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Xiao S, Yang Z, Lin Z, Chen L, Liao W, Wang J, Gao C, Lu J, Song Y, Su S, Jiang G. Spontaneous Brain Activity Abnormalities in Patients With Temporal Lobe Epilepsy: A Meta-Analysis of 1474 Patients. J Magn Reson Imaging 2024. [PMID: 39215606 DOI: 10.1002/jmri.29568] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Revised: 07/31/2024] [Accepted: 08/01/2024] [Indexed: 09/04/2024] Open
Abstract
BACKGROUND Abnormalities in resting-state functional brain activity have been detected in patients with temporal lobe epilepsy (TLE). The results of individual neuroimaging studies of TLE, however, are frequently inconsistent due to small and heterogeneous samples, analytical flexibility, and publication bias toward positive findings. PURPOSE To investigate the most consistent regions of resting-state functional brain activity abnormality in patients with TLE through a quantitative meta-analysis of published neuroimaging data. STUDY TYPE Meta-analysis. SUBJECTS Exactly 1474 TLE patients (716 males and 758 females) from 31 studies on resting-state functional brain activity were included in this study. FIELD STRENGTH/SEQUENCE Studies utilizing 1.5 T or 3 T MR scanners were included for meta-analysis. Resting-state functional MRI using gradient echo-planar imaging, T1-weighted imaging. ASSESSMENT PubMed, Web of Science, Chinese National Knowledge Infrastructure, and WanFang databases were searched to identify studies investigating amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo) at the whole-brain level between patients with TLE and healthy controls (HCs). STATISTICAL TESTS Seed-based d Mapping with Permutation of Subject Images, standard randomization tests and meta-regression analysis were used. Results were significant if P < 0.05 with family-wise error corrected. RESULTS Patients with TLE displayed resting-state functional brain activity which was a significant increase in the right hippocampus, and significant decrease in the right angular gurus and right precuneus. Additionally, the meta-regression analysis demonstrated that age (P = 0.231), sex distribution (P = 0.376), and illness duration (P = 0.184), did not show significant associations with resting state functional brain activity in patients with TLE. DATA CONCLUSION Common alteration patterns of spontaneous brain activity were identified in the right hippocampus and default-model network regions in patients with TLE. These findings may contribute to understanding of the underlying mechanism for potentially effective intervention of TLE. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE Stage 2.
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Affiliation(s)
- Shu Xiao
- Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
- Department of Radiology, Xiamen Humanity Hospital Fujian Medical University, Xiamen, China
| | - Zibin Yang
- Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
| | - Zitao Lin
- Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
| | - Liqing Chen
- Department of Catheter Intervention, Maoming Maonan District People's Hospital, Maoming, China
| | - Weiming Liao
- Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
| | - Jurong Wang
- Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
| | - Cuihua Gao
- Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
| | - Jianjun Lu
- Department of Neurosurgery, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Yang Song
- Siemens Healthineers Ltd, Shanghai, China
| | - Sulian Su
- Department of Radiology, Xiamen Humanity Hospital Fujian Medical University, Xiamen, China
| | - Guihua Jiang
- Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
- Department of Radiology, Xiamen Humanity Hospital Fujian Medical University, Xiamen, China
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Costa C, Pezzetta R, Masina F, Lago S, Gastaldon S, Frangi C, Genon S, Arcara G, Scarpazza C. Comprehensive investigation of predictive processing: A cross- and within-cognitive domains fMRI meta-analytic approach. Hum Brain Mapp 2024; 45:e26817. [PMID: 39169641 PMCID: PMC11339134 DOI: 10.1002/hbm.26817] [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: 02/21/2024] [Revised: 07/15/2024] [Accepted: 07/30/2024] [Indexed: 08/23/2024] Open
Abstract
