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Jung M, Han KM. Behavioral Activation and Brain Network Changes in Depression. J Clin Neurol 2024; 20:362-377. [PMID: 38951971 PMCID: PMC11220350 DOI: 10.3988/jcn.2024.0148] [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: 03/27/2024] [Revised: 04/19/2024] [Accepted: 04/22/2024] [Indexed: 07/03/2024] Open
Abstract
Behavioral activation (BA) is a well-established method of evidence-based treatment for depression. There are clear links between the neural mechanisms underlying reward processing and BA treatment for depressive symptoms, including anhedonia; however, integrated interpretations of these two domains are lacking. Here we examine brain imaging studies involving BA treatments to investigate how changes in brain networks, including the reward networks, mediate the therapeutic effects of BA, and whether brain circuits are predictors of BA treatment responses. Increased activation of the prefrontal and subcortical regions associated with reward processing has been reported after BA treatment. Activation of these regions improves anhedonia. Conversely, some studies have found decreased activation of prefrontal regions after BA treatment in response to cognitive control stimuli in sad contexts, which indicates that the therapeutic mechanism of BA may involve disengagement from negative or sad contexts. Furthermore, the decrease in resting-state functional connectivity of the default-mode network after BA treatment appears to facilitate the ability to counteract depressive rumination, thereby promoting enjoyable and valuable activities. Conflicting results suggest that an intact neural response to rewards or defective reward functioning is predictive of the efficacy of BA treatments. Increasing the benefits of BA treatments requires identification of the unique individual characteristics determining which of these conflicting findings are relevant for the personalized treatment of each individual with depression.
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Affiliation(s)
- Minjee Jung
- Department of Biomedical Sciences, Korea University College of Medicine, Seoul, Korea
| | - Kyu-Man Han
- Department of Psychiatry, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Korea.
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Xiao X, Hammond C, Salmeron BJ, Wang D, Gu H, Zhai T, Nguyen H, Lu H, Ross TJ, Yang Y. Brain Functional Connectome Defines a Transdiagnostic Dimension Shared by Cognitive Function and Psychopathology in Preadolescents. Biol Psychiatry 2024; 95:1081-1090. [PMID: 37769982 PMCID: PMC10963340 DOI: 10.1016/j.biopsych.2023.08.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Revised: 07/27/2023] [Accepted: 08/30/2023] [Indexed: 10/03/2023]
Abstract
BACKGROUND Cognitive function and general psychopathology are two important classes of human behavior dimensions that are individually related to mental disorders across diagnostic categories. However, whether these two transdiagnostic dimensions are linked to common or distinct brain networks that convey resilience or risk for the development of psychiatric disorders remains unclear. METHODS The current study is a longitudinal investigation with 11,875 youths from the Adolescent Brain Cognitive Development (ABCD) Study at ages 9 to 10 years at the onset of the study. A machine learning approach based on canonical correlation analysis was used to identify latent dimensional associations of the resting-state functional connectome with multidomain behavioral assessments including cognitive functions and psychopathological measures. For the latent resting-state functional connectivity factor showing a robust behavioral association, its ability to predict psychiatric disorders was assessed using 2-year follow-up data, and its genetic association was evaluated using twin data from the same cohort. RESULTS A latent functional connectome pattern was identified that showed a strong and generalizable association with the multidomain behavioral assessments (5-fold cross-validation: ρ = 0.68-0.73 for the training set [n = 5096]; ρ = 0.56-0.58 for the test set [n = 1476]). This functional connectome pattern was highly heritable (h2 = 74.42%, 95% CI: 56.76%-85.42%), exhibited a dose-response relationship with the cumulative number of psychiatric disorders assessed concurrently and at 2 years post-magnetic resonance imaging scan, and predicted the transition of diagnosis across disorders over the 2-year follow-up period. CONCLUSIONS These findings provide preliminary evidence for a transdiagnostic connectome-based measure that underlies individual differences in the development of psychiatric disorders during early adolescence.
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Affiliation(s)
- Xiang Xiao
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, Maryland
| | - Christopher Hammond
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, Maryland
| | - Betty Jo Salmeron
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, Maryland
| | - Danni Wang
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, Maryland
| | - Hong Gu
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, Maryland
| | - Tianye Zhai
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, Maryland
| | - Hieu Nguyen
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, Maryland
| | - Hanbing Lu
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, Maryland
| | - Thomas J Ross
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, Maryland
| | - Yihong Yang
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, Maryland.
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Theis N, Bahuguna J, Rubin JE, Cape J, Iyengar S, Prasad KM. Diagnostically distinct resting state fMRI energy distributions: A subject-specific maximum entropy modeling study. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.23.576937. [PMID: 38328170 PMCID: PMC10849576 DOI: 10.1101/2024.01.23.576937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
Objective Existing neuroimaging studies of psychotic and mood disorders have reported brain activation differences (first-order properties) and altered pairwise correlation-based functional connectivity (second-order properties). However, both approaches have certain limitations that can be overcome by integrating them in a pairwise maximum entropy model (MEM) that better represents a comprehensive picture of fMRI signal patterns and provides a system-wide summary measure called energy. This study examines the applicability of individual-level MEM for psychiatry and identifies image-derived model coefficients related to model parameters. Method MEMs are fit to resting state fMRI data from each individual with schizophrenia/schizoaffective disorder, bipolar disorder, and major depression (n=132) and demographically matched healthy controls (n=132) from the UK Biobank to different subsets of the default mode network (DMN) regions. Results The model satisfactorily explained observed brain energy state occurrence probabilities across all participants, and model parameters were significantly correlated with image-derived coefficients for all groups. Within clinical groups, averaged energy level distributions were higher in schizophrenia/schizoaffective disorder but lower in bipolar disorder compared to controls for both bilateral and unilateral DMN. Major depression energy distributions were higher compared to controls only in the right hemisphere DMN. Conclusions Diagnostically distinct energy states suggest that probability distributions of temporal changes in synchronously active nodes may underlie each diagnostic entity. Subject-specific MEMs allow for factoring in the individual variations compared to traditional group-level inferences, offering an improved measure of biologically meaningful correlates of brain activity that may have potential clinical utility.
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Affiliation(s)
- Nicholas Theis
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Jyotika Bahuguna
- Department of Neuroscience, Laboratoire de Neurosciences Cognitive et Adaptive, University of Strasbourg, France
| | | | - Joshua Cape
- Department of Statistics, University of Wisconsin-Madison, WI, USA
| | - Satish Iyengar
- Department of Statistics, University of Pittsburgh, PA, USA
| | - Konasale M. Prasad
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, PA, USA
- Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA, USA
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Hirsch F, Bumanglag Â, Zhang Y, Wohlschlaeger A. Diverging functional connectivity timescales: Capturing distinct aspects of cognitive performance in early psychosis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.07.24306932. [PMID: 38766002 PMCID: PMC11100938 DOI: 10.1101/2024.05.07.24306932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Background Psychosis spectrum disorders (PSDs) are marked by cognitive impairments, the neurobiological correlates of which remain poorly understood. Here, we investigate the entropy of time-varying functional connectivity (TVFC) patterns from resting-state fMRI (rfMRI) as potential biomarker for cognitive performance in PSDs. By combining our results with multimodal reference data, we hope to generate new insights into the mechanisms underlying cognitive dysfunction in PSDs. We hypothesized that low-entropy TVFC patterns (LEN) would be more behaviorally informative than high-entropy TVFC patterns (HEN), especially for tasks that require extensive integration across diverse cognitive subdomains. Methods rfMRI and behavioral data from 97 patients in the early phases of psychosis and 53 controls were analyzed. Positron-Emission Tomography (PET) and magnetoencephalography (MEG) data were taken from a public repository (Hansen et al., 2022). Multivariate analyses were conducted to examine relationships between TVFC patterns at multiple spatial scales and cognitive performance in patients. Results Compared to HEN, LEN explained significantly more cognitive variance on average in PSD patients, driven by superior encoding of information on psychometrically more integrated tasks. HEN better captured information in specific subdomains of executive functioning. Nodal HEN-LEN transitions were spatially aligned with neurobiological gradients reflecting monoaminergic transporter densities and MEG beta power. Exploratory analyses revealed a close statistical relationship between LEN and positive PSD symptoms. Conclusion Our entropy-based analysis of TVFC patterns dissociates distinct aspects of cognition in PSDs. By linking topographies of neurotransmission and oscillatory dynamics with cognitive performance, it enhances our understanding of the mechanisms underlying cognitive deficits in PSDs. CRediT Authorship Contribution Statement Fabian Hirsch: Conceptualization, Methodology, Software, Formal analysis, Writing - Original Draft, Writing - Review & Editing, Visualization; Ângelo Bumanglag: Methodology, Software, Formal analysis, Writing - Review & Editing; Yifei Zhang: Methodology, Software, Formal analysis, Writing - Review & Editing; Afra Wohlschlaeger: Methodology, Writing - Review & Editing, Supervision, Project administration.
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Feola B, Beermann A, Manzanarez Felix K, Coleman M, Bouix S, Holt DJ, Lewandowski KE, Öngür D, Breier A, Shenton ME, Heckers S, Brady RO, Blackford JU, Ward HB. Data-driven, connectome-wide analysis identifies psychosis-specific brain correlates of fear and anxiety. Mol Psychiatry 2024:10.1038/s41380-024-02512-w. [PMID: 38503924 DOI: 10.1038/s41380-024-02512-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 02/27/2024] [Accepted: 03/01/2024] [Indexed: 03/21/2024]
Abstract
Decades of psychosis research highlight the prevalence and the clinical significance of negative emotions, such as fear and anxiety. Translational evidence demonstrates the pivotal role of the amygdala in fear and anxiety. However, most of these approaches have used hypothesis-driven analyses with predefined regions of interest. A data-driven analysis may provide a complimentary, unbiased approach to identifying brain correlates of fear and anxiety. The aim of the current study was to identify the brain basis of fear and anxiety in early psychosis and controls using a data-driven approach. We analyzed data from the Human Connectome Project for Early Psychosis, a multi-site study of 125 people with psychosis and 58 controls with resting-state fMRI and clinical characterization. Multivariate pattern analysis of whole-connectome data was used to identify shared and psychosis-specific brain correlates of fear and anxiety using the NIH Toolbox Fear-Affect and Fear-Somatic Arousal scales. We then examined clinical correlations of Fear-Affect scores and connectivity patterns. Individuals with psychosis had higher levels of Fear-Affect scores than controls (p < 0.05). The data-driven analysis identified a cluster encompassing the amygdala and hippocampus where connectivity was correlated with Fear-Affect score (p < 0.005) in the entire sample. The strongest correlate of Fear-Affect was between this cluster and the anterior insula and stronger connectivity was associated with higher Fear-Affect scores (r = 0.31, p = 0.0003). The multivariate pattern analysis also identified a psychosis-specific correlate of Fear-Affect score between the amygdala/hippocampus cluster and a cluster in the ventromedial prefrontal cortex (VMPFC). Higher Fear-Affect scores were correlated with stronger amygdala/hippocampal-VMPFC connectivity in the early psychosis group (r = 0.33, p = 0.002), but not in controls (r = -0.15, p = 0.28). The current study provides evidence for the transdiagnostic role of the amygdala, hippocampus, and anterior insula in the neural basis of fear and anxiety and suggests a psychosis-specific relationship between fear and anxiety symptoms and amygdala/hippocampal-VMPFC connectivity. Our novel data-driven approach identifies novel, psychosis-specific treatment targets for fear and anxiety symptoms and provides complimentary evidence to decades of hypothesis-driven approaches examining the brain basis of threat processing.
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Affiliation(s)
- Brandee Feola
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Adam Beermann
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | | | - Michael Coleman
- Department of Psychiatry, Brigham & Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Sylvain Bouix
- Department of Software Engineering and Information Technology, École de technologie supérieure, Montréal, QC, Canada
| | - Daphne J Holt
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School Boston, Boston, MA, USA
| | | | - Dost Öngür
- McLean Hospital and Harvard Medical School, Boston, MA, USA
| | - Alan Breier
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Martha E Shenton
- Department of Psychiatry, Brigham & Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham & Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Stephan Heckers
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Roscoe O Brady
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
- McLean Hospital and Harvard Medical School, Boston, MA, USA
| | - Jennifer Urbano Blackford
- Munroe-Meyer Institute for Genetics and Rehabilitation, University of Nebraska Medical Center, Omaha, NE, USA
| | - Heather Burrell Ward
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.
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Dunlop K, Grosenick L, Downar J, Vila-Rodriguez F, Gunning FM, Daskalakis ZJ, Blumberger DM, Liston C. Dimensional and Categorical Solutions to Parsing Depression Heterogeneity in a Large Single-Site Sample. Biol Psychiatry 2024:S0006-3223(24)00055-6. [PMID: 38280408 DOI: 10.1016/j.biopsych.2024.01.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 12/21/2023] [Accepted: 01/13/2024] [Indexed: 01/29/2024]
Abstract
BACKGROUND Recent studies have reported significant advances in modeling the biological basis of heterogeneity in major depressive disorder, but investigators have also identified important technical challenges, including scanner-related artifacts, a propensity for multivariate models to overfit, and a need for larger samples with more extensive clinical phenotyping. The goals of the current study were to evaluate dimensional and categorical solutions to parsing heterogeneity in depression that are stable and generalizable in a large, single-site sample. METHODS We used regularized canonical correlation analysis to identify data-driven brain-behavior dimensions that explain individual differences in depression symptom domains in a large, single-site dataset comprising clinical assessments and resting-state functional magnetic resonance imaging data for 328 patients with major depressive disorder and 461 healthy control participants. We examined the stability of clinical loadings and model performance in held-out data. Finally, hierarchical clustering on these dimensions was used to identify categorical depression subtypes. RESULTS The optimal regularized canonical correlation analysis model yielded 3 robust and generalizable brain-behavior dimensions that explained individual differences in depressed mood and anxiety, anhedonia, and insomnia. Hierarchical clustering identified 4 depression subtypes, each with distinct clinical symptom profiles, abnormal resting-state functional connectivity patterns, and antidepressant responsiveness to repetitive transcranial magnetic stimulation. CONCLUSIONS Our results define dimensional and categorical solutions to parsing neurobiological heterogeneity in major depressive disorder that are stable, generalizable, and capable of predicting treatment outcomes, each with distinct advantages in different contexts. They also provide additional evidence that regularized canonical correlation analysis and hierarchical clustering are effective tools for investigating associations between functional connectivity and clinical symptoms.
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Affiliation(s)
- Katharine Dunlop
- Centre for Depression and Suicide Studies, St Michael's Hospital, Toronto, Ontario, Canada; Keenan Research Centre for Biomedical Science, St. Michael's Hospital, Toronto, Ontario, Canada; Department of Psychiatry and Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Logan Grosenick
- Department of Psychiatry, Weill Cornell Medicine, New York, New York
| | - Jonathan Downar
- Department of Psychiatry and Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Fidel Vila-Rodriguez
- Non-Invasive Neurostimulation Therapies Laboratory, Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Faith M Gunning
- Institute of Geriatric Psychiatry, Weill Cornell Medicine, White Plains, New York
| | - Zafiris J Daskalakis
- Department of Psychiatry, University of California San Diego, San Diego, California
| | - Daniel M Blumberger
- Department of Psychiatry and Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada; Department of Psychiatry, Weill Cornell Medicine, New York, New York; Temerty Centre for Therapeutic Brain Intervention and Campbell Family Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Conor Liston
- Department of Psychiatry, Weill Cornell Medicine, New York, New York; Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York.
