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Xu J, Liang J, Yan H, Zhang C, Zhang X, Li X, Huang W, Guo H, Yang Y, Ye J, Ou Y, Deng W, Xu J, Li X, Xie G, Guo W. Alterations in amygdala subregions-Default mode network connectivity after treatment in patients with schizophrenia. J Neurosci Res 2024; 102:e25376. [PMID: 39158151 DOI: 10.1002/jnr.25376] [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: 12/25/2023] [Revised: 06/22/2024] [Accepted: 08/08/2024] [Indexed: 08/20/2024]
Abstract
Disrupted connectivity in the default mode network (DMN) during resting-state functional MRI (rs-fMRI) is well-documented in schizophrenia (SCZ). The amygdala, a key component in the neurobiology of SCZ, comprises distinct subregions that may exert varying effects on the disorder. This study aimed to investigate variations in functional connectivity (FC) between distinct amygdala subregions and the DMN in SCZ individuals and explore the effects of treatment on these connections. Fifty-six SCZ patients and 51 healthy controls underwent FC analysis and questionnaire surveys during resting state. The amygdala was selected as the region of interest (ROI) and subdivided into four parts. Changes in FC were examined, and correlations between questionnaire scores and brain activity were explored. Pre-treatment, SCZ patients exhibited reduced FC between the amygdala and DMN compared to HCs. After treatment, significant differences persisted in the right medial amygdala, while other regions did not differ significantly from controls. In addition, PANSS scores positively correlated with FC between the Right Medial Amygdala and the left SMFC (r = .347, p = .009), while RBANS5A scores showed a positive correlation with FC between the Left Lateral Amygdala and the right MTG (rho = -.347, p = .009). The rsFC between the amygdala and the DMN plays a crucial role in the treatment mechanisms of SCZ. This could provide a promising predictive indicator for understanding the neural mechanisms behind treatment and symptomatic improvement.
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Affiliation(s)
- Jianxiong Xu
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Jiaquan Liang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Haohao Yan
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Chunguo Zhang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Xinglian Zhang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Xuesong Li
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Wei Huang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Huagui Guo
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Yu Yang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Jinzhong Ye
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Yangpan Ou
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Wen Deng
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Jinbing Xu
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Xiaoling Li
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Guojun Xie
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Wenbin Guo
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
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Masias Bruns M, Ramirez-Mahaluf JP, Valli I, Ortuño M, Ilzarbe D, de la Serna E, Navarro OP, Crossley NA, González Ballester MÁ, Baeza I, Piella G, Castro-Fornieles J, Sugranyes G. Altered Temporal Dynamics of Resting-State Functional Magnetic Resonance Imaging in Adolescent-Onset First-Episode Psychosis. Schizophr Bull 2024; 50:418-426. [PMID: 37607335 PMCID: PMC10919773 DOI: 10.1093/schbul/sbad107] [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] [Indexed: 08/24/2023]
Abstract
BACKGROUND Dynamic functional connectivity (dFC) alterations have been reported in patients with adult-onset and chronic psychosis. We sought to examine whether such abnormalities were also observed in patients with first episode, adolescent-onset psychosis (AOP), in order to rule out potential effects of chronicity and protracted antipsychotic treatment exposure. AOP has been suggested to have less diagnostic specificity compared to psychosis with onset in adulthood and occurs during a period of neurodevelopmental changes in brain functional connections. STUDY DESIGN Seventy-nine patients with first episode, AOP (36 patients with schizophrenia-spectrum disorder, SSD; and 43 with affective psychotic disorder, AF) and 54 healthy controls (HC), aged 10 to 17 years were included. Participants underwent clinical and cognitive assessments and resting-state functional magnetic resonance imaging. Graph-based measures were used to analyze temporal trajectories of dFC, which were compared between patients with SSD, AF, and HC. Within patients, we also tested associations between dFC parameters and clinical variables. STUDY RESULTS Patients with SSD temporally visited the different connectivity states in a less efficient way (reduced global efficiency), visiting fewer nodes (larger temporal modularity, and increased immobility), with a reduction in the metabolic expenditure (cost and leap size), relative to AF and HC (effect sizes: Cohen's D, ranging 0.54 to.91). In youth with AF, these parameters did not differ compared to HC. Connectivity measures were not associated with clinical severity, intelligence, cannabis use, or dose of antipsychotic medication. CONCLUSIONS dFC measures hold potential towards the development of brain-based biomarkers characterizing adolescent-onset SSD.