Predictive processing (PP) stands as a predominant theoretical framework in neuroscience. While some efforts have been made to frame PP within a cognitive domain-general network perspective, suggesting the existence of a "prediction network," these studies have primarily focused on specific cognitive domains or functions. The question of whether a domain-general predictive network that encompasses all well-established cognitive domains exists remains unanswered. The present meta-analysis aims to address this gap by testing the hypothesis that PP relies on a large-scale network spanning across cognitive domains, supporting PP as a unified account toward a more integrated approach to neuroscience. The Activation Likelihood Estimation meta-analytic approach was employed, along with Meta-Analytic Connectivity Mapping, conjunction analysis, and behavioral decoding techniques. The analyses focused on prediction incongruency and prediction congruency, two conditions likely reflective of core phenomena of PP. Additionally, the analysis focused on a prediction phenomena-independent dimension, regardless of prediction incongruency and congruency. These analyses were first applied to each cognitive domain considered (cognitive control, attention, motor, language, social cognition). Then, all cognitive domains were collapsed into a single, cross-domain dimension, encompassing a total of 252 experiments. Results pertaining to prediction incongruency rely on a defined network across cognitive domains, while prediction congruency results exhibited less overall activation and slightly more variability across cognitive domains. The converging patterns of activation across prediction phenomena and cognitive domains highlight the role of several brain hubs unfolding within an organized large-scale network (Dynamic Prediction Network), mainly encompassing bilateral insula, frontal gyri, claustrum, parietal lobules, and temporal gyri. Additionally, the crucial role played at a cross-domain, multimodal level by the anterior insula, as evidenced by the conjunction and Meta-Analytic Connectivity Mapping analyses, places it as the major hub of the Dynamic Prediction Network. Results support the hypothesis that PP relies on a domain-general, large-scale network within whose regions PP units are likely to operate, depending on the context and environmental demands. The wide array of regions within the Dynamic Prediction Network seamlessly integrate context- and stimulus-dependent predictive computations, thereby contributing to the adaptive updating of the brain's models of the inner and external world.
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Affiliation(s)
| | | | | | - Sara Lago
- Padova Neuroscience CenterPaduaItaly
- IRCCS Ospedale San CamilloVeniceItaly
| | - Simone Gastaldon
- Padova Neuroscience CenterPaduaItaly
- Dipartimento di Psicologia dello Sviluppo e della SocializzazioneUniversità degli Studi di PadovaPaduaItaly
| | - Camilla Frangi
- Dipartimento di Psicologia GeneraleUniversità degli Studi di PadovaPaduaItaly
| | - Sarah Genon
- Institute for Systems NeuroscienceHeinrich Heine University DüsseldorfDüsseldorfGermany
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM‐7)Research Centre JülichJülichGermany
| | | | - Cristina Scarpazza
- IRCCS Ospedale San CamilloVeniceItaly
- Dipartimento di Psicologia GeneraleUniversità degli Studi di PadovaPaduaItaly
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Yu Y, Lobo RP, Riedel MC, Bottenhorn K, Laird AR, Nichols TE. Neuroimaging meta regression for coordinate based meta analysis data with a spatial model. Biostatistics 2024:kxae024. [PMID: 39002146 DOI: 10.1093/biostatistics/kxae024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 06/09/2024] [Accepted: 06/10/2024] [Indexed: 07/15/2024] Open
Abstract
Coordinate-based meta-analysis combines evidence from a collection of neuroimaging studies to estimate brain activation. In such analyses, a key practical challenge is to find a computationally efficient approach with good statistical interpretability to model the locations of activation foci. In this article, we propose a generative coordinate-based meta-regression (CBMR) framework to approximate a smooth activation intensity function and investigate the effect of study-level covariates (e.g. year of publication, sample size). We employ a spline parameterization to model the spatial structure of brain activation and consider four stochastic models for modeling the random variation in foci. To examine the validity of CBMR, we estimate brain activation on 20 meta-analytic datasets, conduct spatial homogeneity tests at the voxel level, and compare the results to those generated by existing kernel-based and model-based approaches. Keywords: generalized linear models; meta-analysis; spatial statistics; statistical modeling.
