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Roberts AC, Mulvihill KG. Multiple faces of anxiety: a frontal lobe perspective. Trends Neurosci 2024; 47:708-721. [PMID: 39127569 DOI: 10.1016/j.tins.2024.07.001] [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: 03/27/2024] [Revised: 06/20/2024] [Accepted: 07/11/2024] [Indexed: 08/12/2024]
Abstract
Marked dysregulation of the human prefrontal cortex (PFC) and anterior cingulate cortex (ACC) characterises a variety of anxiety disorders, and its amelioration is a key feature of treatment success. Overall treatment response, however, is highly variable, and about a third of patients are resistant to treatment. In this review we hypothesise that a major contributor to this variation in treatment response are the multiple faces of anxiety induced by distinct forms of frontal cortex dysregulation. Comparison of findings from humans and non-human primates reveals marked similarity in the functional organisation of threat regulation across the frontal lobes. This organisation is discussed in relation to the 'predatory imminence continuum' model of threat and the differential engagement of executive functions at the core of both emotion generation and regulation strategies.
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Affiliation(s)
- Angela C Roberts
- Department of Physiology, Development, and Neuroscience, University of Cambridge, Cambridge, UK.
| | - Kevin G Mulvihill
- Department of Physiology, Development, and Neuroscience, University of Cambridge, Cambridge, UK.
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2
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Cheng Y, Cai H, Liu S, Yang Y, Pan S, Zhang Y, Mo F, Yu Y, Zhu J. Brain Network Localization of Gray Matter Atrophy and Neurocognitive and Social Cognitive Dysfunction in Schizophrenia. Biol Psychiatry 2024:S0006-3223(24)01489-6. [PMID: 39103010 DOI: 10.1016/j.biopsych.2024.07.021] [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: 05/13/2024] [Revised: 07/13/2024] [Accepted: 07/29/2024] [Indexed: 08/07/2024]
Abstract
BACKGROUND Numerous studies have established the presence of gray matter atrophy and brain activation abnormalities during neurocognitive and social cognitive tasks in schizophrenia. Despite a growing consensus that diseases localize better to distributed brain networks than individual anatomical regions, relatively few studies have examined brain network localization of gray matter atrophy and neurocognitive and social cognitive dysfunction in schizophrenia. METHODS To address this gap, we initially identified brain locations of structural and functional abnormalities in schizophrenia from 301 published neuroimaging studies with 8712 individuals with schizophrenia and 9275 healthy control participants. By applying novel functional connectivity network mapping to large-scale resting-state functional magnetic resonance imaging datasets, we mapped these affected brain locations to 3 brain abnormality networks of schizophrenia. RESULTS The gray matter atrophy network of schizophrenia comprised a broadly distributed set of brain areas predominantly implicating the ventral attention, somatomotor, and default networks. The neurocognitive dysfunction network was also composed of widespread brain areas primarily involving the frontoparietal and default networks. By contrast, the social cognitive dysfunction network consisted of circumscribed brain regions mainly implicating the default, subcortical, and visual networks. CONCLUSIONS Our findings suggest shared and unique brain network substrates of gray matter atrophy and neurocognitive and social cognitive dysfunction in schizophrenia, which may not only refine the understanding of disease neuropathology from a network perspective but may also contribute to more targeted and effective treatments for impairments in different cognitive domains in schizophrenia.
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Affiliation(s)
- Yan Cheng
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China; Anhui Provincial Institute of Translational Medicine, Hefei, China; Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China
| | - Huanhuan Cai
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China; Anhui Provincial Institute of Translational Medicine, Hefei, China; Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China
| | - Siyu Liu
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China; Anhui Provincial Institute of Translational Medicine, Hefei, China; Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China
| | - Yang Yang
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China; Anhui Provincial Institute of Translational Medicine, Hefei, China; Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China
| | - Shan Pan
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China; Anhui Provincial Institute of Translational Medicine, Hefei, China; Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China
| | - Yongqi Zhang
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China; Anhui Provincial Institute of Translational Medicine, Hefei, China; Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China
| | - Fan Mo
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China; Anhui Provincial Institute of Translational Medicine, Hefei, China; Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China
| | - Yongqiang Yu
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China; Anhui Provincial Institute of Translational Medicine, Hefei, China; Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China.
| | - Jiajia Zhu
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China; Anhui Provincial Institute of Translational Medicine, Hefei, China; Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China.
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3
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Klugah-Brown B, Bore MC, Liu X, Gan X, Biswal BB, Kendrick KM, Chang DHF, Zhou B, Becker B. The neurostructural consequences of glaucoma and their overlap with disorders exhibiting emotional dysregulations: A voxel-based meta-analysis and tripartite system model. J Affect Disord 2024; 358:487-499. [PMID: 38705527 DOI: 10.1016/j.jad.2024.05.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 04/23/2024] [Accepted: 05/02/2024] [Indexed: 05/07/2024]
Abstract
BACKGROUND Glaucoma, a progressive neurodegenerative disorder leading to irreversible blindness, is associated with heightened rates of generalized anxiety and depression. This study aims to comprehensively investigate brain morphological changes in glaucoma patients, extending beyond visual processing areas, and explores overlaps with morphological alterations observed in anxiety and depression. METHODS A comparative meta-analysis was conducted, using case-control studies of brain structural integrity in glaucoma patients. We aimed to identify regions with gray matter volume (GMV) changes, examine their role within distinct large-scale networks, and assess overlap with alterations in generalized anxiety disorder (GAD) and major depressive disorder (MDD). RESULTS Glaucoma patients exhibited significant GMV reductions in visual processing regions (lingual gyrus, thalamus). Notably, volumetric reductions extended beyond visual systems, encompassing the left putamen and insula. Behavioral and functional network decoding revealed distinct large-scale networks, implicating visual, motivational, and affective domains. The insular region, linked to pain and affective processes, displayed reductions overlapping with alterations observed in GAD. LIMITATIONS While the study identified significant morphological alterations, the number of studies from both the glaucoma and GAD cohorts remains limited due to the lack of independent studies meeting our inclusion criteria. CONCLUSION The study proposes a tripartite brain model for glaucoma, with visual processing changes related to the lingual gyrus and additional alterations in the putamen and insular regions tied to emotional or motivational functions. These neuroanatomical changes extend beyond the visual system, implying broader implications for brain structure and potential pathological developments, providing insights into the overall neurological consequences of glaucoma.
