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Ravan M, Noroozi A, Sanchez MM, Borden L, Alam N, Flor-Henry P, Colic S, Khodayari-Rostamabad A, Minuzzi L, Hasey G. Diagnostic deep learning algorithms that use resting EEG to distinguish major depressive disorder, bipolar disorder, and schizophrenia from each other and from healthy volunteers. J Affect Disord 2024; 346:285-298. [PMID: 37963517 DOI: 10.1016/j.jad.2023.11.017] [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: 05/02/2023] [Revised: 11/02/2023] [Accepted: 11/07/2023] [Indexed: 11/16/2023]
Abstract
BACKGROUND Mood disorders and schizophrenia affect millions worldwide. Currently, diagnosis is primarily determined by reported symptomatology. As symptoms may overlap, misdiagnosis is common, potentially leading to ineffective or destabilizing treatment. Diagnostic biomarkers could significantly improve clinical care by reducing dependence on symptomatic presentation. METHODS We used deep learning analysis (DLA) of resting electroencephalograph (EEG) to differentiate healthy control (HC) subjects (N = 239), from those with major depressive disorder (MDD) (N = 105), MDD-atypical (MDD-A) (N = 27), MDD-psychotic (MDD-P) (N = 35), bipolar disorder-depressed episode (BD-DE) (N = 71), BD-manic episode (BD-ME) (N = 49), and schizophrenia (SCZ) (N = 122) and also differentiate subjects with mental disorders on a pair-wise basis. DSM-III-R diagnoses were determined and supplemented by computerized Quick Diagnostic Interview Schedule. After EEG preprocessing, robust exact low-resolution electromagnetic tomography (ReLORETA) computed EEG sources for 82 brain regions. 20 % of all subjects were then set aside for independent testing. Feature selection methods were then used for the remaining subjects to identify brain source regions that are discriminating between diagnostic categories. RESULTS Pair-wise classification accuracies between 90 % and 100 % were obtained using independent test subjects whose data were not used for training purposes. The most frequently selected features across various pairs are in the postcentral, supramarginal, and fusiform gyri, the hypothalamus, and the left cuneus. Brain sites discriminating SCZ from HC were mainly in the left hemisphere while those separating BD-ME from HC were on the right. LIMITATIONS The use of superseded DSM-III-R diagnostic system and relatively small sample size in some disorder categories that may increase the risk of overestimation. CONCLUSIONS DLA of EEG could be trained to autonomously classify psychiatric disorders with over 90 % accuracy compared to an expert clinical team using standardized operational methods.
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Affiliation(s)
- Maryam Ravan
- Department of Electrical and Computer Engineering, New York Institute of Technology, New York, NY, USA.
| | - Amin Noroozi
- Department of Digital, Technologies, and Arts, Staffordshire University, Staffordshire, England, UK
| | - Mary Margarette Sanchez
- Department of Electrical and Computer Engineering, New York Institute of Technology, New York, NY, USA
| | - Lee Borden
- Department of Electrical and Computer Engineering, New York Institute of Technology, New York, NY, USA
| | - Nafia Alam
- Department of Electrical and Computer Engineering, New York Institute of Technology, New York, NY, USA
| | | | - Sinisa Colic
- Department of Electrical Engineering, University of Toronto, Canada
| | | | - Luciano Minuzzi
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Gary Hasey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
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Ford A, Ammar Z, Li L, Shultz S. Lateralization of major white matter tracts during infancy is time-varying and tract-specific. Cereb Cortex 2023; 33:10221-10233. [PMID: 37595203 PMCID: PMC10545441 DOI: 10.1093/cercor/bhad277] [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: 03/24/2023] [Revised: 07/08/2023] [Accepted: 07/10/2023] [Indexed: 08/20/2023] Open
Abstract
Lateralization patterns are a major structural feature of brain white matter and have been investigated as a neural architecture that indicates and supports the specialization of cognitive processing and observed behaviors, e.g. language skills. Many neurodevelopmental disorders have been associated with atypical lateralization, reinforcing the need for careful measurement and study of this structural characteristic. Unfortunately, there is little consensus on the direction and magnitude of lateralization in major white matter tracts during the first months and years of life-the period of most rapid postnatal brain growth and cognitive maturation. In addition, no studies have examined white matter lateralization in a longitudinal pediatric sample-preventing confirmation of if and how white matter lateralization changes over time. Using a densely sampled longitudinal data set from neurotypical infants aged 0-6 months, we aim to (i) chart trajectories of white matter lateralization in 9 major tracts and (ii) link variable findings from cross-sectional studies of white matter lateralization in early infancy. We show that patterns of lateralization are time-varying and tract-specific and that differences in lateralization results during this period may reflect the dynamic nature of lateralization through development, which can be missed in cross-sectional studies.
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Affiliation(s)
- Aiden Ford
- Neuroscience Program, Emory University, Atlanta, GA 30322, United States
- Marcus Autism Center, Children’s Healthcare of Atlanta, Atlanta, GA 30329, United States
| | - Zeena Ammar
- Neuroscience Program, Emory University, Atlanta, GA 30322, United States
- Marcus Autism Center, Children’s Healthcare of Atlanta, Atlanta, GA 30329, United States
| | - Longchuan Li
- Marcus Autism Center, Children’s Healthcare of Atlanta, Atlanta, GA 30329, United States
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA 30322, United States
| | - Sarah Shultz
- Neuroscience Program, Emory University, Atlanta, GA 30322, United States
- Marcus Autism Center, Children’s Healthcare of Atlanta, Atlanta, GA 30329, United States
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA 30322, United States
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Abraham M, Peterburs J, Mundorf A. Oligodendrocytes matter: a review of animal studies on early adversity. J Neural Transm (Vienna) 2023; 130:1177-1185. [PMID: 37138023 PMCID: PMC10460720 DOI: 10.1007/s00702-023-02643-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 04/26/2023] [Indexed: 05/05/2023]
Abstract
Exposure to adversities in early life appears to affect the development of white matter, especially oligodendrocytes. Furthermore, altered myelination is present in regions subjected to maturation during the developmental time when early adversities are experienced. In this review, studies applying two well-established animal models of early life adversity, namely maternal separation and maternal immune activation, focusing on oligodendrocyte alterations and resulting implications for psychiatric disorders are discussed. Studies revealed that myelination is reduced as a result of altered oligodendrocyte expression. Furthermore, early adversity is associated with increased cell death, a simpler morphology, and inhibited oligodendrocyte maturation. However, these effects seem to be region- specific as some brain regions show increased expression while others show decreased expression of oligodendroglia-related genes, and they occur especially in regions of ongoing development. Some studies furthermore suggest that early adversity leads to premature differentiation of oligodendrocytes. Importantly, especially early exposure results in stronger oligodendrocyte-related impairments. However, resulting alterations are not restricted to exposure during the early pre- and postnatal days as social isolation after weaning leads to fewer internodes and branches and shorter processes of oligodendrocytes in adulthood. Eventually, the found alterations may lead to dysfunction and long-lasting alterations in structural brain development associated with psychiatric disorders. To date, only few preclinical studies have focused on the effects of early adversity on oligodendrocytes. More studies including several developmental stages are needed to further disentangle the role of oligodendrocytes in the development of psychiatric disorders.
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Affiliation(s)
- Mate Abraham
- Division of Experimental and Molecular Psychiatry, Department of Psychiatry, Psychotherapy and Preventive Medicine, LWL University Hospital, Ruhr-University Bochum, Bochum, Germany
| | - Jutta Peterburs
- Institute for Systems Medicine and Department of Human Medicine, MSH Medical School Hamburg, Hamburg, Germany
| | - Annakarina Mundorf
- Institute for Systems Medicine and Department of Human Medicine, MSH Medical School Hamburg, Hamburg, Germany.