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Lv R, Cai M, Tang N, Shi Y, Zhang Y, Liu N, Han T, Zhang Y, Wang H. Active versus sham DLPFC-NAc rTMS for depressed adolescents with anhedonia using resting-state functional magnetic resonance imaging (fMRI): a study protocol for a randomized placebo-controlled trial. Trials 2024; 25:44. [PMID: 38218932 PMCID: PMC10787505 DOI: 10.1186/s13063-023-07814-y] [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: 08/20/2023] [Accepted: 11/21/2023] [Indexed: 01/15/2024] Open
Abstract
BACKGROUND Anhedonia, which is defined as the inability to feel pleasure, is considered a core symptom of major depressive disorder (MDD). It can lead to several adverse outcomes in adolescents, including heightened disease severity, resistance to antidepressants, recurrence of MDD, and even suicide. Specifically, patients who suffer from anhedonia may exhibit a limited response to selective serotonin reuptake inhibitors (SSRIs) and cognitive behavioral therapy (CBT). Previous researches have revealed a link between anhedonia and abnormalities within the reward circuitry, making the nucleus accumbens (NAc) a potential target for treatment. However, since the NAc is deep within the brain, repetitive transcranial magnetic stimulation (rTMS) has the potential to modulate this specific region. Recent advances have enabled treatment technology to precisely target the left dorsolateral prefrontal cortex (DLPFC) and modify the functional connectivity (FC) between DLPFC and NAc in adolescent patients with anhedonia. Therefore, we plan to conduct a study to explore the safety and effectiveness of using resting-state functional connectivity magnetic resonance imaging (fcMRI)-guided rTMS to alleviate anhedonia in adolescents diagnosed with MDD. METHODS The aim of this article is to provide a study protocol for a parallel-group randomized, double-blind, placebo-controlled experiment. The study will involve 88 participants who will be randomly assigned to receive either active rTMS or sham rTMS. The primary object is to measure the percentage change in the severity of anhedonia, using the Snaith-Hamilton Pleasure Scale (SHAPS). The assessment will be conducted from the baseline to 8-week post-treatment period. The secondary outcome includes encompassing fMRI measurements, scores on the 17-item Hamilton Rating Scale for Depression (HAMD-17), the Montgomery Asberg Depression Rating Scale (MADRS), the Chinese Version of Temporal Experience of Pleasure Scale (CV-TEPS), and the Chinese Version of Beck Scale for Suicide Ideation (BSI-CV). The Clinical Global Impression (CGI) scores will also be taken into account, and adverse events will be monitored. These evaluations will be conducted at baseline, as well as at 1, 2, 4, and 8 weeks. DISCUSSION If the hypothesis of the current study is confirmed, (fcMRI)-guided rTMS could be a powerful tool to alleviate the core symptoms of MDD and provide essential data to explore the mechanism of anhedonia. TRIAL REGISTRATION ClinicalTrials.gov NCT05544071. Registered on 16 September 2022.
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Affiliation(s)
- Runxin Lv
- Department of Psychiatry of Xijing Hospital of Air Force Medical University, 127 Changle West Road, Xi'an, Shaanxi Province, China
| | - Min Cai
- Department of Psychiatry of Xijing Hospital of Air Force Medical University, 127 Changle West Road, Xi'an, Shaanxi Province, China
| | - Nailong Tang
- Department of Psychiatry of Xijing Hospital of Air Force Medical University, 127 Changle West Road, Xi'an, Shaanxi Province, China
- Department of Psychiatry, 907 Hospital, No. 99 Binjiang North Road, Yanping District, Nanping City, Fujian Province, China
| | - Yifan Shi
- Department of Psychiatry of Xijing Hospital of Air Force Medical University, 127 Changle West Road, Xi'an, Shaanxi Province, China
| | - Yuyu Zhang
- Department of Psychiatry of Xijing Hospital of Air Force Medical University, 127 Changle West Road, Xi'an, Shaanxi Province, China
| | - Nian Liu
- Department of Psychiatry of Xijing Hospital of Air Force Medical University, 127 Changle West Road, Xi'an, Shaanxi Province, China
| | - Tianle Han
- Department of Psychiatry of Xijing Hospital of Air Force Medical University, 127 Changle West Road, Xi'an, Shaanxi Province, China
| | - Yaochi Zhang
- Department of Psychiatry of Xijing Hospital of Air Force Medical University, 127 Changle West Road, Xi'an, Shaanxi Province, China
| | - Huaning Wang
- Department of Psychiatry of Xijing Hospital of Air Force Medical University, 127 Changle West Road, Xi'an, Shaanxi Province, China.
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Ding Y, Ou Y, Yan H, Liu F, Li H, Li P, Xie G, Cui X, Guo W. Uncovering the Neural Correlates of Anhedonia Subtypes in Major Depressive Disorder: Implications for Intervention Strategies. Biomedicines 2023; 11:3138. [PMID: 38137360 PMCID: PMC10740577 DOI: 10.3390/biomedicines11123138] [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: 10/03/2023] [Revised: 11/10/2023] [Accepted: 11/21/2023] [Indexed: 12/24/2023] Open
Abstract
Major depressive disorder (MDD) represents a serious public health concern, negatively affecting individuals' quality of life and making a substantial contribution to the global burden of disease. Anhedonia is a core symptom of MDD and is associated with poor treatment outcomes. Variability in anhedonia components within MDD has been observed, suggesting heterogeneity in psychopathology across subgroups. However, little is known about anhedonia subgroups in MDD and their underlying neural correlates across subgroups. To address this question, we employed a hierarchical cluster analysis based on Temporal Experience of Pleasure Scale subscales in 60 first-episode, drug-naive MDD patients and 32 healthy controls. Then we conducted a connectome-wide association study and whole-brain voxel-wise functional analyses for identified subgroups. There were three main findings: (1) three subgroups with different anhedonia profiles were identified using a data mining approach; (2) several parts of the reward network (especially pallidum and dorsal striatum) were associated with anticipatory and consummatory pleasure; (3) different patterns of within- and between-network connectivity contributed to the disparities of anhedonia profiles across three MDD subgroups. Here, we show that anhedonia in MDD is not uniform and can be categorized into distinct subgroups, and our research contributes to the understanding of neural underpinnings, offering potential treatment directions. This work emphasizes the need for tailored approaches in the complex landscape of MDD. The identification of homogeneous, stable, and neurobiologically valid MDD subtypes could significantly enhance our comprehension and management of this multifaceted condition.
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Affiliation(s)
- Yudan Ding
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, China; (Y.D.); (H.Y.); (G.X.)
| | - Yangpan Ou
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, China; (Y.D.); (H.Y.); (G.X.)
| | - Haohao Yan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, China; (Y.D.); (H.Y.); (G.X.)
| | - Feng Liu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China;
| | - Huabing Li
- Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha 410011, China;
| | - Ping Li
- Department of Psychiatry, Qiqihar Medical University, Qiqihar 161006, China;
| | - Guangrong Xie
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, China; (Y.D.); (H.Y.); (G.X.)
| | - Xilong Cui
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, China; (Y.D.); (H.Y.); (G.X.)
| | - Wenbin Guo
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, China; (Y.D.); (H.Y.); (G.X.)
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Hamzehpour L, Bohn T, Jaspers L, Grimm O. Exploring the link between functional connectivity of ventral tegmental area and physical fitness in schizophrenia and healthy controls. Eur Neuropsychopharmacol 2023; 76:77-86. [PMID: 37562082 DOI: 10.1016/j.euroneuro.2023.07.009] [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: 11/21/2022] [Revised: 07/13/2023] [Accepted: 07/17/2023] [Indexed: 08/12/2023]
Abstract
Decreased physical fitness and being overweight are highly prevalent in schizophrenia, represent a major risk factor for comorbid cardio-vascular diseases and decrease the life expectancy of the patients. Thus, it is important to understand the underlying mechanisms that link psychopathology and weight gain. We hypothesize that the dopaminergic reward system plays an important role in this. We analyzed the seed-based functional connectivity (FC) of the ventral tegmental area (VTA) in a group of schizophrenic patients (n=32) and age-, as well as gender-, matched healthy controls (n=27). We then correlated the resting-state results with physical fitness parameters, obtained in a fitness test, and psychopathology. The FC analysis revealed decreased functional connections between the VTA and the anterior cingulate cortex (ACC), as well as the dorsolateral prefrontal cortex, which negatively correlated with psychopathology, and increased FC between the VTA and the middle temporal gyrus in patients compared to healthy controls, which positively correlated with psychopathology. The decreased FC between the VTA and the ACC of the patient group further positively correlated with total body fat (p = .018, FDR-corr.) and negatively correlated with the overall physical fitness (p = .022). This study indicates a link between decreased physical fitness and higher body fat with functional dysconnectivity between the VTA and the ACC. These findings demonstrate that a dysregulated reward system might also be involved in comorbidities and could pave the way for future lifestyle therapy interventions.
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Affiliation(s)
- Lara Hamzehpour
- Goethe University Frankfurt, University Hospital, Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, Heinrich-Hoffmann-Straße 10, 60528, Frankfurt am Main, Germany; Goethe University Frankfurt, Faculty 15 Biological Sciences, Frankfurt am Main, Germany.
| | - Tamara Bohn
- Goethe University Frankfurt, University Hospital, Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, Heinrich-Hoffmann-Straße 10, 60528, Frankfurt am Main, Germany
| | - Lucia Jaspers
- Goethe University Frankfurt, University Hospital, Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, Heinrich-Hoffmann-Straße 10, 60528, Frankfurt am Main, Germany
| | - Oliver Grimm
- Goethe University Frankfurt, University Hospital, Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, Heinrich-Hoffmann-Straße 10, 60528, Frankfurt am Main, Germany
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10
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León JJ, Fernández-Martin P, González-Rodríguez A, Rodríguez-Herrera R, García-Pinteño J, Pérez-Fernández C, Sánchez-Kuhn A, Amaya-Pascasio L, Soto-Ontoso M, Martínez-Sánchez P, Sánchez-Santed F, Flores P. Decision-making and frontoparietal resting-state functional connectivity among impulsive-compulsive diagnoses. Insights from a Bayesian approach. Addict Behav 2023; 143:107683. [PMID: 36963236 DOI: 10.1016/j.addbeh.2023.107683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 02/20/2023] [Accepted: 02/24/2023] [Indexed: 03/13/2023]
Abstract
The Iowa Gambling Task (IGT) is one of the most widely used paradigms for assessing decision-making. An impairment in this process may be linked to several psychopathological disorders, such as obsessive-compulsive disorder (OCD), substance abuse disorder (SUD) or attention-deficit/hyperactivity disorder (ADHD), which could make it a good candidate for being consider a transdiagnostic domain. Resting-state functional connectivity (rsFC) has been proposed as a promising biomarker of decision-making. In this study, we aimed to identify idiosyncratic decision-making profiles among healthy people and impulsive-compulsive spectrum patients during the IGT, and to investigate the role of frontoparietal network (FPN) rsFC as a possible biomarker of different decision-making patterns. Using functional near-infrared spectroscopy (fNIRS), rsFC of 114 adults (34 controls; 25 OCD; 41 SUD; 14 ADHD) was obtained. Then, they completed the IGT. Hybrid clustering methods based on individual deck choices yielded three decision-makers subgroups. Cluster 1 (n = 27) showed a long-term advantageous strategy. Cluster 2 (n = 25) presented a maladaptive decision-making strategy. Cluster 3 (n = 62) did not develop a preference for any deck during the task. Interestingly, the proportion of participants in each cluster was not different between diagnostic groups. A Bayesian general linear model showed no credible differences in the IGT performance between diagnostic groups nor credible evidence to support the role of FPN rsFC as a biomarker of decision-making under the IGT context. This study highlights the importance of exploring in depth the behavioral and neurophysiological variables that may drive decision-making in clinical and healthy populations.
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Affiliation(s)
- J J León
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
| | - P Fernández-Martin
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
| | - A González-Rodríguez
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
| | - R Rodríguez-Herrera
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
| | - J García-Pinteño
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
| | - C Pérez-Fernández
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
| | - A Sánchez-Kuhn
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
| | - L Amaya-Pascasio
- Department of Neurology and Stroke Centre. Torrecárdenas University Hospital, Spain.
| | - M Soto-Ontoso
- Mental Health Departament. Torrecárdenas University Hospital, Spain.
| | - P Martínez-Sánchez
- Department of Neurology and Stroke Centre. Torrecárdenas University Hospital, Spain.
| | - F Sánchez-Santed
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
| | - P Flores
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
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11
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Mehta K, Pines A, Adebimpe A, Larsen B, Bassett DS, Calkins ME, Baller EB, Gell M, Patrick LM, Shafiei G, Gur RE, Gur RC, Roalf DR, Romer D, Wolf DH, Kable JW, Satterthwaite TD. Individual differences in delay discounting are associated with dorsal prefrontal cortex connectivity in children, adolescents, and adults. Dev Cogn Neurosci 2023; 62:101265. [PMID: 37327696 PMCID: PMC10285090 DOI: 10.1016/j.dcn.2023.101265] [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: 01/25/2023] [Revised: 05/24/2023] [Accepted: 06/11/2023] [Indexed: 06/18/2023] Open
Abstract
Delay discounting is a measure of impulsive choice relevant in adolescence as it predicts many real-life outcomes, including obesity and academic achievement. However, resting-state functional networks underlying individual differences in delay discounting during youth remain incompletely described. Here we investigate the association between multivariate patterns of functional connectivity and individual differences in impulsive choice in a large sample of children, adolescents, and adults. A total of 293 participants (9-23 years) completed a delay discounting task and underwent 3T resting-state fMRI. A connectome-wide analysis using multivariate distance-based matrix regression was used to examine whole-brain relationships between delay discounting and functional connectivity. These analyses revealed that individual differences in delay discounting were associated with patterns of connectivity emanating from the left dorsal prefrontal cortex, a default mode network hub. Greater delay discounting was associated with greater functional connectivity between the dorsal prefrontal cortex and other default mode network regions, but reduced connectivity with regions in the dorsal and ventral attention networks. These results suggest delay discounting in children, adolescents, and adults is associated with individual differences in relationships both within the default mode network and between the default mode and networks involved in attentional and cognitive control.
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Affiliation(s)
- Kahini Mehta
- Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Adam Pines
- Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Azeez Adebimpe
- Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Bart Larsen
- Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Danielle S Bassett
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, PA 19104, USA; Department of Electrical & Systems Engineering, University of Pennsylvania, PA 19104, USA; Department of Neurology, University of Pennsylvania, Philadelphia, PA, 19104, USA; Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, PA, 19104, USA; Santa Fe Institute, Santa Fe, NM, 87051, USA
| | - Monica E Calkins
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Erica B Baller
- Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Martin Gell
- Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen University, Aachen, Germany; Institute of Neuroscience and Medicine (INM-7: Brain & Behaviour), Research Centre Jülich, Jülich, Germany
| | - Lauren M Patrick
- Department of Psychology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Golia Shafiei
- Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Raquel E Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA; Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Neurology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Ruben C Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA; Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Neurology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - David R Roalf
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Daniel Romer
- Annenberg Public Policy Center, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Daniel H Wolf
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Joseph W Kable
- Department of Psychology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Theodore D Satterthwaite
- Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA; Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA 19104, USA.