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Affiliation(s)
- Benjamin Klugah-Brown
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China; School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Mercy C Bore
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China; School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Xiqin Liu
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Xianyang Gan
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China; School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Bharat B Biswal
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China; School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, USA
| | - Keith M Kendrick
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China; School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Dorita H F Chang
- State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China; Department of Psychology, The University of Hong Kong, Hong Kong, China
| | - Bo Zhou
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
| | - Benjamin Becker
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China; School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China; Department of Psychology, The University of Hong Kong, Hong Kong, China.
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4
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Li J, Wang D, Xia J, Zhang C, Meng Y, Xu S, Chen H, Liao W. Divergent suicidal symptomatic activations converge on somato-cognitive action network in depression. Mol Psychiatry 2024; 29:1980-1989. [PMID: 38351174 PMCID: PMC11408245 DOI: 10.1038/s41380-024-02450-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 01/19/2024] [Accepted: 01/23/2024] [Indexed: 02/16/2024]
Abstract
Individuals with depression have the highest lifetime prevalence of suicide attempts (SA) among mental illnesses. Numerous neuroimaging studies have developed biomarkers from task-related neural activation in depressive patients with SA, but the findings are inconsistent. Empowered by the contemporary interconnected view of depression as a neural system disorder, we sought to identify a specific brain circuit utilizing published heterogeneous neural activations. We systematically reviewed all published cognitive and emotional task-related functional MRI studies that investigated differences in the location of neural activations between depressive patients with and without SA. We subsequently mapped an underlying brain circuit functionally connecting to each experimental activation using a large normative connectome database (n = 1000). The identified SA-related functional network was compared to the network derived from the disease control group. Finally, we decoded this convergent functional connectivity network using microscale transcriptomic and chemo-architectures, and macroscale psychological processes. We enrolled 11 experimental tasks from eight studies, including depressive patients with SA (n = 147) and without SA (n = 196). The heterogeneous SA-related neural activations localized to the somato-cognitive action network (SCAN), exhibiting robustness to little perturbations and specificity for depression. Furthermore, the SA-related functional network was colocalized with brain-wide gene expression involved in inflammatory and immunity-related biological processes and aligned with the distribution of the GABA and noradrenaline neurotransmitter systems. The findings demonstrate that the SA-related functional network of depression is predominantly located at the SCAN, which is an essential implication for understanding depressive patients with SA.
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Affiliation(s)
- Jiao Li
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. 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, P.R. China.
| | - Dajing 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, P.R. 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, P.R. China
| | - Jie Xia
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. 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, P.R. China
| | - Chao Zhang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. 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, P.R. China
| | - Yao Meng
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. 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, P.R. China
| | - Shuo Xu
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. 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, P.R. 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, P.R. 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, P.R. China.
| | - Wei Liao
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. 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, P.R. China.
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5
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Zhang X, Xu R, Ma H, Qian Y, Zhu J. Brain Structural and Functional Damage Network Localization of Suicide. Biol Psychiatry 2024; 95:1091-1099. [PMID: 38215816 DOI: 10.1016/j.biopsych.2024.01.003] [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: 11/04/2023] [Revised: 12/20/2023] [Accepted: 01/02/2024] [Indexed: 01/14/2024]
Abstract
BACKGROUND Extensive neuroimaging research on brain structural and functional correlates of suicide has produced inconsistent results. Despite increasing recognition that damage in multiple different brain locations that causes the same symptom can map to a common brain network, there is still a paucity of research investigating network localization of suicide. METHODS To clarify this issue, we initially identified brain structural and functional damage locations in relation to suicide from 63 published studies with 2135 suicidal and 2606 nonsuicidal individuals. By applying novel functional connectivity network mapping to large-scale discovery and validation resting-state functional magnetic resonance imaging datasets, we mapped these affected brain locations to 3 suicide brain damage networks corresponding to different imaging modalities. RESULTS The suicide gray matter volume damage network comprised widely distributed brain areas primarily involving the dorsal default mode, basal ganglia, and anterior salience networks. The suicide task-induced activation damage network was similar to but less extensive than the gray matter volume damage network, predominantly implicating the same canonical networks. The suicide resting-state activity damage network manifested as a localized set of brain regions encompassing the orbitofrontal cortex and middle cingulate cortex. CONCLUSIONS Our findings not only may help reconcile prior heterogeneous neuroimaging results, but also may provide insights into the neurobiological mechanisms of suicide from a network perspective, which may ultimately inform more targeted and effective strategies to prevent suicide.
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Affiliation(s)
- Xiaohan Zhang
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China; Anhui Provincial Institute of Translational Medicine, Hefei, China; Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China
| | - Ruoxuan Xu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China; Anhui Provincial Institute of Translational Medicine, Hefei, China; Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China
| | - Haining Ma
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China; Anhui Provincial Institute of Translational Medicine, Hefei, China; Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China
| | - Yinfeng Qian
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China; Anhui Provincial Institute of Translational Medicine, Hefei, China; Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China.
| | - Jiajia Zhu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China; Anhui Provincial Institute of Translational Medicine, Hefei, China; Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China.
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6
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Lu B, Chen X, Xavier Castellanos F, Thompson PM, Zuo XN, Zang YF, Yan CG. The power of many brains: Catalyzing neuropsychiatric discovery through open neuroimaging data and large-scale collaboration. Sci Bull (Beijing) 2024; 69:1536-1555. [PMID: 38519398 DOI: 10.1016/j.scib.2024.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 12/12/2023] [Accepted: 02/27/2024] [Indexed: 03/24/2024]
Abstract
Recent advances in open neuroimaging data are enhancing our comprehension of neuropsychiatric disorders. By pooling images from various cohorts, statistical power has increased, enabling the detection of subtle abnormalities and robust associations, and fostering new research methods. Global collaborations in imaging have furthered our knowledge of the neurobiological foundations of brain disorders and aided in imaging-based prediction for more targeted treatment. Large-scale magnetic resonance imaging initiatives are driving innovation in analytics and supporting generalizable psychiatric studies. We also emphasize the significant role of big data in understanding neural mechanisms and in the early identification and precise treatment of neuropsychiatric disorders. However, challenges such as data harmonization across different sites, privacy protection, and effective data sharing must be addressed. With proper governance and open science practices, we conclude with a projection of how large-scale imaging resources and collaborations could revolutionize diagnosis, treatment selection, and outcome prediction, contributing to optimal brain health.