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Affiliation(s)
- Mireia Masias Bruns
- BCN-MedTech, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - Juan Pablo Ramirez-Mahaluf
- BCN-MedTech, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
- Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Isabel Valli
- Clinical and Experimental Neuroscience, Fundació de Recerca Clínic Barcelona, Institut d’Investigacions Biomèdiques Agustí Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - María Ortuño
- Clinical and Experimental Neuroscience, Fundació de Recerca Clínic Barcelona, Institut d’Investigacions Biomèdiques Agustí Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Daniel Ilzarbe
- Clinical and Experimental Neuroscience, Fundació de Recerca Clínic Barcelona, Institut d’Investigacions Biomèdiques Agustí Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Department of Child and Adolescent Psychiatry, 2017SGR881, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain
- Group G04, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
- Department of Medicine, Universitat de Barcelona, Barcelona, Spain
| | - Elena de la Serna
- Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- Department of Child and Adolescent Psychiatry, 2017SGR881, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain
- Group G04, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
| | - Olga Puig Navarro
- Department of Child and Adolescent Psychiatry, 2017SGR881, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain
- Group G04, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
| | - Nicolas A Crossley
- Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Miguel Ángel González Ballester
- BCN-MedTech, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
- Clinical and Experimental Neuroscience, Fundació de Recerca Clínic Barcelona, Institut d’Investigacions Biomèdiques Agustí Pi i Sunyer (IDIBAPS), Barcelona, Spain
- ICREA, Barcelona, Spain
| | - Inmaculada Baeza
- Clinical and Experimental Neuroscience, Fundació de Recerca Clínic Barcelona, Institut d’Investigacions Biomèdiques Agustí Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Department of Child and Adolescent Psychiatry, 2017SGR881, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain
- Group G04, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
- Department of Medicine, Universitat de Barcelona, Barcelona, Spain
| | - Gemma Piella
- BCN-MedTech, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - Josefina Castro-Fornieles
- Clinical and Experimental Neuroscience, Fundació de Recerca Clínic Barcelona, Institut d’Investigacions Biomèdiques Agustí Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Department of Child and Adolescent Psychiatry, 2017SGR881, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain
- Group G04, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
- Department of Medicine, Universitat de Barcelona, Barcelona, Spain
| | - Gisela Sugranyes
- Clinical and Experimental Neuroscience, Fundació de Recerca Clínic Barcelona, Institut d’Investigacions Biomèdiques Agustí Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Department of Child and Adolescent Psychiatry, 2017SGR881, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain
- Group G04, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
- Department of Medicine, Universitat de Barcelona, Barcelona, Spain
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Shoeibi A, Ghassemi N, Khodatars M, Moridian P, Khosravi A, Zare A, Gorriz JM, Chale-Chale AH, Khadem A, Rajendra Acharya U. Automatic diagnosis of schizophrenia and attention deficit hyperactivity disorder in rs-fMRI modality using convolutional autoencoder model and interval type-2 fuzzy regression. Cogn Neurodyn 2023; 17:1501-1523. [PMID: 37974583 PMCID: PMC10640504 DOI: 10.1007/s11571-022-09897-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Revised: 09/23/2022] [Accepted: 10/04/2022] [Indexed: 11/13/2022] Open
Abstract