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12
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Tian S, Zhu R, Chen Z, Wang H, Chattun MR, Zhang S, Shao J, Wang X, Yao Z, Lu Q. Prediction of suicidality in bipolar disorder using variability of intrinsic brain activity and machine learning. Hum Brain Mapp 2023; 44:2767-2777. [PMID: 36852459 PMCID: PMC10089096 DOI: 10.1002/hbm.26243] [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: 07/27/2022] [Revised: 02/03/2023] [Accepted: 02/10/2023] [Indexed: 03/01/2023] Open
Abstract
Bipolar disorder (BD) is associated with marked suicidal susceptibility, particularly during a major depressive episode. However, the evaluation of suicidal risk remains challenging since it relies mainly on self-reported information from patients. Hence, it is necessary to complement neuroimaging features with advanced machine learning techniques in order to predict suicidal behavior in BD patients. In this study, a total of 288 participants, including 75 BD suicide attempters, 101 BD nonattempters and 112 healthy controls, underwent a resting-state functional magnetic resonance imaging (rs-fMRI). Intrinsic brain activity was measured by amplitude of low-frequency fluctuation (ALFF). We trained and tested a two-level k-nearest neighbors (k-NN) model based on resting-state variability of ALFF with fivefold cross-validation. BD suicide attempters had increased dynamic ALFF values in the right anterior cingulate cortex, left thalamus and right precuneus. Compared to other machine learning methods, our proposed framework had a promising performance with 83.52% accuracy, 78.75% sensitivity and 87.50% specificity. The trained models could also replicate and validate the results in an independent cohort with 72.72% accuracy. These findings based on a relatively large data set, provide a promising way of combining fMRI data with machine learning technique to reliably predict suicide attempt at an individual level in bipolar depression. Overall, this work might enhance our understanding of the neurobiology of suicidal behavior by detecting clinically defined disruptions in the dynamics of instinct brain activity.
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Affiliation(s)
- Shui Tian
- Department of RadiologyThe First Affiliated Hospital of Nanjing Medical UniversityNanjingChina
- Laboratory for Artificial Intelligence in Medical Imaging (LAIMI)Nanjing Medical UniversityNanjingChina
| | - Rongxin Zhu
- Department of PsychiatryThe Affiliated Nanjing Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Zhilu Chen
- Department of PsychiatryThe Affiliated Nanjing Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Huan Wang
- School of Biological Sciences and Medical EngineeringSoutheast UniversityNanjingChina
- Child Development and Learning ScienceKey Laboratory of Ministry of EducationBeijingChina
| | - Mohammad Ridwan Chattun
- Department of PsychiatryThe Affiliated Nanjing Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Siqi Zhang
- School of Biological Sciences and Medical EngineeringSoutheast UniversityNanjingChina
- Child Development and Learning ScienceKey Laboratory of Ministry of EducationBeijingChina
| | - Junneng Shao
- School of Biological Sciences and Medical EngineeringSoutheast UniversityNanjingChina
- Child Development and Learning ScienceKey Laboratory of Ministry of EducationBeijingChina
| | - Xinyi Wang
- School of Biological Sciences and Medical EngineeringSoutheast UniversityNanjingChina
- Child Development and Learning ScienceKey Laboratory of Ministry of EducationBeijingChina
| | - Zhijian Yao
- Department of PsychiatryThe Affiliated Nanjing Brain Hospital of Nanjing Medical UniversityNanjingChina
- Nanjing Brain HospitalMedical School of Nanjing UniversityNanjingChina
| | - Qing Lu
- School of Biological Sciences and Medical EngineeringSoutheast UniversityNanjingChina
- Child Development and Learning ScienceKey Laboratory of Ministry of EducationBeijingChina
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13
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Yang Y, Ye C, Ma T. A deep connectome learning network using graph convolution for connectome-disease association study. Neural Netw 2023; 164:91-104. [PMID: 37148611 DOI: 10.1016/j.neunet.2023.04.025] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 02/01/2023] [Accepted: 04/16/2023] [Indexed: 05/08/2023]
Abstract
Multivariate analysis approaches provide insights into the identification of phenotype associations in brain connectome data. In recent years, deep learning methods including convolutional neural network (CNN) and graph neural network (GNN), have shifted the development of connectome-wide association studies (CWAS) and made breakthroughs for connectome representation learning by leveraging deep embedded features. However, most existing studies remain limited by potentially ignoring the exploration of region-specific features, which play a key role in distinguishing brain disorders with high intra-class variations, such as autism spectrum disorder (ASD), and attention deficit hyperactivity disorder (ADHD). Here, we propose a multivariate distance-based connectome network (MDCN) that addresses the local specificity problem by efficient parcellation-wise learning, as well as associating population and parcellation dependencies to map individual differences. The approach incorporating an explainable method, parcellation-wise gradient and class activation map (p-GradCAM), is feasible for identifying individual patterns of interest and pinpointing connectome associations with diseases. We demonstrate the utility of our method on two largely aggregated multicenter public datasets by distinguishing ASD and ADHD from healthy controls and assessing their associations with underlying diseases. Extensive experiments have demonstrated the superiority of MDCN in classification and interpretation, where MDCN outperformed competitive state-of-the-art methods and achieved a high proportion of overlap with previous findings. As a CWAS-guided deep learning method, our proposed MDCN framework may narrow the bridge between deep learning and CWAS approaches, and provide new insights for connectome-wide association studies.
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Affiliation(s)
- Yanwu Yang
- Department of Electronic and Information Engineering, Harbin Institute of Technology at Shenzhen, Shenzhen, China; Peng Cheng Laboratory, Shenzhen, China.
| | - Chenfei Ye
- Peng Cheng Laboratory, Shenzhen, China; International Research Institute for Artificial Intelligence, Harbin Institute of Technology at Shenzhen, Shenzhen, China.
| | - Ting Ma
- Department of Electronic and Information Engineering, Harbin Institute of Technology at Shenzhen, Shenzhen, China; Peng Cheng Laboratory, Shenzhen, China; International Research Institute for Artificial Intelligence, Harbin Institute of Technology at Shenzhen, Shenzhen, China; Guangdong Provincial Key Laboratory of Aerospace Communication and Networking Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, China.
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14
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Taylor JJ, Lin C, Talmasov D, Ferguson MA, Schaper FLWVJ, Jiang J, Goodkind M, Grafman J, Etkin A, Siddiqi SH, Fox MD. A transdiagnostic network for psychiatric illness derived from atrophy and lesions. Nat Hum Behav 2023; 7:420-429. [PMID: 36635585 PMCID: PMC10236501 DOI: 10.1038/s41562-022-01501-9] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 11/23/2022] [Indexed: 01/13/2023]
Abstract
Psychiatric disorders share neurobiology and frequently co-occur. This neurobiological and clinical overlap highlights opportunities for transdiagnostic treatments. In this study, we used coordinate and lesion network mapping to test for a shared brain network across psychiatric disorders. In our meta-analysis of 193 studies, atrophy coordinates across six psychiatric disorders mapped to a common brain network defined by positive connectivity to anterior cingulate and insula, and by negative connectivity to posterior parietal and lateral occipital cortex. This network was robust to leave-one-diagnosis-out cross-validation and specific to atrophy coordinates from psychiatric versus neurodegenerative disorders (72 studies). In 194 patients with penetrating head trauma, lesion damage to this network correlated with the number of post-lesion psychiatric diagnoses. Neurosurgical ablation targets for psychiatric illness (four targets) also aligned with the network. This convergent brain network for psychiatric illness may partially explain high rates of psychiatric comorbidity and could highlight neuromodulation targets for patients with more than one psychiatric disorder.
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Affiliation(s)
- Joseph J Taylor
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Christopher Lin
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Daniel Talmasov
- Departments of Neurology and Psychiatry, Columbia University Medical Center, Columbia University College of Physicians and Surgeons, New York, NY, USA
| | - Michael A Ferguson
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Center for the Study of World Religions, Harvard Divinity School, Cambridge, MA, USA
| | - Frederic L W V J Schaper
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jing Jiang
- Stead Family Department of Pediatrics, University of Iowa Carver College of Medicine, Iowa City, IA, USA
- Iowa Neuroscience Institute, University of Iowa Carver College of Medicine, Iowa City, IA, USA
| | - Madeleine Goodkind
- Departments of Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, NM, USA
- New Mexico Veterans Affairs Healthcare System, Albuquerque, NM, USA
| | - Jordan Grafman
- Departments of Physical Medicine and Rehabilitation, Neurology, & Psychiatry, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Shirley Ryan Ability Lab, Chicago, IL, USA
| | - Amit Etkin
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Wu Tsai Neurosciences Institute at Stanford, Stanford University School of Medicine, Stanford, CA, USA
- Alto Neuroscience, Los Altos, CA, USA
| | - Shan H Siddiqi
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michael D Fox
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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15
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Mehta K, Pines A, Adebimpe A, Larsen B, Bassett DS, Calkins ME, Baller E, Gell M, Patrick LM, Gur RE, Gur RC, Roalf DR, Romer D, Wolf DH, Kable JW, Satterthwaite TD. Individual Differences in Delay Discounting are Associated with Dorsal Prefrontal Cortex Connectivity in Youth. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.25.525577. [PMID: 36747838 PMCID: PMC9900814 DOI: 10.1101/2023.01.25.525577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Delay discounting is a measure of impulsive choice relevant in adolescence as it predicts many real-life outcomes, including substance use disorders, obesity, and academic achievement. However, the functional networks underlying individual differences in delay discounting during youth remain incompletely described. Here we investigate the association between multivariate patterns of functional connectivity and individual differences in impulsive choice in a large sample of youth. A total of 293 youth (9-23 years) completed a delay discounting task and underwent resting-state fMRI at 3T. A connectome-wide analysis using multivariate distance-based matrix regression was used to examine whole-brain relationships between delay discounting and functional connectivity was then performed. These analyses revealed that individual differences in delay discounting were associated with patterns of connectivity emanating from the left dorsal prefrontal cortex, a hub of the default mode network. Delay discounting was associated with greater functional connectivity between the dorsal prefrontal cortex and other parts of the default mode network, and reduced connectivity with regions in the dorsal and ventral attention networks. These results suggest that delay discounting in youth is associated with individual differences in relationships both within the default mode network and between the default mode and networks involved in attentional and cognitive control.
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Affiliation(s)
- Kahini Mehta
- Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA,Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Adam Pines
- Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA,Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Azeez Adebimpe
- Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA,Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Bart Larsen
- Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA,Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Dani S. Bassett
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, PA 19104, USA,Department of Electrical & Systems Engineering, University of Pennsylvania, PA 19104, USA,Department of Neurology, University of Pennsylvania, Philadelphia, PA, 19104, USA,Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, PA, 19104, USA,Santa Fe Institute, Santa Fe, NM, 87051, USA
| | - Monica E. Calkins
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Erica Baller
- Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA,Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Martin Gell
- Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA,Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen University, Aachen, Germany,Institute of Neuroscience and Medicine (INM-7: Brain & Behaviour), Research Centre Jülich, Jülich, Germany
| | - Lauren M. Patrick
- Department of Psychology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Raquel E. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA,Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA 19104, USA,Department of Neurology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Ruben C. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA,Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA 19104, USA,Department of Neurology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - David R. Roalf
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Daniel Romer
- Annenberg Public Policy Center, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Daniel H. Wolf
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Joseph W. Kable
- Department of Psychology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Theodore D. Satterthwaite
- Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA,Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA,Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA 19104, USA
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16
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Li R, Shen F, Sun X, Zou T, Li L, Wang X, Deng C, Duan X, He Z, Yang M, Li Z, Chen H. Dissociable salience and default mode network modulation in generalized anxiety disorder: a connectome-wide association study. Cereb Cortex 2023; 33:6354-6365. [PMID: 36627243 DOI: 10.1093/cercor/bhac509] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 11/30/2022] [Accepted: 12/01/2022] [Indexed: 01/12/2023] Open
Abstract
Generalized anxiety disorder (GAD) is a common anxiety disorder experiencing psychological and somatic symptoms. Here, we explored the link between the individual variation in functional connectome and anxiety symptoms, especially psychological and somatic dimensions, which remains unknown. In a sample of 118 GAD patients and matched 85 healthy controls (HCs), we used multivariate distance-based matrix regression to examine the relationship between resting-state functional connectivity (FC) and the severity of anxiety. We identified multiple hub regions belonging to salience network (SN) and default mode network (DMN) where dysconnectivity associated with anxiety symptoms (P < 0.05, false discovery rate [FDR]-corrected). Follow-up analyses revealed that patient's psychological anxiety was dominated by the hyper-connectivity within DMN, whereas the somatic anxiety could be modulated by hyper-connectivity within SN and DMN. Moreover, hypo-connectivity between SN and DMN were related to both anxiety dimensions. Furthermore, GAD patients showed significant network-level FC changes compared with HCs (P < 0.01, FDR-corrected). Finally, we found the connectivity of DMN could predict the individual psychological symptom in an independent GAD sample. Together, our work emphasizes the potential dissociable roles of SN and DMN in the pathophysiology of GAD's anxiety symptoms, which may be crucial in providing a promising neuroimaging biomarker for novel personalized treatment strategies.
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Affiliation(s)
- Rong Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P.R. China
| | - Fei Shen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P.R. China
| | - Xiyue Sun
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P.R. China
| | - Ting Zou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P.R. China
| | - Liyuan Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P.R. China
| | - Xuyang Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P.R. China
| | - Chijun Deng
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P.R. China
| | - Xujun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P.R. China
| | - Zongling He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P.R. China
| | - Mi Yang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P.R. China
| | - Zezhi Li
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou 510370, P.R. China
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P.R. China
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17
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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: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 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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18
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Sheng W, Cui Q, Jiang K, Chen Y, Tang Q, Wang C, Fan Y, Guo J, Lu F, He Z, Chen H. Individual variation in brain network topology is linked to course of illness in major depressive disorder. Cereb Cortex 2022; 32:5301-5310. [PMID: 35152289 DOI: 10.1093/cercor/bhac015] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2021] [Revised: 12/09/2021] [Accepted: 01/13/2022] [Indexed: 12/27/2022] Open
Abstract
Major depressive disorder (MDD) is a chronic and highly recurrent disorder. The functional connectivity in depression is affected by the cumulative effect of course of illness. However, previous neuroimaging studies on abnormal functional connection have not mainly focused on the disease duration, which is seen as a secondary factor. Here, we used a data-driven analysis (multivariate distance matrix regression) to examine the relationship between the course of illness and resting-state functional dysconnectivity in MDD. This method identified a region in the anterior cingulate cortex, which is most linked to course of illness. Specifically, follow-up seed analyses show this phenomenon resulted from the individual differences in the topological distribution of three networks. In individuals with short-duration MDD, the connection to the default mode network was strong. By contrast, individuals with long-duration MDD showed hyperconnectivity to the ventral attention network and the frontoparietal network. These results emphasized the centrality of the anterior cingulate cortex in the pathophysiology of the increased course of illness and implied critical links between network topography and pathological duration. Thus, dissociable patterns of connectivity of the anterior cingulate cortex is an important dimension feature of the disease process of depression.
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Affiliation(s)
- Wei Sheng
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China.,MOE Key Lab for Neuroinformation, High Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Qian Cui
- School of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Kexing Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Yuyan Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Qin Tang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Chong Wang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Yunshuang Fan
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Jing Guo
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Fengmei Lu
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Zongling He
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China.,MOE Key Lab for Neuroinformation, High Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 611731, China
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19
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Lu S, Shao J, Feng Q, Wu C, Fang Z, Jia L, Wang Z, Hu S, Xu Y, Huang M. Aberrant interhemispheric functional connectivity in major depressive disorder with and without anhedonia. BMC Psychiatry 2022; 22:688. [PMID: 36348342 PMCID: PMC9644581 DOI: 10.1186/s12888-022-04343-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 10/27/2022] [Indexed: 11/11/2022] Open
Abstract
OBJECTIVE Anhedonia is a core feature of major depressive disorder (MDD), and as a subtype of depression, MDD with anhedonia may have exceptional neurobiological mechanisms. However, the neuropathology of anhedonia in MDD remains unclear. Thus, this study aimed to investigate the brain functional differences between MDD with and without anhedonia. METHODS A total of 62 individuals including 22 MDD patients with anhedonia, 20 MDD patients without anhedonia, and 20 healthy controls (HCs) were recruited for this study. All participants underwent 3.0-T functional magnetic resonance imaging scan. Voxel-mirrored homotopic connectivity (VMHC) was employed to quantitatively describe bilateral functional connectivity. Analyses of variance (ANOVA) were performed to obtain brain regions with significant differences among three groups and then post hoc tests were calculated for inter-group comparisons. RESULTS The ANOVA revealed significant VMHC differences among three groups in the bilateral middle temporal gyrus (MTG), superior frontal gyrus (SFG), and inferior parietal lobule (IPL) (F = 10.47 ~ 15.09, p < 0.05, AlphaSim corrected). Relative to HCs, MDD with anhedonia showed significantly decreased VMHC in the bilateral MTG (t = -5.368, p < 0.05, AlphaSim corrected), as well as increased VMHC in the bilateral SFG (t = -4.696, p < 0.05, AlphaSim corrected). Compared to MDD without anhedonia, MDD with anhedonia showed significantly decreased VMHC in the bilateral MTG and IPL (t = -5.629 ~ -4.330, p < 0.05, AlphaSim corrected), while increased VMHC in the bilateral SFG (t = 3.926, p < 0.05, AlphaSim corrected). However, no significant difference was found between MDD without anhedonia and HCs. CONCLUSION The present findings suggest that MDD with and without anhedonia exhibit different patterns of interhemispheric connectivity. Anhedonia in MDD is related to aberrant interhemispheric connectivity within brain regions involved in the frontal-temporal-parietal circuit.