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Affiliation(s)
- Bin Lu
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Xiao Chen
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Francisco Xavier Castellanos
- Department of Child and Adolescent Psychiatry, NYU Grossman School of Medicine, New York 10016, USA; Nathan Kline Institute for Psychiatric Research, Orangeburg 10962, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine, University of Southern California, Los Angeles 90033, USA
| | - Xi-Nian Zuo
- Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; National Basic Science Data Center, Beijing 100190, China
| | - Yu-Feng Zang
- Centre for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou 310004, China; Institute of Psychological Science, Hangzhou Normal University, Hangzhou 310030, China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairment, Hangzhou 311121, China
| | - Chao-Gan Yan
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100101, China; International Big-Data Center for Depression Research, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China.
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Wallace R, Fricchione G. Stress-induced failure of embodied cognition: A general model. Biosystems 2024; 239:105193. [PMID: 38522638 DOI: 10.1016/j.biosystems.2024.105193] [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: 03/11/2024] [Accepted: 03/18/2024] [Indexed: 03/26/2024]
Abstract
We derive the classic, ubiquitous, but enigmatic Yerkes-Dodson effect of applied stress on real-world performance in a highly natural manner from fundamental assumptions on cognition and its dynamics, as constrained by the asymptotic limit theorems of information and control theories. We greatly extend the basic approach by showing how differences in an underlying probability model can affect the dynamics of decision across a broad range of cognitive enterprise. Most particularly, however, this development may help inform our understanding of the different expressions of human psychopathology. A 'thin tailed' underlying distribution appears to characterize expression of 'ordinary' situational depression/anxiety symptoms of conditions like burnout induced by toxic stress. A 'fat tailed' underlying distribution appears to be associated with brain structure and function abnormalities leading to serious mental illness and poor decision making where symptoms are not only emerging in the setting of severe stress but may also appear in a highly punctuated manner at relatively lower levels of stress. A simple hierarchical optimization shows how environmental 'shadow price' constraints can buffer or aggravate the effects of stress and arousal. Extension of the underlying theory to other patterns of pathology, like immune disorders and premature aging, seems apt. Applications to the punctuated dynamics of institutional cognition under stress also appear possible. Ultimately, the probability models studied here can be converted to new statistical tools for the analysis of observational and experimental data.
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Affiliation(s)
- Rodrick Wallace
- The New York State Psychiatric Institute, Harvard University, United States of America.
| | - Gregory Fricchione
- The New York State Psychiatric Institute, Harvard University, United States of America.
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Kittleson AR, Woodward ND, Heckers S, Sheffield JM. The insula: Leveraging cellular and systems-level research to better understand its roles in health and schizophrenia. Neurosci Biobehav Rev 2024; 160:105643. [PMID: 38531518 DOI: 10.1016/j.neubiorev.2024.105643] [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: 01/09/2024] [Revised: 03/04/2024] [Accepted: 03/22/2024] [Indexed: 03/28/2024]
Abstract
Schizophrenia is a highly heterogeneous disorder characterized by a multitude of complex and seemingly non-overlapping symptoms. The insular cortex has gained increasing attention in neuroscience and psychiatry due to its involvement in a diverse range of fundamental human experiences and behaviors. This review article provides an overview of the insula's cellular and anatomical organization, functional and structural connectivity, and functional significance. Focusing on specific insula subregions and using knowledge gained from humans and preclinical studies of insular tracings in non-human primates, we review the literature and discuss the functional roles of each subregion, including in somatosensation, interoception, salience processing, emotional processing, and social cognition. Building from this foundation, we then extend these findings to discuss reported abnormalities of these functions in individuals with schizophrenia, implicating insular involvement in schizophrenia pathology. This review underscores the insula's vast role in the human experience and how abnormal insula structure and function could result in the wide-ranging symptoms observed in schizophrenia.
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Affiliation(s)
- Andrew R Kittleson
- Medical Scientist Training Program, Vanderbilt University School of Medicine, Nashville, TN 37235, United States; Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, United States.
| | - Neil D Woodward
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, United States.
| | - Stephan Heckers
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, United States.
| | - Julia M Sheffield
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, United States.
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9
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Tao Y, Zhao R, Yang B, Han J, Li Y. Dissecting the shared genetic landscape of anxiety, depression, and schizophrenia. J Transl Med 2024; 22:373. [PMID: 38637810 PMCID: PMC11025255 DOI: 10.1186/s12967-024-05153-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 04/01/2024] [Indexed: 04/20/2024] Open
Abstract
BACKGROUND Numerous studies highlight the genetic underpinnings of mental disorders comorbidity, particularly in anxiety, depression, and schizophrenia. However, their shared genetic loci are not well understood. Our study employs Mendelian randomization (MR) and colocalization analyses, alongside multi-omics data, to uncover potential genetic targets for these conditions, thereby informing therapeutic and drug development strategies. METHODS We utilized the Consortium for Linkage Disequilibrium Score Regression (LDSC) and Mendelian Randomization (MR) analysis to investigate genetic correlations among anxiety, depression, and schizophrenia. Utilizing GTEx V8 eQTL and deCODE Genetics pQTL data, we performed a three-step summary-data-based Mendelian randomization (SMR) and protein-protein interaction analysis. This helped assess causal and comorbid loci for these disorders and determine if identified loci share coincidental variations with psychiatric diseases. Additionally, phenome-wide association studies, drug prediction, and molecular docking validated potential drug targets. RESULTS We found genetic correlations between anxiety, depression, and schizophrenia, and under a meta-analysis of MR from multiple databases, the causal relationships among these disorders are supported. Based on this, three-step SMR and colocalization analyses identified ITIH3 and CCS as being related to the risk of developing depression, while CTSS and DNPH1 are related to the onset of schizophrenia. BTN3A1, PSMB4, and TIMP4 were identified as comorbidity loci for both disorders. Molecules that could not be determined through colocalization analysis were also presented. Drug prediction and molecular docking showed that some drugs and proteins have good binding affinity and available structural data. CONCLUSIONS Our study indicates genetic correlations and shared risk loci between anxiety, depression, and schizophrenia. These findings offer insights into the underlying mechanisms of their comorbidities and aid in drug development.