Nowadays, many people worldwide suffer from brain disorders, and their health is in danger. So far, numerous methods have been proposed for the diagnosis of Schizophrenia (SZ) and attention deficit hyperactivity disorder (ADHD), among which functional magnetic resonance imaging (fMRI) modalities are known as a popular method among physicians. This paper presents an SZ and ADHD intelligent detection method of resting-state fMRI (rs-fMRI) modality using a new deep learning method. The University of California Los Angeles dataset, which contains the rs-fMRI modalities of SZ and ADHD patients, has been used for experiments. The FMRIB software library toolbox first performed preprocessing on rs-fMRI data. Then, a convolutional Autoencoder model with the proposed number of layers is used to extract features from rs-fMRI data. In the classification step, a new fuzzy method called interval type-2 fuzzy regression (IT2FR) is introduced and then optimized by genetic algorithm, particle swarm optimization, and gray wolf optimization (GWO) techniques. Also, the results of IT2FR methods are compared with multilayer perceptron, k-nearest neighbors, support vector machine, random forest, and decision tree, and adaptive neuro-fuzzy inference system methods. The experiment results show that the IT2FR method with the GWO optimization algorithm has achieved satisfactory results compared to other classifier methods. Finally, the proposed classification technique was able to provide 72.71% accuracy.
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Affiliation(s)
- Afshin Shoeibi
- FPGA Lab, Faculty of Electrical Engineering, K. N. Toosi University of Technology, Tehran, Iran
| | - Navid Ghassemi
- Computer Engineering Department, Ferdowsi University of Mashhad, Mashhad, Iran
| | - Marjane Khodatars
- Department of Medical Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran
| | - Parisa Moridian
- Faculty of Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | - Abbas Khosravi
- Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Geelong, Australia
| | - Assef Zare
- Faculty of Electrical Engineering, Gonabad Branch, Islamic Azad University, Gonabad, Iran
| | - Juan M. Gorriz
- Department of Signal Theory, Networking and Communications, Universidad de Granada, Granada, Spain
| | | | - Ali Khadem
- Faculty of Electrical Engineering, K. N. Toosi University of Technology, Tehran, Iran
| | - U. Rajendra Acharya
- Ngee Ann Polytechnic, Singapore, 599489 Singapore
- Department of Biomedical Informatics and Medical Engineering, Asia University, Taichung, Taiwan
- Department of Biomedical Engineering, School of Science and Technology, Singapore University of Social Sciences, Singapore, Singapore
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Liu S, Zhong H, Qian Y, Cai H, Jia YB, Zhu J. Neural mechanism underlying the beneficial effect of Theory of Mind psychotherapy on early-onset schizophrenia: a randomized controlled trial. J Psychiatry Neurosci 2023; 48:E421-E430. [PMID: 37935475 PMCID: PMC10635708 DOI: 10.1503/jpn.230049] [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: 03/27/2023] [Revised: 06/03/2023] [Accepted: 08/14/2023] [Indexed: 11/09/2023] Open
Abstract
BACKGROUND Psychosocial interventions have emerged as an important component of a comprehensive therapeutic approach in early-onset schizophrenia, typically representing a more severe form of the disorder. Despite the feasibility and efficacy of Theory of Mind (ToM) psychotherapy for schizophrenia, relatively little is known regarding the neural mechanism underlying its effect on early-onset schizophrenia. METHODS We performed a randomized, active controlled trial in patients with early-onset schizophrenia, who were randomly allocated into either an intervention (ToM psychotherapy) or an active control (health education) group. Diffusion tensor imaging data were collected to construct brain structural networks, with both global and regional topological properties measured using graph theory. RESULTS We enrolled 28 patients with early-onset schizophrenia in our study. After 5 weeks of treatment, both the intervention and active control groups showed significant improvement in psychotic symptoms, yet the improvement was greater in the intervention group. Importantly, in contrast with no brain structural network change after treatment in the active control group, the intervention group showed increased nodal centrality of the left insula that was associated with psychotic symptom improvement. LIMITATIONS We did not collect important information concerning the participants' cognitive abilities, particularly ToM performance. CONCLUSION These findings suggest a potential neural mechanism by which ToM psychotherapy exerts a beneficial effect on early-onset schizophrenia via strengthening the coordination capacity of the insula in brain structural networks, which may provide a clinically translatable biomarker for monitoring or predicting responses to ToM psychotherapy.Clinical trial registration: NCT05577338; ClinicalTrials.gov.
