, University of Toronto, Toronto, Canada
| | - Yichen Huang
- Department of Psychology, University of Toronto, Toronto, Canada
| | - Hanyu Liu
- Department of Psychology, University of Toronto, Toronto, Canada
| | - Arina Makarenka
- Department of Psychology, University of Toronto, Toronto, Canada
| | | | - Abigail Windle
- Department of Psychology, University of Toronto, Toronto, Canada
| | - Zhen Yang
- Department of Psychology, University of Toronto, Toronto, Canada
| | - Dirk B Walther
- Department of Psychology, University of Toronto, Toronto, Canada.
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Kokce A, Can MŞ, Karaca O, Ozcan E, Kuş İ. Atlas-based structural analysis of prefrontal cortex atrophy in major depressive disorder: Correlations with severity and episode frequency. Psychiatry Res Neuroimaging 2024; 344:111885. [PMID: 39217669 DOI: 10.1016/j.pscychresns.2024.111885] [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: 03/11/2024] [Revised: 08/07/2024] [Accepted: 08/26/2024] [Indexed: 09/04/2024]
Abstract
BACKGROUND Current models of major depressive disorder (MDD) primarily focus on the structural and functional changes in key prefrontal areas responsible for emotional regulation. Among these regions some sections such as the dorsal prefrontal area, has received limited attention regarding its structural abnormalities in MDD. This study aims to evaluate volumetric abnormalities in brain regions associated with markers of depression severity and episode frequency. METHODS The study included 33 MDD patients and 33 healthy subjects. Using an atlas-based method, we measured the volumes of several key brain regions based on MRI data. The regions of interest included prefrontal and posterior sections of the middle frontal gyrus (MFG) and superior frontal gyrus (SFG). Additionally, we evaluated the volumes of the dorsal anterior cingulate cortex (dACC), perigenual (rostral) anterior cingulate cortex (pgACC), subgenual cingulate cortex (sgACC), posterior cingulate cortex (PCC), hippocampus (HPC), and parahippocampus (paraHPC). Hamilton Depression Scale (HAM-D) scores and count of the depressive episodes of patients were also obtained. A regression analysis with sex as the confounding factor has been made. RESULTS Analysis of covariances, controlling for sex, showed significant atrophy in the sgACC in the depression group: F(1, 63) = 4.013, p = 0.049 (left) and F(1, 63) = 8.786, p < 0.004 (right). Poisson regression, also controlling for sex, found that each additional depressive episode was associated with a significant reduction in left posterior MFG volume (0.952 times, 95 % CI, 0.906 to 1.000; p = 0.049). CONCLUSIONS Findings in this study highlight the structural abnormalities in MDD patients in correlation to either current depression severity or chronicity of the disease.
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Affiliation(s)
- Aybars Kokce
- Eskisehir Osmangazi University, Faculty of Medicine, Department of Anatomy, 26040, Eskisehir, Turkey.
| | - Merve Şahin Can
- Balikesir University, Cagis Yerleskesi, Faculty of Medicine, Department of Psychiatry, 10145, Balıkesir, Turkey.
| | - Omur Karaca
- Balikesir University, Cagis Yerleskesi, Faculty of Medicine, Department of Anatomy, 10145, Balıkesir, Turkey.
| | - Emrah Ozcan
- Balikesir University, Cagis Yerleskesi, Faculty of Medicine, Department of Anatomy, 10145, Balıkesir, Turkey.
| | - İlter Kuş
- Balikesir University, Cagis Yerleskesi, Faculty of Medicine, Department of Anatomy, 10145, Balıkesir, Turkey.
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Kawakami S, Okada N, Satomura Y, Shoji E, Mori S, Kiyota M, Omileke F, Hamamoto Y, Morita S, Koshiyama D, Yamagishi M, Sakakibara E, Koike S, Kasai K. Frontal pole-precuneus connectivity is associated with a discrepancy between self-rated and observer-rated depression severity in mood disorders: a resting-state functional magnetic resonance imaging study. Cereb Cortex 2024; 34:bhae284. [PMID: 39049465 PMCID: PMC11269430 DOI: 10.1093/cercor/bhae284] [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: 02/08/2024] [Revised: 06/10/2024] [Accepted: 07/03/2024] [Indexed: 07/27/2024] Open
Abstract
Discrepancies in self-rated and observer-rated depression severity may underlie the basis for biological heterogeneity in depressive disorders and be an important predictor of outcomes and indicators to optimize intervention strategies. However, the neural mechanisms underlying this discrepancy have been understudied. This study aimed to examine the brain networks that represent the neural basis of the discrepancy between self-rated and observer-rated depression severity using resting-state functional MRI. To examine the discrepancy between self-rated and observer-rated depression severity, self- and observer-ratings discrepancy (SOD) was defined, and the higher and lower SOD groups were selected from depressed patients as participants showing extreme deviation. Resting-state functional MRI analysis was performed to examine regions with significant differences in functional connectivity in the two groups. The results showed that, in the higher SOD group compared to the lower SOD group, there was increased functional connectivity between the frontal pole and precuneus, both of which are subregions of the default mode network that have been reported to be associated with ruminative and self-referential thinking. These results provide insight into the association of brain circuitry with discrepancies between self- and observer-rated depression severity and may lead to more treatment-oriented diagnostic reclassification in the future.
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Affiliation(s)
- Shintaro Kawakami
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Naohiro Okada
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
- The International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo Institutes for Advanced Study (UTIAS), 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Yoshihiro Satomura
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
- Center for Diversity in Medical Education and Research (CDMER), Graduate School of Medicine and Faculty of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Eimu Shoji
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Shunsuke Mori
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Masahiro Kiyota
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Favour Omileke
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Yu Hamamoto
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Susumu Morita
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Daisuke Koshiyama
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Mika Yamagishi
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Eisuke Sakakibara
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Shinsuke Koike
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
- The International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo Institutes for Advanced Study (UTIAS), 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
- University of Tokyo Institute for Diversity & Adaptation of Human Mind (UTIDAHM), 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan
- Center for Evolutionary Cognitive Sciences, Graduate School of Art and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan
| | - Kiyoto Kasai
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
- The International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo Institutes for Advanced Study (UTIAS), 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
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Yang T, Ou Y, Li H, Liu F, Li P, Xie G, Zhao J, Cui X, Guo W. Neural substrates of predicting anhedonia symptoms in major depressive disorder via connectome-based modeling. CNS Neurosci Ther 2024; 30:e14871. [PMID: 39037006 PMCID: PMC11261463 DOI: 10.1111/cns.14871] [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: 12/19/2023] [Revised: 06/23/2024] [Accepted: 07/09/2024] [Indexed: 07/23/2024] Open
Abstract
MAIN PROBLEM Anhedonia is a critical diagnostic symptom of major depressive disorder (MDD), being associated with poor prognosis. Understanding the neural mechanisms underlying anhedonia is of great significance for individuals with MDD, and it encourages the search for objective indicators that can reliably identify anhedonia. METHODS A predictive model used connectome-based predictive modeling (CPM) for anhedonia symptoms was developed by utilizing pre-treatment functional connectivity (FC) data from 59 patients with MDD. Node-based FC analysis was employed to compare differences in FC patterns between melancholic and non-melancholic MDD patients. The support vector machines (SVM) method was then applied for classifying these two subtypes of MDD patients. RESULTS CPM could successfully predict anhedonia symptoms in MDD patients (positive network: r = 0.4719, p < 0.0020, mean squared error = 23.5125, 5000 iterations). Compared to non-melancholic MDD patients, melancholic MDD patients showed decreased FC between the left cingulate gyrus and the right parahippocampus gyrus (p_bonferroni = 0.0303). This distinct FC pattern effectively discriminated between melancholic and non-melancholic MDD patients, achieving a sensitivity of 93.54%, specificity of 67.86%, and an overall accuracy of 81.36% using the SVM method. CONCLUSIONS This study successfully established a network model for predicting anhedonia symptoms in MDD based on FC, as well as a classification model to differentiate between melancholic and non-melancholic MDD patients. These findings provide guidance for clinical treatment.