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Affiliation(s)
- Yiming Tao
- Department of Intensive Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hankou, Wuhan, 430030, China
- Department of Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250101, Shandong, China
| | - Rui Zhao
- Department of Laboratory Medicine, The First Afliated Hospital of Chongqing Medical University, Chongqing, 400042, China
| | - Bin Yang
- Department of Intensive Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hankou, Wuhan, 430030, China
| | - Jie Han
- Department of Emergency, School of Medicine, Qingdao Municipal Hospital, Qingdao University, Qingdao, 266071, China.
| | - Yongsheng Li
- Department of Intensive Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hankou, Wuhan, 430030, China.
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10
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Strohman A, Isaac G, Payne B, Verdonk C, Khalsa SS, Legon W. Low-intensity focused ultrasound to the human insular cortex differentially modulates the heartbeat-evoked potential: a proof-of-concept study. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.08.584152. [PMID: 38559271 PMCID: PMC10979877 DOI: 10.1101/2024.03.08.584152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Background The heartbeat evoked potential (HEP) is a brain response time-locked to the heartbeat and a potential marker of interoceptive processing. The insula and dorsal anterior cingulate cortex (dACC) are brain regions that may be involved in generating the HEP. Low-intensity focused ultrasound (LIFU) is a non-invasive neuromodulation technique that can selectively target sub-regions of the insula and dACC to better understand their contributions to the HEP. Objective Proof-of-concept study to determine whether LIFU modulation of the anterior insula (AI), posterior insula (PI), and dACC influences the HEP. Methods In a within-subject, repeated-measures design, healthy human participants (n=16) received 10 minutes of stereotaxically targeted LIFU to the AI, PI, dACC or Sham at rest during continuous electroencephalography (EEG) and electrocardiography (ECG) recording on separate days. Primary outcome was change in HEP amplitudes. Relationships between LIFU pressure and HEP changes were examined using linear mixed modelling. Peripheral indices of visceromotor output including heart rate and heart rate variability (HRV) were explored between conditions. Results Relative to sham, LIFU to the PI, but not AI or dACC, decreased HEP amplitudes; this was partially explained by increased LIFU pressure. LIFU did not affect time or frequency dependent measures of HRV. Conclusions These results demonstrate the ability to modulate HEP amplitudes via non-invasive targeting of key interoceptive brain regions. Our findings have implications for the causal role of these areas in bottom-up heart-brain communication that could guide future work investigating the HEP as a marker of interoceptive processing in healthy and clinical populations.
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Affiliation(s)
- Andrew Strohman
- Fralin Biomedical Research Institute at Virginia Tech Carilion, Roanoke, VA, 24016, USA
- Virginia Tech Carilion School of Medicine, Roanoke, VA, 24016, USA
- Graduate Program in Translational Biology, Medicine, and Health, Virginia Polytechnic Institute and State University, Roanoke, VA, 24016, USA
| | - Gabriel Isaac
- Fralin Biomedical Research Institute at Virginia Tech Carilion, Roanoke, VA, 24016, USA
- School of Neuroscience, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24016, USA
| | - Brighton Payne
- Fralin Biomedical Research Institute at Virginia Tech Carilion, Roanoke, VA, 24016, USA
| | - Charles Verdonk
- Laureate Institute for Brain Research, Tulsa, OK, USA
- VIFASOM (EA 7330 Vigilance Fatigue, Sommeil et Santé Publique), Université Paris Cité, Paris, France
- French Armed Forces Biomedical Research Institute, Brétigny-sur-Orge, France
| | - Sahib S. Khalsa
- Laureate Institute for Brain Research, Tulsa, OK, USA
- Oxley College of Health Sciences, University of Tulsa, Tulsa, OK, USA
| | - Wynn Legon
- Fralin Biomedical Research Institute at Virginia Tech Carilion, Roanoke, VA, 24016, USA
- Center for Human Neuroscience Research, Fralin Biomedical Research Institute at Virginia Tech Carilion, Roanoke, VA, 24016, USA
- Center for Health Behaviors Research, Fralin Biomedical Research Institute at Virginia Tech Carilion, Roanoke, VA, 24016, USA
- School of Neuroscience, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24016, USA
- Virginia Tech Carilion School of Medicine, Roanoke, VA, 24016, USA
- Graduate Program in Translational Biology, Medicine, and Health, Virginia Polytechnic Institute and State University, Roanoke, VA, 24016, USA
- Department of Neurosurgery, Carilion Clinic, Roanoke, VA, 24016, USA
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11
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Howard CW, Ferguson MH, Siddiqi SH, Fox MD. Lesion voxels to lesion networks: The enduring value of the Vietnam Head Injury Study. Cortex 2024; 172:109-113. [PMID: 38271817 DOI: 10.1016/j.cortex.2023.12.006] [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: 05/16/2023] [Revised: 10/10/2023] [Accepted: 12/20/2023] [Indexed: 01/27/2024]
Abstract
The Vietnam Head Injury Study has been curated by Dr Jordan Grafman since the 1980s in an effort to study patients with penetrating traumatic brain injuries suffered during the Vietnam War. Unlike many datasets of ischemic stroke lesions, the VHIS collected extraordinarily deep phenotyping and was able to sample lesion locations that are not constrained to typical vascular territories. For decades, this dataset has helped researchers draw causal links between neuroanatomical regions and neuropsychiatric symptoms. The value of the VHIS has only increased over time as techniques for analyzing the dataset have developed and evolved. Tools such as voxel lesion symptom mapping allowed one to relate symptoms to individual brain voxels. With the advent of the human connectome, tools such as lesion network mapping allow one to relate symptoms to connected brain networks by combining lesion datasets with new atlases of human brain connectivity. In a series of recent studies, lesion network mapping has been combined with the Vietnam Head Injury dataset to identify brain networks associated with spirituality, religiosity, consciousness, memory, emotion regulation, addiction, depression, and even transdiagnostic mental illness. These findings are enhancing our ability to make diagnoses, identify potential treatment targets for focal brain stimulation, and understand the human brain generally. Our techniques for studying brain lesions will continue to improve, as will our tools for modulating brain circuits. As these advances occur, the value of well characterized lesion datasets such as the Vietnam Head Injury Study will continue to grow. This study aims to review the history of the Vietnam Head Injury Study and contextualize its role in modern-day localization of neurological symptoms.