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Affiliation(s)
- Shaojia Lu
- grid.13402.340000 0004 1759 700XDepartment of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory of Mental Disorder’s Management of Zhejiang Province, Zhejiang Engineering Center for Mathematical Mental Health, Hangzhou, Zhejiang China
| | - Jiamin Shao
- grid.13402.340000 0004 1759 700XDepartment of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory of Mental Disorder’s Management of Zhejiang Province, Zhejiang Engineering Center for Mathematical Mental Health, Hangzhou, Zhejiang China ,grid.13402.340000 0004 1759 700XFaculty of Clinical Medicine, Zhejiang University School of Medicine, Hangzhou, Zhejiang China
| | - Qian Feng
- grid.13402.340000 0004 1759 700XDepartment of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory of Mental Disorder’s Management of Zhejiang Province, Zhejiang Engineering Center for Mathematical Mental Health, Hangzhou, Zhejiang China ,grid.13402.340000 0004 1759 700XFaculty of Clinical Medicine, Zhejiang University School of Medicine, Hangzhou, Zhejiang China
| | - Congchong Wu
- grid.13402.340000 0004 1759 700XDepartment of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory of Mental Disorder’s Management of Zhejiang Province, Zhejiang Engineering Center for Mathematical Mental Health, Hangzhou, Zhejiang China ,grid.13402.340000 0004 1759 700XFaculty of Clinical Medicine, Zhejiang University School of Medicine, Hangzhou, Zhejiang China
| | - Zhe Fang
- grid.13402.340000 0004 1759 700XDepartment of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory of Mental Disorder’s Management of Zhejiang Province, Zhejiang Engineering Center for Mathematical Mental Health, Hangzhou, Zhejiang China ,grid.13402.340000 0004 1759 700XFaculty of Clinical Medicine, Zhejiang University School of Medicine, Hangzhou, Zhejiang China
| | - Lili Jia
- grid.13402.340000 0004 1759 700XDepartment of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory of Mental Disorder’s Management of Zhejiang Province, Zhejiang Engineering Center for Mathematical Mental Health, Hangzhou, Zhejiang China ,grid.13402.340000 0004 1759 700XFaculty of Clinical Medicine, Zhejiang University School of Medicine, Hangzhou, Zhejiang China ,Department of Clinical Psychology, The Fifth Peoples’ Hospital of Lin’an District, Hangzhou, Zhejiang China
| | - Zheng Wang
- grid.13402.340000 0004 1759 700XDepartment of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory of Mental Disorder’s Management of Zhejiang Province, Zhejiang Engineering Center for Mathematical Mental Health, Hangzhou, Zhejiang China
| | - Shaohua Hu
- grid.13402.340000 0004 1759 700XDepartment of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory of Mental Disorder’s Management of Zhejiang Province, Zhejiang Engineering Center for Mathematical Mental Health, Hangzhou, Zhejiang China
| | - Yi Xu
- Department of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory of Mental Disorder's Management of Zhejiang Province, Zhejiang Engineering Center for Mathematical Mental Health, Hangzhou, Zhejiang, China.
| | - Manli Huang
- Department of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory of Mental Disorder's Management of Zhejiang Province, Zhejiang Engineering Center for Mathematical Mental Health, Hangzhou, Zhejiang, China.
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20
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Oestreich LKL, Wright P, O’Sullivan MJ. Hyperconnectivity and altered interactions of a nucleus accumbens network in post-stroke depression. Brain Commun 2022; 4:fcac281. [PMCID: PMC9677459 DOI: 10.1093/braincomms/fcac281] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 08/30/2022] [Accepted: 10/31/2022] [Indexed: 11/22/2022] Open
Abstract
Abstract
Post-stroke depression is a common complication of stroke. To date, no consistent locus of injury is associated with this complication. Here, we probed network dynamics and structural alterations in post-stroke depression in four functional circuits linked to major depressive disorder and a visual network, which served as a control network. Forty-four participants with recent stroke (mean age = 69.03, standard deviation age = 8.59, age range = 51–86 and gender: female = 10) and 16 healthy volunteers (mean age = 71.53, standard deviation age = 10.62, age range = 51–84 and gender: female = 11) were imaged with 3-Tesla structural, diffusion and resting-state functional MRI. The Geriatric Depression Scale was administered to measure depression severity. Associations between depression severity and functional connectivity were investigated within networks seeded from nucleus accumbens, amygdala, dorsolateral prefrontal cortex and primary visual cortex. In addition, the default mode network was identified by connectivity with medial prefrontal cortex and posterior cingulate cortex. Circuits that exhibited altered activity associated with depression severity were further investigated by extracting within-network volumetric and microstructural measures from structural images. In the stroke group, functional connectivity within the nucleus accumbens-seeded network (left hemisphere: P = 0.001; and right hemisphere: P = 0.004) and default mode network (cluster one: P < 0.001; and cluster two: P < 0.001) correlated positively with depressive symptoms. Normal anticorrelations between these two networks were absent in patients with post-stroke depression. Grey matter volume of the right posterior cingulate cortex (Pearson correlation coefficient = −0.286, P = 0.03), as well as microstructural measures in the posterior cingulate cortex (right: Pearson correlation coefficient = 0.4, P = 0.024; and left: Pearson correlation coefficient = 0.3, P = 0.048), right medial prefrontal cortex (Pearson correlation coefficient = 0.312, P = 0.039) and the medial forebrain bundle (Pearson correlation coefficient = 0.450, P = 0.003), a major projection pathway interconnecting the nucleus accumbens-seeded network and linking to medial prefrontal cortex, were associated with depression severity. Depression after stroke is marked by reduced mutual inhibition between functional circuits involving nucleus accumbens and default mode network as well as volumetric and microstructural changes within these networks. Aberrant network dynamics present in patients with post-stroke depression are therefore likely to be influenced by secondary, pervasive alterations in grey and white matter, remote from the site of injury.
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Affiliation(s)
- Lena K L Oestreich
- UQ Centre for Clinical Research, The University of Queensland , Brisbane 4072 , Australia
- Centre for Advanced Imaging, The University of Queensland , Brisbane 4072 , Australia
| | - Paul Wright
- Biomedical Engineering Department, King’s College London , London , UK
| | - Michael J O’Sullivan
- UQ Centre for Clinical Research, The University of Queensland , Brisbane 4072 , Australia
- Biomedical Engineering Department, King’s College London , London , UK
- Department of Neurology, Royal Brisbane and Women’s Hospital , Brisbane 4072 , Australia
- Institute of Molecular Bioscience, The University of Queensland , Brisbane 4072 , Australia
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21
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Wang K, He Q, Zhu X, Hu Y, Yao Y, Hommel B, Beste C, Liu J, Yang Y, Zhang W. Smaller putamen volumes are associated with greater problems in external emotional regulation in depressed adolescents with nonsuicidal self-injury. J Psychiatr Res 2022; 155:338-346. [PMID: 36179414 DOI: 10.1016/j.jpsychires.2022.09.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 08/17/2022] [Accepted: 09/16/2022] [Indexed: 10/31/2022]
Abstract
The functions of nonsuicidal self-injury (NSSI) consist of social and emotional aspects (Social influence, Sensation seeking, Internal and External emotion regulation). Previous studies have indicated that dysfunction in reward-related brain structures especially the striatum might drive this habitual behavior. However, no studies to date have investigated the associations between striatum and different functions for adolescents engaging in NSSI behaviors. Here, we recruited 35 depressed adolescents with recent NSSI behaviors and 36 healthy controls and acquired structural brain images, depressive symptoms, social, academic and family environments assessments, in addition to NSSI functions in patients only. Subcortical volumes and cortical thickness were estimated with FreeSurfer. Mixed linear regressions were performed to examine associations between striatal structures (caudate, putamen, nucleus accumbens, pallidum) and NSSI functions, with age, sex, total intracranial volume, hemisphere and depression severity included as covariates. Effect of environmental factors and potential associations with cortical thickness and other subcortical volumes were also tested. We found that, among the four functions, external emotional regulation represented the main function for NSSI engagement. Increased external emotion regulation was significantly associated with smaller putamen volume. No environmental factors biased the association with putamen. No associations with other cortical or subcortical regions were observed. Our findings suggested that smaller putamen might be a biomarker of NSSI engagement for depressed adolescents when they regulated frustrated or angry emotions. The results have potentially clinical implications in early identification and brain intervention of NSSI in youth.
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Affiliation(s)
- Kangcheng Wang
- School of Psychology, Shandong Normal University, Jinan, 250358, China
| | - Qiang He
- Department of Psychiatry, School of Clinical Medicine, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China
| | - Xingxing Zhu
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Yufei Hu
- School of Psychology, Shandong Normal University, Jinan, 250358, China
| | - Yuan Yao
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, 250012, China
| | - Bernhard Hommel
- School of Psychology, Shandong Normal University, Jinan, 250358, China; Cognitive Psychology Unit, & Leiden Institute for Brain & Cognition, Institute of Psychology, Leiden University, Netherlands; Department of Child and Adolescent Psychiatry, TU Dresden, Germany
| | - Christian Beste
- School of Psychology, Shandong Normal University, Jinan, 250358, China; Department of Child and Adolescent Psychiatry, TU Dresden, Germany; University Neuropsychology Center, TU Dresden, Germany
| | - Jintong Liu
- Department of Psychiatry, School of Clinical Medicine, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China; Childhood Psychiatry Unit, Shandong Mental Health Center, Jinan, 250014, China
| | - Ying Yang
- Department of Psychiatry, School of Clinical Medicine, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China; Childhood Psychiatry Unit, Shandong Mental Health Center, Jinan, 250014, China.
| | - Wenxin Zhang
- School of Psychology, Shandong Normal University, Jinan, 250358, China.
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22
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Mendelian randomization analyses support causal relationships between brain imaging-derived phenotypes and risk of psychiatric disorders. Nat Neurosci 2022; 25:1519-1527. [PMID: 36216997 DOI: 10.1038/s41593-022-01174-7] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Accepted: 08/29/2022] [Indexed: 01/13/2023]
Abstract
Observational studies have reported the correlations between brain imaging-derived phenotypes (IDPs) and psychiatric disorders; however, whether the relationships are causal is uncertain. We conducted bidirectional two-sample Mendelian randomization (MR) analyses to explore the causalities between 587 reliable IDPs (N = 33,224 individuals) and 10 psychiatric disorders (N = 9,725 to 161,405). We identified nine IDPs for which there was evidence of a causal influence on risk of schizophrenia, anorexia nervosa and bipolar disorder. For example, 1 s.d. increase in the orientation dispersion index of the forceps major was associated with 32% lower odds of schizophrenia risk. Reverse MR indicated that only genetically predicted schizophrenia was positively associated with two IDPs, the cortical surface area and the volume of the right pars orbitalis. We established the BrainMR database ( http://www.bigc.online/BrainMR/ ) to share our results. Our findings provide potential strategies for the prediction and intervention for psychiatric disorder risk at the brain-imaging level.
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23
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Souther MK, Wolf DH, Kazinka R, Lee S, Ruparel K, Elliott MA, Xu A, Cieslak M, Prettyman G, Satterthwaite TD, Kable JW. Decision value signals in the ventromedial prefrontal cortex and motivational and hedonic symptoms across mood and psychotic disorders. Neuroimage Clin 2022; 36:103227. [PMID: 36242852 PMCID: PMC9668619 DOI: 10.1016/j.nicl.2022.103227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 10/05/2022] [Accepted: 10/08/2022] [Indexed: 11/11/2022]
Abstract
Deficits in motivation and pleasure are common across many psychiatric disorders, and manifest as symptoms of amotivation and anhedonia, which are prominent features of both mood and psychotic disorders. Here we provide evidence for an association between neural value signals and symptoms of amotivation and anhedonia across adults with major depression, bipolar disorder, schizophrenia, or no psychiatric diagnosis. We found that value signals in the ventromedial prefrontal cortex (vmPFC) during intertemporal decision-making were dampened in individuals with greater motivational and hedonic deficits, after accounting for primary diagnosis. This relationship remained significant while controlling for diagnosis-specific symptoms of mood and psychosis, such as depression as well as positive and negative symptoms. Our results demonstrate that dysfunction in the vmPFC during value-based decision-making is specifically linked to motivational and hedonic impairments. These findings provide a quantitative neural target for the potential development of novel treatments for amotivation and anhedonia.
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Affiliation(s)
- Min K Souther
- Department of Psychology, University of Pennsylvania, US.
| | - Daniel H Wolf
- Department of Psychiatry, Perelman School of Medicine, US
| | - Rebecca Kazinka
- Department of Psychology, University of Pennsylvania, US; Department of Psychiatry, University of Minnesota, US
| | - Sangil Lee
- Department of Psychology, University of Pennsylvania, US
| | - Kosha Ruparel
- Department of Psychiatry, Perelman School of Medicine, US
| | | | - Anna Xu
- Department of Psychiatry, Perelman School of Medicine, US
| | | | | | - Theodore D Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, US; Penn-CHOP Lifespan Brain Institute, US
| | - Joseph W Kable
- Department of Psychology, University of Pennsylvania, US
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24
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Nunez C, Hoots JK, Schepers ST, Bower M, de Wit H, Wardle MC. Pharmacological investigations of effort-based decision-making in humans: Naltrexone and nicotine. PLoS One 2022; 17:e0275027. [PMID: 36197897 PMCID: PMC9534411 DOI: 10.1371/journal.pone.0275027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 09/08/2022] [Indexed: 11/19/2022] Open
Abstract
Many mental health disorders are characterized by an impaired ability, or willingness, to exert effort to obtain rewards. This impairment is modeled in effort-based decision tasks, and neuropharmacological studies implicate dopamine in this process. However, other transmitter systems such as opioidergic and cholinergic systems have received less attention. Here, in two separate studies we tested the acute effects of naltrexone and nicotine on effort-based decision-making in healthy adults. In Study 1, we compared naltrexone (50mg and 25mg) to placebo, and in Study 2, a pilot study, we compared nicotine (7mg) to placebo. In both studies, participants completed the Effort Expenditure for Rewards Task (EEfRT), which measured effort-based decision-making related to monetary rewards. Although subjects expended greater effort for larger reward magnitude and when there was a higher probability of receiving the reward, neither naltrexone nor nicotine affected willingness to exert effort for monetary rewards. Although the drugs produced significant and typical drug effects on measures of mood and behavior, they did not alter effort-based decision-making. This has implications both for the clinical use of these drugs, as well as for understanding the neuropharmacology of effort-related behavior.