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4
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He X, Zhao X, Sun Y, Geng P, Zhang X. Application of TBSS-based machine learning models in the diagnosis of pediatric autism. Front Neurol 2023; 13:1078147. [PMID: 36742048 PMCID: PMC9889873 DOI: 10.3389/fneur.2022.1078147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 12/30/2022] [Indexed: 01/19/2023] Open
Abstract
Objective To explore the microstructural changes of white matter in children with pediatric autism by using diffusion kurtosis imaging (DKI), and evaluate whether the combination of tract-based spatial statistics (TBSS) and back-propagation neural network (BPNN)/support vector machine (SVM)/logistic regression (LR) was feasible for the classification of pediatric autism. Methods DKI data were retrospectively collected from 32 children with autism and 27 healthy controls (HCs). Kurtosis fractional anisotropy (FAK), mean kurtosis (MK), axial kurtosis (KA), radial kurtosis (RK), fractional anisotropy (FA), axial diffusivity (DA), mean diffusivity (MD) and Radial diffusivity (DR) were generated by iQuant workstation. TBSS was used to detect the regions of parameters values abnormalities and for the comparison between these two groups. In addition, we also introduced the lateralization indices (LI) to study brain lateralization in children with pediatric autism, using TBSS for additional analysis. The parameters values of the differentiated regions from TBSS were then calculated for each participant and used as the features in SVM/BPNN/LR. All models were trained and tested with leave-one-out cross validation (LOOCV). Results Compared to the HCs group, the FAK, DA, and KA values of multi-fibers [such as the bilateral superior longitudinal fasciculus (SLF), corticospinal tract (CST) and anterior thalamic radiation (ATR)] were lower in pediatric autism group (p < 0.05, TFCE corrected). And we also found DA lateralization abnormality in Superior longitudinal fasciculus (SLF) (the LI in HCs group was higher than that in pediatric autism group). However, there were no significant differences in FA, MD, MK, DR, and KR values between HCs and pediatric autism group (P > 0.05, TFCE corrected). After performing LOOCV to train and test three model (SVM/BPNN/LR), we found the accuracy of BPNN (accuracy = 86.44%) was higher than that of LR (accuracy = 76.27%), but no different from SVM (RBF, accuracy = 81.36%; linear, accuracy = 84.75%). Conclusion Our proposed method combining TBSS findings with machine learning (LR/SVM/BPNN), was applicable in the classification of pediatric autism with high accuracy. Furthermore, the FAK, DA, and KA values and Lateralization index (LI) value could be used as neuroimaging biomarkers to discriminate the children with pediatric autism or not.
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Affiliation(s)
- Xiongpeng He
- Department of Imaging, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China,Henan International Joint Laboratory of Neuroimaging, Zhengzhou, China
| | - Xin Zhao
- Department of Imaging, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China,Henan International Joint Laboratory of Neuroimaging, Zhengzhou, China
| | - Yongbing Sun
- Department of Imaging, People's Hospital of Zhengzhou University, Zhengzhou, China
| | - Pengfei Geng
- Department of Imaging, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China,Henan International Joint Laboratory of Neuroimaging, Zhengzhou, China
| | - Xiaoan Zhang
- Department of Imaging, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China,Henan International Joint Laboratory of Neuroimaging, Zhengzhou, China,*Correspondence: Xiaoan Zhang ✉
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5
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Mallet J, Godin O, Le Strat Y, Mazer N, Berna F, Boyer L, Capdevielle D, Clauss J, Chéreau I, D'Amato T, Dubreucq J, Leigner S, Llorca PM, Misdrahi D, Passerieux C, Rey R, Pignon B, Urbach M, Schürhoff F, Fond G, Dubertret C. Handedness as a neurodevelopmental marker in schizophrenia: Results from the FACE-SZ cohort. World J Biol Psychiatry 2022; 23:525-536. [PMID: 34918618 DOI: 10.1080/15622975.2021.2013094] [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] [Indexed: 01/25/2023]
Abstract
OBJECTIVES High rates of non-right-handedness (NRH) including mixed-handedness have been reported in neurodevelopmental disorders. In schizophrenia (SZ), atypical handedness has been inconsistently related to impaired features. We aimed to determine whether SZ subjects with NRH and mixed-handedness had poorer clinical and cognitive outcomes compared to their counterparts. METHODS 667 participants were tested with a battery of neuropsychological tests, and assessed for laterality using the Edinburg Handedness Inventory. Clinical symptomatology was assessed. Learning disorders and obstetrical complications were recorded. Biological parameters were explored. RESULTS The prevalence of NRH and mixed-handedness was high (respectively, 42.4% and 34.1%). In the multivariable analyses, NRH was associated with cannabis use disorder (p = 0.045). Mixed-handedness was associated with positive symptoms (p = 0.041), current depressive disorder (p = 0.005)), current cannabis use (p = 0.024) and less akathisia (p = 0.019). A history of learning disorder was associated with NRH. No association was found with cognition, trauma history, obstetrical complications, psychotic symptoms, peripheral inflammation. CONCLUSIONS Non-right and mixed-handedness are very high in patients with SZ, possibly reflecting a neurodevelopmental origin. NRH is associated with learning disorders and cannabis use. Mixed-handedness is associated with positive symptoms, current depressive disorder, cannabis use and less akathisia. However, this study did not confirm greater cognitive impairment in these patients.
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Affiliation(s)
- Jasmina Mallet
- Institute of Psychiatry and Neuroscience of Paris, Université de Paris INSERM UMR1266, Paris, France.,AP-HP, Groupe Hospitalo-Universitaire AP-HP Nord, Service de Psychiatrie et Addictologie, Hôpital Louis Mourier, Colombes, France.,Fondation Fondamental F94010, Créteil, France
| | - Ophélia Godin
- Fondation Fondamental F94010, Créteil, France.,UPEC, Créteil, France Inserm, U955, Equipe 15 Psychiatrie Génétique, Créteil, France AP-HP, Hôpital H. Mondor-A. Chenevier, Pôle de Psychiatrie, Créteil, France Fondation FondaMental, Fondation de Cooperation Scientifique, Université Paris-Est, UMR_S955, Créteil, France
| | - Yann Le Strat
- Institute of Psychiatry and Neuroscience of Paris, Université de Paris INSERM UMR1266, Paris, France.,AP-HP, Groupe Hospitalo-Universitaire AP-HP Nord, Service de Psychiatrie et Addictologie, Hôpital Louis Mourier, Colombes, France.,Fondation Fondamental F94010, Créteil, France
| | - Nicolas Mazer
- Institute of Psychiatry and Neuroscience of Paris, Université de Paris INSERM UMR1266, Paris, France.,AP-HP, Groupe Hospitalo-Universitaire AP-HP Nord, Service de Psychiatrie et Addictologie, Hôpital Louis Mourier, Colombes, France.,Fondation Fondamental F94010, Créteil, France
| | - Fabrice Berna
- Fondation Fondamental F94010, Créteil, France.,Fédération de Médecine Translationnelle de Strasbourg, Hôpitaux Universitaires de Strasbourg, Université de Strasbourg, INSERM U1114, Strasbourg, France
| | - Laurent Boyer
- School of medicine - La Timone Medical Campus, EA 3279: CEReSS - Health Service Research and Quality of Life Center, AP-HM, Aix-Marseille University, Marseille, France
| | - Delphine Capdevielle
- Fondation Fondamental F94010, Créteil, France.,Service Universitaire de Psychiatrie Adulte, Hôpital la Colombière, CHRU Montpellier, Université Montpellier 1, Montpellier, France
| | - Julie Clauss
- Fondation Fondamental F94010, Créteil, France.,Fédération de Médecine Translationnelle de Strasbourg, Hôpitaux Universitaires de Strasbourg, Université de Strasbourg, INSERM U1114, Strasbourg, France
| | - Isabelle Chéreau
- Fondation Fondamental F94010, Créteil, France.,CHU Clermont-Ferrand, Department of Psychiatry, University of Clermont Auvergne, Clermont-Ferrand, France
| | - Thierry D'Amato
- Fondation Fondamental F94010, Créteil, France.,INSERM U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Université Claude Bernard Lyon 1, Equipe PSYR2, Centre Hospitalier Le Vinatier, Lyon, France
| | - Julien Dubreucq
- Fondation Fondamental F94010, Créteil, France.,Centre Référent de Réhabilitation Psychosociale et de Remédiation Cognitive (C3R), CH Alpes Isère, Saint-Egrève, France
| | - Sylvain Leigner
- Fondation Fondamental F94010, Créteil, France.,Centre Référent de Réhabilitation Psychosociale et de Remédiation Cognitive (C3R), CH Alpes Isère, Saint-Egrève, France
| | - Pierre-Michel Llorca
- Fondation Fondamental F94010, Créteil, France.,CHU Clermont-Ferrand, Department of Psychiatry, University of Clermont Auvergne, Clermont-Ferrand, France
| | - David Misdrahi
- Fondation Fondamental F94010, Créteil, France.,Department of Adult Psychiatry, Charles Perrens Hospital, Bordeaux, France, University of Bordeaux, Laboratory of Nutrition and Integrative Neurobiology (UMR INRA 1286), France
| | - Christine Passerieux
- Fondation Fondamental F94010, Créteil, France.,Service Universitaire de Psychiatrie d'Adultes, Centre Hospitalier de Versailles, Le Chesnay, France
| | - Romain Rey
- Fondation Fondamental F94010, Créteil, France.,INSERM U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Université Claude Bernard Lyon 1, Equipe PSYR2, Centre Hospitalier Le Vinatier, Lyon, France
| | - Baptiste Pignon
- Fondation Fondamental F94010, Créteil, France.,UPEC, Créteil, France Inserm, U955, Equipe 15 Psychiatrie Génétique, Créteil, France AP-HP, Hôpital H. Mondor-A. Chenevier, Pôle de Psychiatrie, Créteil, France Fondation FondaMental, Fondation de Cooperation Scientifique, Université Paris-Est, UMR_S955, Créteil, France
| | - Mathieu Urbach
- Fondation Fondamental F94010, Créteil, France.,Service Universitaire de Psychiatrie d'Adultes, Centre Hospitalier de Versailles, Le Chesnay, France.,Laboratoire HandiRESP, EA4047, UFR des Sciences de la Santé Simone Veil, Université de Versailles Saint-Quentin-En-Yvelines, Montigny-le-Bretonneux, France
| | - Franck Schürhoff