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Affiliation(s)
- Tingyu Yang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental DisordersThe Second Xiangya Hospital of Central South UniversityChangshaChina
- Department of Child HealthcareHunan Children's HospitalChangshaChina
| | - Yangpan Ou
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental DisordersThe Second Xiangya Hospital of Central South UniversityChangshaChina
| | - Huabing Li
- Department of RadiologyThe Second Xiangya Hospital of Central South UniversityChangshaChina
| | - Feng Liu
- Department of RadiologyTianjin Medical University General HospitalTianjinChina
| | - Ping Li
- Department of PsychiatryQiqihar Medical UniversityQiqiharChina
| | - Guangrong Xie
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental DisordersThe Second Xiangya Hospital of Central South UniversityChangshaChina
| | - Jingping Zhao
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental DisordersThe Second Xiangya Hospital of Central South UniversityChangshaChina
| | - Xilong Cui
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental DisordersThe Second Xiangya Hospital of Central South UniversityChangshaChina
| | - Wenbin Guo
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental DisordersThe Second Xiangya Hospital of Central South UniversityChangshaChina
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Gao Y, Feng R, Ouyang X, Zhou Z, Bao W, Li Y, Zhuo L, Hu X, Li H, Zhang L, Huang G, Huang X. Multivariate association between psychosocial environment, behaviors, and brain functional networks in adolescent depression. Asian J Psychiatr 2024; 95:104009. [PMID: 38520945 DOI: 10.1016/j.ajp.2024.104009] [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: 11/07/2023] [Revised: 02/06/2024] [Accepted: 03/17/2024] [Indexed: 03/25/2024]
Abstract
BACKGROUND Adolescent depression shows high clinical heterogeneity. Brain functional networks serve as a powerful tool for investigating neural mechanisms underlying depression profiles. A key challenge is to characterize how variation in brain functional organization links to behavioral features and psychosocial environmental influences. METHODS We recruited 80 adolescents with major depressive disorder (MDD) and 42 healthy controls (HCs). First, we estimated the differences in functional connectivity of resting-state networks (RSN) between the two groups. Then, we used sparse canonical correlation analysis to characterize patterns of associations between RSN connectivity and symptoms, cognition, and psychosocial environmental factors in MDD adolescents. Clustering analysis was applied to stratify patients into homogenous subtypes according to these brain-behavior-environment associations. RESULTS MDD adolescents showed significantly hyperconnectivity between the ventral attention and cingulo-opercular networks compared with HCs. We identified one reliable pattern of covariation between RSN connectivity and clinical/environmental features in MDD adolescents. In this pattern, psychosocial factors, especially the interpersonal and family relationships, were major contributors to variation in connectivity of salience, cingulo-opercular, ventral attention, subcortical and somatosensory-motor networks. Based on this association, we categorized patients into two subgroups which showed different environment and symptoms characteristics, and distinct connectivity alterations. These differences were covered up when the patients were taken as a whole group. CONCLUSION This study identified the environmental exposures associated with specific functional networks in MDD youths. Our findings emphasize the importance of the psychosocial context in assessing brain function alterations in adolescent depression and have the potential to promote targeted treatment and precise prevention.
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Affiliation(s)
- Yingxue Gao
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China
| | - Ruohan Feng
- Department of Radiology, the Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China
| | - Xinqin Ouyang
- Department of Radiology, the Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China
| | - Zilin Zhou
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China
| | - Weijie Bao
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China
| | - Yang Li
- Department of Psychiatry, the Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China
| | - Lihua Zhuo
- Department of Radiology, the Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China
| | - Xinyue Hu
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China
| | - Hailong Li
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China
| | - Lianqing Zhang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China
| | - Guoping Huang
- Department of Psychiatry, the Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China
| | - Xiaoqi Huang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China; The Xiaman Key Lab of psychoradiology and neuromodulation, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China.
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Ding H, Zhang Q, Shu YP, Tian B, Peng J, Hou YZ, Wu G, Lin LY, Li JL. Vulnerable brain regions in adolescent major depressive disorder: A resting-state functional magnetic resonance imaging activation likelihood estimation meta-analysis. World J Psychiatry 2024; 14:456-466. [PMID: 38617984 PMCID: PMC11008390 DOI: 10.5498/wjp.v14.i3.456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 02/04/2024] [Accepted: 03/06/2024] [Indexed: 03/19/2024] Open
Abstract
BACKGROUND Adolescent major depressive disorder (MDD) is a significant mental health concern that often leads to recurrent depression in adulthood. Resting-state functional magnetic resonance imaging (rs-fMRI) offers unique insights into the neural mechanisms underlying this condition. However, despite previous research, the specific vulnerable brain regions affected in adolescent MDD patients have not been fully elucidated. AIM To identify consistent vulnerable brain regions in adolescent MDD patients using rs-fMRI and activation likelihood estimation (ALE) meta-analysis. METHODS We performed a comprehensive literature search through July 12, 2023, for studies investigating brain functional changes in adolescent MDD patients. We utilized regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF) and fractional ALFF (fALFF) analyses. We compared the regions of aberrant spontaneous neural activity in adolescents with MDD vs healthy controls (HCs) using ALE. RESULTS Ten studies (369 adolescent MDD patients and 313 HCs) were included. Combining the ReHo and ALFF/fALFF data, the results revealed that the activity in the right cuneus and left precuneus was lower in the adolescent MDD patients than in the HCs (voxel size: 648 mm3, P < 0.05), and no brain region exhibited increased activity. Based on the ALFF data, we found decreased activity in the right cuneus and left precuneus in adolescent MDD patients (voxel size: 736 mm3, P < 0.05), with no regions exhibiting increased activity. CONCLUSION Through ALE meta-analysis, we consistently identified the right cuneus and left precuneus as vulnerable brain regions in adolescent MDD patients, increasing our understanding of the neuropathology of affected adolescents.
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Affiliation(s)
- Hui Ding
- Department of Radiology, The Second People’s Hospital of Guizhou Province, Guiyang 550000, Guizhou Province, China
| | - Qin Zhang
- Department of Radiology, The Second People’s Hospital of Guizhou Province, Guiyang 550000, Guizhou Province, China
- Department of Radiology, Guizhou Provincial People’s Hospital, Guiyang 550000, Guizhou Province, China
| | - Yan-Ping Shu
- Department of Psychiatry of Women and Children, The Second People's Hospital of Guizhou Province, Guiyang 550000, Guizhou Province, China
| | - Bin Tian
- Department of Radiology, The Second People’s Hospital of Guizhou Province, Guiyang 550000, Guizhou Province, China
| | - Ji Peng
- Department of Radiology, The Second People’s Hospital of Guizhou Province, Guiyang 550000, Guizhou Province, China
| | - Yong-Zhe Hou
- Department of Psychiatry of Women and Children, The Second People's Hospital of Guizhou Province, Guiyang 550000, Guizhou Province, China
| | - Gang Wu
- Department of Psychiatry of Women and Children, The Second People's Hospital of Guizhou Province, Guiyang 550000, Guizhou Province, China
| | - Li-Yun Lin
- Department of Radiology, Zhijin County People's Hospital, Bijie 552100, Guizhou Province, China
| | - Jia-Lin Li
- Medical Humanities College, Guizhou Medical University, Guiyang 550000, Guizhou Province, China
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Wang X, Zhou X, Li J, Gong Y, Feng Z. A feasibility study of goal-directed network-based real-time fMRI neurofeedback for anhedonic depression. Front Psychiatry 2023; 14:1253727. [PMID: 38125285 PMCID: PMC10732355 DOI: 10.3389/fpsyt.2023.1253727] [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: 07/07/2023] [Accepted: 11/06/2023] [Indexed: 12/23/2023] Open
Abstract
Anhedonia is a hallmark symptom of depression that often lacks adequate interventions. The translational gap remains in clinical treatments based on neural substrates of anhedonia. Our pilot study found that depressed individuals depended less on goal-directed (GD) reward learning (RL), with reduced reward prediction error (RPE) BOLD signal. Previous studies have found that anhedonia is related to abnormal activities and/or functional connectivities of the central executive network (CEN) and salience network (SN), both of which belong to the goal-directed system. In addition, it was found that real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback (NF) could improve the balance between CEN and SN in healthy individuals. Therefore, we speculate that rt-fMRI NF of the CEN and SN associated with the GD system may improve depressive and/or anhedonic symptoms. Therefore, this study (1) will examine individuals with anhedonic depression using GD-RL behavioral task, combined with functional magnetic resonance imaging and computational modeling to explore the role of CEN/SN deficits in anhedonic depression; and (2) will utilize network-based rt-fMRI NF to investigate whether it is feasible to regulate the differential signals of brain CEN/SN of GD system through rt-fMRI NF to alleviate depressive and/or anhedonic symptoms. This study highlights the need to elucidate the intervention effects of rt-fMRI NF and the underlying computational network neural mechanisms.