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Affiliation(s)
- Calvin W Howard
- Center for Brain Circuit Therapeutics, Department of Neurology Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA; Clinician Investigator Program, Postgraduate Medical Education, University of Manitoba, Winnipeg, Manitoba, Canada; Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité -Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.
| | - Michael H Ferguson
- Center for Brain Circuit Therapeutics, Department of Neurology Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Shan H Siddiqi
- Center for Brain Circuit Therapeutics, Department of Neurology Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Psychiatry, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michael D Fox
- Center for Brain Circuit Therapeutics, Department of Neurology Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
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12
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Mo F, Zhao H, Li Y, Cai H, Song Y, Wang R, Yu Y, Zhu J. Network Localization of State and Trait of Auditory Verbal Hallucinations in Schizophrenia. Schizophr Bull 2024:sbae020. [PMID: 38401526 DOI: 10.1093/schbul/sbae020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/26/2024]
Abstract
BACKGROUND AND HYPOTHESIS Neuroimaging studies investigating the neural substrates of auditory verbal hallucinations (AVH) in schizophrenia have yielded mixed results, which may be reconciled by network localization. We sought to examine whether AVH-state and AVH-trait brain alterations in schizophrenia localize to common or distinct networks. STUDY DESIGN We initially identified AVH-state and AVH-trait brain alterations in schizophrenia reported in 48 previous studies. By integrating these affected brain locations with large-scale discovery and validation resting-state functional magnetic resonance imaging datasets, we then leveraged novel functional connectivity network mapping to construct AVH-state and AVH-trait dysfunctional networks. STUDY RESULTS The neuroanatomically heterogeneous AVH-state and AVH-trait brain alterations in schizophrenia localized to distinct and specific networks. The AVH-state dysfunctional network comprised a broadly distributed set of brain regions mainly involving the auditory, salience, basal ganglia, language, and sensorimotor networks. Contrastingly, the AVH-trait dysfunctional network manifested as a pattern of circumscribed brain regions principally implicating the caudate and inferior frontal gyrus. Additionally, the AVH-state dysfunctional network aligned with the neuromodulation targets for effective treatment of AVH, indicating possible clinical relevance. CONCLUSIONS Apart from unifying the seemingly irreproducible neuroimaging results across prior AVH studies, our findings suggest different neural mechanisms underlying AVH state and trait in schizophrenia from a network perspective and more broadly may inform future neuromodulation treatment for AVH.
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Affiliation(s)
- Fan Mo
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China
- Anhui Provincial Institute of Translational Medicine, Hefei, China
- Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China
| | - Han Zhao
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China
- Anhui Provincial Institute of Translational Medicine, Hefei, China
- Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China
| | - Yifan Li
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China
- Anhui Provincial Institute of Translational Medicine, Hefei, China
- Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China
| | - Huanhuan Cai
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China
- Anhui Provincial Institute of Translational Medicine, Hefei, China
- Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China
| | - Yang Song
- Department of Pain, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Rui Wang
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China
- Anhui Provincial Institute of Translational Medicine, Hefei, China
- Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China
| | - Yongqiang Yu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China
- Anhui Provincial Institute of Translational Medicine, Hefei, China
- Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China
| | - Jiajia Zhu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China
- Anhui Provincial Institute of Translational Medicine, Hefei, China
- Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China
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13
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Ikawa H, Takeda Y, Osawa R, Sato A, Mizuno H, Noda Y. A Retrospective Case-Control Study on the Differences in the Effectiveness of Theta-Burst Stimulation Therapy for Depression with and without Antidepressant Medication. J Clin Med 2024; 13:399. [PMID: 38256534 PMCID: PMC10816069 DOI: 10.3390/jcm13020399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 01/03/2024] [Accepted: 01/10/2024] [Indexed: 01/24/2024] Open
Abstract
Transcranial magnetic stimulation (TMS) therapy has few side effects and comparable therapeutic effects to antidepressant treatment, but few studies have introduced TMS therapy as an initial treatment for MDD. The objective of this study was to retrospectively compare the clinical outcomes between 50 MDD patients without antidepressants (i.e., TMS monotherapy) and 50 MDD patients with antidepressants plus TMS therapy, matched for age, sex, and depression severity. The presence or absence of antidepressant therapy in first-line treatment was determined via a detailed interview by psychiatrists. The study design was a retrospective observational case-control study using the TMS registry data. The key inclusion criteria were adult patients who met the diagnosis of MDD and received 20-30 sessions of intermittent theta-burst stimulation (iTBS) therapy to the left dorsolateral prefrontal cortex (DLPFC). In this study, the Montgomery-Åsberg Depression Rating Scale (MADRS) was used as the primary outcome measure. No significant group differences existed in the baseline MADRS total score between the unmedicated and medicated patient groups. Following TMS therapy, no significant group differences in response rate, remission rate, or relative total score change in the MADRS were observed. The main limitations were the retrospective design and the use of registry data as a source. Our findings suggest that TMS monotherapy may be as effective as TMS add-on therapy to antidepressants when used as the first-line therapy for MDD, but randomized controlled trials are needed.