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Affiliation(s)
- Cecilia Nunez
- Department of Psychology, University of Illinois Chicago, Chicago, Illinois, United States of America
| | - Jennifer K. Hoots
- Department of Psychology, University of Illinois Chicago, Chicago, Illinois, United States of America
| | - Scott T. Schepers
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, Illinois, United States of America
| | - Michael Bower
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, Illinois, United States of America
| | - Harriet de Wit
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, Illinois, United States of America
| | - Margaret C. Wardle
- Department of Psychology, University of Illinois Chicago, Chicago, Illinois, United States of America
- * E-mail:
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25
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Kroemer NB, Opel N, Teckentrup V, Li M, Grotegerd D, Meinert S, Lemke H, Kircher T, Nenadić I, Krug A, Jansen A, Sommer J, Steinsträter O, Small DM, Dannlowski U, Walter M. Functional Connectivity of the Nucleus Accumbens and Changes in Appetite in Patients With Depression. JAMA Psychiatry 2022; 79:993-1003. [PMID: 36001327 PMCID: PMC9403857 DOI: 10.1001/jamapsychiatry.2022.2464] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 06/14/2022] [Indexed: 11/14/2022]
Abstract
Importance Major depressive disorder (MDD) is characterized by a substantial burden on health, including changes in appetite and body weight. Heterogeneity of depressive symptoms has hampered the identification of biomarkers that robustly generalize to most patients, thus calling for symptom-based mapping. Objective To define the functional architecture of the reward circuit subserving increases vs decreases in appetite and body weight in patients with MDD by specifying their contributions and influence on disease biomarkers using resting-state functional connectivity (FC). Design, Setting, and Participants In this case-control study, functional magnetic resonance imaging (fMRI) data were taken from the Marburg-Münster FOR 2107 Affective Disorder Cohort Study (MACS), collected between September 2014 and November 2016. Cross-sectional data of patients with MDD (n = 407) and healthy control participants (n = 400) were analyzed from March 2018 to June 2022. Main Outcomes and Measures Changes in appetite during the depressive episode and their association with FC were examined using fMRI. By taking the nucleus accumbens (NAcc) as seed of the reward circuit, associations with opposing changes in appetite were mapped, and a sparse symptom-specific elastic-net model was built with 10-fold cross-validation. Results Among 407 patients with MDD, 249 (61.2%) were women, and the mean (SD) age was 36.79 (13.4) years. Reduced NAcc-based FC to the ventromedial prefrontal cortex (vmPFC) and the hippocampus was associated with reduced appetite (vmPFC: bootstrap r = 0.13; 95% CI, 0.02-0.23; hippocampus: bootstrap r = 0.15; 95% CI, 0.05-0.26). In contrast, reduced NAcc-based FC to the insular ingestive cortex was associated with increased appetite (bootstrap r = -0.14; 95% CI, -0.24 to -0.04). Critically, the cross-validated elastic-net model reflected changes in appetite based on NAcc FC and explained variance increased with increasing symptom severity (all patients: bootstrap r = 0.24; 95% CI, 0.16-0.31; patients with Beck Depression Inventory score of 28 or greater: bootstrap r = 0.42; 95% CI, 0.25-0.58). In contrast, NAcc FC did not classify diagnosis (MDD vs healthy control). Conclusions and Relevance In this study, NAcc-based FC reflected important individual differences in appetite and body weight in patients with depression that can be leveraged for personalized prediction. However, classification of diagnosis using NAcc-based FC did not exceed chance levels. Such symptom-specific associations emphasize the need to map biomarkers onto more confined facets of psychopathology to improve the classification and treatment of MDD.
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Affiliation(s)
- Nils B. Kroemer
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health, University of Tübingen, Tübingen, Germany
- Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
| | - Nils Opel
- Department of Psychiatry and Psychotherapy, University Hospital Jena, Jena, Germany
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Vanessa Teckentrup
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health, University of Tübingen, Tübingen, Germany
- Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Meng Li
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health, University of Tübingen, Tübingen, Germany
- Department of Psychiatry and Psychotherapy, University Hospital Jena, Jena, Germany
- Department of Psychiatry and Psychotherapy, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Hannah Lemke
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Axel Krug
- Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Jens Sommer
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Olaf Steinsträter
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Dana M. Small
- Departments of Psychiatry and Psychology, Yale University, New Haven, Connecticut
- Modern Diet and Physiology Research Center, Yale University, New Haven, Connecticut
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Martin Walter
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health, University of Tübingen, Tübingen, Germany
- Department of Psychiatry and Psychotherapy, University Hospital Jena, Jena, Germany
- Department of Psychiatry and Psychotherapy, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
- Leibniz Institute for Neurobiology, Magdeburg, Germany
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26
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Millman ZB, Roemer C, Vargas T, Schiffman J, Mittal VA, Gold JM. Neuropsychological Performance Among Individuals at Clinical High-Risk for Psychosis vs Putatively Low-Risk Peers With Other Psychopathology: A Systematic Review and Meta-Analysis. Schizophr Bull 2022; 48:999-1010. [PMID: 35333372 PMCID: PMC9434467 DOI: 10.1093/schbul/sbac031] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
BACKGROUND AND HYPOTHESIS Youth at clinical high-risk (CHR) for psychosis present with neuropsychological impairments relative to healthy controls (HC), but whether these impairments are distinguishable from those seen among putatively lower risk peers with other psychopathology remains unknown. We hypothesized that any excess impairment among CHR cohorts beyond that seen in other clinical groups is minimal and accounted for by the proportion who transition to psychosis (CHR-T). STUDY DESIGN We performed a systematic review and meta-analysis of studies comparing cognitive performance among CHR youth to clinical comparators (CC) who either sought mental health services but did not meet CHR criteria or presented with verified nonpsychotic psychopathology. STUDY RESULTS Twenty-one studies were included representing nearly 4000 participants. Individuals at CHR showed substantial cognitive impairments relative to HC (eg, global cognition: g = -0.48 [-0.60, -0.34]), but minimal impairments relative to CC (eg, global cognition: g = -0.13 [-0.20, -0.06]). Any excess impairment among CHR was almost entirely attributable to CHR-T; impairment among youth at CHR without transition (CHR-NT) was typically indistinguishable from CC (eg, global cognition, CHR-T: g = -0.42 [-0.64, -0.19], CHR-NT: g = -0.09 [-0.18, 0.00]; processing speed, CHR-T: g = -0.59 [-0.82, -0.37], CHR-NT: g = -0.12 [-0.25, 0.07]; working memory, CHR-T: g = -0.42 [-0.62, -0.22], CHR-NT: g = -0.03 [-0.14, 0.08]). CONCLUSIONS Neurocognitive impairment in CHR cohorts should be interpreted cautiously when psychosis or even CHR status is the specific clinical syndrome of interest as these impairments most likely represent a transdiagnostic vs psychosis-specific vulnerability.
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Affiliation(s)
- Zachary B Millman
- Psychotic Disorders Division, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Caroline Roemer
- Psychology Department, University of Maryland, Baltimore County, Baltimore, MD, USA
| | - Teresa Vargas
- Department of Psychology, Northwestern University, Evanston, IL, USA
| | - Jason Schiffman
- Department of Psychological Science, University of California, Irvine, CA, USA
| | - Vijay A Mittal
- Department of Psychology, Northwestern University, Evanston, IL, USA
| | - James M Gold
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, USA
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27
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Wang YY, Wang Y, Huang J, Sun XH, Wang XZ, Zhang SX, Zhu GH, Lui SSY, Cheung EFC, Sun HW, Chan RCK. Shared and distinct reward neural mechanisms among patients with schizophrenia, major depressive disorder, and bipolar disorder: an effort-based functional imaging study. Eur Arch Psychiatry Clin Neurosci 2022; 272:859-871. [PMID: 35079855 DOI: 10.1007/s00406-021-01376-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Accepted: 12/16/2021] [Indexed: 12/13/2022]
Abstract
Unwillingness to exert effort for rewards has been found in patients with schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BD), but the underlying shared and distinct reward neural mechanisms remain unclear. This study aimed to compare the neural correlates of such impairments across different diagnoses. The neural responses in an effort-expenditure for reward task (EEfRT) were assessed in 20 SCZ patients, 23 MDD patients, 17 BD patients, and 30 healthy controls (HC). The results found shared activation in the cingulate gyrus, the medial frontal gyrus, and the middle frontal gyrus during the EEfRT administration. Compared to HC, SCZ patients exhibited stronger variations of functional connectivity between the right caudate and the left amygdala, the left hippocampus and the left putamen, with increase in reward magnitude. In MDD patients, an enhanced activation compared to HC in the right superior temporal gyrus was found with the increase of reward magnitude. The variations of functional connectivity between the caudate and the right cingulate gyrus, the left postcentral gyrus and the left inferior parietal lobule with increase in reward magnitude were weaker than that found in HC. In BD patients, the degree of activation in the left precuneus was increased, but that in the left dorsolateral prefrontal cortex was decreased with increase in reward probability compared to HC. These findings demonstrate both shared and distinct reward neural mechanisms associated with EEfRT in patients with SCZ, MDD, and BD, implicating potential intervention targets to alleviate amotivation in these clinical disorders.
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Affiliation(s)
- Yan-Yu Wang
- School of Psychology, Weifang Medical University, Shandong, 261053, China
- Neuropsychology and Applied Cognitive Neuroscience Laboratory; CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, 16 Lincui Road, Beijing, 100101, China
| | - Yi Wang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory; CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, 16 Lincui Road, Beijing, 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100048, China
| | - Jia Huang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory; CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, 16 Lincui Road, Beijing, 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100048, China
| | - Xi-He Sun
- Magnetic Resonance Imaging Centre, Affiliated Hospital of Weifang Medical University, Shandong, 261031, China
| | - Xi-Zhen Wang
- Magnetic Resonance Imaging Centre, Affiliated Hospital of Weifang Medical University, Shandong, 261031, China
| | - Shu-Xian Zhang
- Magnetic Resonance Imaging Centre, Affiliated Hospital of Weifang Medical University, Shandong, 261031, China
| | - Guo-Hui Zhu
- Mental Health Centre of Weifang City, Shandong, 261071, China
| | - Simon S Y Lui
- Department of Psychiatry, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Eric F C Cheung
- Castle Peak Hospital, Hong Kong Special Administrative Region, China
| | - Hong-Wei Sun
- School of Psychology, Weifang Medical University, Shandong, 261053, China
| | - Raymond C K Chan
- Neuropsychology and Applied Cognitive Neuroscience Laboratory; CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, 16 Lincui Road, Beijing, 100101, China.
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100048, China.
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28
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Feng C, Huang W, Xu K, Stewart JL, Camilleri JA, Yang X, Wei P, Gu R, Luo W, Eickhoff SB. Neural substrates of motivational dysfunction across neuropsychiatric conditions: Evidence from meta-analysis and lesion network mapping. Clin Psychol Rev 2022; 96:102189. [PMID: 35908312 PMCID: PMC9720091 DOI: 10.1016/j.cpr.2022.102189] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 04/13/2022] [Accepted: 07/18/2022] [Indexed: 02/03/2023]
Abstract
Motivational dysfunction constitutes one of the fundamental dimensions of psychopathology cutting across traditional diagnostic boundaries. However, it is unclear whether there is a common neural circuit responsible for motivational dysfunction across neuropsychiatric conditions. To address this issue, the current study combined a meta-analysis on psychiatric neuroimaging studies of reward/loss anticipation and consumption (4308 foci, 438 contrasts, 129 publications) with a lesion network mapping approach (105 lesion cases). Our meta-analysis identified transdiagnostic hypoactivation in the ventral striatum (VS) for clinical/at-risk conditions compared to controls during the anticipation of both reward and loss. Moreover, the VS subserves a key node in a distributed brain network which encompasses heterogeneous lesion locations causing motivation-related symptoms. These findings do not only provide the first meta-analytic evidence of shared neural alternations linked to anticipatory motivation-related deficits, but also shed novel light on the role of VS dysfunction in motivational impairments in terms of both network integration and psychological functions. Particularly, the current findings suggest that motivational dysfunction across neuropsychiatric conditions is rooted in disruptions of a common brain network anchored in the VS, which contributes to motivational salience processing rather than encoding positive incentive values.
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Affiliation(s)
- Chunliang Feng
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education (South China Normal University), Guangzhou, China,Guangdong Provincial Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou, China,Corresponding authors at: Guangdong Provincial Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou 510631, China; Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China. (C. Feng), (R. Gu)
| | - Wenhao Huang
- Beijing Key Laboratory of Learning and Cognition, and School of Psychology, Capital Normal University, Beijing, China,Department of Decision Neuroscience and Nutrition, German Institute of Human Nutrition (DIfE), Potsdam-Rehbrücke, Germany
| | - Kangli Xu
- The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, China
| | | | - Julia A. Camilleri
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany,Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Xiaofeng Yang
- The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, China
| | - Ping Wei
- Beijing Key Laboratory of Learning and Cognition, and School of Psychology, Capital Normal University, Beijing, China
| | - Ruolei Gu
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China,Corresponding authors at: Guangdong Provincial Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou 510631, China; Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China. (C. Feng), (R. Gu)
| | - Wenbo Luo
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian, China
| | - Simon B. Eickhoff
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany,Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
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29
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Altered brain activation during reward anticipation in bipolar disorder. Transl Psychiatry 2022; 12:300. [PMID: 35902559 PMCID: PMC9334601 DOI: 10.1038/s41398-022-02075-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 07/15/2022] [Accepted: 07/19/2022] [Indexed: 02/05/2023] Open
Abstract
Although altered reward sensitivity has been observed in individuals with bipolar disorder (BD), the brain function findings related to reward processing remain unexplored and inconsistent. This meta-analysis aimed to identify brain activation alterations underlying reward anticipation in BD. A systematic literature research was conducted to identify fMRI studies of reward-relevant tasks performed by BD individuals. Using Anisotropic Effect Size Signed Differential Mapping, whole-brain and ROI of the ventral striatum (VS) coordinate-based meta-analyses were performed to explore brain regions showing anomalous activation in individuals with BD compared to healthy controls (HC), respectively. A total of 21 studies were identified in the meta-analysis, 15 of which were included in the whole-brain meta-analysis and 17 in the ROI meta-analysis. The whole-brain meta-analysis revealed hypoactivation in the bilateral angular gyrus and right inferior frontal gyrus during reward anticipation in individuals with BD compared to HC. No significant activation differences were observed in bilateral VS between two groups by whole-brain or ROI-based meta-analysis. Individuals with BD type I and individuals with euthymic BD showed altered activation in prefrontal, angular, fusiform, middle occipital gyrus, and striatum. Hypoactivation in the right angular gyrus was positively correlated with the illness duration of BD. The present study reveals the potential neural mechanism underlying impairment in reward anticipation in BD. Some clinical features such as clinical subtype, mood state, and duration of illness confound the underlying neurobiological abnormality reward anticipation in BD. These findings may have implications for identifying clinically relevant biomarkers to guide intervention strategies for BD.