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Affiliation(s)
- Yifan Yu
- Oxford Big Data Institute, University of Oxford, Old road campus, Oxford, OX3 7LF, United Kingdom
| | - Rosario Pintos Lobo
- Department of Psychology, Florida International University, Miami, FL, 33199, United States
| | - Michael Cody Riedel
- Department of Physics, Florida International University, Miami, FL, 33199, United States
| | - Katherine Bottenhorn
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, 90032, United States
| | - Angela R Laird
- Center for Imaging Science, Florida International University, Miami, FL, 33199, United States
| | - Thomas E Nichols
- Oxford Big Data Institute, University of Oxford, Old road campus, Oxford, OX3 7LF, United Kingdom
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, Oxford, OX3 9DU, United Kingdom
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Boch M, Huber L, Lamm C. Domestic dogs as a comparative model for social neuroscience: Advances and challenges. Neurosci Biobehav Rev 2024; 162:105700. [PMID: 38710423 PMCID: PMC7616343 DOI: 10.1016/j.neubiorev.2024.105700] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 03/19/2024] [Accepted: 04/30/2024] [Indexed: 05/08/2024]
Abstract
Dogs and humans have lived together for thousands of years and share many analogous socio-cognitive skills. Dog neuroimaging now provides insight into the neural bases of these shared social abilities. Here, we summarize key findings from dog fMRI identifying neocortical brain areas implicated in visual social cognition, such as face, body, and emotion perception, as well as action observation in dogs. These findings provide converging evidence that the temporal cortex plays a significant role in visual social cognition in dogs. We further briefly review investigations into the neural base of the dog-human relationship, mainly involving limbic brain regions. We then discuss current challenges in the field, such as statistical power and lack of common template spaces, and how to overcome them. Finally, we argue that the foundation has now been built to investigate and compare the neural bases of more complex socio-cognitive phenomena shared by dogs and humans. This will strengthen and expand the role of the domestic dog as a powerful comparative model species and provide novel insights into the evolutionary roots of social cognition.
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Affiliation(s)
- Magdalena Boch
- Social, Cognitive and Affective Neuroscience Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna 1010, Austria; Department of Cognitive Biology, Faculty of Life Sciences, University of Vienna, Vienna 1090, Austria.
| | - Ludwig Huber
- Comparative Cognition, Messerli Research Institute, University of Veterinary Medicine Vienna, Medical University of Vienna and University of Vienna, Vienna 1210, Austria
| | - Claus Lamm
- Social, Cognitive and Affective Neuroscience Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna 1010, Austria; Vienna Cognitive Science Hub, University of Vienna, Vienna 1010, Austria
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5
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Costa T, Ferraro M, Manuello J, Camasio A, Nani A, Mancuso L, Cauda F, Fox PT, Liloia D. Activation Likelihood Estimation Neuroimaging Meta-Analysis: a Powerful Tool for Emotion Research. Psychol Res Behav Manag 2024; 17:2331-2345. [PMID: 38882233 PMCID: PMC11179639 DOI: 10.2147/prbm.s453035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 05/31/2024] [Indexed: 06/18/2024] Open
Abstract
Over the past two decades, functional magnetic resonance imaging (fMRI) has become the primary tool for exploring neural correlates of emotion. To enhance the reliability of results in understanding the complex nature of emotional experiences, researchers combine findings from multiple fMRI studies using coordinate-based meta-analysis (CBMA). As one of the most widely employed CBMA methods worldwide, activation likelihood estimation (ALE) is of great importance in affective neuroscience and neuropsychology. This comprehensive review provides an introductory guide for implementing the ALE method in emotion research, outlining the experimental steps involved. By presenting a case study about the emotion of disgust, with regard to both its core and social processing, we offer insightful commentary as to how ALE can enable researchers to produce consistent results and, consequently, fruitfully investigate the neural mechanisms underpinning emotions, facilitating further progress in this field.