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Affiliation(s)
- Xiaoxia Wang
- Department of Basic Psychology, School of Psychology, Army Medical University, Chongqing, China
| | - Xiaoyan Zhou
- Chongqing City Mental Health Center, Southwest University, Chongqing, China
| | - Jing Li
- Department of Radiology, Southwest Hospital, Army Medical University, Chongqing, China
| | - Yushun Gong
- Department of Medical Equipment and Metrology, College of Biomedical Engineering, Army Medical University, Chongqing, China
| | - Zhengzhi Feng
- School of Psychology, Army Medical University, Chongqing, China
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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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9
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Zhou Y, Pat N, Neale MC. Associations between resting state functional brain connectivity and childhood anhedonia: A reproduction and replication study. PLoS One 2023; 18:e0277158. [PMID: 37141274 PMCID: PMC10159190 DOI: 10.1371/journal.pone.0277158] [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: 10/21/2022] [Accepted: 02/28/2023] [Indexed: 05/05/2023] Open
Abstract
BACKGROUND Previously, a study using a sample of the Adolescent Brain Cognitive Development (ABCD)® study from the earlier 1.0 release found differences in several resting state functional MRI (rsfMRI) brain connectivity measures associated with children reporting anhedonia. Here, we aim to reproduce, replicate, and extend the previous findings using data from the later ABCD study 4.0 release, which includes a significantly larger sample. METHODS To reproduce and replicate the previous authors' findings, we analyzed data from the ABCD 1.0 release (n = 2437), from an independent subsample from the newer ABCD 4.0 release (excluding individuals from the 1.0 release) (n = 6456), and from the full ABCD 4.0 release sample (n = 8866). Additionally, we assessed whether using a multiple linear regression approach could improve replicability by controlling for the effects of comorbid psychiatric conditions and sociodemographic covariates. RESULTS While the previously reported associations were reproducible, effect sizes for most rsfMRI measures were drastically reduced in replication analyses (including for both t-tests and multiple linear regressions) using the ABCD 4.0 (excluding 1.0) sample. However, 2 new rsfMRI measures (the Auditory vs. Right Putamen and the Retrosplenial-Temporal vs. Right-Thalamus-Proper measures) exhibited replicable associations with anhedonia and stable, albeit small, effect sizes across the ABCD samples, even after accounting for sociodemographic covariates and comorbid psychiatric conditions using a multiple linear regression approach. CONCLUSION The most statistically significant associations between anhedonia and rsfMRI connectivity measures found in the ABCD 1.0 sample tended to be non-replicable and inflated. Contrastingly, replicable associations exhibited smaller effects with less statistical significance in the ABCD 1.0 sample. Multiple linear regressions helped assess the specificity of these findings and control the effects of confounding covariates.
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Affiliation(s)
- Yi Zhou
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, United States of America
| | - Narun Pat
- Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Michael C. Neale
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, United States of America
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10
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Son JJ, Schantell M, Picci G, Wang YP, Stephen JM, Calhoun VD, Doucet GE, Taylor BK, Wilson TW. Altered longitudinal trajectory of default mode network connectivity in healthy youth with subclinical depressive and posttraumatic stress symptoms. Dev Cogn Neurosci 2023; 60:101216. [PMID: 36857850 PMCID: PMC9986502 DOI: 10.1016/j.dcn.2023.101216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 02/08/2023] [Accepted: 02/14/2023] [Indexed: 02/19/2023] Open
Abstract
The default mode network (DMN) plays a crucial role in internal self-processing, rumination, and social functions. Disruptions to DMN connectivity have been linked with early adversity and the emergence of psychopathology in adolescence and early adulthood. Herein, we investigate how subclinical psychiatric symptoms can impact DMN functional connectivity during the pubertal transition. Resting-state fMRI data were collected annually from 190 typically-developing youth (9-15 years-old) at three timepoints and within-network DMN connectivity was computed. We used latent growth curve modeling to determine how self-reported depressive and posttraumatic stress symptoms predicted rates of change in DMN connectivity over the three-year period. In the baseline model without predictors, we found no systematic changes in DMN connectivity over time. However, significant modulation emerged after adding psychopathology predictors; greater depressive symptomatology was associated with significant decreases in connectivity over time, whereas posttraumatic stress symptoms were associated with significant increases in connectivity over time. Follow-up analyses revealed that these effects were driven by connectivity changes involving the dorsal medial prefrontal cortex subnetwork. In conclusion, these data suggest that subclinical depressive and posttraumatic symptoms alter the trajectory of DMN connectivity, which may indicate that this network is a nexus of clinical significance in mental health disorders.
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Affiliation(s)
- Jake J Son
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA; Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA; College of Medicine, University of Nebraska Medical Center (UNMC), Omaha, NE, USA
| | - Mikki Schantell
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA; Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA; College of Medicine, University of Nebraska Medical Center (UNMC), Omaha, NE, USA
| | - Giorgia Picci
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA; Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Yu-Ping Wang
- Department of Biomedical Engineering, Tulane University, New Orleans, LA, USA
| | | | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of technology, and Emory University, Atlanta, GA, USA
| | - Gaelle E Doucet
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA; Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA; Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, USA
| | - Brittany K Taylor
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA; Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA; Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, USA
| | - Tony W Wilson
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA; Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA; College of Medicine, University of Nebraska Medical Center (UNMC), Omaha, NE, USA; Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, USA.
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11
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Yang X, Kumar P, Wang M, Zhao L, Du Y, Zhang BY, Qi S, Sui J, Li T, Ma X. Antidepressant treatment-related brain activity changes in remitted major depressive disorder. Psychiatry Res Neuroimaging 2023; 330:111601. [PMID: 36724678 DOI: 10.1016/j.pscychresns.2023.111601] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 12/21/2022] [Accepted: 01/24/2023] [Indexed: 01/29/2023]
Abstract
Recent evidence has shown that some brain regions are core hubs and play a key role in the treatment of depression. Twenty-five unmedicated patients with major depressive disorder (MDD) were included, and telephone follow-up was performed at 8, 24, and 48 weeks after enrollment. After reaching clinical remission, they were scheduled for a second magnetic resonance imaging scan and clinical evaluation. Thirty-one healthy controls were also investigated. The intrinsic functional connectivity (degree centrality) of each participant was mapped using a computationally efficient approach. Then, functional connectivity of patients was calculated between the identified regions of interest by degree centrality analysis and every voxel. Later, linear regression analysis was used to identify potential variables predictive of an improvement in disease severity. The prominent hubs identified by degree centrality analysis included the cerebellum, inferior temporal gyrus, lingual gyrus, dorsal medial prefrontal cortex (DMPFC), and dorsal lateral prefrontal cortex. We also found that the increased degree centrality of DMPFC was associated with improvement in depressive symptoms. The brain activity associated with antidepressant effects, especially brain connectivity changes in the left DMPFC, can potentially be used to monitor treatment response and predict treatment outcomes.
