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Wang L, Han K, Huang Q, Hu W, Mo J, Wang J, Deng K, Zhang R, Tan X. Systemic lupus erythematosus-related brain abnormalities in the default mode network and the limbic system: A resting-state fMRI meta-analysis. J Affect Disord 2024; 355:190-199. [PMID: 38548195 DOI: 10.1016/j.jad.2024.03.121] [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: 12/20/2023] [Revised: 02/29/2024] [Accepted: 03/23/2024] [Indexed: 04/04/2024]
Abstract
BACKGROUND Systemic lupus erythematosus (SLE) is an immune-mediated and multi-systemic disease which may affect the nervous system, causing neuropsychiatric SLE (NPSLE). Recent neuroimaging studies have examined brain functional alterations in SLE. However, discrepant findings were reported. This meta-analysis aims to identify consistent resting-state functional abnormalities in SLE. METHODS PubMed and Web of Science were searched to identify candidate resting-state functional MRI studies assessing SLE. A voxel-based meta-analysis was performed using the anisotropic effect-size version of the seed-based d mapping (AES-SDM). The abnormal intrinsic functional patterns extracted from SDM were mapped onto the brain functional network atlas to determine brain abnormalities at a network level. RESULTS Twelve studies evaluating fifteen datasets were included in this meta-analysis, comprising 572 SLE patients and 436 healthy controls (HCs). Compared with HCs, SLE patients showed increased brain activity in the bilateral hippocampus and right superior temporal gyrus, and decreased brain activity in the left superior frontal gyrus, left middle temporal gyrus, bilateral thalamus, left inferior frontal gyrus and right cerebellum. Mapping the abnormal patterns to the network atlas revealed the default mode network and the limbic system as core neural systems commonly affected in SLE. LIMITATIONS The number of included studies is relatively small, with heterogeneous analytic methods and a risk of publication bias. CONCLUSIONS Brain functional alterations in SLE are predominantly found in the default mode network and the limbic system. These findings uncovered a consistent pattern of resting-state functional network abnormalities in SLE which may serve as a potential objective neuroimaging biomarker.
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Affiliation(s)
- Linhui Wang
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Kai Han
- Department of Dermatology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Qin Huang
- Department of Rheumatology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Wenjun Hu
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Jiaying Mo
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Jingyi Wang
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Kan Deng
- Philips Healthcare, Guangzhou, China
| | - Ruibin Zhang
- Cognitive control and Brain Healthy Laboratory, Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China; Department of Psychiatry, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
| | - Xiangliang Tan
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China.
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de Freitas MBL, Luna LP, Beatriz M, Pinto RK, Alves CHL, Bittencourt L, Nardi AE, Oertel V, Veras AB, de Lucena DF, Alves GS. Resting-state fMRI is associated with trauma experiences, mood and psychosis in Afro-descendants with bipolar disorder and schizophrenia. Psychiatry Res Neuroimaging 2024; 340:111766. [PMID: 38408419 DOI: 10.1016/j.pscychresns.2023.111766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 11/19/2023] [Accepted: 11/26/2023] [Indexed: 02/28/2024]
Abstract
BACKGROUND Bipolar disorder (BD) and schizophrenia (SCZ) may exhibit functional abnormalities in several brain areas, including the medial temporal and prefrontal cortex and hippocampus; however, a less explored topic is how brain connectivity is linked to premorbid trauma experiences and clinical features in non-Caucasian samples of SCZ and BD. METHODS Sixty-two individuals with SCZ (n = 20), BD (n = 21), and healthy controls (HC, n = 21) from indigenous and African ethnicity were submitted to clinical screening (Di-PAD), traumata experiences (ETISR-SF), cognitive and functional MRI assessment. The item psychosis/hallucinations in SCZ patients showed a negative correlation with the global efficiency (GE) in the right dorsal attention network. The items mania, irritable mood, and racing thoughts in the Di-PAD scale had a significant negative correlation with the GE in the parietal right default mode network. CONCLUSIONS Differences in the activation of specific networks were associated with earlier disease onset, history of physical abuse, and more severe psychotic and mood symptoms in SCZ and BD subjects of indigenous and black ethnicity. Findings provide further evidence on SZ and BD's brain connectivity disturbances, and their clinical significance, in non-Caucasian samples.
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Affiliation(s)
| | - Licia P Luna
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Hospital, Baltimore, MD, USA
| | - Márcia Beatriz
- Neuroradiology Service, São Domingos Hospital, São Luís, Brazil; Translational Psychiatry Research Group, Federal University of Maranhão, São Luís, Brazil
| | | | - Candida H Lopes Alves
- Translational Psychiatry Research Group, Federal University of Maranhão, São Luís, Brazil
| | - Lays Bittencourt
- Neuropsychiatry Service, Nina Rodrigues Hospital, São Luís, Brazil
| | - Antônio E Nardi
- Post-Graduation in Psychiatry and Mental Health (PROPSAM), Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Viola Oertel
- Department of Psychiatry, Psychosomatics, and Psychotherapy, Frankfurt Goethe University, Germany
| | - André B Veras
- Post-Graduation in Psychiatry and Mental Health (PROPSAM), Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | | | - Gilberto Sousa Alves
- Translational Psychiatry Research Group, Federal University of Maranhão, São Luís, Brazil; Neuropsychiatry Service, Nina Rodrigues Hospital, São Luís, Brazil; Post-Graduation in Psychiatry and Mental Health (PROPSAM), Federal University of Rio de Janeiro, Rio de Janeiro, Brazil.
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Zhang C, Liang J, Yan H, Li X, Li X, Jing H, Liang W, Li R, Ou Y, Wu W, Guo H, Deng W, Xie G, Guo W. Fractional amplitude of low-frequency fluctuations in sensory-motor networks and limbic system as a potential predictor of treatment response in patients with schizophrenia. Schizophr Res 2024; 267:519-527. [PMID: 38704344 DOI: 10.1016/j.schres.2024.04.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 03/21/2024] [Accepted: 04/26/2024] [Indexed: 05/06/2024]
Abstract
BACKGROUND Previous investigations have revealed substantial differences in neuroimaging characteristics between healthy controls (HCs) and individuals diagnosed with schizophrenia (SCZ). However, we are not entirely sure how brain activity links to symptoms in schizophrenia, and there is a need for reliable brain imaging markers for treatment prediction. METHODS In this longitudinal study, we examined 56 individuals diagnosed with 56 SCZ and 51 HCs. The SCZ patients underwent a three-month course of antipsychotic treatment. We employed resting-state functional magnetic resonance imaging (fMRI) along with fractional Amplitude of Low Frequency Fluctuations (fALFF) and support vector regression (SVR) methods for data acquisition and subsequent analysis. RESULTS In this study, we initially noted lower fALFF values in the right postcentral/precentral gyrus and left postcentral gyrus, coupled with higher fALFF values in the left hippocampus and right putamen in SCZ patients compared to the HCs at baseline. However, when comparing fALFF values in brain regions with abnormal baseline fALFF values for SCZ patients who completed the follow-up, no significant differences in fALFF values were observed after 3 months of treatment compared to baseline data. The fALFF values in the right postcentral/precentral gyrus and left postcentral gyrus, and the left postcentral gyrus were useful in predicting treatment effects. CONCLUSION Our findings suggest that reduced fALFF values in the sensory-motor networks and increased fALFF values in the limbic system may constitute distinctive neurobiological features in SCZ patients. These findings may serve as potential neuroimaging markers for the prognosis of SCZ patients.
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Affiliation(s)
- Chunguo Zhang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong 528000, China
| | - Jiaquan Liang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong 528000, China
| | - Haohao Yan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Xiaoling Li
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong 528000, China
| | - Xuesong Li
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong 528000, China
| | - Huan Jing
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong 528000, China
| | - Wenting Liang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong 528000, China
| | - Rongwei Li
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong 528000, China
| | - Yangpan Ou
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Weibin Wu
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong 528000, China
| | - Huagui Guo
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong 528000, China
| | - Wen Deng
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong 528000, China
| | - Guojun Xie
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong 528000, China.
| | - Wenbin Guo
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China.
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Zhang L, Ding Y, Li T, Li H, Liu F, Li P, Zhao J, Lv D, Lang B, Guo W. Similar imaging changes and their relations to genetic profiles in bipolar disorder across different clinical stages. Psychiatry Res 2024; 335:115868. [PMID: 38554494 DOI: 10.1016/j.psychres.2024.115868] [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: 01/04/2024] [Revised: 03/12/2024] [Accepted: 03/20/2024] [Indexed: 04/01/2024]
Abstract
Bipolar disorder (BD) across different clinical stages may present shared and distinct changes in brain activity. We aimed to reveal the neuroimaging homogeneity and heterogeneity of BD and its relationship with clinical variables and genetic variations. In present study, we conducted fractional amplitude of low-frequency fluctuations (fALFF), functional connectivity (FC) and genetic neuroimaging association analyses with 32 depressed, 26 manic, 35 euthymic BD patients and 87 healthy controls (HCs). Significant differences were found in the bilateral pre/subgenual anterior cingulate cortex (ACC) across the four groups, and all bipolar patients exhibited decreased fALFF values in the ACC when compared to HCs. Furthermore, positive associations were significantly observed between fALFF values in the pre/subgenual ACC and participants' cognitive functioning. No significant changes were found in ACC-based FC. We identified fALFF-alteration-related genes in BD, with enrichment in biological progress including synaptic and ion transmission. Taken together, abnormal activity in ACC is a characteristic change associated with BD, regardless of specific mood stages, serving as a potential neuroimaging feature in BD patients. Our genetic neuroimaging association analysis highlights possible heterogeneity in biological processes that could be responsible for different clinical stages in BD.
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Affiliation(s)
- Leyi Zhang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Yudan Ding
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Tingting Li
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Huabing Li
- Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Feng Liu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Ping Li
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang 161006, China
| | - Jingping Zhao
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Dongsheng Lv
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China; Center of Mental Health, Inner Mongolia Autonomous Region, Hohhot 010010, China.
| | - Bing Lang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Wenbin Guo
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China.
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Wu YK, Su YA, Li L, Zhu LL, Li K, Li JT, Mitchell PB, Yan CG, Si TM. Brain functional changes across mood states in bipolar disorder: from a large-scale network perspective. Psychol Med 2024; 54:763-774. [PMID: 38084586 DOI: 10.1017/s0033291723002453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/05/2024]
Abstract
BACKGROUND Exploring the neural basis related to different mood states is a critical issue for understanding the pathophysiology underlying mood switching in bipolar disorder (BD), but research has been scarce and inconsistent. METHODS Resting-state functional magnetic resonance imaging data were acquired from 162 patients with BD: 33 (hypo)manic, 64 euthymic, and 65 depressive, and 80 healthy controls (HCs). The differences of large-scale brain network functional connectivity (FC) between the four groups were compared and correlated with clinical characteristics. To validate the generalizability of our findings, we recruited a small longitudinal independent sample of BD patients (n = 11). In addition, we examined topological nodal properties across four groups as exploratory analysis. RESULTS A specific strengthened pattern of network FC, predominantly involving the default mode network (DMN), was observed in (hypo)manic patients when compared with HCs and bipolar patients in other mood states. Longitudinal observation revealed an increase in several network FCs in patients during (hypo)manic episode. Both samples evidenced an increase in the FC between the DMN and ventral attention network, and between the DMN and limbic network (LN) related to (hypo)mania. The altered network connections were correlated with mania severity and positive affect. Bipolar depressive patients exhibited decreased FC within the LN compared with HCs. The exploratory analysis also revealed an increase in degree in (hypo)manic patients. CONCLUSIONS Our findings identify a distributed pattern of large-scale network disturbances in the unique context of (hypo)mania and thus provide new evidence for our understanding of the neural mechanism of BD.
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Affiliation(s)
- Yan-Kun Wu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Yun-Ai Su
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Le Li
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Center for Cognitive Science of Language, Beijing Language and Culture University, Beijing, China
| | - Lin-Lin Zhu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Ke Li
- PLA Strategic Support Force Characteristic Medical Center, Beijing, China
| | - Ji-Tao Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Philip B Mitchell
- School of Psychiatry, University of New South Wales, Sydney, Australia
- Black Dog Institute, Prince of Wales Hospital, Sydney, Australia
| | - Chao-Gan Yan
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Tian-Mei Si
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
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Kong L, Zhang Y, Wu XM, Wang XX, Wu HS, Li SB, Chu MY, Wang Y, Lui SSY, Lv QY, Yi ZH, Chan RCK. The network characteristics in schizophrenia with prominent negative symptoms: a multimodal fusion study. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2024; 10:10. [PMID: 38233433 PMCID: PMC10851703 DOI: 10.1038/s41537-023-00408-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 10/26/2023] [Indexed: 01/19/2024]
Abstract
Previous studies on putative neural mechanisms of negative symptoms in schizophrenia mainly used single modal imaging data, and seldom utilized schizophrenia patients with prominent negative symptoms (PNS).This study adopted the multimodal fusion method and recruited a homogeneous sample with PNS. We aimed to identify negative symptoms-related structural and functional neural correlates of schizophrenia. Structural magnetic resonance imaging (sMRI) and resting-state functional MRI (rs-fMRI) were performed in 31 schizophrenia patients with PNS and 33 demographically matched healthy controls.Compared to healthy controls, schizophrenia patients with PNS exhibited significantly altered functional activations in the default mode network (DMN) and had structural gray matter volume (GMV) alterations in the cerebello-thalamo-cortical network. Correlational analyses showed that negative symptoms severity was significantly correlated with the cerebello-thalamo-cortical structural network, but not with the DMN network in schizophrenia patients with PNS.Our findings highlight the important role of the cerebello-thalamo-cortical structural network underpinning the neuropathology of negative symptoms in schizophrenia. Future research should recruit a large sample and schizophrenia patients without PNS, and apply adjustments for multiple comparison, to verify our preliminary findings.