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Affiliation(s)
- Siyu Liu
- From the Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China (Liu, Qian, Cai, Zhu); the Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China (Liu, Qian, Cai, Zhu); the Anhui Provincial Institute of Translational Medicine, Hefei, China (Liu, Qian, Cai, Zhu); the Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, China (Zhong, Jia); the Department of Child and Adolescent Psychology, Anhui Mental Health Center, Hefei, China (Zhong); and the Hefei Fourth People's Hospital, Hefei, China (Zhong)
| | - Hui Zhong
- From the Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China (Liu, Qian, Cai, Zhu); the Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China (Liu, Qian, Cai, Zhu); the Anhui Provincial Institute of Translational Medicine, Hefei, China (Liu, Qian, Cai, Zhu); the Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, China (Zhong, Jia); the Department of Child and Adolescent Psychology, Anhui Mental Health Center, Hefei, China (Zhong); and the Hefei Fourth People's Hospital, Hefei, China (Zhong)
| | - Yinfeng Qian
- From the Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China (Liu, Qian, Cai, Zhu); the Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China (Liu, Qian, Cai, Zhu); the Anhui Provincial Institute of Translational Medicine, Hefei, China (Liu, Qian, Cai, Zhu); the Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, China (Zhong, Jia); the Department of Child and Adolescent Psychology, Anhui Mental Health Center, Hefei, China (Zhong); and the Hefei Fourth People's Hospital, Hefei, China (Zhong)
| | - Huanhuan Cai
- From the Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China (Liu, Qian, Cai, Zhu); the Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China (Liu, Qian, Cai, Zhu); the Anhui Provincial Institute of Translational Medicine, Hefei, China (Liu, Qian, Cai, Zhu); the Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, China (Zhong, Jia); the Department of Child and Adolescent Psychology, Anhui Mental Health Center, Hefei, China (Zhong); and the Hefei Fourth People's Hospital, Hefei, China (Zhong)
| | - Yan-Bin Jia
- From the Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China (Liu, Qian, Cai, Zhu); the Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China (Liu, Qian, Cai, Zhu); the Anhui Provincial Institute of Translational Medicine, Hefei, China (Liu, Qian, Cai, Zhu); the Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, China (Zhong, Jia); the Department of Child and Adolescent Psychology, Anhui Mental Health Center, Hefei, China (Zhong); and the Hefei Fourth People's Hospital, Hefei, China (Zhong)
| | - Jiajia Zhu
- From the Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China (Liu, Qian, Cai, Zhu); the Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China (Liu, Qian, Cai, Zhu); the Anhui Provincial Institute of Translational Medicine, Hefei, China (Liu, Qian, Cai, Zhu); the Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, China (Zhong, Jia); the Department of Child and Adolescent Psychology, Anhui Mental Health Center, Hefei, China (Zhong); and the Hefei Fourth People's Hospital, Hefei, China (Zhong)
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5
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Fan YS, Xu Y, Bayrak Ş, Shine JM, Wan B, Li H, Li L, Yang S, Meng Y, Valk SL, Chen H. Macroscale Thalamic Functional Organization Disturbances and Underlying Core Cytoarchitecture in Early-Onset Schizophrenia. Schizophr Bull 2023; 49:1375-1386. [PMID: 37078906 PMCID: PMC10483446 DOI: 10.1093/schbul/sbad048] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/21/2023]
Abstract
BACKGROUND AND HYPOTHESIS Schizophrenia is a polygenetic mental disorder with heterogeneous positive and negative symptom constellations, and is associated with abnormal cortical connectivity. The thalamus has a coordinative role in cortical function and is key to the development of the cerebral cortex. Conversely, altered functional organization of the thalamus might relate to overarching cortical disruptions in schizophrenia, anchored in development. STUDY DESIGN Here, we contrasted resting-state fMRI in 86 antipsychotic-naive first-episode early-onset schizophrenia (EOS) patients and 91 typically developing controls to study whether macroscale thalamic organization is altered in EOS. Employing dimensional reduction techniques on thalamocortical functional connectome (FC), we derived