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Affiliation(s)
- Xiao Yang
- Psychiatric Laboratory and Mental Health Center, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, 610041, Chengdu, China; Huaxi Brain Research Center, West China Hospital of Sichuan University, 610041, Chengdu, China
| | - Poornima Kumar
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, United States of America; Department of Psychiatry, Harvard Medical School, United States of America
| | - Min Wang
- Psychiatric Laboratory and Mental Health Center, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, 610041, Chengdu, China; Huaxi Brain Research Center, West China Hospital of Sichuan University, 610041, Chengdu, China
| | - Liansheng Zhao
- Psychiatric Laboratory and Mental Health Center, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, 610041, Chengdu, China; Huaxi Brain Research Center, West China Hospital of Sichuan University, 610041, Chengdu, China
| | - Yue Du
- Psychiatric Laboratory and Mental Health Center, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, 610041, Chengdu, China; Huaxi Brain Research Center, West China Hospital of Sichuan University, 610041, Chengdu, China
| | - Belinda Y Zhang
- School of Nursing and Health Professions, University of San Francisco, CA, United States
| | - Shile Qi
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology, Emory University], 30303, Atlanta, GA, United States
| | - Jing Sui
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China; Chinese Academy of Sciences Center for Excellence in Brain Science, Institute of Automation, 100190, Beijing, China
| | - Tao Li
- Psychiatric Laboratory and Mental Health Center, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, 610041, Chengdu, China; Huaxi Brain Research Center, West China Hospital of Sichuan University, 610041, Chengdu, China
| | - Xiaohong Ma
- Psychiatric Laboratory and Mental Health Center, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, 610041, Chengdu, China; Huaxi Brain Research Center, West China Hospital of Sichuan University, 610041, Chengdu, China.
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12
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Yoon L, Rohrsetzer F, Battel L, Anés M, Manfro PH, Rohde LA, Viduani A, Zajkowska Z, Mondelli V, Kieling C, Swartz JR. Frontolimbic Network Topology Associated With Risk and Presence of Depression in Adolescents: A Study Using a Composite Risk Score in Brazil. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:426-435. [PMID: 35358744 DOI: 10.1016/j.bpsc.2022.03.008] [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: 11/02/2021] [Revised: 03/09/2022] [Accepted: 03/20/2022] [Indexed: 11/20/2022]
Abstract
BACKGROUND There have been significant challenges in understanding functional brain connectivity associated with adolescent depression, including the need for a more comprehensive approach to defining risk, the lack of representation of participants from low- and middle-income countries, and the need for network-based approaches to model connectivity. The current study aimed to address these challenges by examining resting-state functional connectivity of frontolimbic circuitry associated with the risk and presence of depression in adolescents in Brazil. METHODS Adolescents in Brazil ages 14 to 16 years were classified into low-risk, high-risk, and depressed groups using a clinical assessment and composite risk score that integrates 11 sociodemographic risk variables. After excluding participants with excessive head movement, resting-state functional magnetic resonance imaging data of 126 adolescents were analyzed. We compared group differences in frontolimbic network connectivity using region of interest-to-region of interest, graph theory, and seed-based connectivity analyses. Associations between self-reported depressive symptoms and brain connectivity were also explored. RESULTS Adolescents with depression showed greater dorsal anterior cingulate cortex (ACC) connectivity with the orbitofrontal cortex compared with the 2 risk groups and greater dorsal ACC global efficiency than the low-risk group. Adolescents with depression also showed reduced local efficiency and a lower clustering coefficient of the subgenual ACC compared with the 2 risk groups. The high-risk group also showed a lower subgenual ACC clustering coefficient relative to the low-risk group. CONCLUSIONS These findings highlight altered connectivity and topology of the ACC within frontolimbic circuitry as potential neural correlates and risk factors of developing depression in adolescents in Brazil. This study broadens our understanding of the neural connectivity associated with adolescent depression in a global context.
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Affiliation(s)
- Leehyun Yoon
- Department of Human Ecology, University of California, Davis, Davis, California
| | - Fernanda Rohrsetzer
- Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Lucas Battel
- Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil; Department of Medicine, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, New York
| | - Mauricio Anés
- Division of Medical Physics and Radioprotection, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil
| | - Pedro H Manfro
- Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Luis A Rohde
- Institute of Developmental Psychiatry for Children and Adolescents, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil; ADHD Outpatient and Developmental Psychiatry Programs, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil
| | - Anna Viduani
- Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Zuzanna Zajkowska
- Institute of Psychiatry, Psychology and Neuroscience, Department of Psychological Medicine, King's College London, London, United Kingdom
| | - Valeria Mondelli
- Institute of Psychiatry, Psychology and Neuroscience, Department of Psychological Medicine, King's College London, London, United Kingdom; National Institute for Health Research Maudsley Biomedical Research Centre, South London and Maudsley National Health Service Foundation Trust, King's College London, London, United Kingdom
| | - Christian Kieling
- Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Johnna R Swartz
- Department of Human Ecology, University of California, Davis, Davis, California.
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13
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Liu C, Duan G, Zhang S, Wei Y, Liang L, Geng B, Piao R, Xu K, Li P, Zeng X, Deng D, Liu P. Altered functional connectivity density and structural covariance networks in women with premenstrual syndrome. Quant Imaging Med Surg 2023; 13:835-851. [PMID: 36819237 PMCID: PMC9929399 DOI: 10.21037/qims-22-506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 11/21/2022] [Indexed: 01/05/2023]
Abstract
Background Premenstrual syndrome (PMS) is a menstrual-related disorder, characterized by physical, emotional, behavioral and cognitive symptoms. However, the neuropathological mechanisms of PMS remain unclear. This study aimed to investigate the frequency-specific functional connectivity density (FCD) and structural covariance in PMS. Methods Functional and T1-weighted structural data were obtained from 35 PMS patients and 36 healthy controls (HCs). This study was a cross-sectional and prospective design. The local/long-range FCD (LFCD/LRFCD) across slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz) bands were computed, and two-way analysis of variance (ANOVA) was performed to ascertain the main effects of group and interaction effects between group and frequency band. Receiver operating characteristic (ROC) curve was performed to investigate reliable biomarkers for identifying PMS from HCs. Based on the ROC results, characterized the changes of whole-brain structural covariance patterns of striatum subregions in two groups. Correlation analysis was applied to examine relationships between the clinical symptoms and abnormal brain regions. Results Compared with HCs, PMS patients exhibited: (I) aberrant functional communication in the middle cingulate cortex and precentral gyrus; (II) significant frequency band-by-group interaction effects of the striatum, thalamus and orbitofrontal cortex; (III) the better classification ability of the LFCD in the striatum in ROC analysis (slow-5); (IV) decreased gray matter volumes in the caudate subregions and decreased structural associations of between the caudate subregions and frontal cortex; (V) the LFCD value in thalamus were significantly negatively correlated with the sleep problems (slow-5). Conclusions Based on multi-modal magnetic resonance imaging (MRI) analysis, this study might imply the aberrant emotional regulation and cognitive function related to menstrual cycle in PMS and improve our understanding of the pathophysiologic mechanism in PMS from novel perspective.