- Fondation Fondamental F94010, Créteil, France.,UPEC, Créteil, France Inserm, U955, Equipe 15 Psychiatrie Génétique, Créteil, France AP-HP, Hôpital H. Mondor-A. Chenevier, Pôle de Psychiatrie, Créteil, France Fondation FondaMental, Fondation de Cooperation Scientifique, Université Paris-Est, UMR_S955, Créteil, France
| | - Guillaume Fond
- Fondation Fondamental F94010, Créteil, France.,School of medicine - La Timone Medical Campus, EA 3279: CEReSS - Health Service Research and Quality of Life Center, AP-HM, Aix-Marseille University, Marseille, France
| | - Caroline Dubertret
- Institute of Psychiatry and Neuroscience of Paris, Université de Paris INSERM UMR1266, Paris, France.,AP-HP, Groupe Hospitalo-Universitaire AP-HP Nord, Service de Psychiatrie et Addictologie, Hôpital Louis Mourier, Colombes, France.,Fondation Fondamental F94010, Créteil, France
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Mallet J, Godin O, Mazer N, Le Strat Y, Bellivier F, Belzeaux R, Etain B, Fond G, Gard S, Henry C, Leboyer M, Llorca PM, Loftus J, Olié E, Passerieux C, Polosan M, Schwan R, Roux P, Dubertret C. Handedness in bipolar disorders is associated with specific neurodevelopmental features: results of the BD-FACE cohort. Eur Arch Psychiatry Clin Neurosci 2022; 272:827-838. [PMID: 34374842 DOI: 10.1007/s00406-021-01314-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 07/26/2021] [Indexed: 11/26/2022]
Abstract
OBJECTIVES High rates of non-right-handedness (NRH) and mixed-handedness exist in neurodevelopmental disorders. Dysfunctional neurodevelopmental pathways may be implicated in the underlying pathophysiology of bipolar disorders (BD), at least in some subgroups. Yet little is known about correlates of NRH and mixed-handedness in BD. The objectives of this national study are to determine (i) the prevalence of NRH and mixed-handedness in a well-stabilized sample of BD individuals; (ii) if NRH/mixed-handedness in BD is associated with a different clinical, biological and neurocognitive profile. METHODS We included 2174 stabilized individuals. Participants were tested with a comprehensive battery of neuropsychological tests. Handedness was assessed using a single oral question. Learning and/or language disorders and obstetrical complications were recorded using childhood records. Common environmental, clinical and biological parameters were assessed. RESULTS The prevalence of NRH and mixed-handedness were, respectively, 11.6 and 2.4%. Learning/language disorders were found in 9.7% out of the total sample and were associated with atypical handedness (only dyslexia for mixed-handedness (p < 0.01), and dyslexia and dysphasia for NRH (p = 0.01 and p = 0.04, respectively). In multivariate analyses, NRH was associated with a younger age of BD onset (aOR 0.98 (95% CI 0.96-0.99) and lifetime substance use disorder (aOR 1.40 (95% CI 1.03-1.82) but not with any of the cognitive subtasks. Mixed-handedness was associated in univariate analyses with lifetime substance use disorder, lifetime cannabis use disorder (all p < 0.01) and less mood stabilizer prescription (p = 0.028). No association was found between NRH or mixed-handedness and the following parameters: trauma history, obstetrical complications, prior psychotic symptoms, bipolar subtype, attention deficit/hyperactivity disorder, peripheral inflammation or body mass index. CONCLUSIONS Handedness may be associated with specific features in BD, possibly reflecting a specific subgroup with a neurodevelopmental load.
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Affiliation(s)
- Jasmina Mallet
- Fondation Fondamental, Créteil, France.
- Faculté de médecine, AP-HP, Department of Psychiatry, Université de Paris, Louis Mourier Hospital, CHU Louis Mourier, 178 rue des Renouillers, 92700, Colombes, France.
- INSERM UMR1266, Institute of Psychiatry and Neuroscience of Paris, University Paris Descartes, Paris, France.
| | - Ophélia Godin
- Fondation Fondamental, Créteil, France
- UMR_S955, UPEC, Créteil, France Inserm, Université Paris-Est, U955, Equipe 15 Psychiatrie génétique, Créteil, France
- AP-HP, Hôpital H. Mondor-A. Chenevier, Pôle de psychiatrie, Créteil, France
| | - Nicolas Mazer
- Fondation Fondamental, Créteil, France
- Faculté de médecine, AP-HP, Department of Psychiatry, Université de Paris, Louis Mourier Hospital, CHU Louis Mourier, 178 rue des Renouillers, 92700, Colombes, France
- INSERM UMR1266, Institute of Psychiatry and Neuroscience of Paris, University Paris Descartes, Paris, France
| | - Yann Le Strat
- Fondation Fondamental, Créteil, France
- Faculté de médecine, AP-HP, Department of Psychiatry, Université de Paris, Louis Mourier Hospital, CHU Louis Mourier, 178 rue des Renouillers, 92700, Colombes, France
- INSERM UMR1266, Institute of Psychiatry and Neuroscience of Paris, University Paris Descartes, Paris, France
| | - Frank Bellivier
- Fondation Fondamental, Créteil, France
- AP-HP, GH Saint-Louis-Lariboisière-Fernand Widal, Pôle Neurosciences Tête et Cou, INSERM UMRS 1144, University Paris Diderot, Paris, France
| | - Raoul Belzeaux
- Fondation Fondamental, Créteil, France
- AP-HM, Department of Psychiatry, Marseille, France
- INT-UMR7289, CNRS Aix Marseille University, Marseille, France
| | - Bruno Etain
- Fondation Fondamental, Créteil, France
- AP-HP, GH Saint-Louis-Lariboisière-Fernand Widal, Pôle Neurosciences Tête et Cou, INSERM UMRS 1144, University Paris Diderot, Paris, France
| | - Guillaume Fond
- Fondation Fondamental, Créteil, France
- AP-HM, Aix-Marseille University, School of Medicine-La Timone Medical Campus, EA 3279: CEReSS-Health Service Research and Quality of Life Center, 27 Boulevard Jean Moulin, 13005, Marseille, France
| | - Sébastien Gard
- Fondation Fondamental, Créteil, France
- Centre Expert Troubles Bipolaires, Service de Psychiatrie Adulte, Hôpital Charles-Perrens, Bordeaux, France
| | - Chantal Henry
- Fondation Fondamental, Créteil, France
- Department of Psychiatry, Service Hospitalo-Universitaire, GHU Paris Psychiatrie and Neurosciences, 75014, Paris, France
| | - Marion Leboyer
- Fondation Fondamental, Créteil, France
- UMR_S955, UPEC, Créteil, France Inserm, Université Paris-Est, U955, Equipe 15 Psychiatrie génétique, Créteil, France
- AP-HP, Hôpital H. Mondor-A. Chenevier, Pôle de psychiatrie, Créteil, France
- Fondation de Cooperation Scientifique, Fondation FondaMental, Créteil, France
| | - Pierre-Michel Llorca
- Fondation Fondamental, Créteil, France
- CHU Clermont-Ferrand, Department of Psychiatry, University of Clermont Auvergne, EA 7280, Clermont-Ferrand, France
| | - Joséphine Loftus
- Fondation Fondamental, Créteil, France
- Pôle de Psychiatrie, Centre Hospitalier Princesse Grace, Monaco, France
| | - Emilie Olié
- Fondation Fondamental, Créteil, France
- Department of Emergency Psychiatry and Acute Care, CHU Montpellier, INSERM U1061, Montpellier University, Montpellier, France
| | - Christine Passerieux
- Fondation Fondamental, Créteil, France
- Service Universitaire de Psychiatrie d'Adultes et d'Addictologie, Centre Hospitalier de Versailles, 177 rue de Versailles, 78157, Le Chesnay, France
- CESP, INSERM, Université Paris Saclay, Université de Versailles Saint-Quentin-En-Yvelines, 2 Avenue de la Source de la Bièvre, 78180, Montigny-le-Bretonneux, France
| | - Mircea Polosan
- Fondation Fondamental, Créteil, France
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut des Neurosciences, CHU Grenoble Alpes, 38000, Grenoble, France
| | - Raymund Schwan
- Faculté de médecine, AP-HP, Department of Psychiatry, Université de Paris, Louis Mourier Hospital, CHU Louis Mourier, 178 rue des Renouillers, 92700, Colombes, France
- CHRU de Nancy et Pôle de Psychiatrie et Psychologie Clinique, Université de Lorraine, Centre Psychothérapique de Nancy, Nancy, France
| | - Paul Roux
- Fondation Fondamental, Créteil, France
- Service Universitaire de Psychiatrie d'Adultes et d'Addictologie, Centre Hospitalier de Versailles, 177 rue de Versailles, 78157, Le Chesnay, France
- CESP, INSERM, Université Paris Saclay, Université de Versailles Saint-Quentin-En-Yvelines, 2 Avenue de la Source de la Bièvre, 78180, Montigny-le-Bretonneux, France
| | - Caroline Dubertret
- Fondation Fondamental, Créteil, France
- Faculté de médecine, AP-HP, Department of Psychiatry, Université de Paris, Louis Mourier Hospital, CHU Louis Mourier, 178 rue des Renouillers, 92700, Colombes, France
- INSERM UMR1266, Institute of Psychiatry and Neuroscience of Paris, University Paris Descartes, Paris, France
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Hu M, Qian X, Liu S, Koh AJ, Sim K, Jiang X, Guan C, Zhou JH. Structural and diffusion MRI based schizophrenia classification using 2D pretrained and 3D naive Convolutional Neural Networks. Schizophr Res 2022; 243:330-341. [PMID: 34210562 DOI: 10.1016/j.schres.2021.06.011] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 05/11/2021] [Accepted: 06/18/2021] [Indexed: 02/06/2023]
Abstract
The ability of automatic feature learning makes Convolutional Neural Network (CNN) potentially suitable to uncover the complex and widespread brain changes in schizophrenia. Despite that, limited studies have been done on schizophrenia identification using interpretable deep learning approaches on multimodal neuroimaging data. Here, we developed a deep feature approach based on pre-trained 2D CNN and naive 3D CNN models trained from scratch for schizophrenia classification by integrating 3D structural and diffusion magnetic resonance imaging (MRI) data. We found that the naive 3D CNN models outperformed the pretrained 2D CNN models and the handcrafted feature-based machine learning approach using support vector machine during both cross-validation and testing on an independent dataset. Multimodal neuroimaging-based models accomplished performance superior to models based on a single modality. Furthermore, we identified brain grey matter and white matter regions critical for illness classification at the individual- and group-level which supported the salience network and striatal dysfunction hypotheses in schizophrenia. Our findings underscore the potential of CNN not only to automatically uncover and integrate multimodal 3D brain imaging features for schizophrenia identification, but also to provide relevant neurobiological interpretations which are crucial for developing objective and interpretable imaging-based probes for prognosis and diagnosis in psychiatric disorders.