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Affiliation(s)
- Li Kong
- Department of Psychology, Shanghai Normal University, Shanghai, China
| | - Yao Zhang
- Shanghai Mental Health Centre, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Psychiatry, Huashan Hospital, Fudan University, Shanghai, China
| | - Xu-Ming Wu
- Nantong Fourth People's Hospital, Nantong, China
| | - Xiao-Xiao Wang
- Shanghai Mental Health Centre, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Psychiatry, Huashan Hospital, Fudan University, Shanghai, China
| | - Hai-Su Wu
- Shanghai Mental Health Centre, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shuai-Biao Li
- Shanghai Mental Health Centre, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Min-Yi Chu
- Shanghai Mental Health Centre, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yi Wang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Simon S Y Lui
- Department of Psychiatry, School of Clinical Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Qin-Yu Lv
- Shanghai Mental Health Centre, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Psychiatry, Huashan Hospital, Fudan University, Shanghai, China
| | - Zheng-Hui Yi
- Shanghai Mental Health Centre, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Department of Psychiatry, Huashan Hospital, Fudan University, Shanghai, China.
- Institute of Mental Health, Fudan University, Shanghai, China.
| | - Raymond C K Chan
- Shanghai Mental Health Centre, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
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Martino M, Magioncalda P. A three-dimensional model of neural activity and phenomenal-behavioral patterns. Mol Psychiatry 2023:10.1038/s41380-023-02356-w. [PMID: 38114633 DOI: 10.1038/s41380-023-02356-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 11/16/2023] [Accepted: 11/27/2023] [Indexed: 12/21/2023]
Abstract
How phenomenal experience and behavior are related to neural activity in physiology and psychopathology represents a fundamental question in neuroscience and psychiatry. The phenomenal-behavior patterns may be deconstructed into basic dimensions, i.e., psychomotricity, affectivity, and thought, which might have distinct neural correlates. This work provides a data overview on the relationship of these phenomenal-behavioral dimensions with brain activity across physiological and pathological conditions (including major depressive disorder, bipolar disorder, schizophrenia, attention-deficit/hyperactivity disorder, anxiety disorders, addictive disorders, Parkinson's disease, Tourette syndrome, Alzheimer's disease, and frontotemporal dementia). Accordingly, we propose a three-dimensional model of neural activity and phenomenal-behavioral patterns. In this model, neural activity is organized into distinct units in accordance with connectivity patterns and related input/output processing, manifesting in the different phenomenal-behavioral dimensions. (1) An external neural unit, which involves the sensorimotor circuit/brain's sensorimotor network and is connected with the external environment, processes external inputs/outputs, manifesting in the psychomotor dimension (processing of exteroception/somatomotor activity). External unit hyperactivity manifests in psychomotor excitation (hyperactivity/hyperkinesia/catatonia), while external unit hypoactivity manifests in psychomotor inhibition (retardation/hypokinesia/catatonia). (2) An internal neural unit, which involves the interoceptive-autonomic circuit/brain's salience network and is connected with the internal/body environment, processes internal inputs/outputs, manifesting in the affective dimension (processing of interoception/autonomic activity). Internal unit hyperactivity manifests in affective excitation (anxiety/dysphoria-euphoria/panic), while internal unit hypoactivity manifests in affective inhibition (anhedonia/apathy/depersonalization). (3) An associative neural unit, which involves the brain's associative areas/default-mode network and is connected with the external/internal units (but not with the environment), processes associative inputs/outputs, manifesting in the thought dimension (processing of ideas). Associative unit hyperactivity manifests in thought excitation (mind-wandering/repetitive thinking/psychosis), while associative unit hypoactivity manifests in thought inhibition (inattention/cognitive deficit/consciousness loss). Finally, these neural units interplay and dynamically combine into various neural states, resulting in the complex phenomenal experience and behavior across physiology and neuropsychiatric disorders.
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Affiliation(s)
- Matteo Martino
- Graduate Institute of Mind Brain and Consciousness, Taipei Medical University, Taipei, Taiwan.
| | - Paola Magioncalda
- Graduate Institute of Mind Brain and Consciousness, Taipei Medical University, Taipei, Taiwan.
- International Master/Ph.D. Program in Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.
- Department of Radiology, Taipei Medical University-Shuang Ho Hospital, New Taipei City, Taiwan.
- Department of Medical Research, Taipei Medical University-Shuang Ho Hospital, New Taipei City, Taiwan.
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Xue R, Li X, Chen J, Liang S, Yu H, Zhang Y, Wei W, Xu Y, Deng W, Guo W, Li T. Shared and Distinct Topographic Alterations of Alpha-Range Resting EEG Activity in Schizophrenia, Bipolar Disorder, and Depression. Neurosci Bull 2023; 39:1887-1890. [PMID: 37610645 PMCID: PMC10661671 DOI: 10.1007/s12264-023-01106-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 05/07/2023] [Indexed: 08/24/2023] Open
Affiliation(s)
- Rui Xue
- Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, China
- Department of Neurobiology, Affiliated Mental Health Center and Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, 311121, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, 310058, China
| | - Xiaojing Li
- Department of Neurobiology, Affiliated Mental Health Center and Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, 311121, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, 310058, China
| | - Jianning Chen
- Department of Neurobiology, Affiliated Mental Health Center and Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, 311121, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, 310058, China
| | - Sugai Liang
- Department of Neurobiology, Affiliated Mental Health Center and Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, 311121, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, 310058, China
| | - Hua Yu
- Department of Neurobiology, Affiliated Mental Health Center and Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, 311121, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, 310058, China
| | - Yamin Zhang
- Department of Neurobiology, Affiliated Mental Health Center and Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, 311121, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, 310058, China
| | - Wei Wei
- Department of Neurobiology, Affiliated Mental Health Center and Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, 311121, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, 310058, China
| | - Yan Xu
- Department of Neurobiology, Affiliated Mental Health Center and Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, 311121, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, 310058, China
| | - Wei Deng
- Department of Neurobiology, Affiliated Mental Health Center and Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, 311121, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, 310058, China
| | - Wanjun Guo
- Department of Neurobiology, Affiliated Mental Health Center and Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, 311121, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, 310058, China
| | - Tao Li
- Department of Neurobiology, Affiliated Mental Health Center and Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, 310000, China.
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, 311121, China.
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, 310058, China.
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9
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Sunaga M, Takei Y, Kato Y, Tagawa M, Suto T, Hironaga N, Sakurai N, Fukuda M. The Characteristics of Power Spectral Density in Bipolar Disorder at the Resting State. Clin EEG Neurosci 2023; 54:574-583. [PMID: 34677105 DOI: 10.1177/15500594211050487] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Bipolar disorder (BD) is a common psychiatric disorder, but its pathophysiology is not fully elucidated. The current study focused on its electrophysiological characteristics, especially power spectral density (PSD). Resting state with eyes opened magnetoencephalography data were collected from 21 patients with BD and 22 healthy controls. The whole brain's PSD was calculated from source reconstructed waveforms at each frequency band (delta: 1-3 Hz, theta: 4-7 Hz, alpha: 8-12 Hz, low beta: 13-19 Hz, high beta: 20-29 Hz, and gamma: 30-80 Hz). We compared PSD values on the marked vertices at each frequency band between healthy and patient groups using a Mann-Whitney rank test to examine the relationship between significantly different PSD and clinical measures. The PSD in patients with BD was significantly decreased in lower frequency bands, mainly in the default mode network (DMN) areas (bilateral medial prefrontal cortex, bilateral precuneus, left inferior parietal lobe, and right temporal cortex in the alpha band) and salience network areas (SAL; left anterior insula [AI] at the delta band, anterior cingulate cortex at the theta band, and right AI at the alpha band). No significant differences in PSD were observed at low beta and high beta. PSD was not correlated with age or other clinical scales. Altered PSDs of the DMN and SAL were observed in the delta, theta, and alpha bands. These alterations contribute to the vulnerability of BD through the disturbance of self-referential mental activity and switching between the default mode and frontoparietal networks.
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Affiliation(s)
- Masakazu Sunaga
- Gunma Prefectural Psychiatric Medical Center, Isesaki, Japan
| | - Yuichi Takei
- Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Yutaka Kato
- Gunma University Graduate School of Medicine, Maebashi, Japan
- Tsutsuji Mental Hospital, Tatebayashi, Japan
| | - Minami Tagawa
- Gunma Prefectural Psychiatric Medical Center, Isesaki, Japan
- Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Tomohiro Suto
- Gunma Prefectural Psychiatric Medical Center, Isesaki, Japan
| | | | - Noriko Sakurai
- Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Masato Fukuda
- Gunma University Graduate School of Medicine, Maebashi, Japan
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10
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Li F, Wang G, Jiang L, Yao D, Xu P, Ma X, Dong D, He B. Disease-specific resting-state EEG network variations in schizophrenia revealed by the contrastive machine learning. Brain Res Bull 2023; 202:110744. [PMID: 37591404 DOI: 10.1016/j.brainresbull.2023.110744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 08/03/2023] [Accepted: 08/14/2023] [Indexed: 08/19/2023]
Abstract
Given a multitude of genetic and environmental factors, when investigating the variability in schizophrenia (SCZ) and the first-degree relatives (R-SCZ), latent disease-specific variation is usually hidden. To reliably investigate the mechanism underlying the brain deficits from the aspect of functional networks, we newly iterated a framework of contrastive variational autoencoders (cVAEs) applied in the contrasts among three groups, to disentangle the latent resting-state network patterns specified for the SCZ and R-SCZ. We demonstrated that the comparison in reconstructed resting-state networks among SCZ, R-SCZ, and healthy controls (HC) revealed network distortions of the inner-frontal hypoconnectivity and frontal-occipital hyperconnectivity, while the original ones illustrated no differences. And only the classification by adopting the reconstructed network metrics achieved satisfying performances, as the highest accuracy of 96.80% ± 2.87%, along with the precision of 95.05% ± 4.28%, recall of 98.18% ± 3.83%, and F1-score of 96.51% ± 2.83%, was obtained. These findings consistently verified the validity of the newly proposed framework for the contrasts among the three groups and provided related resting-state network evidence for illustrating the pathological mechanism underlying the brain deficits in SCZ, as well as facilitating the diagnosis of SCZ.
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Affiliation(s)
- Fali Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, China; School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, China; Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau, China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035 Chengdu, China
| | - Guangying Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, China; School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Lin Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, China; School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, China; School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035 Chengdu, China; School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China
| | - Peng Xu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, China; School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035 Chengdu, China; Radiation Oncology Key Laboratory of Sichuan Province, Chengdu 610041, China; Rehabilitation Center, Qilu Hospital of Shandong University, Jinan 250012, China.
| | - Xuntai Ma
- Clinical Medical College of Chengdu Medical College, Chengdu 610500, China; The First Affiliated Hospital of Chengdu Medical College, Chengdu 610599, China.
| | - Debo Dong
- Faculty of Psychology, Southwest University, Chongqing 400715, China; Institute of Neuroscience and Medicine, Brain and Behavior (INM-7), Research Center Jülich, Jülich, Germany.
| | - Baoming He
- Department of Neurology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 610072, China; Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu 610072, China.
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11
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Sun Y, Zhang M, Saggar M. Cross-attractor modeling of resting-state functional connectivity in psychiatric disorders. Neuroimage 2023; 279:120302. [PMID: 37579998 PMCID: PMC10515743 DOI: 10.1016/j.neuroimage.2023.120302] [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: 10/29/2022] [Revised: 07/26/2023] [Accepted: 07/29/2023] [Indexed: 08/16/2023] Open
Abstract
Resting-state functional connectivity (RSFC) is altered across various psychiatric disorders. Brain network modeling (BNM) has the potential to reveal the neurobiological underpinnings of such abnormalities by dynamically modeling the structure-function relationship and examining biologically relevant parameters after fitting the models with real data. Although innovative BNM approaches have been developed, two main issues need to be further addressed. First, previous BNM approaches are primarily limited to simulating noise-driven dynamics near a chosen attractor (or a stable brain state). An alternative approach is to examine multi(or cross)-attractor dynamics, which can be used to better capture non-stationarity and switching between states in the resting brain. Second, previous BNM work is limited to characterizing one disorder at a time. Given the large degree of co-morbidity across psychiatric disorders, comparing BNMs across disorders might provide a novel avenue to generate insights regarding the dynamical features that are common across (vs. specific to) disorders. Here, we address these issues by (1) examining the layout of the attractor repertoire over the entire multi-attractor landscape using a recently developed cross-attractor BNM approach; and (2) characterizing and comparing multiple disorders (schizophrenia, bipolar, and ADHD) with healthy controls using an openly available and moderately large multimodal dataset from the UCLA Consortium for Neuropsychiatric Phenomics. Both global and local differences were observed across disorders. Specifically, the global coupling between regions was significantly decreased in schizophrenia patients relative to healthy controls. At the same time, the ratio between local excitation and inhibition was significantly higher in the schizophrenia group than the ADHD group. In line with these results, the schizophrenia group had the lowest switching costs (energy gaps) across groups for several networks including the default mode network. Paired comparison also showed that schizophrenia patients had significantly lower energy gaps than healthy controls for the somatomotor and visual networks. Overall, this study provides preliminary evidence supporting transdiagnostic multi-attractor BNM approaches to better understand psychiatric disorders' pathophysiology.
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Affiliation(s)
- Yinming Sun
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94304, USA
| | - Mengsen Zhang
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
| | - Manish Saggar
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94304, USA.