lateral-medial and anterior-posterior thalamic functional axes. STUDY RESULTS We observed increased segregation of macroscale thalamic functional organization in EOS patients, which was related to altered thalamocortical interactions both in unimodal and transmodal networks. Using an ex vivo approximation of core-matrix cell distribution, we found that core cells particularly underlie the macroscale abnormalities in EOS patients. Moreover, the disruptions were associated with schizophrenia-related gene expression maps. Behavioral and disorder decoding analyses indicated that the macroscale hierarchy disturbances might perturb both perceptual and abstract cognitive functions and contribute to negative syndromes in patients. CONCLUSIONS These findings provide mechanistic evidence for disrupted thalamocortical system in schizophrenia, suggesting a unitary pathophysiological framework.
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Affiliation(s)
- Yun-Shuang Fan
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Yong Xu
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China
| | - Şeyma Bayrak
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - James M Shine
- Brain and Mind Center, The University of Sydney, Sydney, Australia
| | - Bin Wan
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behavior), Research Centre Jülich, Jülich, Germany
- International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity (IMPRS NeuroCom), Leipzig, Germany
| | - Haoru Li
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Liang Li
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Siqi Yang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yao Meng
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Sofie L Valk
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behavior), Research Centre Jülich, Jülich, Germany
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
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6
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Perini F, Nazimek JM, Mckie S, Capitão LP, Scaife J, Pal D, Browning M, Dawson GR, Nishikawa H, Campbell U, Hopkins SC, Loebel A, Elliott R, Harmer CJ, Deakin B, Koblan KS. Effects of ulotaront on brain circuits of reward, working memory, and emotion processing in healthy volunteers with high or low schizotypy. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2023; 9:49. [PMID: 37550314 PMCID: PMC10406926 DOI: 10.1038/s41537-023-00385-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 07/27/2023] [Indexed: 08/09/2023]
Abstract
Ulotaront, a trace amine-associated receptor 1 (TAAR1) and serotonin 5-HT1A receptor agonist without antagonist activity at dopamine D2 or the serotonin 5-HT2A receptors, has demonstrated efficacy in the treatment of schizophrenia. Here we report the phase 1 translational studies that profiled the effect of ulotaront on brain responses to reward, working memory, and resting state connectivity (RSC) in individuals with low or high schizotypy (LS or HS). Participants were randomized to placebo (n = 32), ulotaront (50 mg; n = 30), or the D2 receptor antagonist amisulpride (400 mg; n = 34) 2 h prior to functional magnetic resonance imaging (fMRI) of blood oxygen level-dependent (BOLD) responses to task performance. Ulotaront increased subjective drowsiness, but reaction times were impaired by less than 10% and did not correlate with BOLD responses. In the Monetary Incentive Delay task (reward processing), ulotaront significantly modulated striatal responses to incentive cues, induced medial orbitofrontal responses, and prevented insula activation seen in HS subjects. In the N-Back working memory task, ulotaront modulated BOLD signals in brain regions associated with cognitive impairment in schizophrenia. Ulotaront did not show antidepressant-like biases in an emotion processing task. HS had significantly reduced connectivity in default, salience, and executive networks compared to LS participants and both drugs reduced this difference. Although performance impairment may have weakened or contributed to the fMRI findings, the profile of ulotaront on BOLD activations elicited by reward, memory, and resting state is compatible with an indirect modulation of dopaminergic function as indicated by preclinical studies. This phase 1 study supported the subsequent clinical proof of concept trial in people with schizophrenia.Clinical trial registration: Registry# and URL: ClinicalTrials.gov NCT01972711, https://clinicaltrials.gov/ct2/show/NCT01972711.