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Affiliation(s)
- Mengjiao Hu
- NTU Institute for Health Technologies, Interdisciplinary Graduate Programme, Nanyang Technological University, Singapore, Singapore; Center for Sleep and Cognition, Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Xing Qian
- Center for Sleep and Cognition, Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Siwei Liu
- Center for Sleep and Cognition, Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Amelia Jialing Koh
- Center for Sleep and Cognition, Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Kang Sim
- West Region, Institute of Mental Health (IMH), Singapore, Singapore; Department of Research, Institute of Mental Health (IMH), Singapore, Singapore
| | - Xudong Jiang
- School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore, Singapore
| | - Cuntai Guan
- School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore
| | - Juan Helen Zhou
- Center for Sleep and Cognition, Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore; Center for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore; Neuroscience and Behavioural Disorders Program, Duke-NUS Medical School, Singapore, Singapore; NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore, Singapore.
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8
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Pretreatment abnormalities in white matter integrity predict one-year clinical outcome in first episode schizophrenia. Schizophr Res 2021; 228:241-248. [PMID: 33486391 DOI: 10.1016/j.schres.2020.12.011] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 08/17/2020] [Accepted: 12/06/2020] [Indexed: 02/05/2023]
Abstract
Schizophrenia is a serious mental illness for which the mainstay of treatment is antipsychotics. Up to 30% of schizophrenia patients show limited response to antipsychotics. Identifying these patients before treatment could guide individualized treatment for improving outcomes in those not likely to show robust benefit from antipsychotics. Diffusion tensor imaging was performed with 56 drug-naïve first-episode schizophrenia patients and 69 matched healthy controls. Patients were followed clinically after one-year of antipsychotic treatment and classified at that point into groups of 17 poor outcome and 39 good outcome patients based on whether they showed at least a 50% reduction of Positive and Negative Syndrome Scale (PANSS) scores from baseline. Tract-based spatial statistics were applied to assess white matter microstructure in the two patient subgroups and healthy controls. Poor outcome patients showed reduced pretreatment fractional anisotropy (FA) in left cingulum and anterior thalamic radiation and increased FA in right superior and inferior longitudinal fasciculus compared with good outcome patients. FA in each of these four tracts was decreased in both patient subgroups relative to healthy controls. Considered together, the four altered tracts showed promising ability to differentiate poor from good outcome patients (sensitivity = 74.4%, specificity = 95.2%, AUC = 0.90, p < 0.001), and superior prediction of clinical outcome to baseline PANSS scores (p < 0.015). Prediction of outcomes using DTI features was not related to duration of untreated psychosis. Baseline alterations in white matter integrity may identify schizophrenia patients less likely to respond to treatment, which could be useful information for stratification in clinical trials and for individualized treatment planning.
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9
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Saito J, Nemoto T, Katagiri N, Hori M, Tagata H, Funatogawa T, Yamaguchi T, Tsujino N, Mizuno M. Can reduced leftward asymmetry of white matter integrity be a marker of transition to psychosis in at-risk mental state? Asian J Psychiatr 2020; 54:102450. [PMID: 33271729 DOI: 10.1016/j.ajp.2020.102450] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Revised: 10/08/2020] [Accepted: 10/11/2020] [Indexed: 12/12/2022]
Abstract
As a biomarker for the degree of psychosis development, the lateral asymmetry of white matter (WM) integrity in each area of the cerebrum has been investigated; as a result, a reduced leftward asymmetry of WM integrity has been reported in patients with schizophrenia. Although individuals with an at-risk mental state for psychosis (ARMS) who subsequently develop psychosis are believed to have poorer social functioning, only a few studies have actually examined the associations between WM abnormalities and social functioning. The aim of the present study was to clarify the possibly predictive association between a reduced asymmetry of WM integrity and impairments in social functioning in patients with ARMS. Thirty ARMS subjects underwent MRI scanning and were assessed using the Social Functioning Scale (SFS). We examined the fractional anisotropy (FA) values in the cingulum bundle (CB) and the uncinate fasciculus (UF) using a tract-specific analysis. Lateral asymmetry was assessed using the laterality index (LI). The LI of the FA value was positive (leftward) in the CB and negative (rightward) in the UF. Although the LI was not correlated with the Scale of Prodromal Symptoms (SOPS) score, the LI in the CB was positively correlated with the SFS score. In ARMS patients, the degree of reduced leftward asymmetry in the CB might affect deteriorations in social functioning and may be useful as a biomarker for predicting future outcomes at an early stage of psychosis.
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Affiliation(s)
- Junichi Saito
- Department of Neuropsychiatry, Toho University Faculty of Medicine, Tokyo, Japan; Department of Psychiatry, Saiseikai Yokohamashi Tobu Hospital, Kanagawa, Japan
| | - Takahiro Nemoto
- Department of Neuropsychiatry, Toho University Faculty of Medicine, Tokyo, Japan.