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12
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Chu SA, Tadayonnejad R, Corlier J, Wilson AC, Citrenbaum C, Leuchter AF. Rumination symptoms in treatment-resistant major depressive disorder, and outcomes of repetitive Transcranial Magnetic Stimulation (rTMS) treatment. Transl Psychiatry 2023; 13:293. [PMID: 37684229 PMCID: PMC10491586 DOI: 10.1038/s41398-023-02566-4] [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: 12/12/2022] [Revised: 07/18/2023] [Accepted: 07/20/2023] [Indexed: 09/10/2023] Open
Abstract
Rumination is a maladaptive style of regulating thoughts and emotions. It is a common symptom of Major Depressive Disorder (MDD), and more severe rumination is associated with poorer medication and psychotherapy treatment outcomes, particularly among women. It is unclear to what extent rumination may influence the outcomes of, or be responsive to, repetitive Transcranial Magnetic Stimulation (rTMS) treatment of MDD. We retrospectively examined data collected during rTMS treatment of 155 patients (age 42.52 ± 14.22, 79 female) with moderately severe treatment-resistant MDD. The severity of rumination and depression was assessed before and during a course of 30 sessions of measurement-based rTMS treatment using the Ruminative Responses Scale (RSS) and the Patient Health Questionnaire (PHQ-9), respectively. Relationships among baseline levels of rumination, depression, and treatment outcome were assessed using a series of repeated measures linear mixed effects models. Both depression and rumination symptoms significantly improved after treatment, but improvement in depression was not a significant mediator of rumination improvement. Higher baseline rumination (but not depression severity) was associated with poorer depression outcomes independently of depression severity. Female gender was a significant predictor of worse outcomes for all RRS subscales. Both depressive and ruminative symptoms in MDD improved following rTMS treatment. These improvements were correlated, but improvement in rumination was not fully explained by reduction in depressive symptoms. These findings suggest that while improvement in rumination and depression severity during rTMS treatment are correlated, they are partly independent processes. Future studies should examine whether rumination symptoms should be specifically targeted with different rTMS treatment parameters.
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Affiliation(s)
- Stephanie A Chu
- Neuroscience Interdepartmental Program, UCLA, Los Angeles, USA.
- TMS Clinical and Research Service, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, Los Angeles, CA, USA.
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
| | - Reza Tadayonnejad
- TMS Clinical and Research Service, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, USA
| | - Juliana Corlier
- TMS Clinical and Research Service, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Andrew C Wilson
- TMS Clinical and Research Service, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Cole Citrenbaum
- TMS Clinical and Research Service, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Andrew F Leuchter
- TMS Clinical and Research Service, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
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13
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Luna LP, Sousa MB, Passinho JS, Nardi AE, Oertel V, Veras AB, Alves GS. Resting-state fMRI functional connectivity and clinical correlates in Afro-descendants with schizophrenia and bipolar disorder. Psychiatry Res Neuroimaging 2023; 331:111628. [PMID: 36924740 DOI: 10.1016/j.pscychresns.2023.111628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 02/12/2023] [Accepted: 03/07/2023] [Indexed: 03/18/2023]
Abstract
Schizophrenia (SCZ) and bipolar disorder (BD) exhibited altered activation in several brain areas, including the prefrontal and temporal cortex; however, a less explored topic is how brain connectivity and functional disturbances occur in non-Caucasian samples of SCZ and BD. Individuals with SCZ (n=20), BD (n=21), and healthy controls (HC, n=21) from indigenous and African ethnicity were submitted to clinical screening and functional assessments. Mood, compulsive and psychotic symptoms were also correlated to network dysfunction in each group. Two distinct networks' subcomponents demonstrated significant lower global efficiency (GE) in SCZ versus HC, corresponding to left posterior dorsal attention and medial left ventral attention (VA) networks. Lower GE was found in BD versus controls in four subcomponents, including the left medial and right VA. Higher compulsion scores correlated in BD with lower GE in the left VA, whereas increased report of alcohol abuse was associated with higher GE in left default mode network. Although preliminary, differences in the activation of specific networks, notably the left hemisphere, in SCZ versus controls, and lower activation in VA areas, in BD versus controls. Results highlight default mode and salient network as relevant for the emotional processing of SCZ and BD of indigenous and black ethnicity. Abstract: schizophrenia, bipolar disorder, functional neuroimaging, ethnicity, default network.
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Affiliation(s)
- Licia P Luna
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Hospital, Baltimore, MD, USA
| | | | - Jhule S Passinho
- Neuropsychology Laboratory, CEUMA University, São Luís, Maranhão, Brazil
| | - Antônio E Nardi
- Post-Graduation in Psychiatry and Mental Health (PROPSAM), Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Viola Oertel
- Department of Psychiatry, Psychosomatics, and Psychotherapy, Frankfurt Goethe University, Germany
| | - André Barciela Veras
- Post-Graduation in Psychiatry and Mental Health (PROPSAM), Federal University of Rio de Janeiro, Rio de Janeiro, Brazil; Translational Research Group on Mental Health (GPTranSMe), Dom Bosco Catholic University, Campo Grande, Mato Grosso do Sul, Brazil
| | - Gilberto Sousa Alves
- Post-Graduation in Psychiatry and Mental Health (PROPSAM), Federal University of Rio de Janeiro, Rio de Janeiro, Brazil; Translational Psychiatry Research Group, Federal University of Maranhão, São Luís, Maranhão, Brazil.
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14
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Medina AM, Hagenauer MH, Krolewski DM, Hughes E, Forrester LCT, Walsh DM, Waselus M, Richardson E, Turner CA, Sequeira PA, Cartagena PM, Thompson RC, Vawter MP, Bunney BG, Myers RM, Barchas JD, Lee FS, Schatzberg AF, Bunney WE, Akil H, Watson SJ. Neurotransmission-related gene expression in the frontal pole is altered in subjects with bipolar disorder and schizophrenia. Transl Psychiatry 2023; 13:118. [PMID: 37031222 PMCID: PMC10082811 DOI: 10.1038/s41398-023-02418-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 03/22/2023] [Accepted: 03/27/2023] [Indexed: 04/10/2023] Open
Abstract
The frontal pole (Brodmann area 10, BA10) is the largest cytoarchitectonic region of the human cortex, performing complex integrative functions. BA10 undergoes intensive adolescent grey matter pruning prior to the age of onset for bipolar disorder (BP) and schizophrenia (SCHIZ), and its dysfunction is likely to underly aspects of their shared symptomology. In this study, we investigated the role of BA10 neurotransmission-related gene expression in BP and SCHIZ. We performed qPCR to measure the expression of 115 neurotransmission-related targets in control, BP, and SCHIZ postmortem samples (n = 72). We chose this method for its high sensitivity to detect low-level expression. We then strengthened our findings by performing a meta-analysis of publicly released BA10 microarray data (n = 101) and identified sources of convergence with our qPCR results. To improve interpretation, we leveraged the unusually large database of clinical metadata accompanying our samples to explore the relationship between BA10 gene expression, therapeutics, substances of abuse, and symptom profiles, and validated these findings with publicly available datasets. Using these convergent sources of evidence, we identified 20 neurotransmission-related genes that were differentially expressed in BP and SCHIZ in BA10. These results included a large diagnosis-related decrease in two important therapeutic targets with low levels of expression, HTR2B and DRD4, as well as other findings related to dopaminergic, GABAergic and astrocytic function. We also observed that therapeutics may produce a differential expression that opposes diagnosis effects. In contrast, substances of abuse showed similar effects on BA10 gene expression as BP and SCHIZ, potentially amplifying diagnosis-related dysregulation.
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Affiliation(s)
- Adriana M Medina
- Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA
| | | | - David M Krolewski
- Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA
| | - Evan Hughes
- Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA
| | | | | | - Maria Waselus
- Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA
| | - Evelyn Richardson
- Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA
| | - Cortney A Turner
- Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA
| | | | | | - Robert C Thompson
- Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA
| | | | | | - Richard M Myers
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | | | | | | | | | - Huda Akil
- Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA
| | - Stanley J Watson
- Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA
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15
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Xue C, Zhang X, Cao P, Yuan Q, Liang X, Zhang D, Qi W, Hu J, Xiao C. Evidence of functional abnormalities in the default mode network in bipolar depression: A coordinate-based activation likelihood estimation meta-analysis. J Affect Disord 2023; 326:96-104. [PMID: 36717032 DOI: 10.1016/j.jad.2023.01.088] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 01/15/2023] [Accepted: 01/25/2023] [Indexed: 01/30/2023]
Abstract
BACKGROUND The default mode network (DMN) is thought to be involved in the pathophysiology of bipolar depression (BD). However, the findings of prior studies on DMN alterations in BD are inconsistent. Thus, this study aimed to systematically investigate functional abnormalities of the DMN in BD patients. METHODS We systematically searched PubMed, Ovid, and Web of Science for functional neuroimaging studies on regional homogeneity, amplitude of low frequency fluctuations (ALFF), and functional connectivity of the DMN in BD patients published before March 18, 2022. The stereotactic coordinates of the reported altered brain regions were extracted and incorporated into a brain map using the coordinate-based activation likelihood estimation approach. RESULTS A total of 43 original research studies were included in the meta-analysis. BD patients showed specific changes in the DMN including decreased ALFF/fractional ALFF in the left cingulate gyrus (CG) and bilateral precuneus (PCUN); increased functional connectivity (FC) in the left CG, left posterior CG, left PCUN, bilateral medial frontal gyrus, and bilateral superior frontal gyrus; and decreased FC in the left CG, left PCUN, left inferior parietal lobule, and left postcentral gyrus. LIMITATIONS Conclusions are limited by the small number of studies, additional meta-analyses are needed to obtain more data in BD subgroup. CONCLUSION This meta-analysis supports specific changes in DMN activity and FC in BD patients, which may be powerful biomarkers for the diagnosis of BD. The CG and PCUN were the most affected regions and are thus potential targets for clinical interventions to delay BD progression.
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Affiliation(s)
- Chen Xue
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Xulian Zhang
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Ping Cao
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Qianqian Yuan
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Xuhong Liang
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Da Zhang
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Wenzhang Qi
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Jun Hu
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China.
| | - Chaoyong Xiao
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China.
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16
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Fan F, Wang Z, Fan H, Shi J, Guo H, Yang F, Tan S, Tan Y. Functional disconnection between subsystems of the default mode network in bipolar disorder. J Affect Disord 2023; 325:22-28. [PMID: 36623564 DOI: 10.1016/j.jad.2023.01.026] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Revised: 01/03/2023] [Accepted: 01/04/2023] [Indexed: 01/09/2023]
Affiliation(s)
- Fengmei Fan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing 100096, China
| | - Zhiren Wang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing 100096, China.
| | - Hongzhen Fan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing 100096, China
| | - Jing Shi
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing 100096, China
| | - Hua Guo
- Zhumadian Psychiatry Hospital Henan Province, China
| | - Fude Yang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing 100096, China
| | - Shuping Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing 100096, China.
| | - Yunlong Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing 100096, China
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17
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Sankar A, Shen X, Colic L, Goldman DA, Villa LM, Kim JA, Pittman B, Scheinost D, Constable RT, Blumberg HP. Predicting depressed and elevated mood symptomatology in bipolar disorder using brain functional connectomes. Psychol Med 2023; 53:1-10. [PMID: 36891769 PMCID: PMC10491744 DOI: 10.1017/s003329172300003x] [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: 07/14/2022] [Revised: 12/07/2022] [Accepted: 01/03/2023] [Indexed: 03/10/2023]
Abstract
BACKGROUND The study is aimed to identify brain functional connectomes predictive of depressed and elevated mood symptomatology in individuals with bipolar disorder (BD) using the machine learning approach Connectome-based Predictive Modeling (CPM). METHODS Functional magnetic resonance imaging data were obtained from 81 adults with BD while they performed an emotion processing task. CPM with 5000 permutations of leave-one-out cross-validation was applied to identify functional connectomes predictive of depressed and elevated mood symptom scores on the Hamilton Depression and Young Mania rating scales. The predictive ability of the identified connectomes was tested in an independent sample of 43 adults with BD. RESULTS CPM predicted the severity of depressed [concordance between actual and predicted values (r = 0.23, pperm (permutation test) = 0.031) and elevated (r = 0.27, pperm = 0.01) mood. Functional connectivity of left dorsolateral prefrontal cortex and supplementary motor area nodes, with inter- and intra-hemispheric connections to other anterior and posterior cortical, limbic, motor, and cerebellar regions, predicted depressed mood severity. Connectivity of left fusiform and right visual association area nodes with inter- and intra-hemispheric connections to the motor, insular, limbic, and posterior cortices predicted elevated mood severity. These networks were predictive of mood symptomatology in the independent sample (r ⩾ 0.45, p = 0.002). CONCLUSIONS This study identified distributed functional connectomes predictive of depressed and elevated mood severity in BD. Connectomes subserving emotional, cognitive, and psychomotor control predicted depressed mood severity, while those subserving emotional and social perceptual functions predicted elevated mood severity. Identification of these connectome networks may help inform the development of targeted treatments for mood symptoms.