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Affiliation(s)
- Francesca Perini
- Faculty of Biology, Medicine and Health, Division of Neuroscience and Experimental Psychology, School of Biological Sciences, University of Manchester, Manchester Academic Health Science Centre, Manchester, M13 9PT, UK
| | - Jadwiga Maria Nazimek
- Faculty of Biology, Medicine and Health, Division of Neuroscience and Experimental Psychology, School of Biological Sciences, University of Manchester, Manchester Academic Health Science Centre, Manchester, M13 9PT, UK
| | - Shane Mckie
- Faculty of Biology, Medicine and Health, Division of Neuroscience and Experimental Psychology, School of Biological Sciences, University of Manchester, Manchester Academic Health Science Centre, Manchester, M13 9PT, UK
| | - Liliana P Capitão
- University Department of Psychiatry, University of Oxford and Oxford Health NHS Foundation Trust, Warneford Hospital, Warneford Lane, Oxford, OX3 7JX, UK
| | - Jessica Scaife
- University Department of Psychiatry, University of Oxford and Oxford Health NHS Foundation Trust, Warneford Hospital, Warneford Lane, Oxford, OX3 7JX, UK
| | - Deepa Pal
- University Department of Psychiatry, University of Oxford and Oxford Health NHS Foundation Trust, Warneford Hospital, Warneford Lane, Oxford, OX3 7JX, UK
| | - Michael Browning
- University Department of Psychiatry, University of Oxford and Oxford Health NHS Foundation Trust, Warneford Hospital, Warneford Lane, Oxford, OX3 7JX, UK
- P1vital LTD, Manor House, Howbery Business Park, Wallingford, OX10 8BA, UK
| | - Gerard R Dawson
- P1vital LTD, Manor House, Howbery Business Park, Wallingford, OX10 8BA, UK
| | - Hiroyuki Nishikawa
- Sunovion Pharmaceuticals Inc., 84 Waterford Drive, Marlborough, MA, 01752, USA
| | - Una Campbell
- Sunovion Pharmaceuticals Inc., 84 Waterford Drive, Marlborough, MA, 01752, USA
| | - Seth C Hopkins
- Sunovion Pharmaceuticals Inc., 84 Waterford Drive, Marlborough, MA, 01752, USA.
| | - Antony Loebel
- Sunovion Pharmaceuticals Inc., 84 Waterford Drive, Marlborough, MA, 01752, USA
| | - Rebecca Elliott
- Faculty of Biology, Medicine and Health, Division of Neuroscience and Experimental Psychology, School of Biological Sciences, University of Manchester, Manchester Academic Health Science Centre, Manchester, M13 9PT, UK
| | - Catherine J Harmer
- University Department of Psychiatry, University of Oxford and Oxford Health NHS Foundation Trust, Warneford Hospital, Warneford Lane, Oxford, OX3 7JX, UK
| | - Bill Deakin
- Faculty of Biology, Medicine and Health, Division of Neuroscience and Experimental Psychology, School of Biological Sciences, University of Manchester, Manchester Academic Health Science Centre, Manchester, M13 9PT, UK
| | - Kenneth S Koblan
- Sunovion Pharmaceuticals Inc., 84 Waterford Drive, Marlborough, MA, 01752, USA
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7
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Wong SMY, Chen EYH, Lee MCY, Suen YN, Hui CLM. Rumination as a Transdiagnostic Phenomenon in the 21st Century: The Flow Model of Rumination. Brain Sci 2023; 13:1041. [PMID: 37508974 PMCID: PMC10377138 DOI: 10.3390/brainsci13071041] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 06/15/2023] [Accepted: 07/06/2023] [Indexed: 07/30/2023] Open
Abstract