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Affiliation(s)
- Haruki Ikawa
- Tokyo Yokohama TMS Clinic, Kawasaki 211-0063, Japan
| | - Yuya Takeda
- Tokyo Yokohama TMS Clinic, Kawasaki 211-0063, Japan
| | - Ryota Osawa
- Tokyo Yokohama TMS Clinic, Kawasaki 211-0063, Japan
| | - Akiko Sato
- Tokyo Yokohama TMS Clinic, Kawasaki 211-0063, Japan
| | | | - Yoshihiro Noda
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo 160-8582, Japan
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14
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Siddiqi SH, Khosravani S, Rolston JD, Fox MD. The future of brain circuit-targeted therapeutics. Neuropsychopharmacology 2024; 49:179-188. [PMID: 37524752 PMCID: PMC10700386 DOI: 10.1038/s41386-023-01670-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Revised: 07/07/2023] [Accepted: 07/10/2023] [Indexed: 08/02/2023]
Abstract
The principle of targeting brain circuits has drawn increasing attention with the growth of brain stimulation treatments such as transcranial magnetic stimulation (TMS), deep brain stimulation (DBS), and focused ultrasound (FUS). Each of these techniques can effectively treat different neuropsychiatric disorders, but treating any given disorder depends on choosing the right treatment target. Here, we propose a three-phase framework for identifying and modulating these targets. There are multiple approaches to identifying a target, including correlative neuroimaging, retrospective optimization based on existing stimulation sites, and lesion localization. These techniques can then be optimized using personalized neuroimaging, physiological monitoring, and engagement of a specific brain state using pharmacological or psychological interventions. Finally, a specific stimulation modality or combination of modalities can be chosen after considering the advantages and tradeoffs of each. While there is preliminary literature to support different components of this framework, there are still many unanswered questions. This presents an opportunity for the future growth of research and clinical care in brain circuit therapeutics.
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Affiliation(s)
- Shan H Siddiqi
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Boston, MA, USA.
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
| | - Sanaz Khosravani
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - John D Rolston
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Boston, MA, USA
- Department of Neurosurgery, Harvard Medical School, Boston, MA, USA
| | - Michael D Fox
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
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15
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Downar J, Siddiqi SH, Mitra A, Williams N, Liston C. Mechanisms of Action of TMS in the Treatment of Depression. Curr Top Behav Neurosci 2024; 66:233-277. [PMID: 38844713 DOI: 10.1007/7854_2024_483] [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] [Indexed: 07/26/2024]
Abstract
Transcranial magnetic stimulation (TMS) is entering increasingly widespread use in treating depression. The most common stimulation target, in the dorsolateral prefrontal cortex (DLPFC), emerged from early neuroimaging studies in depression. Recently, more rigorous casual methods have revealed whole-brain target networks and anti-networks based on the effects of focal brain lesions and focal brain stimulation on depression symptoms. Symptom improvement during therapeutic DLPFC-TMS appears to involve directional changes in signaling between the DLPFC, subgenual and dorsal anterior cingulate cortex, and salience-network regions. However, different networks may be involved in the therapeutic mechanisms for other TMS targets in depression, such as dorsomedial prefrontal cortex or orbitofrontal cortex. The durability of therapeutic effects for TMS involves synaptic neuroplasticity, and specifically may depend upon dopamine acting at the D1 receptor family, as well as NMDA-receptor-dependent synaptic plasticity mechanisms. Although TMS protocols are classically considered 'excitatory' or 'inhibitory', the actual effects in individuals appear quite variable, and might be better understood at the level of populations of synapses rather than individual synapses. Synaptic meta-plasticity may provide a built-in protective mechanism to avoid runaway facilitation or inhibition during treatment, and may account for the relatively small number of patients who worsen rather than improve with TMS. From an ethological perspective, the antidepressant effects of TMS may involve promoting a whole-brain attractor state associated with foraging/hunting behaviors, centered on the rostrolateral periaqueductal gray and salience network, and suppressing an attractor state associated with passive threat defense, centered on the ventrolateral periaqueductal gray and default-mode network.
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Affiliation(s)
- Jonathan Downar
- Department of Psychiatry, Faculty of Medicine, Institute of Medical Science, University of Toronto, Toronto, ON, Canada.
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada.
| | - Shan H Siddiqi
- Center for Brain Circuit Therapeutics, Brigham & Women's Hospital, Boston, MA, USA
- Department of Psychiatry, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Anish Mitra
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Nolan Williams
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Conor Liston
- Department of Psychiatry, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
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16
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Etami Y, Lildharrie C, Manza P, Wang GJ, Volkow ND. Neuroimaging in Adolescents: Post-Traumatic Stress Disorder and Risk for Substance Use Disorders. Genes (Basel) 2023; 14:2113. [PMID: 38136935 PMCID: PMC10743116 DOI: 10.3390/genes14122113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2023] [Revised: 11/17/2023] [Accepted: 11/21/2023] [Indexed: 12/24/2023] Open
Abstract
Trauma in childhood and adolescence has long-term negative consequences in brain development and behavior and increases the risk for psychiatric disorders. Among them, post-traumatic stress disorder (PTSD) during adolescence illustrates the connection between trauma and substance misuse, as adolescents may utilize substances to cope with PTSD. Drug misuse may in turn lead to neuroadaptations in learning processes that facilitate the consolidation of traumatic memories that perpetuate PTSD. This reflects, apart from common genetic and epigenetic modifications, overlapping neurocircuitry engagement triggered by stress and drug misuse that includes structural and functional changes in limbic brain regions and the salience, default-mode, and frontoparietal networks. Effective strategies to prevent PTSD are needed to limit the negative consequences associated with the later development of a substance use disorder (SUD). In this review, we will examine the link between PTSD and SUDs, along with the resulting effects on memory, focusing on the connection between the development of an SUD in individuals who struggled with PTSD in adolescence. Neuroimaging has emerged as a powerful tool to provide insight into the brain mechanisms underlying the connection of PTSD in adolescence and the development of SUDs.