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Affiliation(s)
- Anjali Sankar
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Neurobiology Research Unit, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Xilin Shen
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Lejla Colic
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- German Center for Mental Health, Halle-Jena-Magdeburg, Magdeburg, Germany
| | - Danielle A. Goldman
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, USA
| | - Luca M. Villa
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Jihoon A. Kim
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Brian Pittman
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Dustin Scheinost
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - R. Todd Constable
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Hilary P. Blumberg
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
- Child Study Center, Yale School of Medicine, New Haven, CT, USA
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18
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Prieto-Alcántara M, Ibáñez-Molina A, Crespo-Cobo Y, Molina R, Soriano MF, Iglesias-Parro S. Alpha and gamma EEG coherence during on-task and mind wandering states in schizophrenia. Clin Neurophysiol 2023; 146:21-29. [PMID: 36495599 DOI: 10.1016/j.clinph.2022.11.010] [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: 06/15/2022] [Revised: 10/12/2022] [Accepted: 11/13/2022] [Indexed: 11/27/2022]
Abstract
OBJECTIVE Electroencephalographic (EEG) coherence is one of the most relevant physiological measures used to detect abnormalities in patients with schizophrenia. The present study applies a task-related EEG coherence approach to understand cognitive processing in patients with schizophrenia and healthy controls. METHODS EEG coherence for alpha and gamma frequency bands was analyzed in a group of patients with schizophrenia and a group of healthy controls during the performance of an ecological task of sustained attention. We compared EEG coherence when participants presented externally directed cognitive states (On-Task) and when they presented cognitive distraction episodes (Mind-Wandering). RESULTS Results reflect cortical differences between groups (higher coherence for schizophrenia in the frontocentral and fronto-temporal regions, and higher coherence for healthy-controls in the postero-central regions), especially in the On-Task condition for the alpha band, compared to Mind-Wandering episodes. Few individual differences in gamma coherence were found. CONCLUSIONS The current study provides evidence of neurophysiological differences underlying different cognitive states in schizophrenia and healthy controls. SIGNIFICANCE Differences between groups may reflect inhibitory processes necessary for the successful processing of information, especially in the alpha band, given its role in cortical inhibition processes. Patients may activate compensatory inhibitory mechanisms when performing the task, reflected in increased coherence in fronto-temporal regions.
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Affiliation(s)
| | | | | | - Rosa Molina
- Psychology Department, University of Jaén, 23071 Jaén, Spain
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19
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Hong J, Hwang J, Lee JH. General psychopathology factor (p-factor) prediction using resting-state functional connectivity and a scanner-generalization neural network. J Psychiatr Res 2023; 158:114-125. [PMID: 36580867 DOI: 10.1016/j.jpsychires.2022.12.037] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 12/09/2022] [Accepted: 12/20/2022] [Indexed: 12/24/2022]
Abstract
The general psychopathology factor (p-factor) represents shared variance across mental disorders based on psychopathologic symptoms. The Adolescent Brain Cognitive Development (ABCD) Study offers an unprecedented opportunity to investigate functional networks (FNs) from functional magnetic resonance imaging (fMRI) associated with the psychopathology of an adolescent cohort (n > 10,000). However, the heterogeneities associated with the use of multiple sites and multiple scanners in the ABCD Study need to be overcome to improve the prediction of the p-factor using fMRI. We proposed a scanner-generalization neural network (SGNN) to predict the individual p-factor by systematically reducing the scanner effect for resting-state functional connectivity (RSFC). We included 6905 adolescents from 18 sites whose fMRI data were collected using either Siemens or GE scanners. The p-factor was estimated based on the Child Behavior Checklist (CBCL) scores available in the ABCD study using exploratory factor analysis. We evaluated the Pearson's correlation coefficients (CCs) for p-factor prediction via leave-one/two-site-out cross-validation (LOSOCV/LTSOCV) and identified important FNs from the weight features (WFs) of the SGNN. The CCs were higher for the SGNN than for alternative models when using both LOSOCV (0.1631 ± 0.0673 for the SGNN vs. 0.1497 ± 0.0710 for kernel ridge regression [KRR]; p < 0.05 from a two-tailed paired t-test) and LTSOCV (0.1469 ± 0.0381 for the SGNN vs. 0.1394 ± 0.0359 for KRR; p = 0.01). It was found that (a) the default-mode and dorsal attention FNs were important for p-factor prediction, and (b) the intra-visual FN was important for scanner generalization. We demonstrated the efficacy of our novel SGNN model for p-factor prediction while simultaneously eliminating scanner-related confounding effects for RSFC.
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Affiliation(s)
- Jinwoo Hong
- Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea
| | - Jundong Hwang
- Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea
| | - Jong-Hwan Lee
- Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea.
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Abstract
There is now a significant body of literature concerning sex/gender differences in the human brain. This chapter will critically review and synthesise key findings from several studies that have investigated sex/gender differences in structural and functional lateralisation and connectivity. We argue that while small, relative sex/gender differences reliably exist in lateralisation and connectivity, there is considerable overlap between the sexes. Some inconsistencies exist, however, and this is likely due to considerable variability in the methodologies, tasks, measures, and sample compositions between studies. Moreover, research to date is limited in its consideration of sex/gender-related factors, such as sex hormones and gender roles, that can explain inter-and inter-individual differences in brain and behaviour better than sex/gender alone. We conclude that conceptualising the brain as 'sexually dimorphic' is incorrect, and the terms 'male brain' and 'female brain' should be avoided in the neuroscientific literature. However, this does not necessarily mean that sex/gender differences in the brain are trivial. Future research involving sex/gender should adopt a biopsychosocial approach whenever possible, to ensure that non-binary psychological, biological, and environmental/social factors related to sex/gender, and their interactions, are routinely accounted for.
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Affiliation(s)
- Sophie Hodgetts
- School of Psychology, University of Sunderland, Sunderland, UK
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21
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Xi C, Liu Z, Zeng C, Tan W, Sun F, Yang J, Palaniyappan L. The centrality of working memory networks in differentiating bipolar type I depression from unipolar depression: A task-fMRI study. CANADIAN JOURNAL OF PSYCHIATRY. REVUE CANADIENNE DE PSYCHIATRIE 2023; 68:22-32. [PMID: 35244484 PMCID: PMC9720478 DOI: 10.1177/07067437221078646] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
OBJECTIVES Up to 70%-80% of patients with bipolar disorder are misdiagnosed as having major depressive disorder (MDD), leading to both delayed intervention and worsening disability. Differences in the cognitive neurophysiology may serve to distinguish between the depressive phase of type 1 bipolar disorder (BDD-I) from MDD, though this remains to be demonstrated. To this end, we investigate the discriminatory signal in the topological organization of the functional connectome during a working memory (WM) task in BDD-I and MDD, as a candidate identification approach. METHODS We calculated and compared the degree centrality (DC) at the whole-brain voxel-wise level in 31 patients with BDD-I, 35 patients with MDD, and 80 healthy controls (HCs) during an n-back task. We further extracted the distinct DC patterns in the two patient groups under different WM loads and used machine learning approaches to determine the distinguishing ability of the DC map. RESULTS Patients with BDD-I had lower accuracy and longer reaction time (RT) than HCs at high WM loads. BDD-I is characterized by decreased DC in the default mode network (DMN) and the sensorimotor network (SMN) when facing high WM load. In contrast, MDD is characterized by increased DC in the DMN during high WM load. Higher WM load resulted in better classification performance, with the distinct aberrant DC maps under 2-back load discriminating the two disorders with 90.91% accuracy. CONCLUSIONS The distributed brain connectivity during high WM load provides novel insights into the neurophysiological mechanisms underlying cognitive impairment of depression. This could potentially distinguish BDD-I from MDD if replicated in future large-scale evaluations of first-episode depression with longitudinal confirmation of diagnostic transition.
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Affiliation(s)
- Chang Xi
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, Changsha, China
| | - Zhening Liu
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, Changsha, China
| | - Can Zeng
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, Changsha, China
| | - Wenjian Tan
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, Changsha, China
| | - Fuping Sun
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, Changsha, China
| | - Jie Yang
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, Changsha, China
| | - Lena Palaniyappan
- 113611Robarts Research Institute, Western University, London, Canada.,Departments of Psychiatry and Medical Biophysics, Schulich School of Medicine, Western University, London, Canada
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22
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Xue K, Chen J, Wei Y, Chen Y, Han S, Wang C, Zhang Y, Song X, Cheng J. Altered static and dynamic functional connectivity of habenula in first-episode, drug-naïve schizophrenia patients, and their association with symptoms including hallucination and anxiety. Front Psychiatry 2023; 14:1078779. [PMID: 36741115 PMCID: PMC9892902 DOI: 10.3389/fpsyt.2023.1078779] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 01/04/2023] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND AND OBJECTIVE The pathogenesis of schizophrenia (SCH) is related to the dysfunction of monoamine neurotransmitters, and the habenula participates in regulating the synthesis and release of dopamine. We examined the static functional connectivity (sFC) and dynamic functional connectivity (dFC) of habenula in first-episode schizophrenia patients using resting state functional magnetic resonance imaging (rs-fMRI) in this study. METHODS A total of 198 first-Episode, drug-Naïve schizophrenia patients and 199 healthy controls (HC) underwent rs-fMRI examinations. The sFC and dFC analysis with habenula as seed was performed to produce a whole-brain diagram initially, which subsequently were compared between SCH and HC groups. Finally, the correlation analysis of sFC and dFC values with the Positive and Negative Symptom Scale (PANSS) were performed. RESULTS Compared with the HC groups, the left habenula showed increased sFC with the bilateral middle temporal gyrus, bilateral superior temporal gyrus, and right temporal pole in the SCH group, and the right habenula exhibited increased sFC with the left middle temporal gyrus, left superior temporal gyrus, and left angular gyrus. Additionally, compared with the HC group, the left habenula showed decreased dFC with the bilateral cuneus gyrus and bilateral calcarine gyrus in the SCH group. The PANSS negative sub-scores were positively correlated with the sFC values of the bilateral habenula with the bilateral middle temporal gyrus, superior temporal gyrus and angular gyrus. The PANSS general sub-scores were positively correlated with the sFC values of the right habenula with the left middle temporal gyrus and left superior temporal gyrus. The hallucination scores of PANSS were negatively correlated with the sFC values of the left habenula with the bilateral cuneus gyrus and bilateral calcarine gyrus; The anxiety scores of PANSS were positively correlated with the dFC values of the left habenula with the right temporal pole. CONCLUSION This study provides evidence that the habenula of the first-episode schizophrenia patients presented abnormal static functional connectivity with temporal lobe and angular gyrus, and additionally showed weakened stability of functional connectivity in occipital lobe. This abnormality is closely related to the symptoms of hallucination and anxiety in schizophrenia, which may indicate that the habenula involved in the pathophysiology of schizophrenia by affecting the dopamine pathway.
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Affiliation(s)
- Kangkang Xue
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingli Chen
- Department of Magnetic Resonance Imaging, 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
| | - Yuan Chen
- 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
| | - Caihong Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xueqin Song
- Department of Psychiatry, 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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23
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de Sousa TR, Dt C, Novais F. Exploring the Hypothesis of a Schizophrenia and Bipolar Disorder Continuum: Biological, Genetic and Pharmacologic Data. CNS & NEUROLOGICAL DISORDERS DRUG TARGETS 2023; 22:161-171. [PMID: 34477537 DOI: 10.2174/1871527320666210902164235] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 07/19/2021] [Accepted: 08/08/2021] [Indexed: 12/16/2022]
Abstract
Present time nosology has its roots in Kraepelin's demarcation of schizophrenia and bipolar disorder. However, accumulating evidence has shed light on several commonalities between the two disorders, and some authors have advocated for the consideration of a disease continuum. Here, we review previous genetic, biological and pharmacological findings that provide the basis for this conceptualization. There is a cross-disease heritability, and they share single-nucleotide polymorphisms in some common genes. EEG and imaging patterns have a number of similarities, namely reduced white matter integrity and abnormal connectivity. Dopamine, serotonin, GABA and glutamate systems have dysfunctional features, some of which are identical among the disorders. Finally, cellular calcium regulation and mitochondrial function are, also, impaired in the two.
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Affiliation(s)
- Teresa Reynolds de Sousa
- Department of Neurosciences and Mental Health, Centro Hospitalar Universitário Lisboa Norte (CHULN), Hospital de Santa Maria, Lisbon, Portugal
| | - Correia Dt
- Department of Neurosciences and Mental Health, Centro Hospitalar Universitário Lisboa Norte (CHULN), Hospital de Santa Maria, Lisbon, Portugal
- Faculdade de Medicina da Universidade de Lisboa, Lisboa, Portugal
- ISAMB - Instituto de Saúde Ambiental, Lisboa, Portugal
| | - Filipa Novais
- Department of Neurosciences and Mental Health, Centro Hospitalar Universitário Lisboa Norte (CHULN), Hospital de Santa Maria, Lisbon, Portugal
- Faculdade de Medicina da Universidade de Lisboa, Lisboa, Portugal
- ISAMB - Instituto de Saúde Ambiental, Lisboa, Portugal
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24
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Si Y, Liu C, Kou Y, Dong Z, Zhang J, Wang J, Lu C, Luo Y, Ni T, Du Y, Zhang H. Antipsychotics-induced improvement of cool executive function in individuals living with schizophrenia. Front Psychiatry 2023; 14:1154011. [PMID: 37181875 PMCID: PMC10172485 DOI: 10.3389/fpsyt.2023.1154011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 04/07/2023] [Indexed: 05/16/2023] Open
Abstract
Cool executive dysfunction is a crucial feature in people living with schizophrenia which is related to cognition impairment and the severity of the clinical symptoms. Based on electroencephalogram (EEG), our current study explored the change of brain network under the cool executive tasks in individuals living with schizophrenia before and after atypical antipsychotic treatment (before_TR vs. after_TR). 21 patients with schizophrenia and 24 healthy controls completed the cool executive tasks, involving the Tower of Hanoi Task (THT) and Trail-Marking Test A-B (TMT A-B). The results of this study uncovered that the reaction time of the after_TR group was much shorter than that of the before_TR group in the TMT-A and TMT-B. And the after_TR group showed fewer error numbers in the TMT-B than those of the before_TR group. Concerning the functional network, stronger DMN-like linkages were found in the before_TR group compared to the control group. Finally, we adopted a multiple linear regression model based on the change network properties to predict the patient's PANSS change ratio. Together, the findings deepened our understanding of cool executive function in individuals living with schizophrenia and might provide physiological information to reliably predict the clinical efficacy of schizophrenia after atypical antipsychotic treatment.