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Affiliation(s)
- Chengxiang Liu
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi’an, China;,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi’an, China;,Xi’an Key Laboratory of Intelligent Sensing and Regulation of Trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi’an, China
| | - Gaoxiong Duan
- Department of Radiology, the People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Shuming Zhang
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi’an, China;,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi’an, China;,Xi’an Key Laboratory of Intelligent Sensing and Regulation of Trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi’an, China
| | - Yichen Wei
- Department of Radiology, the People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Lingyan Liang
- Department of Radiology, the People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Bowen Geng
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi’an, China;,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi’an, China;,Xi’an Key Laboratory of Intelligent Sensing and Regulation of Trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi’an, China
| | - Ruiqing Piao
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi’an, China;,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi’an, China;,Xi’an Key Laboratory of Intelligent Sensing and Regulation of Trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi’an, China
| | - Ke Xu
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi’an, China;,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi’an, China;,Xi’an Key Laboratory of Intelligent Sensing and Regulation of Trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi’an, China
| | - Pengyu Li
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi’an, China;,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi’an, China;,Xi’an Key Laboratory of Intelligent Sensing and Regulation of Trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi’an, China
| | - Xiao Zeng
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi’an, China;,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi’an, China;,Xi’an Key Laboratory of Intelligent Sensing and Regulation of Trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi’an, China
| | - Demao Deng
- Department of Radiology, the People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Peng Liu
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi’an, China;,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi’an, China;,Xi’an Key Laboratory of Intelligent Sensing and Regulation of Trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi’an, China
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14
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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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15
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Seok D, Beer J, Jaskir M, Smyk N, Jaganjac A, Makhoul W, Cook P, Elliott M, Shinohara R, Sheline YI. Differential Impact of Anxious Misery Psychopathology on Multiple Representations of the Functional Connectome. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2022; 2:489-499. [PMID: 36324648 PMCID: PMC9616351 DOI: 10.1016/j.bpsgos.2021.11.004] [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: 08/26/2021] [Revised: 11/03/2021] [Accepted: 11/07/2021] [Indexed: 11/27/2022] Open
Abstract
Background One aim of characterizing dimensional psychopathology is associating different domains of affective dysfunction with brain circuitry. The functional connectome, as measured by functional magnetic resonance imaging, can be modeled and associated with psychopathology through multiple methods; some methods assess univariate relationships while others summarize broad patterns of activity. It remains unclear whether different dimensions of psychopathology require different representations of the connectome to generate reproducible associations. Methods Patients experiencing anxious misery symptomology (depression, anxiety, and trauma; n = 192) received resting-state functional magnetic resonance imaging scans. Three modeling approaches (seed-based correlation analysis, edgewise regression, and brain basis set modeling), each relying on increasingly broader representations of the functional connectome, were used to associate connectivity patterns with six data-driven dimensions of psychopathology: anxiety sensitivity, anxious arousal, rumination, anhedonia, insomnia, and negative affect. To protect against overfitting, 50 participants were held out in a testing dataset, leaving 142 participants as training data. Results Different modeling approaches varied in the extent to which they could model different symptom dimensions: seed-based correlation analysis failed to reproducibly model any symptoms, subsets of the connectome (edgewise regression) were sufficient to model insomnia and anxious arousal, and broad representations of the entire connectome (brain basis set modeling) were necessary to model negative affect and ruminative thought. Conclusions These results indicate that different methods of representing the functional connectome differ in the degree that they can model different symptom dimensions, highlighting the potential sufficiency of subsets of connections for some dimensions and the necessity of connectome-wide approaches in others.
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Affiliation(s)
- Darsol Seok
- Center for Neuromodulation in Depression and Stress, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Joanne Beer
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Marc Jaskir
- Center for Neuromodulation in Depression and Stress, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Nathan Smyk
- Center for Neuromodulation in Depression and Stress, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Adna Jaganjac
- Center for Neuromodulation in Depression and Stress, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Walid Makhoul
- Center for Neuromodulation in Depression and Stress, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Philip Cook
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Mark Elliott
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Russell Shinohara
- Center for Neuromodulation in Depression and Stress, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Yvette I. Sheline
- Center for Neuromodulation in Depression and Stress, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
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16
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Akbar SA, Mattfeld AT, Laird AR, McMakin DL. Sleep to Internalizing Pathway in Young Adolescents (SIPYA): A proposed neurodevelopmental model. Neurosci Biobehav Rev 2022; 140:104780. [PMID: 35843345 PMCID: PMC10750488 DOI: 10.1016/j.neubiorev.2022.104780] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 05/28/2022] [Accepted: 07/12/2022] [Indexed: 01/28/2023]
Abstract
The prevalence of internalizing disorders, i.e., anxiety and depressive disorders, spikes in adolescence and has been increasing amongst adolescents despite the existence of evidence-based treatments, highlighting the need for advancing theories on how internalizing disorders emerge. The current review presents a theoretical model, called the Sleep to Internalizing Pathway in Young Adolescents (SIPYA) Model, to explain how risk factors, namely sleep-related problems (SRPs), are prospectively associated with internalizing disorders in adolescence. Specifically, SRPs during late childhood and early adolescence, around the initiation of pubertal development, contribute to the interruption of intrinsic brain networks dynamics, both within the default mode network and between the default mode network and other networks in the brain. This interruption leaves adolescents vulnerable to repetitive negative thought, such as worry or rumination, which then increases vulnerability to internalizing symptoms and disorders later in adolescence. Sleep-related behaviors are observable, modifiable, low-stigma, and beneficial beyond treating internalizing psychopathology, highlighting the intervention potential associated with understanding the neurodevelopmental impact of SRPs around the transition to adolescence. This review details support for the SIPYA Model, as well as gaps in the literature and future directions.
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Affiliation(s)
- Saima A Akbar
- Department of Psychology, Florida International University, Miami, FL, USA.
| | - Aaron T Mattfeld
- Department of Psychology, Florida International University, Miami, FL, USA
| | - Angela R Laird
- Department of Physics, Florida International University, Miami, FL, USA
| | - Dana L McMakin
- Department of Psychology, Florida International University, Miami, FL, USA
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17
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Elemery M, Kiss S, Dome P, Pogany L, Faludi G, Lazary J. Change of Circulating Vascular Endothelial Growth Factor Level and Reduction of Anhedonia Are Associated in Patients With Major Depressive Disorder Treated With Repetitive Transcranial Magnetic Stimulation. Front Psychiatry 2022; 13:806731. [PMID: 35711587 PMCID: PMC9193814 DOI: 10.3389/fpsyt.2022.806731] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 04/27/2022] [Indexed: 12/27/2022] Open
Abstract
AIM Vascular endothelial growth factor (VEGF) has been implicated in mediating the effect of antidepressant therapies as it plays a significant role in the neurogenesis. Anhedonia, an endophenotype of major depressive disorder (MDD), is related to the dorsolateral prefrontal cortex, the major focus of brain stimulation in MDD. The aim of our study was to analyze the change of serum VEGF level after rTMS treatment in association with anhedonia. MATERIALS AND METHODS A dataset of 17 patients with TRD who were treated with antidepressants and bilateral rTMS for 2 × 5 days was analyzed. Depression was measured by the Montgomery-Asberg Depression Scale (MADRS) and anhedonia by the Snaith-Hamilton Pleasure Scale (SHAPS) for monitoring the symptom changes. The serum VEGF levels and symptoms were assessed on the first (V1), on the 14th (V2), and on the 28th day (V3). The level of VEGF was measured by ELISA assay. RESULTS There was no significant association between MADRS scores and serum VEGF levels at any timepoint. The decrease in the SHAPS score was significantly associated with the increase in VEGF level between V1 and V2 (p = 0.001). The VEGF levels were significantly higher in non-responders than in responders (p = 0.04). The baseline VEGF level has been proven as a significant predictor of treatment response (p = 0.045). CONCLUSION Our results suggest that serum VEGF can be sensitive to the changes of anhedonia during rTMS treatment. Considering that the most widely used depression scales are not applicable for the assessment of anhedonia, measurement of anhedonia in rTMS treatment studies of patients with TRD can be suggested as more appropriate data on distinct pathogenic pathways and specific biomarkers of the disorder.