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30
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Parr AC, Calancie OG, Coe BC, Khalid-Khan S, Munoz DP. Impulsivity and Emotional Dysregulation Predict Choice Behavior During a Mixed-Strategy Game in Adolescents With Borderline Personality Disorder. Front Neurosci 2022; 15:667399. [PMID: 35237117 PMCID: PMC8882924 DOI: 10.3389/fnins.2021.667399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Accepted: 12/28/2021] [Indexed: 11/13/2022] Open
Abstract
Impulsivity and emotional dysregulation are two core features of borderline personality disorder (BPD), and the neural mechanisms recruited during mixed-strategy interactions overlap with frontolimbic networks that have been implicated in BPD. We investigated strategic choice patterns during the classic two-player game, Matching Pennies, where the most efficient strategy is to choose each option randomly from trial-to-trial to avoid exploitation by one’s opponent. Twenty-seven female adolescents with BPD (mean age: 16 years) and twenty-seven age-matched female controls (mean age: 16 years) participated in an experiment that explored the relationship between strategic choice behavior and impulsivity in both groups and emotional dysregulation in BPD. Relative to controls, BPD participants showed marginally fewer reinforcement learning biases, particularly decreased lose-shift biases, increased variability in reaction times (coefficient of variation; CV), and a greater percentage of anticipatory decisions. A subset of BPD participants with high levels of impulsivity showed higher overall reward rates, and greater modulation of reaction times by outcome, particularly following loss trials, relative to control and BPD participants with lower levels of impulsivity. Additionally, BPD participants with higher levels of emotional dysregulation showed marginally increased reward rate and increased entropy in choice patterns. Together, our preliminary results suggest that impulsivity and emotional dysregulation may contribute to variability in mixed-strategy decision-making in female adolescents with BPD.
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Affiliation(s)
- Ashley C. Parr
- Centre for Neuroscience Studies, Queen’s University, Kingston, ON, Canada
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
- Division of Child and Youth Mental Health, Kingston Health Sciences Centre, Kingston, ON, Canada
- *Correspondence: Ashley C. Parr,
| | - Olivia G. Calancie
- Centre for Neuroscience Studies, Queen’s University, Kingston, ON, Canada
- Division of Child and Youth Mental Health, Kingston Health Sciences Centre, Kingston, ON, Canada
| | - Brian C. Coe
- Centre for Neuroscience Studies, Queen’s University, Kingston, ON, Canada
| | - Sarosh Khalid-Khan
- Centre for Neuroscience Studies, Queen’s University, Kingston, ON, Canada
- Division of Child and Youth Mental Health, Kingston Health Sciences Centre, Kingston, ON, Canada
| | - Douglas P. Munoz
- Centre for Neuroscience Studies, Queen’s University, Kingston, ON, Canada
- Department of Biomedical and Molecular Sciences, Queen’s University, Kingston, ON, Canada
- Douglas P. Munoz,
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31
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Grigorian A, Kennedy KG, Luciw NJ, MacIntosh BJ, Goldstein BI. Obesity and Cerebral Blood Flow in the Reward Circuitry of Youth With Bipolar Disorder. Int J Neuropsychopharmacol 2022; 25:448-456. [PMID: 35092432 PMCID: PMC9211014 DOI: 10.1093/ijnp/pyac011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 01/13/2022] [Accepted: 01/27/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Bipolar disorder (BD) is associated with elevated body mass index (BMI) and increased rates of obesity. Obesity among individuals with BD is associated with more severe course of illness. Motivated by previous research on BD and BMI in youth as well as brain findings in the reward circuit, the current study investigates differences in cerebral blood flow (CBF) in youth BD with and without comorbid overweight/obesity (OW/OB). METHODS Participants consisted of youth, ages 13-20 years, including BD with OW/OB (BDOW/OB; n = 25), BD with normal weight (BDNW; n = 55), and normal-weight healthy controls (HC; n = 61). High-resolution T1-weighted and pseudo-continuous arterial spin labeling images were acquired using 3 Tesla magnetic resonance imaging. CBF differences were assessed using both region of interest and whole-brain voxel-wise approaches. RESULTS Voxel-wise analysis revealed significantly higher CBF in reward-associated regions in the BDNW group relative to the HC and BDOW/OB groups. CBF did not differ between the HC and BDOW/OB groups. There were no significant region of interest findings. CONCLUSIONS The current study identified distinct CBF levels relating to BMI in BD in the reward circuit, which may relate to underlying differences in cerebral metabolism, compensatory effects, and/or BD severity. Future neuroimaging studies are warranted to examine for changes in the CBF-OW/OB link over time and in relation to treatment.
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Affiliation(s)
- Anahit Grigorian
- Centre for Youth Bipolar Disorder, Department of Child and Youth Psychiatry, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Kody G Kennedy
- Centre for Youth Bipolar Disorder, Department of Child and Youth Psychiatry, Centre for Addiction and Mental Health, Toronto, Ontario, Canada,Department of Pharmacology and Toxicology, University of Toronto, Toronto, Ontario, Canada
| | - Nicholas J Luciw
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Bradley J MacIntosh
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada,Heart and Stroke Foundation Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute, Toronto, Ontario, Canada,Hurvitz Brain Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Benjamin I Goldstein
- Correspondence: Benjamin I. Goldstein, MD, PhD, Centre for Addiction and Mental Health, 80 Workman Way, Toronto, ON, Canada, M6J 1H4 ()
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32
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McLauchlan DJ, Lancaster T, Craufurd D, Linden DEJ, Rosser AE. Different depression: motivational anhedonia governs antidepressant efficacy in Huntington's disease. Brain Commun 2022; 4:fcac278. [PMID: 36440100 PMCID: PMC9683390 DOI: 10.1093/braincomms/fcac278] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 04/13/2022] [Accepted: 11/04/2022] [Indexed: 11/09/2022] Open
Abstract
Depression is more common in neurodegenerative diseases such as Huntington's disease than the general population. Antidepressant efficacy is well-established for depression within the general population: a recent meta-analysis showed serotonin norepinephrine reuptake inhibitors, tricyclic antidepressants and mirtazapine outperformed other antidepressants. Despite the severe morbidity, antidepressant choice in Huntington's disease is based on Class IV evidence. We used complementary approaches to determine treatment choice for depression in Huntington's disease: propensity score analyses of antidepressant treatment outcome using the ENROLL-HD data set, and a dissection of the cognitive mechanisms underlying depression in Huntington's disease using a cognitive battery based on the Research Domain Criteria for Depression. Study 1 included ENROLL-HD 5486 gene-positive adult patients started on an antidepressant medication for depression. Our outcome measures were depression (Hospital Anxiety and Depression Scale or Problem Behaviours Assessment 'Depressed Mood' item) at first follow-up (primary outcome) and all follow-ups (secondary outcome). The intervention was antidepressant class. We used Svyglm&Twang in R to perform propensity scoring, using known variables (disease progression, medical comorbidity, psychiatric morbidity, sedatives, number of antidepressants, demographics and antidepressant contraindications) to determine the probability of receiving different antidepressants (propensity score) and then included the propensity score in a model of treatment efficacy. Study 2 recruited 51 gene-positive adult patients and 26 controls from the South Wales Huntington's Disease Management Service. Participants completed a motor assessment, in addition to measures of depression and apathy, followed by tasks measuring consummatory anhedonia, motivational anhedonia, learning from reward and punishment and reaction to negative outcome. We used generalised linear models to determine the association between task performance and depression scores. Study 1 showed selective serotonin reuptake inhibitors outperformed serotonin norepinephrine reuptake inhibitors on the primary outcome (P = 0.048), whilst both selective serotonin reuptake inhibitors (P = 0.00069) and bupropion (P = 0.0045) were superior to serotonin norepinephrine reuptake inhibitors on the secondary outcome. Study 2 demonstrated an association between depression score and effort for reward that was not explained by apathy. No other mechanisms were associated with depression score. We found that selective serotonin reuptake inhibitors and bupropion outperform serotonin norepinephrine reuptake inhibitors at alleviating depression in Huntington's disease. Moreover, motivational anhedonia appears the most significant mechanism underlying depression in Huntington's disease. Bupropion is improves motivational anhedonia and has a synergistic effect with selective serotonin reuptake inhibitors. This work provides the first large-scale, objective evidence to determine treatment choice for depression in Huntington's disease, and provides a model for determining antidepressant efficacy in other neurodegenerative diseases.
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Affiliation(s)
- Duncan James McLauchlan
- Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff CF24 4HQ, UK.,Department of Neurology, Morriston Hospital, Swansea Bay University Health Board, Swansea SA6 6NL, UK
| | - Thomas Lancaster
- Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff CF24 4HQ, UK.,Cardiff University Brain Research Imaging Center, Cardiff University, Cardiff CF24 4HQ, UK.,Department of Psychology, University of Bath, Bath BA2 7AY, UK
| | - David Craufurd
- Manchester Center for Genomic Medicine, Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Center, Manchester M13 9PL, UK.,St. Mary's Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Center, Manchester M13 9WL, UK
| | - David E J Linden
- Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff CF24 4HQ, UK.,Cardiff University Brain Research Imaging Center, Cardiff University, Cardiff CF24 4HQ, UK.,Department of Psychology, University of Bath, Bath BA2 7AY, UK.,School for Mental Health and Neuroscience, Fac. Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands
| | - Anne E Rosser
- Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff CF24 4HQ, UK.,Department of Neurology, Morriston Hospital, Swansea Bay University Health Board, Swansea SA6 6NL, UK.,School of Biosciences, Cardiff University, Cardiff CF10 3AX, UK
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33
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Liang S, Wu Y, Hanxiaoran L, Greenshaw AJ, Li T. Anhedonia in Depression and Schizophrenia: Brain Reward and Aversion Circuits. Neuropsychiatr Dis Treat 2022; 18:1385-1396. [PMID: 35836582 PMCID: PMC9273831 DOI: 10.2147/ndt.s367839] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 06/28/2022] [Indexed: 11/23/2022] Open
Abstract
Anhedonia, which is defined as markedly diminished interest or pleasure, is a prominent symptom of psychiatric disorders, most notably major depressive disorder (MDD) and schizophrenia. Anhedonia is considered a transdiagnostic symptom that is associated with deficits in neural reward and aversion functions. Here, we review the characteristics of anhedonia in depression and schizophrenia as well as shared or disorder-specific anhedonia-related alterations in reward and aversion pathways of the brain. In particular, we highlight that anhedonia is characterized by impairments in anticipatory pleasure and integration of reward-related information in MDD, whereas anhedonia in schizophrenia is associated with neurocognitive deficits in representing the value of rewards. Dysregulation of the frontostriatal circuit and mesocortical and mesolimbic circuit systems may be the transdiagnostic neurobiological basis of reward and aversion impairments underlying anhedonia in these two disorders. Blunted aversion processing in depression and relatively strong aversion in schizophrenia are primarily attributed to the dysfunction of the habenula, insula, amygdala, and anterior cingulate cortex. Furthermore, patients with schizophrenia appear to exhibit greater abnormal activation and extended functional coupling than those with depression. From a transdiagnostic perspective, understanding the neural mechanisms underlying anhedonia in patients with psychiatric disorders may help in the development of more targeted and efficacious treatment and intervention strategies.
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Affiliation(s)
- Sugai Liang
- Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310013, People's Republic of China
| | - Yue Wu
- Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310013, People's Republic of China
| | - Li Hanxiaoran
- Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310013, People's Republic of China
| | - Andrew J Greenshaw
- Department of Psychiatry, University of Alberta, Edmonton, AB, T6G 2B7, Canada
| | - Tao Li
- Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310013, People's Republic of China
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Zhou B, Chen Y, Zheng R, Jiang Y, Li S, Wei Y, Zhang M, Gao X, Wen B, Han S, Cheng J. Alterations of Static and Dynamic Functional Connectivity of the Nucleus Accumbens in Patients With Major Depressive Disorder. Front Psychiatry 2022; 13:877417. [PMID: 35615457 PMCID: PMC9124865 DOI: 10.3389/fpsyt.2022.877417] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 03/30/2022] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Major depressive disorder (MDD) is associated with dysfunction of the reward system. As an important node in the reward system, the resting-state functional connectivity of the nucleus accumbens (NAc) is related to the etiology of MDD. However, an increasing number of recent studies propose that brain activity is dynamic over time, no study to date has examined whether the NAc dynamic functional connectivity (DFC) is changed in patients with MDD. Moreover, few studies have examined the impact of the clinical characteristics of patients with MDD. METHODS A total of 220 MDD patients and 159 healthy controls (HCs), group-matched for age, sex, and education level, underwent resting-state functional magnetic resonance imagining (rs-fMRI) scans. Seed-based resting-state functional connectivity (RSFC) and DFC of the NAc were conducted. Two sample t-tests were performed to alter RSFC/DFC of NAc. In addition, we examined the association between altered RSFC/DFC and depressive severity using Pearson correlation. Finally, we divided patients with MDD into different subgroups according to clinical characteristics and tested whether there were differences between the subgroups. RESULTS Compared with the HCs, MDD patients show reduced the NAc-based RSFC with the dorsolateral prefrontal cortex (DLPFC), hippocampus, middle temporal gyrus (MTG), inferior temporal gyrus (ITG), precuneus, and insula, and patients with MDD show reduced the NAc-based DFC with the DLPFC, ventromedial prefrontal cortex (VMPFC), ventrolateral prefrontal cortex (VLPFC), MTG, ITG, and insula. MDD severity was associated with RSFC between the NAc and precentral gyrus (r = 0.288, p = 0.002, uncorrected) and insula (r = 0.272, p = 0.003, uncorrected). CONCLUSION This study demonstrates abnormal RSFC and DFC between the NAc and distributed cerebral regions in MDD patients, characterized by decreased RSFC and DFC of the NAc connecting with the reward, executive, default-mode, and salience network. Our results expand previous descriptions of the NAc RSFC abnormalities in MDD, and the altered RSFC/DFC may reflect the disrupted function of the NAc.
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Affiliation(s)
- Bingqian Zhou
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yuan Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Ruiping Zheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yu Jiang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Shuying Li
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yarui Wei
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - MengZhe Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - XinYu Gao
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Baohong Wen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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Ward HB, Beermann A, Nawaz U, Halko MA, Janes AC, Moran LV, Brady RO. Evidence for Schizophrenia-Specific Pathophysiology of Nicotine Dependence. Front Psychiatry 2022; 13:804055. [PMID: 35153877 PMCID: PMC8829345 DOI: 10.3389/fpsyt.2022.804055] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 01/03/2022] [Indexed: 12/30/2022] Open
Abstract
Tobacco use is the top preventable cause of early mortality in schizophrenia. Over 60% of people with schizophrenia smoke, three times the general prevalence. The biological basis of this increased risk is not understood, and existing interventions do not target schizophrenia-specific pathology. We therefore used a connectome-wide analysis to identify schizophrenia-specific circuits of nicotine addiction. We reanalyzed data from two studies: In Cohort 1, 35 smokers (18 schizophrenia, 17 control) underwent resting-state fMRI and clinical characterization. A multivariate pattern analysis of whole-connectome data was used to identify the strongest links between cigarette use and functional connectivity. In Cohort 2, 12 schizophrenia participants and 12 controls were enrolled in a randomized, controlled crossover study of nicotine patch with resting-state fMRI. We correlated change in network functional connectivity with nicotine dose. In Cohort 1, the strongest (p < 0.001) correlate between connectivity and cigarette use was driven by individual variation in default mode network (DMN) topography. In individuals with greater daily cigarette consumption, we observed a pathological expansion of the DMN territory into the identified parieto-occipital region, while in individuals with lower daily cigarette consumption, this region was external to the DMN. This effect was entirely driven by schizophrenia participants. Given the relationship between DMN topography and nicotine use we observed in Cohort 1, we sought to directly test the impact of nicotine on this network using an independent second cohort. In Cohort 2, nicotine reduced DMN connectivity in a dose-dependent manner (R = -0.50; 95% CI -0.75 to -0.12, p < 0.05). In the placebo condition, schizophrenia subjects had hyperconnectivity compared to controls (p < 0.05). Nicotine administration normalized DMN hyperconnectivity in schizophrenia. We here provide direct evidence that the biological basis of nicotine dependence is different in schizophrenia and in non-schizophrenia populations. Our results suggest the high prevalence of nicotine use in schizophrenia may be an attempt to correct a network deficit known to interfere with cognition.