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Affiliation(s)
- Yajing Si
- School of Psychology, Xinxiang Medical University, Xinxiang, Henan, China
- Xinxiang Key Lab for Psychopathology and Cognitive Neuroscience, Xinxiang, Henan, China
| | - Congcong Liu
- School of Psychology, Xinxiang Medical University, Xinxiang, Henan, China
| | - Yanna Kou
- Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China
| | - Zhao Dong
- Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China
- Zhumadian Second People's Hospital, Zhumadian, Henan, China
| | - Jiajia Zhang
- School of Psychology, Xinxiang Medical University, Xinxiang, Henan, China
| | - Juan Wang
- Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China
| | - Chengbiao Lu
- Henan International Key Laboratory for Non-invasive Neuromodulation, Xinxiang, Henan, China
| | - Yanyan Luo
- School of Nursing, Xinxiang Medical University, Xinxiang, Henan, China
| | - Tianjun Ni
- School of Basic Medical Sciences, Xinxiang Medical University, Xinxiang, Henan, China
| | - Yunhong Du
- Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China
| | - Hongxing Zhang
- School of Psychology, Xinxiang Medical University, Xinxiang, Henan, China
- Xinxiang Key Lab for Psychopathology and Cognitive Neuroscience, Xinxiang, Henan, China
- Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China
- Henan International Key Laboratory for Non-invasive Neuromodulation, Xinxiang, Henan, China
- *Correspondence: Hongxing Zhang,
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25
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Miklowitz DJ, Weintraub MJ, Walshaw PD, Schneck CD, Chang KD, Merranko J, Garrett AS, Singh MK. Early Family Intervention for Youth at Risk for Bipolar Disorder: Psychosocial and Neural Mediators of Outcome. Curr Neuropharmacol 2023; 21:1379-1392. [PMID: 36635932 PMCID: PMC10324335 DOI: 10.2174/1570159x21666230111120817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Revised: 05/14/2022] [Accepted: 11/25/2022] [Indexed: 01/14/2023] Open
Abstract
BACKGROUND The impairing neurodevelopmental course of bipolar disorder (BD) suggests the importance of early intervention for youth in the beginning phases of the illness. OBJECTIVE We report the results of a 3-site randomized trial of family-focused therapy for youth at high-risk (FFT-HR) for BD, and explore psychosocial and neuroimaging variables as mediators of treatment effects. METHODS High-risk youth (<18 years) with major depressive disorder or other specified BD, active mood symptoms, and a family history of BD were randomly assigned to 4 months of FFT-HR (psychoeducation, communication and problem-solving skills training) or 4 months of enhanced care psychoeducation. Adjunctive pharmacotherapy was provided by study psychiatrists. Neuroimaging scans were conducted before and after psychosocial treatments in eligible participants. Independent evaluators interviewed participants every 4-6 months over 1-4 years regarding symptomatic outcomes. RESULTS Among 127 youth (mean 13.2 ± 2.6 years) over a median of 98 weeks, FFT-HR was associated with longer intervals prior to new mood episodes and lower levels of suicidal ideation than enhanced care. Reductions in perceived family conflict mediated the effects of psychosocial interventions on the course of mood symptoms. Among 34 participants with pre-/post-treatment fMRI scans, youth in FFT-HR had (a) stronger resting state connectivity between ventrolateral PFC and anterior default mode network, and (b) increased activity of dorsolateral and medial PFC in emotion processing and problem-solving tasks, compared to youth in enhanced care. CONCLUSION FFT-HR may delay new mood episodes in symptomatic youth with familial liability to BD. Putative treatment mechanisms include neural adaptations suggestive of improved emotion regulation.
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Affiliation(s)
- David J. Miklowitz
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
| | - Marc J. Weintraub
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
| | - Patricia D. Walshaw
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
| | | | - Kiki D. Chang
- Private Practice, 2460 Park Blvd, Suite 6 Palo Alto, CA 94306 USA
| | - John Merranko
- Department of Psychiatry, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Amy S. Garrett
- Department of Psychiatry, University of Texas, Health Science Center at San Antonio, San Antonio, TX, USA
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26
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Canessa N, Basso G, Manera M, Poggi P, Gianelli C. Functional Coherence in Intrinsic Frontal Executive Networks Predicts Cognitive Impairments in Alcohol Use Disorder. Brain Sci 2022; 13:45. [PMID: 36672027 PMCID: PMC9856140 DOI: 10.3390/brainsci13010045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 12/03/2022] [Accepted: 12/22/2022] [Indexed: 12/28/2022] Open
Abstract
Growing evidence highlights the potential of innovative rehabilitative interventions such as cognitive remediation and neuromodulation, aimed at reducing relapses in Alcohol Use Disorder (AUD). Enhancing their effectiveness requires a thorough description of the neural correlates of cognitive alterations in AUD. Past related attempts, however, were limited by the focus on selected neuro-cognitive variables. We aimed to fill this gap by combining, in 22 AUD patients and 18 controls, an extensive neuro-cognitive evaluation and metrics of intrinsic connectivity as highlighted by resting-state brain activity. We addressed an inherent property of intrinsic activity such as intra-network coherence, the temporal correlation of the slow synchronous fluctuations within resting-state networks, representing an early biomarker of alterations in the functional brain architecture underlying cognitive functioning. AUD patients displayed executive impairments involving working-memory, attention and visuomotor speed, reflecting abnormal coherence of activity and grey matter atrophy within default mode, in addition to the attentional and the executive networks. The stronger relationship between fronto-lateral coherent activity and executive performance in patients than controls highlighted possible compensatory mechanisms counterbalancing the decreased functionality of networks driving the switch from automatic to controlled behavior. These results provide novel insights into AUD patients' cognitive impairments, their neural bases, and possible targets of rehabilitative interventions.
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Affiliation(s)
- Nicola Canessa
- IUSS Cognitive Neuroscience (ICON) Center, Scuola Universitaria Superiore IUSS, 27100 Pavia, Italy
- Istituti Clinici Scientifici Maugeri IRCCS, Cognitive Neuroscience Laboratory of Pavia Institute, 27100 Pavia, Italy
| | - Gianpaolo Basso
- School of Medicine and Surgery, University of Milano-Bicocca, 20126 Milan, Italy
| | - Marina Manera
- Istituti Clinici Scientifici Maugeri IRCCS, Clinical Psychology Unit of Pavia Institute, 27100 Pavia, Italy
| | - Paolo Poggi
- Istituti Clinici Scientifici Maugeri IRCCS, Radiology Unit of Pavia Institute, 27100 Pavia, Italy
| | - Claudia Gianelli
- IUSS Cognitive Neuroscience (ICON) Center, Scuola Universitaria Superiore IUSS, 27100 Pavia, Italy
- Department of Clinical and Experimental Medicine, University of Messina, 98122 Messina, Italy
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27
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Kazour F, Atanasova B, Mourad M, El Hachem C, Desmidt T, Richa S, El-Hage W. Mania associated olfactory dysfunction: A comparison between bipolar subjects in mania and remission. J Psychiatr Res 2022; 156:330-338. [PMID: 36323136 DOI: 10.1016/j.jpsychires.2022.10.038] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 10/07/2022] [Accepted: 10/17/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVES The aim of this study was to assess the olfactory functions of patients with bipolar disorder in manic phase and to compare them to those of bipolar subjects in remission and healthy controls. METHODS We recruited 96 participants divided in 3 groups: bipolar mania (MB), euthymic bipolar in remission (EB) and healthy controls (HC). All participants underwent an assessment of their olfactory functions using the Sniffin' sticks threshold and identification tests. Odors' pleasantness, intensity, familiarity and emotion were assessed. All participants were screened for the presence of psychiatric disorder through the MINI questionnaire. Clinical evaluation explored dimensions of mania, depression, anxiety respectively through YMRS, MADRS and STAI scales. Anhedonia was explored through the Chapman physical and social anhedonia questionnaire. RESULTS Patients in mania had deficits in identifying positive smells compared to bipolar subjects in remission and to healthy controls (MB < EB < HC; p < 0.001). Hedonic (MB < EB = HC; p < 0.001) and emotional (MB < EB = HC; p < 0.001) ratings of positive smells were lower in patients in manic phase compared to remitted subjects or controls. Mania was associated to higher emotion rating of negative smells compared to remitted subjects and controls (MB > EB = HC; p < 0.001). There was no difference between the 3 groups in the ratings of intensity and familiarity of smells, as well as in the olfactory threshold testing. The 3 groups showed no difference in the identification of negative smells. CONCLUSIONS Patients in manic episodes showed deficits in identifying positive odors. They evaluated these smells as less pleasant and less emotional compared to remitted bipolar subjects and healthy controls. These olfactory dysfunctions may constitute potential indicators of manic state. The persistence of olfactory dysfunction in remission phase (deficit in the olfactory identification of positive odors compared to healthy controls) may constitute a potential trait indicator of bipolarity.
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Affiliation(s)
- Francois Kazour
- UMR 1253, iBrain, Université de Tours, INSERM, Tours, France; Clinique Psychiatrique Universitaire, CHU de Tours, Tours, France; Department of Psychiatry, Faculty of Medicine, Saint Joseph University, Beirut, Lebanon.
| | | | - Marc Mourad
- Department of Psychiatry, Faculty of Medicine, Saint Joseph University, Beirut, Lebanon
| | - Charline El Hachem
- Department of Psychiatry, Faculty of Medicine, Saint Joseph University, Beirut, Lebanon
| | - Thomas Desmidt
- UMR 1253, iBrain, Université de Tours, INSERM, Tours, France; Clinique Psychiatrique Universitaire, CHU de Tours, Tours, France
| | - Sami Richa
- Department of Psychiatry, Faculty of Medicine, Saint Joseph University, Beirut, Lebanon
| | - Wissam El-Hage
- UMR 1253, iBrain, Université de Tours, INSERM, Tours, France; Clinique Psychiatrique Universitaire, CHU de Tours, Tours, France
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28
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Ho NF, Lin AY, Tng JXJ, Chew QH, Cheung MWL, Javitt DC, Sim K. Abnormalities in visual cognition and associated impaired interactions between visual and attentional networks in schizophrenia and brief psychotic disorder. Psychiatry Res Neuroimaging 2022; 327:111545. [PMID: 36272310 DOI: 10.1016/j.pscychresns.2022.111545] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 09/08/2022] [Accepted: 09/23/2022] [Indexed: 12/04/2022]
Abstract
The extent and nature of cognitive impairment in brief psychotic disorder remains unclear, being rarely studied unlike schizophrenia. The present study hence sought to directly compare the visual cognitive dysfunction and its associated brain networks in brief psychotic disorder and schizophrenia. Data from picture completion (a complex visual task) and whole-brain functional connectome from resting-state fMRI were acquired from a sample of clinically stable patients with an established psychotic disorder (twenty with brief psychotic disorder, twenty with schizophrenia) and twenty-nine healthy controls. Group differences and the inter-relationships in task performances and brain networks were tested. Picture completion task deficits were found in brief psychotic disorder compared with healthy controls, though the deficits were less than schizophrenia. Task performance also correlated with severity of psychotic symptoms in patients. The task performance was inversely correlated with the functional connectivity between peripheral visual and attentional networks (dorsal attention and salience ventral attention), with increased functional connectivity in brief psychotic disorder compared with healthy controls and in schizophrenia compared with brief psychotic disorder. Present findings showed pronounced visual cognitive impairments in brief psychotic disorder that were worse in schizophrenia, underpinned by abnormal interactions between higher-order attentional and lower-order visual processing networks.
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Affiliation(s)
- New Fei Ho
- Institute of Mental Health, Singapore; Duke-National University of Singapore Medical School, Singapore.
| | | | | | | | | | | | - Kang Sim
- Institute of Mental Health, Singapore
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Wei Y, de Lange SC, Savage JE, Tissink E, Qi T, Repple J, Gruber M, Kircher T, Dannlowski U, Posthuma D, van den Heuvel MP. Associated Genetics and Connectomic Circuitry in Schizophrenia and Bipolar Disorder. Biol Psychiatry 2022:S0006-3223(22)01719-X. [PMID: 36803976 DOI: 10.1016/j.biopsych.2022.11.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 10/15/2022] [Accepted: 11/02/2022] [Indexed: 11/11/2022]
Abstract
BACKGROUND Schizophrenia (SCZ) and bipolar disorder (BD) are severe psychiatric conditions that can involve symptoms of psychosis and cognitive dysfunction. The 2 conditions share symptomatology and genetic etiology and are regularly hypothesized to share underlying neuropathology. Here, we examined how genetic liability to SCZ and BD shapes normative variations in brain connectivity. METHODS We examined the effect of the combined genetic liability for SCZ and BD on brain connectivity from two perspectives. First, we examined the association between polygenic scores for SCZ and BD for 19,778 healthy subjects from the UK Biobank and individual variation in brain structural connectivity reconstructed by means of diffusion weighted imaging data. Second, we conducted genome-wide association studies using genotypic and imaging data from the UK Biobank, taking SCZ-/BD-involved brain circuits as phenotypes of interest. RESULTS Our findings showed brain circuits of superior parietal and posterior cingulate regions to be associated with polygenic liability for SCZ and BD, circuitry that overlaps with brain networks involved in disease conditions (r = 0.239, p < .001). Genome-wide association study analysis showed 9 significant genomic loci associated with SCZ-involved circuits and 14 loci associated with BD-involved circuits. Genes related to SCZ-/BD-involved circuits were significantly enriched in gene sets previously reported in genome-wide association studies for SCZ and BD. CONCLUSIONS Our findings suggest that polygenic liability of SCZ and BD is associated with normative individual variation in brain circuitry.