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Affiliation(s)
- Monika Elemery
- János Szentágothai Neuroscience Doctoral School, Semmelweis University, Budapest, Hungary.,National Institute of Mental Health, Neurology and Neurosurgery, Budapest, Hungary
| | - Szilvia Kiss
- János Szentágothai Neuroscience Doctoral School, Semmelweis University, Budapest, Hungary.,National Institute of Mental Health, Neurology and Neurosurgery, Budapest, Hungary
| | - Peter Dome
- National Institute of Mental Health, Neurology and Neurosurgery, Budapest, Hungary.,Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Laszlo Pogany
- János Szentágothai Neuroscience Doctoral School, Semmelweis University, Budapest, Hungary.,National Institute of Mental Health, Neurology and Neurosurgery, Budapest, Hungary
| | - Gabor Faludi
- János Szentágothai Neuroscience Doctoral School, Semmelweis University, Budapest, Hungary.,National Institute of Mental Health, Neurology and Neurosurgery, Budapest, Hungary
| | - Judit Lazary
- János Szentágothai Neuroscience Doctoral School, Semmelweis University, Budapest, Hungary.,National Institute of Mental Health, Neurology and Neurosurgery, Budapest, Hungary
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18
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Qu Y, Rappaport BI, Luby JL, Barch DM. No associations in preregistered study of youth depression and functional connectivity of fronto-parietal and default mode networks. NEUROIMAGE. REPORTS 2021; 1:100036. [PMID: 37207026 PMCID: PMC10194089 DOI: 10.1016/j.ynirp.2021.100036] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Adolescence is characterized by vulnerability to the onset of major depressive disorder (MDD). The goal of this preregistered study was to assess neural correlates of depression symptoms in young adolescents, both cross-sectionally and longitudinally. The default mode network (DMN) is believed to support internal attention towards self-referential thoughts, while the fronto-parietal network (FPN) is theorized to support cognitive control and regulation of attention. As MDD diagnosis has been associated with heightened connectivity within DMN regions and diminished connectivity within FPN regions relative to healthy controls, our study builds upon group-difference analyses by using dimensional measures of depression severity. Our preregistered hypotheses were that within-DMN functional connectivity would be positively associated with concurrent depression severity, while within-FPN functional connectivity would be negatively associated with concurrent depression severity. Preregistered analyses also examined between DMN-FPN connectivity as an alternative predictor variable, and assessed the longitudinal associations between all three functional connectivity measures and change in depression severity over three subsequent waves. Multiple regression models tested cross-sectional analyses and hierarchical linear models tested longitudinal analyses. One hundred and twenty-four youth completed a resting state functional MRI. Their depression severity was assessed at the time of the scan and at three follow-up sessions. None of the predictor variables were associated with concurrent depression severity, nor with the slope of depression symptom trajectories in longitudinal analyses. These negative results add to extant cross-sectional studies, and may inform future investigations of brain correlates of depression psychopathology in youth.
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Affiliation(s)
- Yueyue Qu
- Department of Psychological & Brain Sciences, Washington University in St. Louis, One Brrokings Drive, St. Louis, MO, 63105, USA
| | - Brent I. Rappaport
- Department of Psychological & Brain Sciences, Washington University in St. Louis, One Brrokings Drive, St. Louis, MO, 63105, USA
| | - Joan L. Luby
- Department of Psychiatry, Washington University in St. Louis, 660 S. Euclid Avenue, St. Louis, MO, 63110, USA
| | - Deanna M. Barch
- Department of Psychological & Brain Sciences, Washington University in St. Louis, One Brrokings Drive, St. Louis, MO, 63105, USA
- Department of Psychiatry, Washington University in St. Louis, 660 S. Euclid Avenue, St. Louis, MO, 63110, USA
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Avenue, St. Louis, MO, 63110, USA
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19
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Cernasov P, Walsh EC, Kinard JL, Kelley L, Phillips R, Pisoni A, Eisenlohr-Moul TA, Arnold M, Lowery SC, Ammirato M, Truong K, Nagy GA, Oliver JA, Haworth K, Smoski M, Dichter GS. Multilevel growth curve analyses of behavioral activation for anhedonia (BATA) and mindfulness-based cognitive therapy effects on anhedonia and resting-state functional connectivity: Interim results of a randomized trial ✰. J Affect Disord 2021; 292:161-171. [PMID: 34126308 PMCID: PMC8282772 DOI: 10.1016/j.jad.2021.05.054] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Revised: 05/03/2021] [Accepted: 05/23/2021] [Indexed: 12/18/2022]
Abstract
BACKGROUND The neural mechanisms associated with anhedonia treatment response are poorly understood. Additionally, no study has investigated changes in resting-state functional connectivity (rsFC) accompanying psychosocial treatment for anhedonia. METHODS We evaluated a novel psychotherapy, Behavioral Activation Therapy for Anhedonia (BATA, n = 38) relative to Mindfulness-Based Cognitive Therapy (MBCT, n = 35) in a medication-free, transdiagnostic, anhedonic sample in a parallel randomized controlled trial. Participants completed up to 15 sessions of therapy and up to four 7T MRI scans before, during, and after treatment (n = 185 scans). Growth curve models estimated change over time in anhedonia and in rsFC using average region-of-interest (ROI)-to-ROI connectivity within the default mode network (DMN), frontoparietal network (FPN), salience network, and reward network. Changes in rsFC from pre- to post-treatment were further evaluated using whole-network seed-to-voxel and ROI-to-ROI edgewise analyses. RESULTS Growth curve models showed significant reductions in anhedonia symptoms and in average rsFC within the DMN and FPN over time, across BATA and MBCT. There were no differences in anhedonia reductions between treatments. Within-person, changes in average rsFC were unrelated to changes in anhedonia. Between-person, higher than average FPN rsFC was related to less anhedonia across timepoints. Seed-to-voxel and edgewise rsFC analyses corroborated reductions within the DMN and between the DMN and FPN over time, across the sample. CONCLUSIONS Reductions in rsFC within the DMN, FPN, and between these networks co-occurred with anhedonia improvement across two psychosocial treatments for anhedonia. Future anhedonia clinical trials with a waitlist control group should disambiguate treatment versus time-related effects on rsFC.
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Affiliation(s)
- Paul Cernasov
- Department of Psychology and Neuroscience, University of North Carolina-Chapel Hill, Chapel Hill, NC 27514, USA
| | - Erin C Walsh
- Department of Psychiatry, University of North Carolina-Chapel Hill, Chapel Hill, NC 57514, USA
| | - Jessica L Kinard
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC 27510, USA; Division of Speech and Hearing Sciences, University of North Carolina-Chapel Hill, Chapel Hill, NC 27514, USA
| | - Lisalynn Kelley
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27705, USA
| | - Rachel Phillips
- Department of Psychology and Neuroscience, University of North Carolina-Chapel Hill, Chapel Hill, NC 27514, USA
| | - Angela Pisoni
- Department of Psychology and Neuroscience, Duke University, Durham, NC 27505, USA
| | - Tory A Eisenlohr-Moul
- Department of Psychiatry, University of Illinois at Chicago, Neuropsychiatry Institute, Chicago, IL 60612, USA
| | - Macey Arnold
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27705, USA
| | - Sarah C Lowery
- Department of Psychology and Neuroscience, University of North Carolina-Chapel Hill, Chapel Hill, NC 27514, USA
| | - Marcy Ammirato
- Department of Psychology and Neuroscience, University of North Carolina-Chapel Hill, Chapel Hill, NC 27514, USA
| | - Kinh Truong
- Department of Biostatistics, University of North Carolina-Chapel Hill, Chapel Hill, NC, 27514, USA
| | - Gabriela A Nagy
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27705, USA; Duke University School of Nursing, 307 Trent Drive, Durham, NC 27710, USA
| | - Jason A Oliver
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27705, USA; Division of Cancer Control and Population Sciences, Duke Cancer Institute, Durham, NC 27705, USA
| | - Kevin Haworth
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27705, USA
| | - Moria Smoski
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27705, USA; Department of Psychology and Neuroscience, Duke University, Durham, NC 27505, USA
| | - Gabriel S Dichter
- Department of Psychology and Neuroscience, University of North Carolina-Chapel Hill, Chapel Hill, NC 27514, USA; Department of Psychiatry, University of North Carolina-Chapel Hill, Chapel Hill, NC 57514, USA; Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC 27510, USA.