Rumination and its related mental phenomena share associated impairments in cognition, such as executive functions and attentional processes across different clinical conditions (e.g., in psychotic disorders). In recent decades, however, the notion of rumination has been increasingly narrowed to the "self-focused" type in depressive disorders. A closer review of the literature shows that rumination may be construed as a broader process characterized by repetitive thoughts about certain mental contents that interfere with one's daily activities, not only limited to those related to "self". A further examination of the construct of rumination beyond the narrowly focused depressive rumination would help expand intervention opportunities for mental disorders in today's context. We first review the development of the clinical construct of rumination with regard to its historical roots and its roles in psychopathology. This builds the foundation for the introduction of the "Flow Model of Rumination (FMR)", which conceptualizes rumination as a disruption of a smooth flow of mental contents in conscious experience that depends on the coordinated interactions between intention, memory, affect, and external events. The conceptual review concludes with a discussion of the impact of rapid technological advances (such as smartphones) on rumination. Particularly in contemporary societies today, a broader consideration of rumination not only from a cognition viewpoint, but also incorporating a human-device interaction perspective, is necessitated. The implications of the FMR in contemporary mental health practice are discussed.
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Affiliation(s)
- Stephanie M Y Wong
- Department of Psychiatry, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong
| | - Eric Y H Chen
- Department of Psychiatry, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong
- The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong
| | - Michelle C Y Lee
- Department of Psychiatry, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong
| | - Y N Suen
- Department of Psychiatry, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong
| | - Christy L M Hui
- Department of Psychiatry, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong
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Sodré ME, Wießner I, Irfan M, Schenck CH, Mota-Rolim SA. Awake or Sleeping? Maybe Both… A Review of Sleep-Related Dissociative States. J Clin Med 2023; 12:3876. [PMID: 37373570 DOI: 10.3390/jcm12123876] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 05/04/2023] [Accepted: 05/05/2023] [Indexed: 06/29/2023] Open
Abstract
Recent studies have begun to understand sleep not only as a whole-brain process but also as a complex local phenomenon controlled by specific neurotransmitters that act in different neural networks, which is called "local sleep". Moreover, the basic states of human consciousness-wakefulness, sleep onset (N1), light sleep (N2), deep sleep (N3), and rapid eye movement (REM) sleep-can concurrently appear, which may result in different sleep-related dissociative states. In this article, we classify these sleep-related dissociative states into physiological, pathological, and altered states of consciousness. Physiological states are daydreaming, lucid dreaming, and false awakenings. Pathological states include sleep paralysis, sleepwalking, and REM sleep behavior disorder. Altered states are hypnosis, anesthesia, and psychedelics. We review the neurophysiology and phenomenology of these sleep-related dissociative states of consciousness and update them with recent studies. We conclude that these sleep-related dissociative states have a significant basic and clinical impact since their study contributes to the understanding of consciousness and the proper treatment of neuropsychiatric diseases.