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Affiliation(s)
- Tommaso Costa
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
- FOCUS Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Mario Ferraro
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
- FOCUS Laboratory, Department of Psychology, University of Turin, Turin, Italy
- Department of Physics, University of Turin, Turin, Italy
| | - Jordi Manuello
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
- FOCUS Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Alessia Camasio
- FOCUS Laboratory, Department of Psychology, University of Turin, Turin, Italy
- Department of Physics, University of Turin, Turin, Italy
| | - Andrea Nani
- FOCUS Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Lorenzo Mancuso
- FOCUS Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Franco Cauda
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
- FOCUS Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Donato Liloia
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
- FOCUS Laboratory, Department of Psychology, University of Turin, Turin, Italy
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Ou CH, Cheng CS, Lin PL, Lee CL. Grey matter alterations in generalized anxiety disorder: A voxel-wise meta-analysis of voxel-based morphometry studies. Int J Dev Neurosci 2024; 84:281-292. [PMID: 38638086 DOI: 10.1002/jdn.10330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 03/09/2024] [Accepted: 03/26/2024] [Indexed: 04/20/2024] Open
Abstract
OBJECTIVE Grey matter, a crucial component of the brain, has been found altered in generalized anxiety disorder (GAD) of several voxel-based morphometry studies. The conclusive and consistent grey matter alterations in GAD have not been confirmed. METHOD Eleven voxel-based morphometry studies of GAD patients were included in the current systematic review and meta-analysis. The linear model of anxiety severity scores was applied to explore the relationship of grey matter alterations and anxiety severity. The subgroup analysis of adult GAD and adolescent GAD was also performed. RESULTS Significantly modest grey matter alterations in the left superior temporal gyrus of patients with GAD were found. The anxiety severity score was significantly correlated with grey matter alterations in the right insula, lenticular nucleus, putamen and striatum. The subgroup analysis of adult GAD and adolescent GAD all failed to show significant grey matter alterations. However, in the adult GAD subgroup, anxiety severity score was significantly correlated with grey matter alterations in the right insula. CONCLUSION GAD might have the modest grey matter alterations in the left superior temporal gyrus. Anxiety severity might be related to the grey matter alterations in the limbic regions, such as the right insula, lenticular nucleus, putamen and striatum. This kind of correlation might be related to the effects of adult GAD. Future studies with adequate sample sizes and sophisticated GAD categories will be needed.
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Affiliation(s)
- Chang-Hsien Ou
- Department of Neuroradiology, E-Da Hospital, I-Shou University, Kaohsiung, Taiwan
| | - Chiu-Shih Cheng
- Department of Neuroradiology, E-Da Hospital, I-Shou University, Kaohsiung, Taiwan
| | - Pei-Ling Lin
- Department of Neuroradiology, E-Da Hospital, I-Shou University, Kaohsiung, Taiwan
| | - Cheng-Lung Lee
- Department of Neuroradiology, E-Da Hospital, I-Shou University, Kaohsiung, Taiwan
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7
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Chen P, Wang J, Tang G, Chen G, Xiao S, Guo Z, Qi Z, Wang J, Wang Y. Large-scale network abnormality in behavioral addiction. J Affect Disord 2024; 354:743-751. [PMID: 38521138 DOI: 10.1016/j.jad.2024.03.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 03/01/2024] [Accepted: 03/09/2024] [Indexed: 03/25/2024]
Abstract
BACKGROUND Researchers have endeavored to ascertain the network dysfunction associated with behavioral addiction (BA) through the utilization of resting-state functional connectivity (rsFC). Nevertheless, the identification of aberrant patterns within large-scale networks pertaining to BA has proven to be challenging. METHODS Whole-brain seed-based rsFC studies comparing subjects with BA and healthy controls (HC) were collected from multiple databases. Multilevel kernel density analysis was employed to ascertain brain networks in which BA was linked to hyper-connectivity or hypo-connectivity with each prior network. RESULTS Fifty-six seed-based rsFC publications (1755 individuals with BA and 1828 HC) were included in the meta-analysis. The present study indicate that individuals with BAs exhibit (1) hypo-connectivity within the fronto-parietal network (FN) and hypo- and hyper-connectivity within the ventral attention network (VAN); (2) hypo-connectivity between the FN and regions of the VAN, hypo-connectivity between the VAN and regions of the FN and default mode network (DMN), hyper-connectivity between the DMN and regions of the FN; (3) hypo-connectivity between the reward system and regions of the sensorimotor network (SS), DMN and VAN; (4) hypo-connectivity between the FN and regions of the SS, hyper-connectivity between the VAN and regions of the SS. CONCLUSIONS These findings provide impetus for a conceptual framework positing a model of BA characterized by disconnected functional coordination among large-scale networks.
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Affiliation(s)
- Pan Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Junjing Wang
- Department of Applied Psychology, Guangdong University of Foreign Studies, Guangzhou 510006, China
| | - Guixian Tang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Guanmao Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Shu Xiao
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Zixuan Guo
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Zhangzhang Qi
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Jurong Wang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Ying Wang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China.