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20
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Altered neural activity in the reward-related circuit and executive control network associated with amelioration of anhedonia in major depressive disorder by electroconvulsive therapy. Prog Neuropsychopharmacol Biol Psychiatry 2021; 109:110193. [PMID: 33285263 DOI: 10.1016/j.pnpbp.2020.110193] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2020] [Revised: 11/25/2020] [Accepted: 11/30/2020] [Indexed: 02/03/2023]
Abstract
Anhedonia is a core characteristic of depression, the amelioration of which accounts for depressive symptom improvement. Electroconvulsive therapy (ECT) has been shown remarkable antidepressive effect, however, less is known about the effect of ECT on anhedonia and its underlying neural mechanism. Herein, we investigated local and global intrinsic brain functional alterations during the resting state in 46 patients with pre- and post-ECT major depressive disorder using the amplitude of low-frequency fluctuations (ALFF) and degree centrality (DC) approach. Functional connectivity (FC) was also calculated between nodes with significant local and global intrinsic brain functional alterations. The severity of anhedonia and depression was assessed with the Temporal Experience of Pleasure Scale and Hamilton Depression Rating Scale, respectively. The relationship between the change in anhedonia and depressive symptoms and brain functional alterations was determined. Increased ALFF and DC were observed in the bilateral dorsal medial prefrontal cortex (dmPFC), right dorsal lateral prefrontal cortex (dlPFC), left orbitofrontal cortex, and right orbitofrontal cortex (ROFC) after ECT. Correlational analysis between the change in anhedonia and ALFF had positive results in the dmPFC. Similarly, there was a positive correlation between the change in anhedonia and change in DC in the dmPFC, right dlPFC, ROFC, and middle frontal gyrus. Furthermore, there was a significant relationship between the change in anhedonia and altered dmPFC-dlPFC FC. These results revealed that amelioration of anhedonia may be associated with intrinsic neural activity alteration in the reward-related circuit and executive control network following ECT.
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21
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Oberman LM, Hynd M, Nielson DM, Towbin KE, Lisanby SH, Stringaris A. Repetitive Transcranial Magnetic Stimulation for Adolescent Major Depressive Disorder: A Focus on Neurodevelopment. Front Psychiatry 2021; 12:642847. [PMID: 33927653 PMCID: PMC8076574 DOI: 10.3389/fpsyt.2021.642847] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 03/18/2021] [Indexed: 12/31/2022] Open
Abstract
Adolescent depression is a potentially lethal condition and a leading cause of disability for this age group. There is an urgent need for novel efficacious treatments since half of adolescents with depression fail to respond to current therapies and up to 70% of those who respond will relapse within 5 years. Repetitive transcranial magnetic stimulation (rTMS) has emerged as a promising treatment for major depressive disorder (MDD) in adults who do not respond to pharmacological or behavioral interventions. In contrast, rTMS has not demonstrated the same degree of efficacy in adolescent MDD. We argue that this is due, in part, to conceptual and methodological shortcomings in the existing literature. In our review, we first provide a neurodevelopmentally focused overview of adolescent depression. We then summarize the rTMS literature in adult and adolescent MDD focusing on both the putative mechanisms of action and neurodevelopmental factors that may influence efficacy in adolescents. We then identify limitations in the existing adolescent MDD rTMS literature and propose specific parameters and approaches that may be used to optimize efficacy in this uniquely vulnerable age group. Specifically, we suggest ways in which future studies reduce clinical and neural heterogeneity, optimize neuronavigation by drawing from functional brain imaging, apply current knowledge of rTMS parameters and neurodevelopment, and employ an experimental therapeutics platform to identify neural targets and biomarkers for response. We conclude that rTMS is worthy of further investigation. Furthermore, we suggest that following these recommendations in future studies will offer a more rigorous test of rTMS as an effective treatment for adolescent depression.
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22
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Regonia PR, Takamura M, Nakano T, Ichikawa N, Fermin A, Okada G, Okamoto Y, Yamawaki S, Ikeda K, Yoshimoto J. Modeling Heterogeneous Brain Dynamics of Depression and Melancholia Using Energy Landscape Analysis. Front Psychiatry 2021; 12:780997. [PMID: 34899435 PMCID: PMC8656401 DOI: 10.3389/fpsyt.2021.780997] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 11/01/2021] [Indexed: 11/13/2022] Open
Abstract
Our current understanding of melancholic depression is shaped by its position in the depression spectrum. The lack of consensus on how it should be treated-whether as a subtype of depression, or as a distinct disorder altogethe-interferes with the recovery of suffering patients. In this study, we analyzed brain state energy landscape models of melancholic depression, in contrast to healthy and non-melancholic energy landscapes. Our analyses showed significant group differences on basin energy, basin frequency, and transition dynamics in several functional brain networks such as basal ganglia, dorsal default mode, and left executive control networks. Furthermore, we found evidences suggesting the connection between energy landscape characteristics (basin characteristics) and depressive symptom scores (BDI-II and SHAPS). These results indicate that melancholic depression is distinguishable from its non-melancholic counterpart, not only in terms of depression severity, but also in brain dynamics.
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Affiliation(s)
- Paul Rossener Regonia
- Division of Information Science, Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Japan.,Department of Computer Science, College of Engineering, University of the Philippines Diliman, Quezon City, Philippines
| | - Masahiro Takamura
- Center for Brain, Mind and KANSEI Research Sciences, Hiroshima University, Hiroshima, Japan.,Department of Neurology, Faculty of Medicine, Shimane University, Izumo, Japan
| | - Takashi Nakano
- Division of Information Science, Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Japan.,School of Medicine, Fujita Health University, Toyoake, Japan
| | - Naho Ichikawa
- Center for Brain, Mind and KANSEI Research Sciences, Hiroshima University, Hiroshima, Japan
| | - Alan Fermin
- Center for Brain, Mind and KANSEI Research Sciences, Hiroshima University, Hiroshima, Japan
| | - Go Okada
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Yasumasa Okamoto
- Center for Brain, Mind and KANSEI Research Sciences, Hiroshima University, Hiroshima, Japan.,Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Shigeto Yamawaki
- Center for Brain, Mind and KANSEI Research Sciences, Hiroshima University, Hiroshima, Japan
| | - Kazushi Ikeda
- Division of Information Science, Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Japan
| | - Junichiro Yoshimoto
- Division of Information Science, Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Japan
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23
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Chahal R, Gotlib IH, Guyer AE. Research Review: Brain network connectivity and the heterogeneity of depression in adolescence - a precision mental health perspective. J Child Psychol Psychiatry 2020; 61:1282-1298. [PMID: 32458453 PMCID: PMC7688558 DOI: 10.1111/jcpp.13250] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/03/2020] [Indexed: 12/18/2022]
Abstract
BACKGROUND Adolescence is a period of high risk for the onset of depression, characterized by variability in symptoms, severity, and course. During adolescence, the neurocircuitry implicated in depression continues to mature, suggesting that it is an important period for intervention. Reflecting the recent emergence of 'precision mental health' - a person-centered approach to identifying, preventing, and treating psychopathology - researchers have begun to document associations between heterogeneity in features of depression and individual differences in brain circuitry, most frequently in resting-state functional connectivity (RSFC). METHODS In this review, we present emerging work examining pre- and post-treatment measures of network connectivity in depressed adolescents; these studies reveal potential intervention-specific neural markers of treatment efficacy. We also review findings from studies examining associations between network connectivity and both types of depressive symptoms and response to treatment in adults, and indicate how this work can be extended to depressed adolescents. Finally, we offer recommendations for research that we believe will advance the science of precision mental health of adolescence. RESULTS Nascent studies suggest that linking RSFC-based pathophysiological variation with effects of different types of treatment and changes in mood following specific interventions will strengthen predictions of prognosis and treatment response. Studies with larger sample sizes and direct comparisons of treatments are required to determine whether RSFC patterns are reliable neuromarkers of treatment response for depressed adolescents. Although we are not yet at the point of using RSFC to guide clinical decision-making, findings from research examining the stability and reliability of RSFC point to a favorable future for network-based clinical phenotyping. CONCLUSIONS Delineating the correspondence between specific clinical characteristics of depression (e.g., symptoms, severity, and treatment response) and patterns of network-based connectivity will facilitate the development of more tailored and effective approaches to the assessment, prevention, and treatment of depression in adolescents.