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Affiliation(s)
- Heather Burrell Ward
- Beth Israel Deaconess Medical Center, Boston, MA, United States.,Harvard Medical School, Boston, MA, United States
| | - Adam Beermann
- Beth Israel Deaconess Medical Center, Boston, MA, United States
| | - Uzma Nawaz
- Beth Israel Deaconess Medical Center, Boston, MA, United States
| | - Mark A Halko
- Harvard Medical School, Boston, MA, United States.,McLean Hospital, Belmont, MA, United States
| | - Amy C Janes
- Harvard Medical School, Boston, MA, United States.,McLean Hospital, Belmont, MA, United States
| | - Lauren V Moran
- Harvard Medical School, Boston, MA, United States.,McLean Hospital, Belmont, MA, United States
| | - Roscoe O Brady
- Beth Israel Deaconess Medical Center, Boston, MA, United States.,Harvard Medical School, Boston, MA, United States.,McLean Hospital, Belmont, MA, United States
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Kaczkurkin AN. Uncovering Potential Mechanisms of the Relationship Between Structural Deficits and General Psychopathology. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2022; 2:2-4. [PMID: 36324602 PMCID: PMC9616250 DOI: 10.1016/j.bpsgos.2021.11.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Revised: 11/24/2021] [Accepted: 11/29/2021] [Indexed: 11/17/2022] Open
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Pisoni A, Davis SW, Smoski M. Neural signatures of saliency-mapping in anhedonia: A narrative review. Psychiatry Res 2021; 304:114123. [PMID: 34333324 PMCID: PMC8759627 DOI: 10.1016/j.psychres.2021.114123] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 07/09/2021] [Accepted: 07/14/2021] [Indexed: 11/24/2022]
Abstract
Anhedonia is the loss of pleasure or motivation to engage in previously enjoyable activities, and is a transdiagnostic symptom associated with significant clinical impairment. Anhedonia is implicated in several different psychiatric disorders, presenting a promising opportunity for transdiagnostic treatment. Thus, developing targeted treatments for anhedonia is of critical importance for population mental health. An important first step in doing so is establishing a thorough understanding of the neural correlates of anhedonia. The Triple Network Model of Psychopathology provides a frame for how brain activity may go awry in anhedonia, specifically in the context of Salience Network (SN) function (i.e., saliency-mapping). We present a narrative review examining saliency-mapping as it relates to anhedonia severity in depressed and transdiagnostic adult samples. Results revealed increased anhedonia to be associated with hyperactivity of the SN at rest and in the context of negative stimuli, as well as a global lack of SN engagement in the context of positive stimuli. Potential treatments for anhedonia are placed within this model, and future directions for research are discussed.
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Affiliation(s)
- Angela Pisoni
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA.
| | - Simon W. Davis
- Department of Neurology, Duke University Medical Center, Durham, NC, USA,Center for Cognitive Neuroscience, Duke University, Durham, NC, USA
| | - Moria Smoski
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA; Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA.
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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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Alexopoulos GS, Raue PJ, Banerjee S, Marino P, Renn BN, Solomonov N, Adeagbo A, Sirey JA, Hull TD, Kiosses DN, Mauer E, Areán PA. Comparing the streamlined psychotherapy "Engage" with problem-solving therapy in late-life major depression. A randomized clinical trial. Mol Psychiatry 2021; 26:5180-5189. [PMID: 32612251 PMCID: PMC7775269 DOI: 10.1038/s41380-020-0832-3] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2020] [Revised: 06/01/2020] [Accepted: 06/23/2020] [Indexed: 12/12/2022]
Abstract
Effective psychotherapies for late-life depression are underutilized, mainly because of their complexity. "Engage" is a novel, streamlined psychotherapy that relies on neurobiology to identify core behavioral pathology of late-life depression and targets it with simple interventions, co-designed with community therapists so that they can be delivered in community settings. Consecutively recruited adults (≥60 years) with major depression (n = 249) were randomly assigned to 9 weekly sessions of "Engage" or to the evidence-based Problem-Solving Therapy (PST) offered by 35 trained community social workers and assessed by blind raters. "Engage" therapists required an average of 30% less training time to achieve fidelity to treatment than PST therapists and had one-third of the PST therapists' skill drift. Both treatments led to reduction of HAM-D scores over 9 weeks. The mixed effects model-estimated HAM-D ratings were not significantly different between the two treatments at any assessment point of the trial. The one-sided 95% CI for treatment-end difference was (-∞, 0.07) HAM-D points, indicating a non-inferiority margin of 1.3 HAM-D points or greater; this margin is lower than the pre-determined 2.2-point margin. The two treatment arms had similar response (HR = 1.08, 95% CI (0.76, 1.52), p = 0.67) and remission rates (HR = 0.89, 95% CI (0.57, 1.39), p = 0.61). We conclude that "Engage" is non-inferior to PST. If disseminated, "Engage" will increase the number of therapists who can reliably treat late-life depression and make effective psychotherapy available to large numbers of depressed older adults.
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Affiliation(s)
- George S Alexopoulos
- Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medicine, White Plains, NY, USA.
| | - Patrick J Raue
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA
| | - Samprit Banerjee
- Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medicine, White Plains, NY
| | - Patricia Marino
- Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medicine, White Plains, NY
| | - Brenna N. Renn
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA
| | - Nili Solomonov
- Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medicine, White Plains, NY
| | - Adenike Adeagbo
- Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medicine, White Plains, NY
| | - Jo Anne Sirey
- Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medicine, White Plains, NY
| | - Thomas D. Hull
- Talkspace, New York, NY,Teachers College, Columbia University, New York, NY
| | - Dimitris N. Kiosses
- Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medicine, White Plains, NY
| | - Elizabeth Mauer
- Weill Cornell Institute of Geriatric Psychiatry, Weill Cornell Medicine, White Plains, NY
| | - Patricia A. Areán
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA
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Wang S, Leri F, Rizvi SJ. Anhedonia as a central factor in depression: Neural mechanisms revealed from preclinical to clinical evidence. Prog Neuropsychopharmacol Biol Psychiatry 2021; 110:110289. [PMID: 33631251 DOI: 10.1016/j.pnpbp.2021.110289] [Citation(s) in RCA: 56] [Impact Index Per Article: 18.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 01/25/2021] [Accepted: 02/16/2021] [Indexed: 12/21/2022]
Abstract
Anhedonia is one of the core symptoms of major depressive disorder (MDD), which is often inadequately treated by traditional antidepressants. The modern framework of anhedonia extends the definition from impaired consummatory pleasure or interest in rewards to a broad spectrum of deficits that impact functions such as reward anticipation, approach motivation, effort expenditure, reward valuation, expectation, and reward-cue association learning. Substantial preclinical and clinical research has explored the neural basis of reward deficits in the context of depression, and has implicated mesocorticolimbic reward circuitry comprising the nucleus accumbens, ventral pallidum, ventral tegmental area, amygdala, hippocampus, anterior cingulate, insula, orbitofrontal cortex, and other prefrontal cortex regions. Dopamine modulates several reward facets including anticipation, motivation, effort, and learning. As well, serotonin, norepinephrine, opioids, glutamate, Gamma aminobutyric acid (GABA), and acetylcholine are also involved in anhedonia, and medications targeting these systems may also potentially normalize reward processing in depression. Unfortunately, whereas reward anticipation and reward outcome are extensively explored by both preclinical and clinical studies, translational gaps remain in reward motivation, effort, valuation, and learning, where clinical neuroimaging studies are in the early stages. This review aims to synthesize the neurobiological mechanisms underlying anhedonia in MDD uncovered by preclinical and clinical research. The translational difficulties in studying the neural basis of reward are also discussed.
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Affiliation(s)
- Shijing Wang
- Arthur Sommer Rotenberg Suicide and Depression Studies Program, St. Michael's Hospital, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Francesco Leri
- Department of Psychology, University of Guelph, Ontario, Canada
| | - Sakina J Rizvi
- Arthur Sommer Rotenberg Suicide and Depression Studies Program, St. Michael's Hospital, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.
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41
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Wang X, Cheng B, Roberts N, Wang S, Luo Y, Tian F, Yue S. Shared and distinct brain fMRI response during performance of working memory tasks in adult patients with schizophrenia and major depressive disorder. Hum Brain Mapp 2021; 42:5458-5476. [PMID: 34431584 PMCID: PMC8519858 DOI: 10.1002/hbm.25618] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2020] [Revised: 07/02/2021] [Accepted: 07/13/2021] [Indexed: 02/05/2023] Open
Abstract
Working memory (WM) impairments are common features of psychiatric disorders. A systematic meta-analysis was performed to determine common and disorder-specific brain fMRI response during performance of WM tasks in patients with SZ and patients with MDD relative to healthy controls (HC). Thirty-four published fMRI studies of WM in patients with SZ and 18 published fMRI studies of WM in patients with MDD, including relevant HC, were included in the meta-analysis. In both SZ and MDD there was common stronger fMRI response in right medial prefrontal cortex (MPFC) and bilateral anterior cingulate cortex (ACC), which are part of the default mode network (DMN). The effects were of greater magnitude in SZ than MDD, especially in prefrontal-temporal-cingulate-striatal-cerebellar regions. In addition, a disorder-specific weaker fMRI response was observed in right middle frontal gyrus (MFG) in MDD, relative to HC. For both SZ and MDD a significant correlation was observed between the severity of clinical symptoms and lateralized fMRI response relative to HC. These findings indicate that there may be common and distinct anomalies in brain function underlying deficits in WM in SZ and MDD, which may serve as a potential functional neuroimaging-based diagnostic biomarker with value in supporting clinical diagnosis, measuring illness severity and assessing the efficacy of treatments for SZ and MDD at the brain level.
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Affiliation(s)
- Xiuli Wang
- Department of Psychiatry, the Fourth People's Hospital of Chengdu, Chengdu, China
| | - Bochao Cheng
- Department of Radiology, West China Second University Hospital of Sichuan University, Chengdu, China
| | - Neil Roberts
- Edinburgh Imaging Facility, Queens Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Song Wang
- Department of Radiology, Huaxi MR Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Ya Luo
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Fangfang Tian
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China
| | - Suping Yue
- Department of Psychiatry, the Fourth People's Hospital of Chengdu, Chengdu, China
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Olivé I, Makris N, Densmore M, McKinnon MC, Lanius RA. Altered basal forebrain BOLD signal variability at rest in posttraumatic stress disorder: A potential candidate vulnerability mechanism for neurodegeneration in PTSD. Hum Brain Mapp 2021; 42:3561-3575. [PMID: 33960558 PMCID: PMC8249881 DOI: 10.1002/hbm.25454] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 03/15/2021] [Accepted: 04/11/2021] [Indexed: 12/11/2022] Open
Abstract
Individuals with posttraumatic stress disorder (PTSD) are at increased risk for the development of various forms of dementia. Nevertheless, the neuropathological link between PTSD and neurodegeneration remains unclear. Degeneration of the human basal forebrain constitutes a pathological hallmark of neurodegenerative diseases, such as Alzheimer's and Parkinson's disease. In this seed-based resting-state (rs-)fMRI study identifying as outcome measure the temporal BOLD signal fluctuation magnitude, a seed-to-voxel analyses assessed temporal correlations between the average BOLD signal within a bilateral whole basal forebrain region-of-interest and each whole-brain voxel among individuals with PTSD (n = 65), its dissociative subtype (PTSD+DS) (n = 38) and healthy controls (n = 46). We found that compared both with the PTSD and healthy controls groups, the PTSD+DS group exhibited increased BOLD signal variability within two nuclei of the seed region, specifically in its extended amygdaloid region: the nucleus accumbens and the sublenticular extended amygdala. This finding is provocative, because it mimics staging models of neurodegenerative diseases reporting allocation of neuropathology in early disease stages circumscribed to the basal forebrain. Here, underlying candidate etiopathogenetic mechanisms are neurovascular uncoupling, decreased connectivity in local- and large-scale neural networks, or disrupted mesolimbic dopaminergic circuitry, acting indirectly upon the basal forebrain cholinergic pathways. These abnormalities may underpin reward-related deficits representing a putative link between persistent traumatic memory in PTSD and anterograde memory deficits in neurodegeneration. Observed alterations of the basal forebrain in the dissociative subtype of PTSD point towards the urgent need for further exploration of this region as a potential candidate vulnerability mechanism for neurodegeneration in PTSD.
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Affiliation(s)
- Isadora Olivé
- Faculty of Brain Sciences, Division of PsychiatryUniversity College of LondonLondonUnited Kingdom
| | - Nikos Makris
- Departments of Psychiatry and Neurology Services, Center for Neural Systems InvestigationCenter for Morphometric Analysis, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General HospitalBostonMassachusettsUSA
- Department of Psychiatry Neuroimaging LaboratoryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of Anatomy & NeurobiologyBoston University School of MedicineBostonMassachusettsUSA
| | - Maria Densmore
- Department of PsychiatryUniversity of Western OntarioLondonOntarioCanada
- Imaging DivisionLawson Health Research InstituteLondonOntarioCanada
| | - Margaret C. McKinnon
- Department of Psychiatry and Behavioural NeurosciencesMcMaster UniversityHamiltonOntarioCanada
- Homewood Research InstituteGuelphOntarioCanada
- Mood Disorders ProgramSt Joseph's HealthcareHamiltonOntarioCanada
| | - Ruth A. Lanius
- Department of PsychiatryUniversity of Western OntarioLondonOntarioCanada
- Imaging DivisionLawson Health Research InstituteLondonOntarioCanada
- Department of NeurosciencesUniversity of Western OntarioLondonOntarioCanada
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Neural correlates of posttraumatic anhedonia symptoms: Decreased functional connectivity between ventral pallidum and default mode network regions. J Psychiatr Res 2021; 140:30-34. [PMID: 34090100 DOI: 10.1016/j.jpsychires.2021.05.061] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Revised: 05/06/2021] [Accepted: 05/21/2021] [Indexed: 11/21/2022]
Abstract
Anhedonia is common in individuals with traumatic experience. Anhedonia symptoms play an important role in posttraumatic psychopathology, and are related to various adverse outcomes. The current study is a preliminary neuroimaging study of the neural correlates of posttraumatic anhedonia symptoms. Resting-state fMRI data were acquired from 88 Chinese earthquake survivors. Whole brain analyses and exploratory ROI-to-ROI analyses were performed to examine the relationship between posttraumatic anhedonia symptoms and resting-state functional connectivity (rsFC) of reward-related subcortical nucleus including nucleus accumbens and ventral pallidum. The rsFC between left ventral pallidum and areas of bilateral posterior cingulate cortex (PCC) and precuneus cortex were found lower in the high posttraumatic anhedonia group, after controlling for sex, age and other posttraumatic stress symptoms. The rsFC between left ventral pallidum and PCC and the rsFC between left ventral pallidum and lateral parietal cortex were significantly lower in the high anhedonia group. Our findings suggest that decreased functional connectivity between the ventral pallidum and the brain default mode network (DMN) regions could be the neural correlates of posttraumatic anhedonia symptoms.
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Ploski JE, Vaidya VA. The Neurocircuitry of Posttraumatic Stress Disorder and Major Depression: Insights Into Overlapping and Distinct Circuit Dysfunction-A Tribute to Ron Duman. Biol Psychiatry 2021; 90:109-117. [PMID: 34052037 PMCID: PMC8383211 DOI: 10.1016/j.biopsych.2021.04.009] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Revised: 04/13/2021] [Accepted: 04/13/2021] [Indexed: 12/14/2022]
Abstract
The neurocircuitry that contributes to the pathophysiology of posttraumatic stress disorder and major depressive disorder, psychiatric conditions that exhibit a high degree of comorbidity, likely involves both overlapping and unique structural and functional changes within multiple limbic brain regions. In this review, we discuss neurobiological alterations that are associated with posttraumatic stress disorder and major depressive disorder and highlight both similarities and differences that may exist between these disorders to argue for the existence of a shared neurobiology. We highlight the key contributions based on preclinical studies, emerging from the late Professor Ronald Duman's research, that have shaped our understanding of the neurocircuitry that contributes to both the etiopathology and treatment of major depressive disorder and posttraumatic stress disorder.