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8
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Liu H, Hao Z, Qiu S, Wang Q, Zhan L, Huang L, Shao Y, Wang Q, Su C, Cao Y, Sun J, Wang C, Lv Y, Li M, Shen W, Li H, Jia X. Grey matter structural alterations in anxiety disorders: a voxel-based meta-analysis. Brain Imaging Behav 2024; 18:456-474. [PMID: 38150133 DOI: 10.1007/s11682-023-00842-x] [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] [Accepted: 12/07/2023] [Indexed: 12/28/2023]
Abstract
Anxiety disorders (ADs) are a group of prevalent and destructive mental illnesses, but the current understanding of their underlying neuropathology is still unclear. Employing voxel-based morphometry (VBM), previous studies have demonstrated several common brain regions showing grey matter volume (GMV) abnormalities. However, contradictory results have been reported among these studies. Considering that different subtypes of ADs exhibit common core symptoms despite different diagnostic criteria, and previous meta-analyses have found common core GMV-altered brain regions in ADs, the present research aimed to combine the results of individual studies to identify common GMV abnormalities in ADs. Therefore, we first performed a systematic search in PubMed, Embase, and Web of Science on studies investigating GMV differences between patients with ADs and healthy controls (HCs). Then, the anisotropic effect-size signed differential mapping (AES-SDM) was applied in this meta-analysis. A total of 24 studies (including 25 data sets) were included in the current study, and 906 patients with ADs and 1003 HCs were included. Compared with the HCs, the patients with ADs showed increased GMV in the left superior parietal gyrus, right angular gyrus, left precentral gyrus, and right lingual gyrus, and decreased GMV in the bilateral insula, bilateral thalamus, left caudate, and right putamen. In conclusion, the current study has identified some abnormal GMV brain regions that are related to the pathological mechanisms of anxiety disorders. These findings could contribute to a better understanding of the underlying neuropathology of ADs.
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Affiliation(s)
- Han Liu
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China
| | - Zeqi Hao
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China
| | - Shasha Qiu
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China
| | - Qianqian Wang
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China
| | - Linlin Zhan
- School of Western Languages, Heilongjiang University, Heilongjiang, China
| | - Lina Huang
- Department of Radiology, Changshu No.2 People's Hospital, The Affiliated Changshu Hospital of Xuzhou Medical University, Changshu, Jiangsu, China
| | - Youbin Shao
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China
| | - Qing Wang
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian, China
| | - Chang Su
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China
| | - Yikang Cao
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Jiawei Sun
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Chunjie Wang
- Institute of Brain Science, Department of Psychology, School of Education, Hangzhou Normal University, Hangzhou, China
- Center for Cognition and Brain Disorders, the Affiliated Hospital, Hangzhou Normal University, Hangzhou, China
| | - Yating Lv
- Center for Cognition and Brain Disorders, the Affiliated Hospital, Hangzhou Normal University, Hangzhou, China
| | - Mengting Li
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China
| | - Wenbin Shen
- Department of Radiology, Changshu No.2 People's Hospital, The Affiliated Changshu Hospital of Xuzhou Medical University, Changshu, Jiangsu, China
| | - Huayun Li
- School of Psychology, Zhejiang Normal University, Jinhua, China.
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China.
| | - Xize Jia
- School of Psychology, Zhejiang Normal University, Jinhua, China.
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China.
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Cai M, Ji Y, Zhao Q, Xue H, Sun Z, Wang H, Zhang Y, Chen Y, Zhao Y, Zhang Y, Lei M, Wang C, Zhuo C, Liu N, Liu H, Liu F. Homotopic functional connectivity disruptions in schizophrenia and their associated gene expression. Neuroimage 2024; 289:120551. [PMID: 38382862 DOI: 10.1016/j.neuroimage.2024.120551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 02/18/2024] [Accepted: 02/19/2024] [Indexed: 02/23/2024] Open
Abstract
It has been revealed that abnormal voxel-mirrored homotopic connectivity (VMHC) is present in patients with schizophrenia, yet there are inconsistencies in the relevant findings. Moreover, little is known about their association with brain gene expression profiles. In this study, transcription-neuroimaging association analyses using gene expression data from Allen Human Brain Atlas and case-control VMHC differences from both the discovery (meta-analysis, including 9 studies with a total of 386 patients and 357 controls) and replication (separate group-level comparisons within two datasets, including a total of 258 patients and 287 controls) phases were performed to identify genes associated with VMHC alterations. Enrichment analyses were conducted to characterize the biological functions and specific expression of identified genes, and Neurosynth decoding analysis was performed to examine the correlation between cognitive-related processes and VMHC alterations in schizophrenia. In the discovery and replication phases, patients with schizophrenia exhibited consistent VMHC changes compared to controls, which were correlated with a series of cognitive-related processes; meta-regression analysis revealed that illness duration was negatively correlated with VMHC abnormalities in the cerebellum and postcentral/precentral gyrus. The abnormal VMHC patterns were stably correlated with 1287 genes enriched for fundamental biological processes like regulation of cell communication, nervous system development, and cell communication. In addition, these genes were overexpressed in astrocytes and immune cells, enriched in extensive cortical regions and wide developmental time windows. The present findings may contribute to a more comprehensive understanding of the molecular mechanisms underlying VMHC alterations in patients with schizophrenia.