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Affiliation(s)
- Yongbin Wei
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China; Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
| | - Siemon C de Lange
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Department of Sleep and Cognition, Netherlands Institute for Neuroscience, an institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, the Netherlands
| | - Jeanne E Savage
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Elleke Tissink
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Ting Qi
- Department of Neurology, School of Medicine, University of California San Francisco, San Francisco, California
| | - Jonathan Repple
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Marius Gruber
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Danielle Posthuma
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Department of Child and Adolescent Psychiatry and Psychology, Section Complex Trait Genetics, Amsterdam Neuroscience, Vrije Universiteit Medical Center, Amsterdam UMC, Amsterdam, the Netherlands
| | - Martijn P van den Heuvel
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Department of Child and Adolescent Psychiatry and Psychology, Section Complex Trait Genetics, Amsterdam Neuroscience, Vrije Universiteit Medical Center, Amsterdam UMC, Amsterdam, the Netherlands.
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Boosting psychological change: Combining non-invasive brain stimulation with psychotherapy. Neurosci Biobehav Rev 2022; 142:104867. [PMID: 36122739 DOI: 10.1016/j.neubiorev.2022.104867] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 09/01/2022] [Accepted: 09/07/2022] [Indexed: 11/21/2022]
Abstract
Mental health disorders and substance use disorders are a leading cause of morbidity and mortality worldwide, and one of the most important challenges for public health systems. While evidence-based psychotherapy is generally pursued to address mental health challenges, psychological change is often hampered by non-adherence to treatments, relapses, and practical barriers (e.g., time, cost). In recent decades, Non-invasive brain stimulation (NIBS) techniques have emerged as promising tools to directly target dysfunctional neural circuitry and promote long-lasting plastic changes. While the therapeutic efficacy of NIBS protocols for mental illnesses has been established, neuromodulatory interventions might also be employed to support the processes activated by psychotherapy. Indeed, combining psychotherapy with NIBS might help tailor the treatment to the patient's unique characteristics and therapeutic goal, and would allow more direct control of the neuronal changes induced by therapy. Herein, we overview emerging evidence on the use of NIBS to enhance the psychotherapeutic effect, while highlighting the next steps in advancing clinical and research methods toward personalized intervention approaches.
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31
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Schiwy LC, Forlim CG, Fischer DJ, Kühn S, Becker M, Gallinat J. Aberrant functional connectivity within the salience network is related to cognitive deficits and disorganization in psychosis. Schizophr Res 2022; 246:103-111. [PMID: 35753120 DOI: 10.1016/j.schres.2022.06.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 05/10/2022] [Accepted: 06/11/2022] [Indexed: 01/09/2023]
Abstract
In schizophrenia and schizoaffective disorder cognitive deficits are a reliable characteristic predicting a poor functional outcome. It has been theorized that both the default mode network (DMN) and the salience network (SN) play a crucial role in cognitive processes and aberrant functional connectivity within these networks in psychotic patients has been reported. The goal of this study was to reveal potential links between aberrant functional connectivity within these networks and impaired cognitive performance in psychosis. We chose two approaches for cognitive assessment, first the MATRICS Consensus Cognitive Battery (MCCB) combined into a global score and second the disorganization factor derived from a five-factor model of the Positive and Negative Syndrome Scale (PANSS) known to be relevant for cognitive performance. DMN and SN were identified using independent component analysis on resting-state functional magnetic resonance imaging data. We found significantly decreased connectivity within the right supplementary motor area (SMA) and bilateral putamen in patients with psychosis (n = 70; 27F/43M) compared to healthy controls (n = 72; 28F/44M). Within patients, linear regression analysis revealed that aberrant SMA connectivity was associated with impaired global cognition, while dysfunctional bilateral putamen connectivity predicted disorganization. There were no significant changes in connectivity within the DMN. Results support the hypothesis that SN dysfunctional connectivity is important in the pathobiology of cognitive deficits in psychosis. For the first time we were able to show the involvement of dysfunctional SMA connectivity in this context. We interpret the decreased SN connectivity as evidence of reduced functionality in recruiting brain areas necessary for cognitive processing.
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Affiliation(s)
- Lennart Christopher Schiwy
- University Medical Centre Hamburg-Eppendorf, Clinic and Policlinic for Psychiatry and Psychotherapy, Martinistraße 52, 20246 Hamburg, Germany.
| | - Caroline Garcia Forlim
- University Medical Centre Hamburg-Eppendorf, Clinic and Policlinic for Psychiatry and Psychotherapy, Martinistraße 52, 20246 Hamburg, Germany
| | - Djo Juliette Fischer
- University Medical Centre Hamburg-Eppendorf, Clinic and Policlinic for Psychiatry and Psychotherapy, Martinistraße 52, 20246 Hamburg, Germany
| | - Simone Kühn
- University Medical Centre Hamburg-Eppendorf, Clinic and Policlinic for Psychiatry and Psychotherapy, Martinistraße 52, 20246 Hamburg, Germany; Max Planck Institute for Human Development, Center for Lifespan Psychology, Lentzeallee 94, 14195 Berlin, Germany
| | - Maxi Becker
- University Medical Centre Hamburg-Eppendorf, Clinic and Policlinic for Psychiatry and Psychotherapy, Martinistraße 52, 20246 Hamburg, Germany
| | - Jürgen Gallinat
- University Medical Centre Hamburg-Eppendorf, Clinic and Policlinic for Psychiatry and Psychotherapy, Martinistraße 52, 20246 Hamburg, Germany
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32
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Long J, Qin K, Wu Y, Li L, Zhou J. Gray matter abnormalities and associated familial risk endophenotype in individuals with first-episode bipolar disorder: Evidence from whole-brain voxel-wise meta-analysis. Asian J Psychiatr 2022; 74:103179. [PMID: 35691059 DOI: 10.1016/j.ajp.2022.103179] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Revised: 05/16/2022] [Accepted: 05/30/2022] [Indexed: 11/29/2022]
Abstract
Gray matter abnormalities have been widely reported in individuals with and at familial risk for bipolar disorder (BD). However, inconsistent findings were reported, and whether shared abnormalities exist between at-risk individuals and patients which can represent an endophenotype remained unclear. This meta-analysis aimed at identifying robust patterns of gray matter changes in patients with first-episode BD (FEBD) and associated risk endophenotype of BD. A systematic literature search was performed to identify eligible voxel-based morphometry studies comparing FEBD patients and healthy controls. Findings of included studies were integrated using the Seed-based d Mapping toolbox. Common and distinct patterns of gray matter abnormalities between FEBD patients and unaffected at-risk individuals were explored. A total of 16 VBM studies comparing 411 FEBD patients and 521 controls were included. FEBD patients showed increased gray matter volume in the cerebellum, posterior cingulate cortex and striatum, and decreased gray matter volume in the medial superior frontal gyrus and gyrus rectus. No common abnormalities were identified between FEBD patients and unaffected at-risk individuals. More gray matter loss in the medial superior frontal gyrus and insula were found in FEBD patients relative to unaffected at-risk individuals. These findings revealed robust gray matter abnormalities in the cortico-striato-cerebellar and default mode network regions in FEBD, and implicated that gray matter deficits may not represent a familial risk endophenotype of BD.
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Affiliation(s)
- Jingyi Long
- Department of Radiology, Wuhan Mental Health Center, Wuhan 430012, Hubei, China; Department of Radiology, Wuhan Hospital for Psychotherapy, Wuhan 430012, Hubei, China
| | - Kun Qin
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA
| | - Yong Wu
- Department of Depression, Wuhan Hospital for Psychotherapy, Wuhan 430012, Hubei, China
| | - Lu Li
- Department of Interventional Radiology, Wuhan Jinyintan Hospital, Wuhan 430023, Hubei, China.
| | - Juan Zhou
- Department of Ultrasonography, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210000, Jiangsu, China.
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Sendi MSE, Dini H, Bruni LE, Calhoun VD. Default mode network dynamic functional network connectivity predicts psychotic symptom severity. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:247-250. [PMID: 36085610 DOI: 10.1109/embc48229.2022.9871542] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Neuropsychiatric disorders affect millions of people worldwide every year. Recent studies showed that the symptomatic overlaps across neuropsychiatric disorders mislead schizophrenia and bipolar disorder diagnosis. Additionally, recent studies claimed that schizoaffective disorder as a condition overlapped with both schizophrenia and bipolar disorder. Since symptomatic overlap among these disorders causes misdiagnosis, a need for neuroimaging biomarkers differentiating these disorders for a more accurate diagnosis is crucial. This study investigates dynamics functional network connectivity (dFNC) in the default mode network (DMN) of schizophrenia, bipolar, and schizoaffective disorder patients and compares them with their relative and healthy control. Additionally, it explored whether DMN dFNC features can predict the symptom severity of these neuropsychiatric disorders. Here, we found that dFNC features can differentiate schizophrenia from bipolar disorder. At the same time, we did not see a significant difference between schizoaffective with other conditions. Additionally, we found dFNC features can predict symptom severity of these three conditions.
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Huang CC, Low I, Kao CH, Yu CY, Su TP, Hsieh JC, Chen YS, Chen LF. MEG-based Classification and Grad-CAM Visualization for Major Depressive and Bipolar Disorders with Semi-CNN. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:1823-1826. [PMID: 36086021 DOI: 10.1109/embc48229.2022.9871238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Major depressive disorder (MDD) and bipolar disorder (BD) are two major mood disorders with partly overlapped symptoms but different treatments. However, their misdiagnosis and mistreatment are common based on the DSM-V criteria, lacking objective and quantitative indicators. This study aimed to develop a novel approach that accurately classifies MDD and BD based on their resting-state magnetoencephalography (MEG) signals during euthymic phases. A revisited 3D CNN model, Semi-CNN, that could automatically detect brainwave patterns in spatial, temporal, and frequency domains was implemented to classify wavelet-transformed MEG signals of normal controls and MDD and BD patients. The model achieved a test accuracy of 96.05% and an average of 95.71% accuracy for 5-fold cross-validation. Furthermore, saliency maps of the model were estimated using Grad-CAM++ to visualize the proposed classification model and highlight disease-specific brain regions and frequencies. Clinical Relevance - Our model provides a stable pipeline that accurately classifies MDD, BD, and healthy individuals based on resting-state MEG signals during the euthymic phases, opening the potential for quantitative and accurate brain-based diagnosis for the highly misdiagnosed MDD/BD patients.
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35
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Guardiola-Ripoll M, Almodóvar-Payá C, Lubeiro A, Salvador R, Salgado-Pineda P, Gomar JJ, Guerrero-Pedraza A, Sarró S, Maristany T, Fernández-Linsenbarth I, Hernández-García M, Papiol S, Molina V, Pomarol-Clotet E, Fatjó-Vilas M. New insights of the role of the KCNH2 gene in schizophrenia: An fMRI case-control study. Eur Neuropsychopharmacol 2022; 60:38-47. [PMID: 35635995 DOI: 10.1016/j.euroneuro.2022.04.012] [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: 12/20/2021] [Revised: 04/14/2022] [Accepted: 04/19/2022] [Indexed: 11/04/2022]
Abstract
The KCNH2 gene, encoding for a subunit of a voltage-gated potassium channel, has been identified as a key element of neuronal excitability and a promising novel therapeutic target for schizophrenia (SZ). Nonetheless, evidence highlighting the role of KCNH2 on cognitive and brain activity phenotypes comes mainly from studies based on healthy controls (HC). Therefore, we aimed to study the role of KCNH2 on the brain functional differences between patients with SZ and HC. The fMRI sample comprised 78 HC and 79 patients with SZ (matched for age, sex and premorbid IQ). We studied the effect of the polymorphism KCNH2-rs3800779 on attention and working memory-related brain activity, evaluated through the N-back task, in regions with detected diagnostic differences (regression model, controlled for age, sex and premorbid IQ, FEAT-FSL). We report a significant diagnosis x KCNH2 interaction on brain activity (1-back vs baseline contrast) at the medial superior prefrontal cortex (Zmax=3.55, p = 0.00861). In this region, patients with SZ carrying the risk genotype (AA) show a deactivation failure, while HC depict the opposite pattern towards deactivation. The brain region with significant diagnosis x KCNH2 interaction has been previously associated with SZ. The results of this study, in which the role of KCNH2 on fMRI response is analysed for the first time in patients, suggest that KCNH2 variability contributes to inefficient brain activity modulation during the N-back task in affected subjects. These data may pave the way to further understand how KCNH2 genetic variability is related to the pathophysiological mechanisms underlying schizophrenia.
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Affiliation(s)
- Maria Guardiola-Ripoll
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain
| | - Carmen Almodóvar-Payá
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain
| | - Alba Lubeiro
- Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain
| | - Pilar Salgado-Pineda
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain
| | - Jesús J Gomar
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; The Litwin-Zucker Alzheimer's Research Center, NY, United States
| | - Amalia Guerrero-Pedraza
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Hospital Benito Menni-CASM, Sant Boi de Llobregat, Barcelona, Spain
| | - Salvador Sarró
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain
| | - Teresa Maristany
- Diagnostic Imaging Department, Hospital Sant Joan de Déu Research Foundation, Barcelona, Spain
| | | | - Marta Hernández-García
- Neurosciences Institute of Castilla y León (INCYL), University of Salamanca, Salamanca, Spain
| | - Sergi Papiol
- CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain; Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany; Department of Psychiatry, University Hospital, Ludwig Maximilian University, Munich Germany
| | - Vicente Molina
- Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain; Neurosciences Institute of Castilla y León (INCYL), University of Salamanca, Salamanca, Spain; Psychiatry Service, University Hospital of Valladolid, Valladolid, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain.
| | - Mar Fatjó-Vilas
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain; Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia, Universitat de Barcelona; Barcelona, Spain.