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Affiliation(s)
| | - Isabel Wießner
- Brain Institute, Federal University of Rio Grande do Norte, Natal 59078-970, RN, Brazil
| | - Muna Irfan
- Department of Neurology, University of Minnesota, Minneapolis, MN 55455, USA
| | - Carlos H Schenck
- Department of Neurology, University of Minnesota, Minneapolis, MN 55455, USA
| | - Sergio A Mota-Rolim
- Brain Institute, Federal University of Rio Grande do Norte, Natal 59078-970, RN, Brazil
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Immediate modulatory effects of transcutaneous auricular vagus nerve stimulation on the resting state of major depressive disorder. J Affect Disord 2023; 325:513-521. [PMID: 36642310 DOI: 10.1016/j.jad.2023.01.035] [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: 08/16/2022] [Revised: 12/13/2022] [Accepted: 01/08/2023] [Indexed: 01/15/2023]
Abstract
BACKGROUND Previous studies have found that transcutaneous auricular vagus nerve stimulation (taVNS) is clinically effective in the treatment of major depressive disorder (MDD), and its efficacy mechanism is related to modulation of the default mode network (DMN) and cognitive control network (CCN). However, the mechanism of the immediate effect of taVNS for MDD remains to be elucidated. METHODS A total of 58 patients with MDD and 54 healthy controls(HCs) were included in this study. The MDD group was treated with taVNS for 30 min (20 Hz, 4-6 mA) immediately, and we observed amplitude of low-frequency fluctuations (ALFF) abnormalities in the MDD group and changes in ALFF and functional connectivity (FC) before and after immediate treatment. The ALFF brain regions altered by taVNS induction were used as regions of interest to analyze whole-brain FC changes in the MDD group. RESULTS After taVNS treatment, ALFF in the right precuneus was decreased in the MDD group. The FC of the right precuneus with the left middle frontal gyrus, the left posterior cingulate gyrus and the left angular gyrus were decreased in the MDD group. Correlation analysis showed that the FC values between the right precuneus and the left posterior cingulate gyrus in the pre-treatment MDD group was negatively correlated with the 17-item Hamilton depression rating scale scores. CONCLUSION TaVNS has an immediate modulatory effect on DMN and CCN. It would be proposed that these functional networks may be effective targets for the long-term treatment of MDD patients with taVNS.
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Kong M, Chen T, Gao S, Ni S, Ming Y, Chai X, Ling C, Xu X. Abnormal network homogeneity of default-mode network and its relationships with clinical symptoms in antipsychotic-naïve first-diagnosis schizophrenia. Front Neurosci 2022; 16:921547. [PMID: 35968384 PMCID: PMC9369006 DOI: 10.3389/fnins.2022.921547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2022] [Accepted: 07/06/2022] [Indexed: 11/17/2022] Open
Abstract
Schizophrenia is a severe mental disorder affecting around 0.5–1% of the global population. A few studies have shown the functional disconnection in the default-mode network (DMN) of schizophrenia patients. However, the findings remain discrepant. In the current study, we compared the intrinsic network organization of DMN of 57 first-diagnosis drug-naïve schizophrenia patients with 50 healthy controls (HCs) using a homogeneity network (NH) and explored the relationships of DMN with clinical characteristics of schizophrenia patients. Receiver operating characteristic (ROC) curves analysis and support vector machine (SVM) analysis were applied to calculate the accuracy of distinguishing schizophrenia patients from HCs. Our results showed that the NH values of patients were significantly higher in the left superior medial frontal gyrus (SMFG) and right cerebellum Crus I/Crus II and significantly lower in the right inferior temporal gyrus (ITG) and bilateral posterior cingulate cortex (PCC) compared to those of HCs. Additionally, negative correlations were shown between aberrant NH values in the right cerebellum Crus I/Crus II and general psychopathology scores, between NH values in the left SMFG and negative symptom scores, and between the NH values in the right ITG and speed of processing. Also, patients’ age and the NH values in the right cerebellum Crus I/Crus II and the right ITG were the predictors of performance in the social cognition test. ROC curves analysis and SVM analysis showed that a combination of NH values in the left SMFG, right ITG, and right cerebellum Crus I/Crus II could distinguish schizophrenia patients from HCs with high accuracy. The results emphasized the vital role of DMN in the neuropathological mechanisms underlying schizophrenia.
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Affiliation(s)
- Mingjun Kong
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing, China
| | - Tian Chen
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing, China
| | - Shuzhan Gao
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing, China
| | - Sulin Ni
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing, China
| | - Yidan Ming
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing, China
| | - Xintong Chai
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing, China
| | - Chenxi Ling
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing, China
| | - Xijia Xu
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing, China
- Department of Psychiatry, Nanjing Brain Hospital, Medical School, Nanjing University, Nanjing, China
- *Correspondence: Xijia Xu,
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