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Affiliation(s)
| | | | | | - Gene-Jack Wang
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD 20892, USA; (Y.E.); (C.L.); (P.M.); (N.D.V.)
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17
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Jones BDM, Zhukovsky P, Hawco C, Ortiz A, Cipriani A, Voineskos AN, Mulsant BH, Husain MI. Protocol for a systematic review and meta-analysis of coordinate-based network mapping of brain structure in bipolar disorder across the lifespan. BJPsych Open 2023; 9:e178. [PMID: 37811544 PMCID: PMC10594157 DOI: 10.1192/bjo.2023.569] [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: 04/17/2023] [Revised: 08/03/2023] [Accepted: 08/22/2023] [Indexed: 10/10/2023] Open
Abstract
BACKGROUND Studies about brain structure in bipolar disorder have reported conflicting findings. These findings may be explained by the high degree of heterogeneity within bipolar disorder, especially if structural differences are mapped to single brain regions rather than networks. AIMS We aim to complete a systematic review and meta-analysis to identify brain networks underlying structural abnormalities observed on T1-weighted magnetic resonance imaging scans in bipolar disorder across the lifespan. We also aim to explore how these brain networks are affected by sociodemographic and clinical heterogeneity in bipolar disorder. METHOD We will include case-control studies that focus on whole-brain analyses of structural differences between participants of any age with a standardised diagnosis of bipolar disorder and controls. The electronic databases Medline, PsycINFO and Web of Science will be searched. We will complete an activation likelihood estimation analysis and a novel coordinate-based network mapping approach to identify specific brain regions and brain circuits affected in bipolar disorder or relevant subgroups. Meta-regressions will examine the effect of sociodemographic and clinical variables on identified brain circuits. CONCLUSIONS Findings from this systematic review and meta-analysis will enhance understanding of the pathophysiology of bipolar disorder. The results will identify brain circuitry implicated in bipolar disorder, and how they may relate to relevant sociodemographic and clinical variables across the lifespan.
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Affiliation(s)
- Brett D. M. Jones
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Canada; and Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Canada
| | - Peter Zhukovsky
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Canada; and Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Canada
| | - Colin Hawco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Canada; and Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Canada
| | - Abigail Ortiz
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Canada; and Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Canada
| | - Andrea Cipriani
- Department of Psychiatry, University of Oxford, UK; Oxford Health NHS Foundation Trust, Warneford Hospital, Oxford, UK; and Oxford Precision Psychiatry Laboratory, NIHR Oxford Health Biomedical Research Centre, UK
| | - Aristotle N. Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Canada; and Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Canada
| | - Benoit H. Mulsant
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Canada; and Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Canada
| | - Muhammad Ishrat Husain
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Canada; and Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Canada
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18
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Tse NY, Ratheesh A, Ganesan S, Zalesky A, Cash RFH. Functional dysconnectivity in youth depression: Systematic review, meta-analysis, and network-based integration. Neurosci Biobehav Rev 2023; 153:105394. [PMID: 37739327 DOI: 10.1016/j.neubiorev.2023.105394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Revised: 08/11/2023] [Accepted: 09/16/2023] [Indexed: 09/24/2023]
Abstract
Youth depression has been associated with heterogenous patterns of aberrant brain connectivity. To make sense of these divergent findings, we conducted a systematic review encompassing 19 resting-state fMRI seed-to-whole-brain studies (1400 participants, comprising 795 youths with major depression and 605 matched healthy controls). We incorporated separate meta-analyses of connectivity abnormalities across the levels of the most commonly seeded brain networks (default-mode and limbic networks) and, based on recent additions to the literature, an updated meta-analysis of amygdala dysconnectivity in youth depression. Our findings indicated broad and distributed findings at an anatomical level, which could not be captured by conventional meta-analyses in terms of spatial convergence. However, we were able to parse the complexity of region-to-region dysconnectivity by considering constituent regions as components of distributed canonical brain networks. This integration revealed dysconnectivity centred on central executive, default mode, salience, and limbic networks, converging with findings from the adult depression literature and suggesting similar neurobiological underpinnings of youth and adult depression.
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Affiliation(s)
- Nga Yan Tse
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, Australia.
| | - Aswin Ratheesh
- Orygen, Melbourne, Australia; Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
| | - Saampras Ganesan
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, Australia; Department of Biomedical Engineering, Faculty of Engineering and Information Technology, The University of Melbourne, Melbourne, Australia
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, Australia; Department of Biomedical Engineering, Faculty of Engineering and Information Technology, The University of Melbourne, Melbourne, Australia
| | - Robin F H Cash
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, Australia; Department of Biomedical Engineering, Faculty of Engineering and Information Technology, The University of Melbourne, Melbourne, Australia
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19
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Wen J, Skampardoni I, Tian YE, Yang Z, Cui Y, Erus G, Hwang G, Varol E, Boquet-Pujadas A, Chand GB, Nasrallah I, Satterthwaite T, Shou H, Shen L, Toga AW, Zaleskey A, Davatzikos C. Neuroimaging-AI Endophenotypes of Brain Diseases in the General Population: Towards a Dimensional System of Vulnerability. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.16.23294179. [PMID: 37662256 PMCID: PMC10473785 DOI: 10.1101/2023.08.16.23294179] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Disease heterogeneity poses a significant challenge for precision diagnostics in both clinical and sub-clinical stages. Recent work leveraging artificial intelligence (AI) has offered promise to dissect this heterogeneity by identifying complex intermediate phenotypes - herein called dimensional neuroimaging endophenotypes (DNEs) - which subtype various neurologic and neuropsychiatric diseases. We investigate the presence of nine such DNEs derived from independent yet harmonized studies on Alzheimer's disease (AD1-2)1, autism spectrum disorder (ASD1-3)2, late-life depression (LLD1-2)3, and schizophrenia (SCZ1-2)4, in the general population of 39,178 participants in the UK Biobank study. Phenome-wide associations revealed prominent associations between the nine DNEs and phenotypes related to the brain and other human organ systems. This phenotypic landscape aligns with the SNP-phenotype genome-wide associations, revealing 31 genomic loci associated with the nine DNEs (Bonferroni corrected P-value < 5×10-8/9). The DNEs exhibited significant genetic correlations, colocalization, and causal relationships with multiple human organ systems and chronic diseases. A causal effect (odds ratio=1.25 [1.11, 1.40], P-value=8.72×1-4) was established from AD2, characterized by focal medial temporal lobe atrophy, to AD. The nine DNEs and their polygenic risk scores significantly improved the prediction accuracy for 14 systemic disease categories and mortality. These findings underscore the potential of the nine DNEs to identify individuals at a high risk of developing the four brain diseases during preclinical stages for precision diagnostics. All results are publicly available at: http://labs.loni.usc.edu/medicine/.