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36
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Lammertink F, van den Heuvel MP, Hermans EJ, Dudink J, Tataranno ML, Benders MJNL, Vinkers CH. Early-life stress exposure and large-scale covariance brain networks in extremely preterm-born infants. Transl Psychiatry 2022; 12:256. [PMID: 35717524 PMCID: PMC9206645 DOI: 10.1038/s41398-022-02019-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Revised: 05/25/2022] [Accepted: 06/07/2022] [Indexed: 12/03/2022] Open
Abstract
The stressful extrauterine environment following premature birth likely has far-reaching and persistent adverse consequences. The effects of early "third-trimester" ex utero stress on large-scale brain networks' covariance patterns may provide a potential avenue to understand how early-life stress following premature birth increases risk or resilience. We evaluated the impact of early-life stress exposure (e.g., quantification of invasive procedures) on maturational covariance networks (MCNs) between 30 and 40 weeks of gestational age in 180 extremely preterm-born infants (<28 weeks of gestation; 43.3% female). We constructed MCNs using covariance of gray matter volumes between key nodes of three large-scale brain networks: the default mode network (DMN), executive control network (ECN), and salience network (SN). Maturational coupling was quantified by summating the number of within- and between-network connections. Infants exposed to high stress showed significantly higher SN but lower DMN maturational coupling, accompanied by DMN-SN decoupling. Within the SN, the insula, amygdala, and subthalamic nucleus all showed higher maturational covariance at the nodal level. In contrast, within the DMN, the hippocampus, parahippocampal gyrus, and fusiform showed lower coupling following stress. The decoupling between DMN-SN was observed between the insula/anterior cingulate cortex and posterior parahippocampal gyrus. Early-life stress showed longitudinal network-specific maturational covariance patterns, leading to a reprioritization of developmental trajectories of the SN at the cost of the DMN. These alterations may enhance the ability to cope with adverse stimuli in the short term but simultaneously render preterm-born individuals at a higher risk for stress-related psychopathology later in life.
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Affiliation(s)
- Femke Lammertink
- Department of Neonatology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Martijn P van den Heuvel
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije University Amsterdam, Amsterdam, The Netherlands
- Department of Child Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, The Netherlands
| | - Erno J Hermans
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jeroen Dudink
- Department of Neonatology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Maria L Tataranno
- Department of Neonatology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Manon J N L Benders
- Department of Neonatology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
| | - Christiaan H Vinkers
- Department of Anatomy & Neurosciences, Amsterdam UMC (location Vrije University Amsterdam), Amsterdam, The Netherlands
- Department of Psychiatry, Amsterdam UMC (location Vrije University Amsterdam), Amsterdam, The Netherlands
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Falakshahi H, Rokham H, Fu Z, Iraji A, Mathalon DH, Ford JM, Mueller BA, Preda A, van Erp TGM, Turner JA, Plis S, Calhoun VD. Path Analysis: A Method to Estimate Altered Pathways in Time-varying Graphs of Neuroimaging Data. Netw Neurosci 2022; 6:634-664. [PMID: 36204419 PMCID: PMC9531579 DOI: 10.1162/netn_a_00247] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Accepted: 03/23/2022] [Indexed: 11/16/2022] Open
Abstract
Graph-theoretical methods have been widely used to study human brain networks in psychiatric disorders. However, the focus has primarily been on global graphic metrics with little attention to the information contained in paths connecting brain regions. Details of disruption of these paths may be highly informative for understanding disease mechanisms. To detect the absence or addition of multistep paths in the patient group, we provide an algorithm estimating edges that contribute to these paths with reference to the control group. We next examine where pairs of nodes were connected through paths in both groups by using a covariance decomposition method. We apply our method to study resting-state fMRI data in schizophrenia versus controls. Results show several disconnectors in schizophrenia within and between functional domains, particularly within the default mode and cognitive control networks. Additionally, we identify new edges generating additional paths. Moreover, although paths exist in both groups, these paths take unique trajectories and have a significant contribution to the decomposition. The proposed path analysis provides a way to characterize individuals by evaluating changes in paths, rather than just focusing on the pairwise relationships. Our results show promise for identifying path-based metrics in neuroimaging data.
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Affiliation(s)
- Haleh Falakshahi
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Hooman Rokham
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Zening Fu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
| | - Armin Iraji
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
| | - Daniel H. Mathalon
- Department of Psychiatry, University of California, San Francisco, CA, USA
- San Francisco VA Medical Center, San Francisco, CA, USA
| | - Judith M. Ford
- Department of Psychiatry, University of California, San Francisco, CA, USA
- San Francisco VA Medical Center, San Francisco, CA, USA
| | - Bryon A. Mueller
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - Theo G. M. van Erp
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine, CA, USA
| | - Jessica A. Turner
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
- Department of Psychology, Georgia State University, Atlanta, GA, USA
| | - Sergey Plis
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
- Department of Computer Science, Georgia State University, Atlanta, GA, USA
| | - Vince D. Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA
- Department of Computer Science, Georgia State University, Atlanta, GA, USA
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38
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Bi B, Che D, Bai Y. Neural network of bipolar disorder: Toward integration of neuroimaging and neurocircuit-based treatment strategies. Transl Psychiatry 2022; 12:143. [PMID: 35383150 PMCID: PMC8983759 DOI: 10.1038/s41398-022-01917-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 03/22/2022] [Accepted: 03/23/2022] [Indexed: 01/23/2023] Open
Abstract
Bipolar disorder (BD) is a complex psychiatric disorder characterized by dysfunctions in three domains including emotional processing, cognitive processing, and psychomotor dimensions. However, the neural underpinnings underlying these clinical profiles are not well understood. Based on the reported data, we hypothesized that (i) the core neuropathology in BD is damage in fronto-limbic network, which is associated with emotional dysfunction; (ii) changes in intrinsic brain network, such as sensorimotor network, salience network, default-mode network, central executive network are associated with impaired cognition function; and (iii) beyond the dopaminergic-driven basal ganglia-thalamo-cortical motor circuit modulated by other neurotransmitter systems, such as serotonin (subcortical-cortical modulation), the sensorimotor network and related motor function modulated by other non-motor networks such as the default-mode network are involved in psychomotor function. In this review, we propose a neurocircuit-based clinical characteristics and taxonomy to guide the treatment of BD. We draw on findings from neuropsychological and neuroimaging studies in BD and link variations in these clinical profiles to underlying neurocircuit dysfunctions. We consider pharmacological, psychotherapy, and neuromodulatory treatments that could target those specific neurocircuit dysfunctions in BD. Finally, it is suggested that the methods of testing the neurocircuit-based taxonomy and important limitations to this approach should be considered in future.
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Affiliation(s)
- Bo Bi
- Department of Clinical Psychology, The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen, China.
| | - Dongfang Che
- grid.452787.b0000 0004 1806 5224Neurosurgery department, Shenzhen Children’s Hospital, Shenzhen, China
| | - Yuyin Bai
- grid.12981.330000 0001 2360 039XDepartment of Clinical Psychology, The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen, China
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Eken A, Akaslan DS, Baskak B, Münir K. Diagnostic Classification of Schizophrenia and Bipolar Disorder by Using Dynamic Functional Connectivity: an fNIRS Study. J Neurosci Methods 2022; 376:109596. [DOI: 10.1016/j.jneumeth.2022.109596] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 02/26/2022] [Accepted: 04/08/2022] [Indexed: 11/27/2022]
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Claeys EHI, Mantingh T, Morrens M, Yalin N, Stokes PRA. Resting-state fMRI in depressive and (hypo)manic mood states in bipolar disorders: A systematic review. Prog Neuropsychopharmacol Biol Psychiatry 2022; 113:110465. [PMID: 34736998 DOI: 10.1016/j.pnpbp.2021.110465] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 10/01/2021] [Accepted: 10/27/2021] [Indexed: 12/12/2022]
Abstract
OBJECTIVE Abnormalities in spontaneous brain activity, measured with resting-state functional magnetic resonance imaging (rs-fMRI), may be key biomarkers for bipolar disorders. This systematic review compares rs-fMRI findings in people experiencing a bipolar depressive or (hypo)manic episode to bipolar euthymia and/or healthy participants. METHODS Medline, Web of Science and Embase were searched up until April 2021. Studies without control group, or including minors, neurological co-morbidities or mixed episodes, were excluded. Qualitative synthesis was used to report results and risk of bias was assessed using the National Heart, Lung and Blood Institute tool for case-control studies. RESULTS Seventy-one studies were included (3167 bipolar depressed/706 (hypo)manic). In bipolar depression, studies demonstrated default-mode (DMN) and frontoparietal network (FPN) dysfunction, altered baseline activity in the precuneus, insula, striatum, cingulate, frontal and temporal cortex, and disturbed regional homogeneity in parietal, temporal and pericentral areas. Functional connectivity was altered in thalamocortical circuits and between the cingulate cortex and precuneus. In (hypo)mania, studies reported altered functional connectivity in the amygdala, frontal and cingulate cortex. Finally, rs-fMRI disturbances in the insula and putamen correlate with depressive symptoms, cerebellar resting-state alterations could evolve with disease progression and altered amygdala connectivity might mediate lithium effects. CONCLUSIONS Our results suggest DMN and FPN dysfunction in bipolar depression, whereas local rs-fMRI alterations might differentiate mood states. Future studies should consider controlling rs-fMRI findings for potential clinical confounding factors such as medication. Considerable heterogeneity of methodology between studies limits conclusions. Standardised clinical reporting and consistent analysis approaches would increase coherence in this promising field.
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Affiliation(s)
- Eva H I Claeys
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; Department of Psychiatry, Collaborative Antwerp Psychiatric Research Institute (CAPRI), Faculty of Medicine and Health Sciences, University of Antwerp, Campus Drie Eiken, S.033, Universiteitsplein 1, 2610 Antwerpen, Belgium; Department of Psychiatry, University Psychiatric Centre Duffel, Stationsstraat 22, 2570 Duffel, Belgium
| | - Tim Mantingh
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Manuel Morrens
- Department of Psychiatry, Collaborative Antwerp Psychiatric Research Institute (CAPRI), Faculty of Medicine and Health Sciences, University of Antwerp, Campus Drie Eiken, S.033, Universiteitsplein 1, 2610 Antwerpen, Belgium; Department of Psychiatry, University Psychiatric Centre Duffel, Stationsstraat 22, 2570 Duffel, Belgium
| | - Nefize Yalin
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
| | - Paul R A Stokes
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
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Tracing the psychopathology of bipolar disorder to the functional architecture of intrinsic brain activity and its neurotransmitter modulation: a three-dimensional model. Mol Psychiatry 2022; 27:793-802. [PMID: 33414499 DOI: 10.1038/s41380-020-00982-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 11/22/2020] [Accepted: 12/01/2020] [Indexed: 12/17/2022]
Abstract
Bipolar disorder (BD) shows complex alterations in psychomotor, affective, and thought dimensions, as described by Kraepelin in his fundamental model of manic-depressive illness. In turn, the expression of behavioral/phenomenological dimensions is traceable to intrinsic brain activity. We reported a data overview on intrinsic brain functioning and its changes in BD. Accordingly, we proposed a three-dimensional model of the relationship between brain functioning and behavioral/phenomenological patterns, along with its application to BD. In this model, intrinsic brain activity is organized in distinct units in accordance to connectivity patterns and related setting of input/output processing, underlying the different behavioral/phenomenological dimensions. An external unit (mainly involving the sensorimotor network) is connected with the external environment and sets the exteroceptive input/somatomotor output processing, underlying the psychomotor dimension. An internal unit (mainly involving the salience network) is connected to the internal/body environment and sets the interoceptive input/visceromotor output processing, underlying the affective dimension. Finally, an associative unit (mainly involving the default-mode network) is not connected with the environment and sets the processing of associative inputs/outputs, underlying the thought dimension. In each unit, neurotransmitter signaling couples the subcortical-cortical loop, which modulates the network activity levels, in turn setting input/output processing and related expression levels of the behavioral/phenomenological dimension. Different combinations in neurotransmitter signaling favor network balancing into distinct functional brain states, which manifest in different combinations of excitation or inhibition in psychomotricity, affectivity, and thought, resulting in the manic, depressive, and mixed states of BD. Our working model might provide a coherent framework for tracing the complex BD psychopathology to core functional brain alterations.