| | - Naoyuki Katagiri
- Department of Neuropsychiatry, Toho University Faculty of Medicine, Tokyo, Japan
| | - Masaaki Hori
- Department of Radiology, Toho University Omori Medical Center, Tokyo, Japan
| | - Hiromi Tagata
- Department of Neuropsychiatry, Toho University Faculty of Medicine, Tokyo, Japan
| | - Tomoyuki Funatogawa
- Department of Neuropsychiatry, Toho University Faculty of Medicine, Tokyo, Japan
| | - Taiju Yamaguchi
- Department of Neuropsychiatry, Toho University Faculty of Medicine, Tokyo, Japan
| | - Naohisa Tsujino
- Department of Neuropsychiatry, Toho University Faculty of Medicine, Tokyo, Japan; Department of Psychiatry, Saiseikai Yokohamashi Tobu Hospital, Kanagawa, Japan
| | - Masafumi Mizuno
- Department of Neuropsychiatry, Toho University Faculty of Medicine, Tokyo, Japan
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10
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Clark SV, Tannahill A, Calhoun VD, Bernard JA, Bustillo J, Turner JA. Weaker Cerebellocortical Connectivity Within Sensorimotor and Executive Networks in Schizophrenia Compared to Healthy Controls: Relationships with Processing Speed. Brain Connect 2020; 10:490-503. [PMID: 32893675 PMCID: PMC7699013 DOI: 10.1089/brain.2020.0792] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Background: The cognitive dysmetria theory of schizophrenia proposes that communication between the cerebellum and cerebral cortex is disrupted by structural and functional abnormalities, resulting in psychotic symptoms and cognitive deficits. Methods: Using publicly available data, resting-state functional connectivity (rsFC) was calculated from 20 hemispheric cerebellar lobules as seed regions of interest to the rest of the brain. Group differences in rsFC between individuals with schizophrenia (SZ) and healthy controls (HCs) were computed, and relationships between rsFC and symptom severity and cognitive functioning were explored. Results: HCs demonstrated stronger connectivity than SZ between several cerebellar lobules and cortical regions, most robustly between motor-related cerebellar lobules (V and VIIIa/b) and temporal and parietal cortices. In addition, seven of nine lobules in which reduced cerebellocortical connectivity was observed showed diagnosis × processing speed interactions; HC showed a positive relationship between connectivity and processing speed, whereas SZ did not show this relationship. Other cognitive domains and symptom severity did not show relationships with connectivity. Conclusions: These findings partially support the cognitive dysmetria theory, and suggest that disrupted cerebellocortical connectivity is associated with slowed processing speed in schizophrenia. Impact statement We show in this work that in chronic schizophrenia, there is weaker functional connectivity between previously unstudied inferior posterior cerebellar lobules and cortical association areas. These findings align and extend previous work showing abnormal connectivity of anterior cerebellar lobules. Further, we present a novel finding that these connectivity deficits are differentially associated with processing speed in the schizophrenia versus healthy control groups. Findings provide further evidence for cerebellocortical dysconnectivity and processing speed deficits as biomarkers of schizophrenia, which may have implications for downstream effects on higher order cognitive functions, in line with the cognitive dysmetria theory.
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Affiliation(s)
- Sarah V. Clark
- Department of Psychology, Georgia State University, Atlanta, Georgia, USA
| | - Amber Tannahill
- Department of Psychology, Georgia State University, Atlanta, Georgia, USA
| | - Vince D. Calhoun
- Department of Psychology, Georgia State University, Atlanta, Georgia, USA
- Department of Neuroscience, Georgia State University, Atlanta, Georgia, USA
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA
- Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, New Mexico, USA
- The Mind Research Network, Albuquerque, New Mexico, USA
| | - Jessica A. Bernard
- Department of Psychological and Brain Sciences and Texas A&M Institute for Neuroscience, Texas A&M University, College Station, Texas, USA
| | - Juan Bustillo
- Department of Psychiatry, University of New Mexico, Albuquerque, New Mexico, USA
| | - Jessica A. Turner
- Department of Psychology, Georgia State University, Atlanta, Georgia, USA
- Department of Neuroscience, Georgia State University, Atlanta, Georgia, USA
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA
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11
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Li D, Liu W, Yan T, Cui X, Zhang Z, Wei J, Ma Y, Zhang N, Xiang J, Wang B. Disrupted Rich Club Organization of Hemispheric White Matter Networks in Bipolar Disorder. Front Neuroinform 2020; 14:39. [PMID: 32982711 PMCID: PMC7479125 DOI: 10.3389/fninf.2020.00039] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Accepted: 07/22/2020] [Indexed: 11/19/2022] Open
Abstract
Neuroimaging studies suggest disrupted connections of the brain white matter (WM) network in bipolar disorder (BD). A group of highly interconnected high-density structures, termed the 'rich club,' represents an important network for brain functioning. Recent works have revealed abnormal rich club organization in brain networks in BD. However, little is known regarding changes in the rich club organization of the hemispheric WM network in BD. Forty-nine BD patients and fifty-five age- and sex-matched normal controls (NCs) underwent diffusion tensor imaging (DTI). Graph theory approaches were applied to quantify group-specific rich club organization and nodal degree of hemispheric WM networks. We demonstrated that rich club organization of hemispheric WM networks in BD was disrupted, with disrupted feeder and local connections among hub and peripheral regions located in the default mode network (DMN) and the control execution network (CEN). In addition, BD patients showed abnormal asymmetry in the feeder and local connections, involving the hub and peripheral regions associated with emotion regulation and visuospatial functions. Moreover, the clinical symptoms of BD showed a significant correlation with the aberrant asymmetry in the regional degree of peripheral regions. These findings reveal that BD is closely associated with disrupted feeder and local connections but no alteration in rich-club connections in the rich club organization of hemispheric WM networks and provide novel insight into the changes of brain functions in BD.
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Affiliation(s)
- Dandan Li
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Weichen Liu
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Ting Yan
- Translational Medicine Research Center, Shanxi Medical University, Taiyuan, China
| | - Xiaohong Cui
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Zehua Zhang
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Jing Wei
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Yunxiao Ma
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Nan Zhang
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Jie Xiang
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Bin Wang
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
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12
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Antipsychotic effects of sex hormones and atypical hemispheric asymmetries. Cortex 2020; 127:313-332. [DOI: 10.1016/j.cortex.2020.02.016] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Revised: 02/27/2020] [Accepted: 02/29/2020] [Indexed: 12/16/2022]
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13
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The Amygdala in Schizophrenia and Bipolar Disorder: A Synthesis of Structural MRI, Diffusion Tensor Imaging, and Resting-State Functional Connectivity Findings. Harv Rev Psychiatry 2020; 27:150-164. [PMID: 31082993 DOI: 10.1097/hrp.0000000000000207] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Frequently implicated in psychotic spectrum disorders, the amygdala serves as an important hub for elucidating the convergent and divergent neural substrates in schizophrenia and bipolar disorder, the two most studied groups of psychotic spectrum conditions. A systematic search of electronic databases through December 2017 was conducted to identify neuroimaging studies of the amygdala in schizophrenia and bipolar disorder, focusing on structural MRI, diffusion tensor imaging (DTI), and resting-state functional connectivity studies, with an emphasis on cross-diagnostic studies. Ninety-four independent studies were selected for the present review (49 structural MRI, 27 DTI, and 18 resting-state functional MRI studies). Also selected, and analyzed in a separate meta-analysis, were 33 volumetric studies with the amygdala as the region-of-interest. Reduced left, right, and total amygdala volumes were found in schizophrenia, relative to both healthy controls and bipolar subjects, even when restricted to cohorts in the early stages of illness. No volume abnormalities were observed in bipolar subjects relative to healthy controls. Shape morphometry studies showed either amygdala deformity or no differences in schizophrenia, and no abnormalities in bipolar disorder. In contrast to the volumetric findings, DTI studies of the uncinate fasciculus tract (connecting the amygdala with the medial- and orbitofrontal cortices) largely showed reduced fractional anisotropy (a marker of white matter microstructure abnormality) in both schizophrenia and bipolar patients, with no cross-diagnostic differences. While decreased amygdalar-orbitofrontal functional connectivity was generally observed in schizophrenia, varying patterns of amygdalar-orbitofrontal connectivity in bipolar disorder were found. Future studies can consider adopting longitudinal approaches with multimodal imaging and more extensive clinical subtyping to probe amygdalar subregional changes and their relationship to the sequelae of psychotic disorders.
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14
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Lai S, Zhong S, Shan Y, Wang Y, Chen G, Luo X, Chen F, Zhang Y, Shen S, Huang H, Ning Y, Jia Y. Altered biochemical metabolism and its lateralization in the cortico-striato-cerebellar circuit of unmedicated bipolar II depression. J Affect Disord 2019; 259:82-90. [PMID: 31442883 DOI: 10.1016/j.jad.2019.07.021] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Revised: 05/30/2019] [Accepted: 07/04/2019] [Indexed: 12/11/2022]
Abstract
OBJECTIVES Evidence of the relationship between neurometabolic changes in the cortico-striato-cerebellar (CSC) circuit and bipolar disorder (BD) is still limited. To elucidate the pathogenesis of BD, we investigated the underlying neurometabolic changes and their effect on CSC lateralization circuits in unmedicated patients with bipolar II depression. METHODS Forty unmedicated participants with bipolar II depression and forty healthy controls underwent proton magnetic resonance spectroscopy (1H-MRS). We obtained bilateral metabolic ratios of N-acetylaspartate (NAA)/creatine (Cr) and choline (Cho)/Cr in the prefrontal white matter (PWM), anterior cingulate cortex (ACC), basal ganglia (BG) and the cerebellum. Metabolic ratios were characterized using a laterality index (LI) for left-right asymmetry. RESULTS Overall, aberrant lateralization in the CSC circuit was characteristic in patients with bipolar II depression. Patients with bipolar II depression showed significantly lower NAA/Cr ratios in the left PWM, right ACC, left BG and left cerebellum when compared with the healthy controls. For bipolar II depression, we found lower NAA/Cr LI in the PWM, BG, and cerebellum, higher NAA/Cr LI in the ACC, and higher Cho/Cr LI in the BG and cerebellum when compared to the standard value (1.0). For healthy controls, we found lower NAA/Cr LI only in the BG and higher Cho/Cr LI in the cerebellum when compared to 1.0. LIMITATIONS As a cross-sectional study with a small sample size, progressive changes and complex metabolic interactions with treatment were not observed. CONCLUSIONS Our findings suggest that abnormal biochemical metabolism with aberrant lateralization in the CSC circuit may be an underlying pathophysiology of bipolar II depression.