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Affiliation(s)
- Rajpreet Chahal
- Department of Psychology, Stanford University, Stanford, CA, USA
| | - Ian H. Gotlib
- Department of Psychology, Stanford University, Stanford, CA, USA
| | - Amanda E. Guyer
- Department of Human Ecology, University of California, Davis, Davis, CA, USA,Center for Mind and Brain, University of California, Davis, Davis, CA, USA
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24
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Rakesh D, Allen NB, Whittle S. Balancing act: Neural correlates of affect dysregulation in youth depression and substance use - A systematic review of functional neuroimaging studies. Dev Cogn Neurosci 2020; 42:100775. [PMID: 32452461 PMCID: PMC7139159 DOI: 10.1016/j.dcn.2020.100775] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Revised: 03/03/2020] [Accepted: 03/09/2020] [Indexed: 12/22/2022] Open
Abstract
Both depression and substance use problems have their highest incidence during youth (i.e., adolescence and emerging adulthood), and are characterized by emotion regulation deficits. Influential neurodevelopmental theories suggest that alterations in the function of limbic and frontal regions render youth susceptible to these deficits. However, whether depression and substance use in youth are associated with similar alterations in emotion regulation neural circuitry is unknown. In this systematic review we synthesized the results of functional magnetic resonance imaging (fMRI) studies investigating the neural correlates of emotion regulation in youth depression and substance use. Resting-state fMRI studies focusing on limbic connectivity were also reviewed. While findings were largely inconsistent within and between studies of depression and substance use, some patterns emerged. First, youth depression appears to be associated with exaggerated amygdala activity in response to negative stimuli; second, both depression and substance use appear to be associated with lower functional connectivity between the amygdala and prefrontal cortex during rest. Findings are discussed in relation to support for existing neurodevelopmental models, and avenues for future work are suggested, including studying neurodevelopmental trajectories from a network perspective.
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Affiliation(s)
- Divyangana Rakesh
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, Victoria, Australia
| | - Nicholas B Allen
- Department of Psychology, University of Oregon, Eugene, Oregon, USA
| | - Sarah Whittle
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, Victoria, Australia; Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, Victoria, Australia.
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25
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Pan F, Xu Y, Zhou W, Chen J, Wei N, Lu S, Shang D, Wang J, Huang M. Disrupted intrinsic functional connectivity of the cognitive control network underlies disease severity and executive dysfunction in first-episode, treatment-naive adolescent depression. J Affect Disord 2020; 264:455-463. [PMID: 31780136 DOI: 10.1016/j.jad.2019.11.076] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2019] [Revised: 10/01/2019] [Accepted: 11/12/2019] [Indexed: 12/12/2022]
Abstract
BACKGROUND Previous neuroimaging studies have showed that imbalanced functional integration of distributed large-scale brain networks is associated with pathophysiological characteristics of major depressive disorder (MDD). However, the association between network integrative disturbances and clinical features and cognitive functions remains largely unclear in adolescent MDD. This study investigated the neural correlates of abnormal functional connectivity networks with clinical and cognitive characteristics in adolescent MDD. METHODS Twenty-eight first-episode, treatment-naive adolescents with MDD and 24 well-matched healthy controls (HCs) underwent functional magnetic resonance imaging (fMRI) and a battery of cognitive tests. A seed-based functional connectivity (FC) approach was used to depict connectivity patterns of the cognitive control network (CCN), affective network (AN) and default mode network (DMN), whose between-group differences were correlated with clinical variables and cognitive functions in the patients. RESULTS Compared with the HCs, the MDD patients exhibited impaired executive functions. The FC analysis revealed lower CCN FC with the temporal, parietal and frontal regions and the limbic system, higher AN FC with the temporal and occipital regions and the cerebellum, and lower DMN FC with the cerebellum and insula. Interestingly, the decreased CCN FC was related to disease severity (with the inferior frontal gyrus) and executive dysfunctions (with the middle cingulate gyrus and supramarginal gyrus) in the patients. LIMITATIONS The main limitations were the relatively small sample size and suboptimal imaging parameters. CONCLUSION Functional alteration of CCN during the developmentally sensitive period may be important in the neurobiology of adolescent MDD.
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Affiliation(s)
- Fen Pan
- Department of Psychiatry, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China; The Key Laboratory of Mental Disorder's Management of Zhejiang Province, Hangzhou, China
| | - Yi Xu
- Department of Psychiatry, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China; The Key Laboratory of Mental Disorder's Management of Zhejiang Province, Hangzhou, China
| | - Weihua Zhou
- Department of Psychiatry, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China; The Key Laboratory of Mental Disorder's Management of Zhejiang Province, Hangzhou, China
| | - Jinkai Chen
- Department of Psychiatry, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China; The Key Laboratory of Mental Disorder's Management of Zhejiang Province, Hangzhou, China
| | - Ning Wei
- Department of Psychiatry, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China; The Key Laboratory of Mental Disorder's Management of Zhejiang Province, Hangzhou, China
| | - Shaojia Lu
- Department of Psychiatry, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China; The Key Laboratory of Mental Disorder's Management of Zhejiang Province, Hangzhou, China
| | - Desheng Shang
- Department of Radiology, First Affiliated Hospital, College of Medicine, Zhejiang University, The Key Laboratory of Mental Disorder's Management of Zhejiang Province, Hangzhou, China
| | - Jinhui Wang
- Institute for Brain Research and Rehabilitation, Guangdong Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological Application, South China Normal University, Guangzhou, China.
| | - Manli Huang
- Department of Psychiatry, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China; The Key Laboratory of Mental Disorder's Management of Zhejiang Province, Hangzhou, China.
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26
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Kaya S, McCabe C. What Role Does the Prefrontal Cortex Play in the Processing of Negative and Positive Stimuli in Adolescent Depression? Brain Sci 2019; 9:E104. [PMID: 31067810 PMCID: PMC6562900 DOI: 10.3390/brainsci9050104] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Revised: 04/30/2019] [Accepted: 05/03/2019] [Indexed: 11/17/2022] Open
Abstract
This perspective describes the contribution of the prefrontal cortex to the symptoms of depression in adolescents and specifically the processing of positive and negative information. We also discuss how the prefrontal cortex (PFC) activity and connectivity during tasks and at rest might be a biomarker for risk for depression onset in adolescents. We include some of our recent work examining not only the anticipation and consummation of positive and negative stimuli, but also effort to gain positive and avoid negative stimuli in adolescents with depression. We find, using region of interest analyses, that the PFC is blunted in those with depression compared to controls across the different phases but in a larger sample the PFC is blunted in the anticipatory phase of the study only. Taken together, in adolescents with depression there is evidence for dysfunctional PFC activity across different studies and tasks. However, the data are limited with small sample sizes and inconsistent findings. Larger longitudinal studies with more detailed assessments of symptoms across the spectrum are needed to further evaluate the role of the PFC in adolescent depression.
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Affiliation(s)
- Siyabend Kaya
- School of Psychology and Clinical Language Sciences, University of Reading, Reading RG6 6AL, UK.
| | - Ciara McCabe
- School of Psychology and Clinical Language Sciences, University of Reading, Reading RG6 6AL, UK.
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