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Affiliation(s)
- Mengjing Cai
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yuan Ji
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Qiyu Zhao
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Hui Xue
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Zuhao Sun
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - He Wang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yijing Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yayuan Chen
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yao Zhao
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yujie Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Minghuan Lei
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Chunyang Wang
- Department of Scientific Research, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Chuanjun Zhuo
- Laboratory of Psychiatric-Neuroimaging-Genetic and Co-morbidity (PGNP_Lab), Tianjin Anding Hospital, Nankai University Affiliated Tianjin Anding Hospital, Tianjin Mental Health Center of Tianjin Medical University, Tianjin, 300222, China
| | - Nana Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China.
| | - Huaigui Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China.
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China.
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10
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Fiorito AM, Blasi G, Brunelin J, Chowdury A, Diwadkar VA, Goghari VM, Gur RC, Kwon JS, Quarto T, Rolland B, Spilka MJ, Wolf DH, Yun JY, Fakra E, Sescousse G. Blunted brain responses to neutral faces in healthy first-degree relatives of patients with schizophrenia: an image-based fMRI meta-analysis. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2024; 10:38. [PMID: 38503766 PMCID: PMC10951276 DOI: 10.1038/s41537-024-00452-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Accepted: 02/16/2024] [Indexed: 03/21/2024]
Abstract
Schizophrenia is characterized by the misattribution of emotional significance to neutral faces, accompanied by overactivations of the limbic system. To understand the disorder's genetic and environmental contributors, investigating healthy first-degree relatives is crucial. However, inconsistent findings exist regarding their ability to recognize neutral faces, with limited research exploring the cerebral correlates of neutral face processing in this population. Thus, we here investigated brain responses to neutral face processing in healthy first-degree relatives through an image-based meta-analysis of functional magnetic resonance imaging studies. We included unthresholded group-level T-maps from 5 studies comprising a total of 120 first-degree relatives and 150 healthy controls. In sensitivity analyses, we ran a combined image- and coordinate-based meta-analysis including 7 studies (157 first-degree relatives, 207 healthy controls) aiming at testing the robustness of the results in a larger sample of studies. Our findings revealed a pattern of decreased brain responses to neutral faces in relatives compared with healthy controls, particularly in limbic areas such as the bilateral amygdala, hippocampus, and insula. The same pattern was observed in sensitivity analyses. These results contrast with the overactivations observed in patients, potentially suggesting that this trait could serve as a protective factor in healthy relatives. However, further research is necessary to test this hypothesis.
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Affiliation(s)
- Anna M Fiorito
- Université Claude Bernard Lyon 1, CNRS, INSERM, Centre de Recherche en Neurosciences de Lyon CRNL U1028 UMR5292, PSYR2, 69500, Bron, France.
- Centre Hospitalier Le Vinatier, Bron, France.