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Affiliation(s)
- Shunkai Lai
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Shuming Zhong
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Yanyan Shan
- School of Management, Jinan University, Guangzhou 510316, China
| | - Ying Wang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Guanmao Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Xiaomei Luo
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Feng Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Yiliang Zhang
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Shiyi Shen
- School of Management, Jinan University, Guangzhou 510316, China
| | - Hui Huang
- School of Management, Jinan University, Guangzhou 510316, China
| | - Yuping Ning
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou Huiai Hospital, Guangzhou 510370, China
| | - Yanbin Jia
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou 510630, China.
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15
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Natali F, Dolce C, Peters J, Stelletta C, Demé B, Ollivier J, Leduc G, Cupane A, Barbier EL. Brain lateralization probed by water diffusion at the atomic to micrometric scale. Sci Rep 2019; 9:14694. [PMID: 31604980 PMCID: PMC6789030 DOI: 10.1038/s41598-019-51022-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Accepted: 09/23/2019] [Indexed: 01/27/2023] Open
Abstract
Combined neutron scattering and diffusion nuclear magnetic resonance experiments have been used to reveal significant interregional asymmetries (lateralization) in bovine brain hemispheres in terms of myelin arrangement and water dynamics at micron to atomic scales. Thicker myelin sheaths were found in the left hemisphere using neutron diffraction. 4.7 T dMRI and quasi-elastic neutron experiments highlighted significant differences in the properties of water dynamics in the two hemispheres. The results were interpreted in terms of hemisphere-dependent cellular composition (number of neurons, cell distribution, etc.) as well as specificity of neurological functions (such as preferential networking).
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Affiliation(s)
- F Natali
- Institut Laue-Langevin, 71 avenue des Martyrs, CS 20156, 38042, Grenoble cedex 9, France.
- CNR-IOM, OGG, 71 avenue des Martyrs, CS 20156, 38042, Grenoble cedex 9, France.
| | - C Dolce
- Institut Laue-Langevin, 71 avenue des Martyrs, CS 20156, 38042, Grenoble cedex 9, France
- University Grenoble Alpes, LiPhy, 140 rue de la physique, 38402, Saint Martin d'Hères, France
- Department of Physics and Chemistry, University of Palermo, via Archirafi 36, 90123, Palermo, Italy
| | - J Peters
- Institut Laue-Langevin, 71 avenue des Martyrs, CS 20156, 38042, Grenoble cedex 9, France
- University Grenoble Alpes, LiPhy, 140 rue de la physique, 38402, Saint Martin d'Hères, France
| | - C Stelletta
- Department of Animal Med., Production and Health, University of Padova, Viale dell'Università 16, 35020, Agripolis, Legnaro, Italy
| | - B Demé
- Institut Laue-Langevin, 71 avenue des Martyrs, CS 20156, 38042, Grenoble cedex 9, France
| | - J Ollivier
- Institut Laue-Langevin, 71 avenue des Martyrs, CS 20156, 38042, Grenoble cedex 9, France
| | - G Leduc
- Biomedical Facility, ESRF, 71 avenue des Martyrs, CS 20156, 38042, Grenoble cedex 9, France
| | - A Cupane
- Department of Physics and Chemistry, University of Palermo, via Archirafi 36, 90123, Palermo, Italy
| | - E L Barbier
- University Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000, Grenoble, France
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16
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Mitelman SA. Transdiagnostic neuroimaging in psychiatry: A review. Psychiatry Res 2019; 277:23-38. [PMID: 30639090 DOI: 10.1016/j.psychres.2019.01.026] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Revised: 01/07/2019] [Accepted: 01/07/2019] [Indexed: 01/10/2023]
Abstract
Transdiagnostic approach has a long history in neuroimaging, predating its recent ascendance as a paradigm for new psychiatric nosology. Various psychiatric disorders have been compared for commonalities and differences in neuroanatomical features and activation patterns, with different aims and rationales. This review covers both structural and functional neuroimaging publications with direct comparison of different psychiatric disorders, including schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorder, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, conduct disorder, anorexia nervosa, and bulimia nervosa. Major findings are systematically presented along with specific rationales for each comparison.
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Affiliation(s)
- Serge A Mitelman
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA; Department of Psychiatry, Division of Child and Adolescent Psychiatry, Elmhurst Hospital Center, 79-01 Broadway, Elmhurst, NY 11373, USA.
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17
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Abdolmaleky HM, Gower AC, Wong CK, Cox JW, Zhang X, Thiagalingam A, Shafa R, Sivaraman V, Zhou JR, Thiagalingam S. Aberrant transcriptomes and DNA methylomes define pathways that drive pathogenesis and loss of brain laterality/asymmetry in schizophrenia and bipolar disorder. Am J Med Genet B Neuropsychiatr Genet 2019; 180:138-149. [PMID: 30468562 PMCID: PMC6386618 DOI: 10.1002/ajmg.b.32691] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2017] [Revised: 07/23/2018] [Accepted: 09/18/2018] [Indexed: 12/15/2022]
Abstract
Although the loss of brain laterality is one of the most consistent modalities in schizophrenia (SCZ) and bipolar disorder (BD), its molecular basis remains elusive. Our limited previous studies indicated that epigenetic modifications are key to the asymmetric transcriptomes of brain hemispheres. We used whole-genome expression microarrays to profile postmortem brain samples from subjects with SCZ, psychotic BD [BD[+]] or non-psychotic BD [BD(-)], or matched controls (10/group) and performed whole-genome DNA methylation (DNAM) profiling of the same samples (3-4/group) to identify pathways associated with SCZ or BD[+] and genes/sites susceptible to epigenetic regulation. qRT-PCR and quantitative DNAM analysis were employed to validate findings in larger sample sets (35/group). Gene Set Enrichment Analysis (GSEA) demonstrated that BMP signaling and astrocyte and cerebral cortex development are significantly (FDR q < 0.25) coordinately upregulated in both SCZ and BD[+], and glutamate signaling and TGFβ signaling are significantly coordinately upregulated in SCZ. GSEA also indicated that collagens are downregulated in right versus left brain of controls, but not in SCZ or BD[+] patients. Ingenuity Pathway Analysis predicted that TGFB2 is an upstream regulator of these genes (p = .0012). While lateralized expression of TGFB2 in controls (p = .017) is associated with a corresponding change in DNAM (p ≤ .023), lateralized expression and DNAM of TGFB2 are absent in SCZ or BD. Loss of brain laterality in SCZ and BD corresponds to aberrant epigenetic regulation of TGFB2 and changes in TGFβ signaling, indicating potential avenues for disease prevention/treatment.
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Affiliation(s)
- Hamid Mostafavi Abdolmaleky
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA,Nutrition/Metabolism Laboratory, BIDMC, Harvard Medical School, Boston, MA,Corresponding Authors: Hamid Mostafavi Abdolmaleky () and Sam Thiagalingam ()
| | - Adam Chapin Gower
- Clinical and Translational Science Institute, Boston University School of Medicine, Boston, MA
| | - Chen Khuan Wong
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA,Genetics & Genomics Graduate Program, Boston University School of Medicine, Boston, MA
| | - Jiayi Wu Cox
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA,Bioinformatics Graduate Program, Boston University, Boston, MA
| | - Xiaoling Zhang
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA
| | - Arunthathi Thiagalingam
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA
| | | | - Vadivelu Sivaraman
- Critical Care Medicine, Department of Anesthesiology, University of Maryland School of Medicine, Baltimore, MD
| | - Jin-Rong Zhou
- Nutrition/Metabolism Laboratory, BIDMC, Harvard Medical School, Boston, MA
| | - Sam Thiagalingam
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA,Genetics & Genomics Graduate Program, Boston University School of Medicine, Boston, MA,Department of Pathology & Laboratory Medicine, Boston University School of Medicine, Boston, MA,Corresponding Authors: Hamid Mostafavi Abdolmaleky () and Sam Thiagalingam ()
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18
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Sehmbi M, Rowley CD, Minuzzi L, Kapczinski F, Kwiecien JM, Bock NA, Frey BN. Age-related deficits in intracortical myelination in young adults with bipolar disorder type I. J Psychiatry Neurosci 2019; 44:79-88. [PMID: 30525334 PMCID: PMC6397039 DOI: 10.1503/jpn.170220] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Previous studies have implicated white-matter-related changes in the pathophysiology of bipolar disorder. However, most of what is known is derived from in vivo subcortical white-matter imaging or postmortem studies. In this study, we investigated whole-brain intracortical myelin (ICM) content in people with bipolar disorder type I and controls. METHODS Between Sept. 1, 2014, and Jan. 31, 2017, we used a 3 T General Electric scanner to collect T1-weighted images in 45 people with bipolar disorder type I and 60 controls aged 17 to 45 years using an optimized sequence that was sensitive to ICM content. We analyzed images using a surfacebased approach. We used general linear models with quadratic age terms to examine the signal trajectory of ICM across the age range. RESULTS In healthy controls, the T1-weighted signal followed an inverted-U trajectory over age; in people with bipolar disorder type I, the association between ICM and age followed a flat trajectory (p < 0.05, Bonferroni corrected). Exploratory analyses showed that ICM signal intensity was associated with duration of illness, age of onset, and anticonvulsant and antipsychotic use in people with bipolar disorder type I (p < 0.05, uncorrected). LIMITATIONS Because of the cross-sectional nature of the study, we were unable to comment on whether the effects were due to dysmyelination or demyelination in bipolar disorder. CONCLUSION This foundational study is, to our knowledge, the first to show global age-related deficits in ICM maturation throughout the cortex in bipolar disorder. Considering the impact of myelination on the maintenance of neural synchrony and the integrity of neural connections, this work may help us better understand the cognitive and behavioural deficits seen in bipolar disorder.