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Affiliation(s)
- Jonathan E. Ploski
- Department of Neuroscience and Molecular & Cell Biology, School of Behavioral and Brain Sciences, University of Texas at Dallas, GR41, 800 W Campbell Road, Richardson, TX 75080-3021, USA
| | - Vidita A. Vaidya
- Department of Biological Sciences, Tata Institute of Fundamental Research, 1 Homi Bhabha Road, Colaba, Mumbai, Maharashtra, 400005, India
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45
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Yang Y, Ye C, Sun J, Liang L, Lv H, Gao L, Fang J, Ma T, Wu T. Alteration of brain structural connectivity in progression of Parkinson's disease: A connectome-wide network analysis. Neuroimage Clin 2021; 31:102715. [PMID: 34130192 PMCID: PMC8209844 DOI: 10.1016/j.nicl.2021.102715] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 05/08/2021] [Accepted: 05/31/2021] [Indexed: 12/12/2022]
Abstract
Pinpointing the brain dysconnectivity in idiopathic rapid eye movement sleep behaviour disorder (iRBD) can facilitate preventing the conversion of Parkinson's disease (PD) from prodromal phase. Recent neuroimage investigations reported disruptive brain white matter connectivity in both iRBD and PD, respectively. However, the intrinsic process of the human brain structural network evolving from iRBD to PD still remains largely unknown. To address this issue, 151 participants including iRBD, PD and age-matched normal controls were recruited to receive diffusion MRI scans and neuropsychological examinations. The connectome-wide association analysis was performed to detect reorganization of brain structural network along with PD progression. Eight brain seed regions in both cortical and subcortical areas demonstrated significant structural pattern changes along with the progression of PD. Applying machine learning on the key connectivity related to these seed regions demonstrated better classification accuracy compared to conventional network-based statistic. Our study shows that connectome-wide association analysis reveals the underlying structural connectivity patterns related to the progression of PD, and provide a promising distinct capability to predict prodromal PD patients.
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Affiliation(s)
- Yanwu Yang
- Department of Electronic and Information Engineering, Harbin Institute of Technology at Shenzhen, Shenzhen, China
| | | | - Junyan Sun
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Disease, Beijing, China
| | - Li Liang
- Department of Electronic and Information Engineering, Harbin Institute of Technology at Shenzhen, Shenzhen, China
| | - Haiyan Lv
- MindsGo Shenzhen Life Science Co. Ltd, Shenzhen, China
| | - Linlin Gao
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Disease, Beijing, China
| | - Jiliang Fang
- Department of Radiology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Ting Ma
- Department of Electronic and Information Engineering, Harbin Institute of Technology at Shenzhen, Shenzhen, China; Peng Cheng Laboratory, Shenzhen, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China; National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, China.
| | - Tao Wu
- Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Disease, Beijing, China.
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46
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Lee TY, Jung WH, Kwak YB, Yoon YB, Lee J, Kim M, Kim E, Kwon JS. Distinct neural networks associated with obsession and delusion: a connectome-wide association study. Psychol Med 2021; 51:1320-1328. [PMID: 31997729 DOI: 10.1017/s0033291720000057] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
BACKGROUND Obsession and delusion are theoretically distinct from each other in terms of reality testing. Despite such phenomenological distinction, no extant studies have examined the identification of common and distinct neural correlates of obsession and delusion by employing biologically grounded methods. Here, we investigated dimensional effects of obsession and delusion spanning across the traditional diagnostic boundaries reflected upon the resting-state functional connectivity (RSFC) using connectome-wide association studies (CWAS). METHODS Our study sample comprised of 96 patients with obsessive-compulsive disorder, 75 patients with schizophrenia, and 65 healthy controls. A connectome-wide analysis was conducted to examine the relationship between obsession and delusion severity and RFSC using multivariate distance-based matrix regression. RESULTS Obsession was associated with the supplementary motor area, precentral gyrus, and superior parietal lobule, while delusion was associated with the precuneus. Follow-up seed-based RSFC and modularity analyses revealed that obsession was related to aberrant inter-network connectivity strength. Additional inter-network analyses demonstrated the association between obsession severity and inter-network connectivity between the frontoparietal control network and the dorsal attention network. CONCLUSIONS Our CWAS study based on the Research Domain Criteria (RDoC) provides novel evidence for the circuit-level functional dysconnectivity associated with obsession and delusion severity across diagnostic boundaries. Further refinement and accumulation of biomarkers from studies embedded within the RDoC framework would provide useful information in treating individuals who have some obsession or delusion symptoms but cannot be identified by the category of clinical symptoms alone.
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Affiliation(s)
- Tae Young Lee
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Wi Hoon Jung
- Department of Psychology, Daegu University, Gyeongsan, Republic of Korea
| | - Yoo Bin Kwak
- Department of Brain and Cognitive Science, Seoul National University College of Natural Science, Seoul, Republic of Korea
| | - Youngwoo B Yoon
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - Junhee Lee
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Minah Kim
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Euitae Kim
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jun Soo Kwon
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Brain and Cognitive Science, Seoul National University College of Natural Science, Seoul, Republic of Korea
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47
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Sydnor VJ, Larsen B, Kohler C, Crow AJD, Rush SL, Calkins ME, Gur RC, Gur RE, Ruparel K, Kable JW, Young JF, Chawla S, Elliott MA, Shinohara RT, Nanga RPR, Reddy R, Wolf DH, Satterthwaite TD, Roalf DR. Diminished reward responsiveness is associated with lower reward network GluCEST: an ultra-high field glutamate imaging study. Mol Psychiatry 2021; 26:2137-2147. [PMID: 33479514 PMCID: PMC8292427 DOI: 10.1038/s41380-020-00986-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 11/22/2020] [Accepted: 12/03/2020] [Indexed: 12/12/2022]
Abstract
Low reward responsiveness (RR) is associated with poor psychological well-being, psychiatric disorder risk, and psychotropic treatment resistance. Functional MRI studies have reported decreased activity within the brain's reward network in individuals with RR deficits, however the neurochemistry underlying network hypofunction in those with low RR remains unclear. This study employed ultra-high field glutamate chemical exchange saturation transfer (GluCEST) imaging to investigate the hypothesis that glutamatergic deficits within the reward network contribute to low RR. GluCEST images were acquired at 7.0 T from 45 participants (ages 15-29, 30 females) including 15 healthy individuals, 11 with depression, and 19 with psychosis spectrum symptoms. The GluCEST contrast, a measure sensitive to local glutamate concentration, was quantified in a meta-analytically defined reward network comprised of cortical, subcortical, and brainstem regions. Associations between brain GluCEST contrast and Behavioral Activation System Scale RR scores were assessed using multiple linear regressions. Analyses revealed that reward network GluCEST contrast was positively and selectively associated with RR, but not other clinical features. Follow-up investigations identified that this association was driven by the subcortical reward network and network areas that encode the salience of valenced stimuli. We observed no association between RR and the GluCEST contrast within non-reward cortex. This study thus provides new evidence that reward network glutamate levels contribute to individual differences in RR. Decreased reward network excitatory neurotransmission or metabolism may be mechanisms driving reward network hypofunction and RR deficits. These findings provide a framework for understanding the efficacy of glutamate-modulating psychotropics such as ketamine for treating anhedonia.
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Affiliation(s)
- Valerie J. Sydnor
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Bart Larsen
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Christian Kohler
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;,Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Andrew J. D. Crow
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sage L. Rush
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Monica E. Calkins
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;,Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Ruben C. Gur
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;,Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Raquel E. Gur
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;,Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Kosha Ruparel
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;,Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Joseph W. Kable
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA;,MindCORE, University of Pennsylvania, Philadelphia, PA, USA
| | - Jami F. Young
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;,Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Sanjeev Chawla
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Mark A. Elliott
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Russell T. Shinohara
- Penn Statistics in Imaging and Visualization Endeavor, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;,Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Ravinder Reddy
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Daniel H. Wolf
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;,Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, PA, USA;,Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Theodore D. Satterthwaite
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;,Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, PA, USA;,Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - David R. Roalf
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;,Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
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Sagud M, Tudor L, Šimunić L, Jezernik D, Madžarac Z, Jakšić N, Mihaljević Peleš A, Vuksan-Ćusa B, Šimunović Filipčić I, Stefanović I, Kosanović Rajačić B, Kudlek Mikulić S, Pivac N. Physical and social anhedonia are associated with suicidality in major depression, but not in schizophrenia. Suicide Life Threat Behav 2021; 51:446-454. [PMID: 33314250 DOI: 10.1111/sltb.12724] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Revised: 08/04/2020] [Accepted: 08/05/2020] [Indexed: 12/21/2022]
Abstract
OBJECTIVE This cross-sectional study investigated the association of physical and social anhedonia with suicidality in patients with major depressive disorder (MDD), schizophrenia, and in non-psychiatric controls. METHOD All participants completed the revised Physical Anhedonia Scale (RPAS) and the revised Social Anhedonia Scale (RSAS) and were subdivided according to positive life-time suicide attempt history. MDD patients were evaluated with the Montgomery-Ãsberg Depression Rating Scale (MADRS), healthy respondents with the Patient Health Questionnaire-9 (PHQ-9), and schizophrenia patients with the Calgary Depression Scale for Schizophrenia (CDSS). RESULTS In 683 study participants, the prevalence of each anhedonia was the highest in MDD, followed by schizophrenia, and lowest in the control group. Among MDD patients, those with physical and social anhedonia had greater rates of recent suicidal ideation, while a higher frequency of individuals with life-time suicide attempts was detected in those with only social anhedonia. In contrast, no association between either anhedonia and life-time suicide attempts or recent suicidal ideation was found in patients with schizophrenia. CONCLUSIONS Assessing social and physical anhedonia might be important in MDD patients, given its association with both life-time suicide attempts and recent suicidal ideation. Suicidality in schizophrenia, while unrelated to anhedonia, might include other risk factors.
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Affiliation(s)
- Marina Sagud
- School of Medicine, University of Zagreb, Zagreb, Croatia.,Department of Psychiatry and Psychological Medicine, University Hospital Centre Zagreb, Zagreb, Croatia
| | - Lucija Tudor
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Rudjer Boskovic Institute, Zagreb, Croatia
| | - Lucija Šimunić
- Department of Psychiatry and Psychological Medicine, University Hospital Centre Zagreb, Zagreb, Croatia
| | - Dejana Jezernik
- Department of Psychiatry and Psychological Medicine, University Hospital Centre Zagreb, Zagreb, Croatia
| | - Zoran Madžarac
- Department of Psychiatry and Psychological Medicine, University Hospital Centre Zagreb, Zagreb, Croatia
| | - Nenad Jakšić
- Department of Psychiatry and Psychological Medicine, University Hospital Centre Zagreb, Zagreb, Croatia
| | - Alma Mihaljević Peleš
- School of Medicine, University of Zagreb, Zagreb, Croatia.,Department of Psychiatry and Psychological Medicine, University Hospital Centre Zagreb, Zagreb, Croatia
| | - Bjanka Vuksan-Ćusa
- Department of Psychiatry and Psychological Medicine, University Hospital Centre Zagreb, Zagreb, Croatia
| | - Ivona Šimunović Filipčić
- Department of Psychiatry and Psychological Medicine, University Hospital Centre Zagreb, Zagreb, Croatia
| | | | - Biljana Kosanović Rajačić
- Department of Psychiatry and Psychological Medicine, University Hospital Centre Zagreb, Zagreb, Croatia
| | - Suzan Kudlek Mikulić
- Department of Psychiatry and Psychological Medicine, University Hospital Centre Zagreb, Zagreb, Croatia
| | - Nela Pivac
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Rudjer Boskovic Institute, Zagreb, Croatia
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Schizophrenia and bipolar disorder are associated with opposite brain reward anticipation-associated response. Neuropsychopharmacology 2021; 46:1152-1160. [PMID: 33452432 PMCID: PMC8115687 DOI: 10.1038/s41386-020-00940-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 12/03/2020] [Accepted: 12/07/2020] [Indexed: 12/17/2022]
Abstract
Blunted and exaggerated neuronal response to rewards are hypothesized to be core features of schizophrenia spectrum disorders (SZ) and bipolar disorder (BD), respectively. Nonetheless, direct tests of this hypothesis, in which response between SZ and BD is compared in the same study, are lacking. Here we examined the functional correlates of reward processing during the Incentivized Control Engagement Task (ICE-T) using 3T fMRI. Reward-associated activation was examined in 49 healthy controls (HCs), 52 recent-onset individuals with SZ, and 22 recent-onset individuals with Type I BD using anterior cingulate (ACC), anterior insula, and ventral striatal regions of interest. Significant group X reward condition (neutral vs. reward) interactions were observed during reward anticipation in the dorsal ACC (F(2,120) = 4.21, P = 0.017) and right insula (F(2,120) = 4.77, P = 0.010). The ACC interaction was driven by relatively higher activation in the BD group vs. HCs (P = 0.007) and vs. individuals with SZ (P = 0.010). The insula interaction was driven by reduced activation in the SZ group relative to HCs (P = 0.018) and vs. people with BD (P = 0.008). A composite of reward anticipation-associated response across all associated ROIs also differed significantly by diagnosis (F(1,120) = 5.59, P = 0.02), BD > HC > SZ. No effects of group or group X reward interactions were observed during reward feedback. These results suggest that people with SZ and BD have opposite patterns of activation associated with reward anticipation but not reward receipt. Implications of these findings in regard to Research Domain Criteria-based classification of illness and the neurobiology of reward in psychosis are discussed.
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50
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Abramovitch A, Short T, Schweiger A. The C Factor: Cognitive dysfunction as a transdiagnostic dimension in psychopathology. Clin Psychol Rev 2021; 86:102007. [PMID: 33864968 DOI: 10.1016/j.cpr.2021.102007] [Citation(s) in RCA: 65] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Revised: 03/12/2021] [Accepted: 03/12/2021] [Indexed: 12/19/2022]
Abstract
Research into cognitive functions across psychological disorders suggests that cognitive deficiencies may be present across multiple disorders, potentially pointing to a transdiagnostic phenomenon. More recently, a single dimension model of psychopathology, the p factor, has been proposed, in which cognitive deficits are thought to be an intrinsic construct, assumed to be transdiagnostic. However, no systematic investigation to date tested this hypothesis. The aim of the present study was to systematically review meta-analyses to assess the hypothesis that the C factor (cognitive dysfunction) is transdiagnostic in psychopathology and review potential moderators that may account for such a phenomenon. We conducted a systematic review of meta-analyses examining cognitive function across all disorders for which data were available. Included meta-analyses (n = 82), comprising 97 clinical samples, yielded 1,055 effect sizes. Twelve major disorders/categories (e.g., bipolar disorder, substance use disorders) were included, comprising 29 distinct clinical entities (e.g., euthymic bipolar disorder; alcohol use disorder). Results show that all disorders reviewed are associated with underperformance across cognitive domains, supporting the hypothesis that the C factor (or cognitive dysfunction) is a transdiagnostic factor related to p. To examine moderators that may explain or contribute to c, we first consider important interpretative limitations of neuropsychological data in psychopathology. More crucially, we review oft-neglected motivational and emotional transdiagnostic constructs of p, as prominent contributing constructs to the C factor. These constructs are offered as a roadmap for future research examining these constructs related to p, that contribute, and may account for cognitive dysfunctions in psychopathology.
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Affiliation(s)
| | - Tatiana Short
- Department of Psychology, Texas State University, USA
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