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Affiliation(s)
- Junhao Wen
- Laboratory of AI and Biomedical Science (LABS), Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, California, USA
| | - Ioanna Skampardoni
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Ye Ella Tian
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, Victoria, Australia
| | - Zhijian Yang
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Yuhan Cui
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Guray Erus
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Gyujoon Hwang
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Erdem Varol
- Department of Computer Science and Engineering, New York University, New York, USA
| | | | - Ganesh B. Chand
- Department of Radiology, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Ilya Nasrallah
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Theodore Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Haochang Shou
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Li Shen
- Department of Biostatistics, Epidemiology and Informatics University of Pennsylvania Perelman School of Medicine, Philadelphia, USA
| | - Arthur W. Toga
- Laboratory of Neuro Imaging (LONI), Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, California, USA
| | - Andrew Zaleskey
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, Victoria, Australia
| | - Christos Davatzikos
- Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
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20
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Soleimani G, Nitsche MA, Bergmann TO, Towhidkhah F, Violante IR, Lorenz R, Kuplicki R, Tsuchiyagaito A, Mulyana B, Mayeli A, Ghobadi-Azbari P, Mosayebi-Samani M, Zilverstand A, Paulus MP, Bikson M, Ekhtiari H. Closing the loop between brain and electrical stimulation: towards precision neuromodulation treatments. Transl Psychiatry 2023; 13:279. [PMID: 37582922 PMCID: PMC10427701 DOI: 10.1038/s41398-023-02565-5] [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: 07/08/2022] [Revised: 07/06/2023] [Accepted: 07/20/2023] [Indexed: 08/17/2023] Open
Abstract
One of the most critical challenges in using noninvasive brain stimulation (NIBS) techniques for the treatment of psychiatric and neurologic disorders is inter- and intra-individual variability in response to NIBS. Response variations in previous findings suggest that the one-size-fits-all approach does not seem the most appropriate option for enhancing stimulation outcomes. While there is a growing body of evidence for the feasibility and effectiveness of individualized NIBS approaches, the optimal way to achieve this is yet to be determined. Transcranial electrical stimulation (tES) is one of the NIBS techniques showing promising results in modulating treatment outcomes in several psychiatric and neurologic disorders, but it faces the same challenge for individual optimization. With new computational and methodological advances, tES can be integrated with real-time functional magnetic resonance imaging (rtfMRI) to establish closed-loop tES-fMRI for individually optimized neuromodulation. Closed-loop tES-fMRI systems aim to optimize stimulation parameters based on minimizing differences between the model of the current brain state and the desired value to maximize the expected clinical outcome. The methodological space to optimize closed-loop tES fMRI for clinical applications includes (1) stimulation vs. data acquisition timing, (2) fMRI context (task-based or resting-state), (3) inherent brain oscillations, (4) dose-response function, (5) brain target trait and state and (6) optimization algorithm. Closed-loop tES-fMRI technology has several advantages over non-individualized or open-loop systems to reshape the future of neuromodulation with objective optimization in a clinically relevant context such as drug cue reactivity for substance use disorder considering both inter and intra-individual variations. Using multi-level brain and behavior measures as input and desired outcomes to individualize stimulation parameters provides a framework for designing personalized tES protocols in precision psychiatry.
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Affiliation(s)
- Ghazaleh Soleimani
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
- Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
| | - Michael A Nitsche
- Department of Psychology and Neuroscience, Leibniz Research Center for Working Environment and Human Factors, Dortmund, Germany
- Bielefeld University, University Hospital OWL, Protestant Hospital of Bethel Foundation, University Clinic of Psychiatry and Psychotherapy, and University Clinic of Child and Adolescent Psychiatry and Psychotherapy, Bielefeld, Germany
| | - Til Ole Bergmann
- Neuroimaging Center, Focus Program Translational Neuroscience, Johannes Gutenberg University Medical Center Mainz, Mainz, Germany
- Leibniz Institute for Resilience Research, Mainz, Germany
| | - Farzad Towhidkhah
- Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
| | - Ines R Violante
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guilford, UK
| | - Romy Lorenz
- Department of Psychology, Stanford University, Stanford, CA, USA
- MRC CBU, University of Cambridge, Cambridge, UK
- Department of Neurophysics, MPI, Leipzig, Germany
| | | | | | - Beni Mulyana
- Laureate Institute for Brain Research, Tulsa, OK, USA
- School of Electrical and Computer Engineering, University of Oklahoma, Tulsa, OK, USA
| | - Ahmad Mayeli
- University of Pittsburgh Medical Center, Pittsburg, PA, USA
| | - Peyman Ghobadi-Azbari
- Department of Biomedical Engineering, Shahed University, Tehran, Iran
- Iranian National Center for Addiction Studies, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohsen Mosayebi-Samani
- Department of Psychology and Neuroscience, Leibniz Research Center for Working Environment and Human Factors, Dortmund, Germany
| | - Anna Zilverstand
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | | | | | - Hamed Ekhtiari
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA.
- Laureate Institute for Brain Research, Tulsa, OK, USA.
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21
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Di Biase MA. The Search for Unitary Mechanisms in Psychiatric Illness. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:588-589. [PMID: 37286290 DOI: 10.1016/j.bpsc.2023.04.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 04/07/2023] [Indexed: 06/09/2023]
Affiliation(s)
- Maria A Di Biase
- Departments of Psychiatry and Anatomy and Physiology, The University of Melbourne, Melbourne, Australia; Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
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