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Affiliation(s)
- Manpreet Sehmbi
- From the Graduate Student, MiNDS Neuroscience Graduate Program, McMaster University, Hamilton, ON (Sehmbi, Rowley); the Mood Disorders Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON (Minuzzi, Kapczinski, Frey); the Women’s Health Concerns Clinic, St. Joseph’s Healthcare, Hamilton, ON (Minuzzi, Frey); the Department of Pathology and Molecular Medicine, M. deGroote School of Medicine, McMaster University, Hamilton, ON (Kwiecien); the Department of Psychology, Neuroscience, and Behaviour, McMaster University, Hamilton, ON (Bock); and the Department of Clinical Pathomorphology, Medical University of Lublin, Poland (Kwiecien)
| | - Christopher D. Rowley
- From the Graduate Student, MiNDS Neuroscience Graduate Program, McMaster University, Hamilton, ON (Sehmbi, Rowley); the Mood Disorders Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON (Minuzzi, Kapczinski, Frey); the Women’s Health Concerns Clinic, St. Joseph’s Healthcare, Hamilton, ON (Minuzzi, Frey); the Department of Pathology and Molecular Medicine, M. deGroote School of Medicine, McMaster University, Hamilton, ON (Kwiecien); the Department of Psychology, Neuroscience, and Behaviour, McMaster University, Hamilton, ON (Bock); and the Department of Clinical Pathomorphology, Medical University of Lublin, Poland (Kwiecien)
| | - Luciano Minuzzi
- From the Graduate Student, MiNDS Neuroscience Graduate Program, McMaster University, Hamilton, ON (Sehmbi, Rowley); the Mood Disorders Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON (Minuzzi, Kapczinski, Frey); the Women’s Health Concerns Clinic, St. Joseph’s Healthcare, Hamilton, ON (Minuzzi, Frey); the Department of Pathology and Molecular Medicine, M. deGroote School of Medicine, McMaster University, Hamilton, ON (Kwiecien); the Department of Psychology, Neuroscience, and Behaviour, McMaster University, Hamilton, ON (Bock); and the Department of Clinical Pathomorphology, Medical University of Lublin, Poland (Kwiecien)
| | - Flavio Kapczinski
- From the Graduate Student, MiNDS Neuroscience Graduate Program, McMaster University, Hamilton, ON (Sehmbi, Rowley); the Mood Disorders Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON (Minuzzi, Kapczinski, Frey); the Women’s Health Concerns Clinic, St. Joseph’s Healthcare, Hamilton, ON (Minuzzi, Frey); the Department of Pathology and Molecular Medicine, M. deGroote School of Medicine, McMaster University, Hamilton, ON (Kwiecien); the Department of Psychology, Neuroscience, and Behaviour, McMaster University, Hamilton, ON (Bock); and the Department of Clinical Pathomorphology, Medical University of Lublin, Poland (Kwiecien)
| | - Jacek M. Kwiecien
- From the Graduate Student, MiNDS Neuroscience Graduate Program, McMaster University, Hamilton, ON (Sehmbi, Rowley); the Mood Disorders Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON (Minuzzi, Kapczinski, Frey); the Women’s Health Concerns Clinic, St. Joseph’s Healthcare, Hamilton, ON (Minuzzi, Frey); the Department of Pathology and Molecular Medicine, M. deGroote School of Medicine, McMaster University, Hamilton, ON (Kwiecien); the Department of Psychology, Neuroscience, and Behaviour, McMaster University, Hamilton, ON (Bock); and the Department of Clinical Pathomorphology, Medical University of Lublin, Poland (Kwiecien)
| | - Nicholas A. Bock
- From the Graduate Student, MiNDS Neuroscience Graduate Program, McMaster University, Hamilton, ON (Sehmbi, Rowley); the Mood Disorders Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON (Minuzzi, Kapczinski, Frey); the Women’s Health Concerns Clinic, St. Joseph’s Healthcare, Hamilton, ON (Minuzzi, Frey); the Department of Pathology and Molecular Medicine, M. deGroote School of Medicine, McMaster University, Hamilton, ON (Kwiecien); the Department of Psychology, Neuroscience, and Behaviour, McMaster University, Hamilton, ON (Bock); and the Department of Clinical Pathomorphology, Medical University of Lublin, Poland (Kwiecien)
| | - Benicio N. Frey
- From the Graduate Student, MiNDS Neuroscience Graduate Program, McMaster University, Hamilton, ON (Sehmbi, Rowley); the Mood Disorders Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON (Minuzzi, Kapczinski, Frey); the Women’s Health Concerns Clinic, St. Joseph’s Healthcare, Hamilton, ON (Minuzzi, Frey); the Department of Pathology and Molecular Medicine, M. deGroote School of Medicine, McMaster University, Hamilton, ON (Kwiecien); the Department of Psychology, Neuroscience, and Behaviour, McMaster University, Hamilton, ON (Bock); and the Department of Clinical Pathomorphology, Medical University of Lublin, Poland (Kwiecien)
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19
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Wang B, Li T, Zhou M, Zhao S, Niu Y, Wang X, Yan T, Cao R, Xiang J, Li D. The Abnormality of Topological Asymmetry in Hemispheric Brain Anatomical Networks in Bipolar Disorder. Front Neurosci 2018; 12:618. [PMID: 30233301 PMCID: PMC6129594 DOI: 10.3389/fnins.2018.00618] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Accepted: 08/14/2018] [Indexed: 12/24/2022] Open
Abstract
Convergent evidences have demonstrated a variety of regional abnormalities of asymmetry in bipolar disorder (BD). However, little is known about the alterations in hemispheric topological asymmetries. In this study, we used diffusion tensor imaging to construct the hemispheric brain anatomical network of 49 patients with BD and 61 matched normal controls. Graph theory was then applied to quantify topological properties of the hemispheric networks. Although small-world properties were preserved in the hemispheric networks of BD, the degrees of the asymmetry in global efficiency, characteristic path length, and small-world property were significantly decreased. More changes in topological properties of the right hemisphere than those of left hemisphere were found in patients compared with normal controls. Consistent with such changes, the nodal efficiency in patients with BD also showed less rightward asymmetry mainly in the frontal, occipital, parietal, and temporal lobes. In contrast to leftward asymmetry, significant rightward asymmetry was found in supplementary motor area of BD, and attributed to more deficits in nodal efficiency of the left hemisphere. Finally, these asymmetry score of nodal efficiency in the inferior parietal lobule and rolandic operculum were significantly associated with symptom severity of BD. Our results suggested that abnormal hemispheric asymmetries in brain anatomical networks were associated with aberrant neurodevelopment, and providing insights into the potential neural biomarkers of BD by measuring the topological asymmetry in hemispheric brain anatomical networks.