| | - Giuseppe Blasi
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
- Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy
| | - Jérôme Brunelin
- Université Claude Bernard Lyon 1, CNRS, INSERM, Centre de Recherche en Neurosciences de Lyon CRNL U1028 UMR5292, PSYR2, 69500, Bron, France
- Centre Hospitalier Le Vinatier, Bron, France
| | - Asadur Chowdury
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University, Detroit, MI, USA
| | - Vaibhav A Diwadkar
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University, Detroit, MI, USA
| | - Vina M Goghari
- Department of Psychological Clinical Science, University of Toronto, Toronto, ON, Canada
| | - Ruben C Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jun Soo Kwon
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Korea
| | - Tiziana Quarto
- Department of Humanities, University of Foggia, Foggia, Italy
| | - Benjamin Rolland
- Université Claude Bernard Lyon 1, CNRS, INSERM, Centre de Recherche en Neurosciences de Lyon CRNL U1028 UMR5292, PSYR2, 69500, Bron, France
- Centre Hospitalier Le Vinatier, Bron, France
| | | | - Daniel H Wolf
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Je-Yeon Yun
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Korea
| | - Eric Fakra
- Université Claude Bernard Lyon 1, CNRS, INSERM, Centre de Recherche en Neurosciences de Lyon CRNL U1028 UMR5292, PSYR2, 69500, Bron, France
- Department of Psychiatry, University Hospital of Saint-Etienne, Saint-Etienne, France
| | - Guillaume Sescousse
- Université Claude Bernard Lyon 1, CNRS, INSERM, Centre de Recherche en Neurosciences de Lyon CRNL U1028 UMR5292, PSYR2, 69500, Bron, France
- Centre Hospitalier Le Vinatier, Bron, France
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11
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Quah SKL, Jo B, Geniesse C, Uddin LQ, Mumford JA, Barch DM, Fair DA, Gotlib IH, Poldrack RA, Saggar M. A Data-Driven Latent Variable Approach to Validating the Research Domain Criteria Framework. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.31.577486. [PMID: 38559071 PMCID: PMC10979851 DOI: 10.1101/2024.01.31.577486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Despite the widespread use of the Research Domain Criteria (RDoC) framework in psychiatry and neuroscience, recent studies suggest that the RDoC is insufficiently specific or excessively broad relative to the underlying brain circuitry it seeks to elucidate. To address these concerns of the RDoC framework, our study employed a latent variable approach, specifically utilizing bifactor analysis. We examined a total of 84 whole-brain task-based fMRI (tfMRI) activation maps from 19 studies with a total of 6,192 participants. Within this set of 84 maps, a curated subset of 37 maps with a balanced representation of RDoC domains constituted the training set of our analysis, and the remaining held-out maps formed the internal validation set. External validation was performed with 36 peak coordinate activation maps from Neurosynth, using terms of RDoC constructs as seeds for topic meta-analysis. Our results indicate that a bifactor model with a task-general domain and splitting the cognitive systems domain into sub-domains better fits the current corpus of tfMRI data than the current RDoC framework. Our data-driven validation supports revising the RDoC framework to accurately reflect underlying brain circuitry.
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Affiliation(s)
- S K L Quah
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - B Jo
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - C Geniesse
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - L Q Uddin
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, CA USA
| | - J A Mumford
- Department of Psychology, Stanford University, Stanford, CA, USA
| | - D M Barch
- Departments of Psychological & Brain Sciences, Psychiatry, and Radiology, Washington University in St. Louis, St Louis, MO, USA
| | - D A Fair
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN, USA
| | - I H Gotlib
- Department of Psychology, Stanford University, Stanford, CA, USA
| | - R A Poldrack
- Department of Psychology, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - M Saggar
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
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12
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Qiao-Tasserit E, Corradi-Dell’Acqua C, Vuilleumier P. Influence of transient emotional episodes on affective and cognitive theory of mind. Soc Cogn Affect Neurosci 2024; 19:nsae016. [PMID: 38442706 PMCID: PMC10914405 DOI: 10.1093/scan/nsae016] [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: 04/05/2023] [Revised: 12/20/2023] [Accepted: 02/21/2024] [Indexed: 03/07/2024] Open
Abstract
Our emotions may influence how we interact with others. Previous studies have shown an important role of emotion induction in generating empathic reactions towards others' affect. However, it remains unclear whether (and to which extent) our own emotions can influence the ability to infer people's mental states, a process associated with Theory of Mind (ToM) and implicated in the representation of both cognitive (e.g. beliefs and intentions) and affective conditions. We engaged 59 participants in two emotion-induction experiments where they saw joyful, neutral and fearful clips. Subsequently, they were asked to infer other individuals' joy, fear (affective ToM) or beliefs (cognitive ToM) from verbal scenarios. Using functional magnetic resonance imaging, we found that brain activity in the superior temporal gyrus, precuneus and sensorimotor cortices were modulated by the preceding emotional induction, with lower response when the to-be-inferred emotion was incongruent with the one induced in the observer (affective ToM). Instead, we found no effect of emotion induction on the appraisal of people's beliefs (cognitive ToM). These findings are consistent with embodied accounts of affective ToM, whereby our own emotions alter the engagement of key brain regions for social cognition, depending on the compatibility between one's own and others' affect.