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Huang LJ, Hu FC, Wu C, Yang YH, Lee SC, Huang HC, Yu CY, Lai KY. Are the measurement structures of the Traditional Chinese Dispositional Flow Scale-2 equivalent between schizophrenic patients and healthy subjects? J Formos Med Assoc 2022; 121:1981-1992. [DOI: 10.1016/j.jfma.2022.02.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 11/29/2021] [Accepted: 02/07/2022] [Indexed: 10/19/2022] Open
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Hoptman MJ, Tural U, Lim KO, Javitt DC, Oberlin LE. Relationships between Diffusion Tensor Imaging and Resting State Functional Connectivity in Patients with Schizophrenia and Healthy Controls: A Preliminary Study. Brain Sci 2022; 12:brainsci12020156. [PMID: 35203920 PMCID: PMC8870342 DOI: 10.3390/brainsci12020156] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 01/02/2022] [Accepted: 01/19/2022] [Indexed: 11/16/2022] Open
Abstract
Schizophrenia is widely seen as a disorder of dysconnectivity. Neuroimaging studies have examined both structural and functional connectivity in the disorder, but these modalities have rarely been integrated directly. We scanned 29 patients with schizophrenia and 25 healthy control subjects, and we acquired resting state fMRI and diffusion tensor imaging. We used the Functional and Tractographic Connectivity Analysis Toolbox (FATCAT) to estimate functional and structural connectivity of the default mode network. Correlations between modalities were investigated, and multimodal connectivity scores (MCS) were created using principal component analysis. Of the 28 possible region pairs, 9 showed consistent (>80%) tracts across participants. Correlations between modalities were found among those with schizophrenia for the prefrontal cortex, posterior cingulate, and lateral temporal lobes, with frontal and parietal regions, consistent with frontotemporoparietal network involvement in the disorder. In patients, MCS correlated with several aspects of the Positive and Negative Syndrome Scale, with higher multimodal connectivity associated with outward-directed (externalizing) behavior and lower multimodal connectivity related to psychosis per se. In this preliminary sample, we found FATCAT to be a useful toolbox to directly integrate and examine connectivity between imaging modalities. A consideration of conjoint structural and functional connectivity can provide important information about the network mechanisms of schizophrenia.
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Affiliation(s)
- Matthew J. Hoptman
- Clinical Research Division, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA;
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY 10016, USA
- Correspondence: or ; Tel.: +1-845-398-6569
| | - Umit Tural
- Clinical Research Division, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA;
| | - Kelvin O. Lim
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN 55454, USA;
| | - Daniel C. Javitt
- Schizophrenia Research Division, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA; or
- Division of Experimental Therapeutics, College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
| | - Lauren E. Oberlin
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10065, USA;
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44
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Digiovanni A, Ajdinaj P, Russo M, Sensi SL, Onofrj M, Thomas A. Bipolar spectrum disorders in neurologic disorders. Front Psychiatry 2022; 13:1046471. [PMID: 36620667 PMCID: PMC9811836 DOI: 10.3389/fpsyt.2022.1046471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 12/05/2022] [Indexed: 12/24/2022] Open
Abstract
Psychiatric symptoms frequently predate or complicate neurological disorders, such as neurodegenerative diseases. Symptoms of bipolar spectrum disorders (BSD), like mood, behavioral, and psychotic alterations, are known to occur - individually or as a syndromic cluster - in Parkinson's disease and in the behavioral variant of frontotemporal dementia (FTD). Nonetheless, due to shared pathophysiological mechanisms, or genetic predisposition, several other neurological disorders show significant, yet neglected, clinical and biological overlaps with BSD like neuroinflammation, ion channel dysfunctions, neurotransmission imbalance, or neurodegeneration. BSD pathophysiology is still largely unclear, but large-scale network dysfunctions are known to participate in the onset of mood disorders and psychotic symptoms. Thus, functional alterations can unleash BSD symptoms years before the evidence of an organic disease of the central nervous system. The aim of our narrative review was to illustrate the numerous intersections between BSD and neurological disorders from a clinical-biological point of view and the underlying predisposing factors, to guide future diagnostic and therapeutical research in the field.
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Affiliation(s)
- Anna Digiovanni
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Paola Ajdinaj
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Mirella Russo
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Stefano L Sensi
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Marco Onofrj
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Astrid Thomas
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy
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45
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A unified model of the pathophysiology of bipolar disorder. Mol Psychiatry 2022; 27:202-211. [PMID: 33859358 DOI: 10.1038/s41380-021-01091-4] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 03/17/2021] [Accepted: 03/29/2021] [Indexed: 02/02/2023]
Abstract
This work provides an overview of the most consistent alterations in bipolar disorder (BD), attempting to unify them in an internally coherent working model of the pathophysiology of BD. Data on immune-inflammatory changes, structural brain abnormalities (in gray and white matter), and functional brain alterations (from neurotransmitter signaling to intrinsic brain activity) in BD were reviewed. Based on the reported data, (1) we hypothesized that the core pathological alteration in BD is a damage of the limbic network that results in alterations of neurotransmitter signaling. Although heterogeneous conditions can lead to such damage, we supposed that the main pathophysiological mechanism is traceable to an immune/inflammatory-mediated alteration of white matter involving the limbic network connections, which destabilizes the neurotransmitter signaling, such as dopamine and serotonin signaling. Then, (2) we suggested that changes in such neurotransmitter signaling (potentially triggered by heterogeneous stressors onto a structurally-damaged limbic network) lead to phasic (and often recurrent) reconfigurations of intrinsic brain activity, from abnormal subcortical-cortical coupling to changes in network activity. We suggested that the resulting dysbalance between networks, such as sensorimotor networks, salience network, and default-mode network, clinically manifest in combined alterations of psychomotricity, affectivity, and thought during the manic and depressive phases of BD. Finally, (3) we supposed that an additional contribution of gray matter alterations and related cognitive deterioration characterize a clinical-biological subgroup of BD. This model may provide a general framework for integrating the current data on BD and suggests novel specific hypotheses, prompting for a better understanding of the pathophysiology of BD.
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46
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Sun Q, Zhao L, Tan L. Abnormalities of Electroencephalography Microstates in Drug-Naïve, First-Episode Schizophrenia. Front Psychiatry 2022; 13:853602. [PMID: 35360139 PMCID: PMC8964053 DOI: 10.3389/fpsyt.2022.853602] [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: 01/12/2022] [Accepted: 02/22/2022] [Indexed: 01/12/2023] Open
Abstract
OBJECTIVE Microstate analysis is a powerful tool to probe the brain functions, and changes in microstates under electroencephalography (EEG) have been repeatedly reported in patients with schizophrenia. This study aimed to investigate the dynamics of EEG microstates in drug-naïve, first-episode schizophrenia (FE-SCH) and to test the relationship between EEG microstates and clinical symptoms. METHODS Resting-state EEG were recorded for 23 patients with FE-SCH and 23 healthy controls using a 64-channel cap. Three parameters, i.e., contribution, duration, and occurrence, of the four microstate classes were calculated. Group differences in EEG microstates and their clinical symptoms [assessed using the Positive and Negative Syndrome Scale (PANSS)] were analyzed. RESULTS Compared with healthy controls, patients with FE-SCH showed increased duration, occurrence and contribution of microstate class C and decreased contribution and occurrence of microstate class D. In addition, the score of positive symptoms in PANSS was negatively correlated with the occurrence of microstate D. CONCLUSION Our findings showed abnormal patterns of EEG microstates in drug-naïve, first-episode schizophrenia, which might help distinguish individuals with schizophrenia in the early stage and develop early intervention strategies.
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Affiliation(s)
- Qiaoling Sun
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, China National Technology Institute on Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Linlin Zhao
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, China National Technology Institute on Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Liwen Tan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, China National Technology Institute on Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
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47
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Zamani A, Carhart-Harris R, Christoff K. Prefrontal contributions to the stability and variability of thought and conscious experience. Neuropsychopharmacology 2022; 47:329-348. [PMID: 34545195 PMCID: PMC8616944 DOI: 10.1038/s41386-021-01147-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 08/02/2021] [Accepted: 08/03/2021] [Indexed: 02/08/2023]
Abstract
The human prefrontal cortex is a structurally and functionally heterogenous brain region, including multiple subregions that have been linked to different large-scale brain networks. It contributes to a broad range of mental phenomena, from goal-directed thought and executive functions to mind-wandering and psychedelic experience. Here we review what is known about the functions of different prefrontal subregions and their affiliations with large-scale brain networks to examine how they may differentially contribute to the diversity of mental phenomena associated with prefrontal function. An important dimension that distinguishes across different kinds of conscious experience is the stability or variability of mental states across time. This dimension is a central feature of two recently introduced theoretical frameworks-the dynamic framework of thought (DFT) and the relaxed beliefs under psychedelics (REBUS) model-that treat neurocognitive dynamics as central to understanding and distinguishing between different mental phenomena. Here, we bring these two frameworks together to provide a synthesis of how prefrontal subregions may differentially contribute to the stability and variability of thought and conscious experience. We close by considering future directions for this work.
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Affiliation(s)
- Andre Zamani
- Department of Psychology, University of British Columbia, 2136 West Mall, Vancouver, BC, Canada.
| | - Robin Carhart-Harris
- Centre for Psychedelic Research, Department of Brain Sciences, Imperial College London, London, UK
| | - Kalina Christoff
- Department of Psychology, University of British Columbia, 2136 West Mall, Vancouver, BC, Canada
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48
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OUP accepted manuscript. Cereb Cortex 2022; 32:4576-4591. [DOI: 10.1093/cercor/bhab503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 12/06/2021] [Accepted: 12/07/2021] [Indexed: 11/13/2022] Open
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49
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Reardon AM, Li K, Hu XP. Improving Between-Group Effect Size for Multi-Site Functional Connectivity Data via Site-Wise De-Meaning. Front Comput Neurosci 2021; 15:762781. [PMID: 34924984 PMCID: PMC8674307 DOI: 10.3389/fncom.2021.762781] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Accepted: 11/04/2021] [Indexed: 11/18/2022] Open
Abstract
Background: Multi-site functional MRI (fMRI) databases are becoming increasingly prevalent in the study of neurodevelopmental and psychiatric disorders. However, multi-site databases are known to introduce site effects that may confound neurobiological and measures such as functional connectivity (FC). Although studies have been conducted to mitigate site effects, these methods often result in reduced effect size in FC comparisons between controls and patients. Methods: We present a site-wise de-meaning (SWD) strategy in multi-site FC analysis and compare its performance with two common site-effect mitigation methods, i.e., generalized linear model (GLM) and Combining Batches (ComBat) Harmonization. For SWD, after FC was calculated and Fisher z-transformed, the site-wise FC mean was removed from each subject before group-level statistical analysis. The above methods were tested on two multi-site psychiatric consortiums [Autism Brain Imaging Data Exchange (ABIDE) and Bipolar and Schizophrenia Network on Intermediate Phenotypes (B-SNIP)]. Preservation of consistent FC alterations in patients were evaluated for each method through the effect sizes (Hedge’s g) of patients vs. controls. Results: For the B-SNIP dataset, SWD improved the effect size between schizophrenic and control subjects by 4.5–7.9%, while GLM and ComBat decreased the effect size by 22.5–42.6%. For the ABIDE dataset, SWD improved the effect size between autistic and control subjects by 2.9–5.3%, while GLM and ComBat decreased the effect size by up to 11.4%. Conclusion: Compared to the original data and commonly used methods, the SWD method demonstrated superior performance in preserving the effect size in FC features associated with disorders.
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Affiliation(s)
- Alexandra M Reardon
- Department of Bioengineering, University of California, Riverside, Riverside, CA, United States
| | - Kaiming Li
- Department of Bioengineering, University of California, Riverside, Riverside, CA, United States
| | - Xiaoping P Hu
- Department of Bioengineering, University of California, Riverside, Riverside, CA, United States.,Center for Advanced Neuroimaging, University of California, Riverside, Riverside, CA, United States
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50
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Zhang Z, Bo Q, Li F, Zhao L, Wang Y, Liu R, Chen X, Wang C, Zhou Y. Increased ALFF and functional connectivity of the right striatum in bipolar disorder patients. Prog Neuropsychopharmacol Biol Psychiatry 2021; 111:110140. [PMID: 33068681 DOI: 10.1016/j.pnpbp.2020.110140] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 09/19/2020] [Accepted: 10/10/2020] [Indexed: 02/07/2023]
Abstract
BACKGROUND Bipolar disorder (BD) is a serious neuropsychiatric disorder characterized by alternating periods of mania, depression, and euthymia. Abnormal spontaneous brain activity within the cortical-striatal neural circuits has been observed in patients with BD. However, whether the abnormality appears in patients with BD while not in a manic mood state is unclear. METHODS This study collected resting-state fMRI data from 65 patients with BD who were not in a manic mood state and 85 matched healthy controls. First, we examined differences in amplitude of low-frequency fluctuations (ALFF) between the patients with BD and the healthy controls to identify regions that show abnormal local spontaneous activity in the patients. Based on the ALFF results, we conducted seed-based resting-state functional connectivity (rsFC) analysis to identify the changes in brain networks that are centered on the regions showing abnormal local spontaneous activity in the patients. Finally, we repeated these analyses in a sub-sample comprising euthymic BD patients (N = 37) and between the euthymic BD patients and all the other patients who had at least mild depressive symptoms. RESULTS BD patients exhibited increased ALFF in the right caudate/putamen and increased rsFC in the right caudate/putamen with the right inferior parietal lobe (cluster-level FWE p < 0.05). Further analyses showed that the euthymic BD patients showed similar abnormalities in ALFF and rsFC maps as found in all patients with BD. And the euthymic BD patients were comparable with all the other patients who had at least mild depressive symptoms in ALFF values. CONCLUSIONS Our results indicated the important role of the right striatum in the baseline brain function of BD patients and suggested that the abnormality of spontaneous brain activity in the cortical-striatal neural circuits may be a trait-like variant in patients with BD. The results deepen our understanding of the neurobiological mechanisms associated with BD etiology.
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Affiliation(s)
- Zhifang Zhang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Qijing Bo
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Feng Li
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Lei Zhao
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Yun Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Rui Liu
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Xiongying Chen
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Chuanyue Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Yuan Zhou
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China; CAS Key Laboratory of Behavioral Science, Institute of Psychology & Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101,China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China.
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