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Affiliation(s)
- Bin Wang
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Ting Li
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Mengni Zhou
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Shuo Zhao
- Faculty of Human Health Science, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yan Niu
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Xin Wang
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Ting Yan
- Translational Medicine Research Center, Shanxi Medical University, Taiyuan, China
| | - Rui Cao
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Jie Xiang
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Dandan Li
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
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20
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Zhang B, Wang C, Ma G, Fan H, Wang J, Wang W. Cerebral processing of facial emotions in bipolar I and II disorders: An event-related potential study. J Affect Disord 2018; 236:37-44. [PMID: 29709719 DOI: 10.1016/j.jad.2018.04.098] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2017] [Revised: 03/13/2018] [Accepted: 04/08/2018] [Indexed: 10/17/2022]
Abstract
BACKGROUND Behavioral results have shown that bipolar disorder patients have impaired recognition of facial emotions, but the detailed information processing of facial emotions in patients with bipolar I (BD I) and II (BD II) disorders remain unknown. METHODS We tested the cerebral event-related potentials to the static facial expressions of Neutral, Happiness, Anger and Sadness in 39 adult patients with BD I, 22 BD II, and 54 healthy volunteers. Participants' affective states were measured with the Mood Disorder Questionnaire, the Hypomania Checklist-32, and the Plutchik-van Praag Depression Inventory. RESULTS Over-processed right occipitotemporal cortex during N1 time window to Neutral and Happiness, and during P3b window to Sadness were found in BD I; prolonged N1 latencies to Neutral and Happiness, declined P3b amplitude to Sadness, negative correlation between P3b latency to Sadness and depression, and attenuated superior frontal activity during P3b window to Sadness were found in BD II; and the right-side dominance during facial emotion processing were found in both BD I and BD II. LIMITATIONS We didn't record the personality traits or medication used in patients, nor included other facial emotions such as fear and disgust. CONCLUSIONS When responding to facial emotions, both BD I and BD II showed a right-side processing dominance; BD I displayed enhanced processing in the right occipitotemporal cortex during structural encoding and categorical processing of facial emotions; while BD II displayed generalized impairments, less involvement of superior frontal cortex to negative emotions, and reduced ability to process negative emotions which was associated with depression.
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Affiliation(s)
- Bingren Zhang
- Department of Clinical Psychology and Psychiatry/School of Public Health, Zhejiang University College of Medicine, Hangzhou, Zhejiang 310058 China
| | - Chu Wang
- Department of Clinical Psychology and Psychiatry/School of Public Health, Zhejiang University College of Medicine, Hangzhou, Zhejiang 310058 China
| | - Guorong Ma
- Department of Clinical Psychology and Psychiatry/School of Public Health, Zhejiang University College of Medicine, Hangzhou, Zhejiang 310058 China
| | - Hongying Fan
- Department of Clinical Psychology and Psychiatry/School of Public Health, Zhejiang University College of Medicine, Hangzhou, Zhejiang 310058 China
| | - Jiawei Wang
- Department of Clinical Psychology and Psychiatry/School of Public Health, Zhejiang University College of Medicine, Hangzhou, Zhejiang 310058 China
| | - Wei Wang
- Department of Clinical Psychology and Psychiatry/School of Public Health, Zhejiang University College of Medicine, Hangzhou, Zhejiang 310058 China.
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21
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Howells FM, Temmingh HS, Hsieh JH, van Dijen AV, Baldwin DS, Stein DJ. Electroencephalographic delta/alpha frequency activity differentiates psychotic disorders: a study of schizophrenia, bipolar disorder and methamphetamine-induced psychotic disorder. Transl Psychiatry 2018; 8:75. [PMID: 29643331 PMCID: PMC5895848 DOI: 10.1038/s41398-018-0105-y] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2017] [Revised: 11/29/2017] [Accepted: 12/13/2017] [Indexed: 11/17/2022] Open
Abstract
Electroencephalography (EEG) has been proposed as a neurophysiological biomarker to delineate psychotic disorders. It is known that increased delta and decreased alpha, which are apparent in psychosis, are indicative of inappropriate arousal state, which leads to reduced ability to attend to relevant information. On this premise, we investigated delta/alpha frequency activity, as this ratio of frequency activity may serve as an effective neurophysiological biomarker. The current study investigated differences in delta/alpha frequency activity, in schizophrenia (SCZ), bipolar I disorder with psychotic features and methamphetamine-induced psychosis. One hundred and nine participants, including individuals with SCZ (n = 28), bipolar I disorder with psychotic features (n = 28), methamphetamine-induced psychotic disorder (MPD) (n = 24) and healthy controls (CON, n = 29). Diagnosis was ascertained with the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, 4th Edition disorders and current medication was recorded. EEG was undertaken in three testing conditions: resting eyes open, resting eyes closed and during completion of a simple cognitive task (visual continuous performance task). EEG delta/alpha frequency activity was investigated across these conditions. First, delta/alpha frequency activity during resting eyes closed was higher in SCZ and MPD globally, when compared to CON, then lower for bipolar disorder (BPD) than MPD for right hemisphere. Second, delta/alpha frequency activity during resting eyes open was higher in SCZ, BPD and MPD for all electrodes, except left frontal, when compared to CON. Third, delta/alpha frequency activity during the cognitive task was higher in BPD and MPD for all electrodes, except left frontal, when compared to CON. Assessment of EEG delta/alpha frequency activity supports the delineation of underlying neurophysiological mechanisms present in psychotic disorders, which are likely related to dysfunctional thalamo-cortical connectivity. Delta/alpha frequency activity may provide a useful neurophysiological biomarker to delineate psychotic disorders.
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Affiliation(s)
- Fleur M Howells
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa.
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa.
| | - Hendrik S Temmingh
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Jennifer H Hsieh
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Andrea V van Dijen
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - David S Baldwin
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
- Clinical and Experimental Sciences, University of Southampton, Southampton, UK
| | - Dan J Stein
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- MRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
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22
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Prunas C, Delvecchio G, Perlini C, Barillari M, Ruggeri M, Altamura AC, Bellani M, Brambilla P. Diffusion imaging study of the Corpus Callosum in bipolar disorder. Psychiatry Res Neuroimaging 2018; 271:75-81. [PMID: 29129544 DOI: 10.1016/j.pscychresns.2017.11.001] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2017] [Revised: 09/06/2017] [Accepted: 11/02/2017] [Indexed: 01/28/2023]
Abstract
Structural and diffusion imaging studies have provided some evidence of abnormal organization of Corpus Callosum (CC) in Bipolar Disorder (BD). Therefore, by using Diffusion Weighted Imaging (DWI), which allows to build subtle prediction models of fiber integrity for white matter (WM) tracts, this study aims to further explore the microstructure integrity of CC in BD patients compared to matched healthy controls. Twenty-four chronic patients with BD and 35 healthy controls were included in the study. Circular regions of interest were placed, on diffusion images, in the left and right side of callosal regions (i.e. rostrum/genu, anterior body, posterior body, splenium) and the Apparent Diffusion Coefficient (ADC) was then calculated. Significantly increased ADC values were found in right anterior body and in right splenium in BD patients compared to healthy controls (all p < 0.05, Bonferroni corrected). In this study, we found abnormally increased ADC callosal values in BD suggesting microstructural anomalies specifically in the right hemisphere. Interestingly, this finding further supports the presence of an altered inter-hemispheric communication between frontal and temporo-parietal association areas in patients with BD, which may ultimately result in clinical symptoms and cognitive deficits.
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Affiliation(s)
- Cecilia Prunas
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, University of Milan, Milan, Italy
| | | | - Cinzia Perlini
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Clinical Psychology, University of Verona, Verona, Italy; InterUniversity Centre for Behavioural Neurosciences, University of Verona, Verona, Italy
| | - Marco Barillari
- Section of Neurology, Department of Neurological and Movement Sciences, University Hospital of Verona, Verona, Italy
| | | | - A Carlo Altamura
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, University of Milan, Milan, Italy
| | - Marcella Bellani
- InterUniversity Centre for Behavioural Neurosciences, University of Verona, Verona, Italy; Section of Psychiatry, AOUI Verona, Verona, Italy
| | - Paolo Brambilla
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, University of Milan, Milan, Italy; Department of Psychiatry and Behavioural Neurosciences, University of Texas at Houston, TX, USA.
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23
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Elucidation of shared and specific white matter findings underlying psychopathology clusters in schizophrenia. Asian J Psychiatr 2017; 30:144-151. [PMID: 28938151 DOI: 10.1016/j.ajp.2017.08.016] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2017] [Accepted: 08/28/2017] [Indexed: 12/27/2022]
Abstract
BACKGROUND Schizophrenia is associated with diverse white matter (WM) brain abnormalities. In this study, we sought to examine the WM microstructural findings which underlie clinical psychopathology clusters in schizophrenia and hypothesized that these symptom clusters are associated with common and unique WM tracts. METHODS Overall, 76 healthy controls (HC), and 148 patients with schizophrenia (SZ) were recruited and severity of symptomatology in schizophrenia was assessed using the Positive and Negative Syndrome Scale. WM fractional anisotropy (FA) values were extracted from their diffusion tensor images. Psychopathology clusters were first determined using factor analysis and the relationship between these symptom factors and FA values were then assessed with structural equation modelling, which included covariates such as age, sex, duration of illness and medications prescribed. RESULTS Patients with schizophrenia had reduced FA in the genu of corpus callosum (gCC) compared to HC. A three-factor model, namely Positive, Negative, Disorganised factors, was determined as the best fit for the data. All three psychopathology factors were associated with decreased FA in the gCC and bilateral cingulate gyrus. Higher Negative factor scores were uniquely associated with decreased FA in the right sagittal striatum and right superior longitudinal fasciculus. CONCLUSIONS This study found shared and specific WM changes and their associations with specific symptom clusters, which potentially allows for monitoring of such white matter findings associated with clinical presentations in schizophrenia over treatment and illness course.
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