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Affiliation(s)
- Emilie Qiao-Tasserit
- Laboratory of Behavioural Neurology and Imaging of Cognition, Department of Neuroscience, University Medical Center, University of Geneva, Geneva CH-1206, Switzerland
- Geneva Neuroscience Center, University of Geneva, Geneva CH-1206, Switzerland
- Swiss Center for Affective Sciences, University of Geneva, Geneva CH-1209, Switzerland
| | - Corrado Corradi-Dell’Acqua
- Geneva Neuroscience Center, University of Geneva, Geneva CH-1206, Switzerland
- Theory of Pain Laboratory, Department of Psychology, Faculty of Psychology and Educational Sciences (FPSE), University of Geneva, Geneva CH-1211, Switzerland
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Rovereto IT-38068, Italy
| | - Patrik Vuilleumier
- Laboratory of Behavioural Neurology and Imaging of Cognition, Department of Neuroscience, University Medical Center, University of Geneva, Geneva CH-1206, Switzerland
- Geneva Neuroscience Center, University of Geneva, Geneva CH-1206, Switzerland
- Swiss Center for Affective Sciences, University of Geneva, Geneva CH-1209, Switzerland
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13
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Dugré JR, Potvin S. Functional Connectivity of the Nucleus Accumbens across Variants of Callous-Unemotional Traits: A Resting-State fMRI Study in Children and Adolescents. Res Child Adolesc Psychopathol 2024; 52:353-368. [PMID: 37878131 PMCID: PMC10896801 DOI: 10.1007/s10802-023-01143-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/13/2023] [Indexed: 10/26/2023]
Abstract
A large body of literature suggests that the primary (high callousness-unemotional traits [CU] and low anxiety) and secondary (high CU traits and anxiety) variants of psychopathy significantly differ in terms of their clinical profiles. However, little is known about their neurobiological differences. While few studies showed that variants differ in brain activity during fear processing, it remains unknown whether they also show atypical functioning in motivational and reward system. Latent Profile Analysis (LPA) was conducted on a large sample of adolescents (n = 1416) to identify variants based on their levels of callousness and anxiety. Seed-to-voxel connectivity analysis was subsequently performed on resting-state fMRI data to compare connectivity patterns of the nucleus accumbens across subgroups. LPA failed to identify the primary variant when using total score of CU traits. Using a family-wise cluster correction, groups did not differ on functional connectivity. However, at an uncorrected threshold the secondary variant showed distinct functional connectivity between the nucleus accumbens and posterior insula, lateral orbitofrontal cortex, supplementary motor area, and parietal regions. Secondary LPA analysis using only the callousness subscale successfully distinguish both variants. Group differences replicated results of deficits in functional connectivity between the nucleus accumbens and posterior insula and supplementary motor area, but additionally showed effect in the superior temporal gyrus which was specific to the primary variant. The current study supports the importance of examining the neurobiological markers across subgroups of adolescents at risk for conduct problems to precise our understanding of this heterogeneous population.
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Affiliation(s)
- Jules Roger Dugré
- School of Psychology and Centre for Human Brain Health, University of Birmingham, Birmingham, B15 2TT, England.
| | - Stéphane Potvin
- Research Center of the Institut Universitaire en Santé Mentale de Montréal, Hochelaga, Montreal, 7331, H1N 3V2, Canada.
- Department of Psychiatry and Addictology, Faculty of medicine, University of Montreal, Montreal, Canada.
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14
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Naghibi N, Jahangiri N, Khosrowabadi R, Eickhoff CR, Eickhoff SB, Coull JT, Tahmasian M. Embodying Time in the Brain: A Multi-Dimensional Neuroimaging Meta-Analysis of 95 Duration Processing Studies. Neuropsychol Rev 2024; 34:277-298. [PMID: 36857010 PMCID: PMC10920454 DOI: 10.1007/s11065-023-09588-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 10/05/2022] [Indexed: 03/02/2023]
Abstract
Time is an omnipresent aspect of almost everything we experience internally or in the external world. The experience of time occurs through such an extensive set of contextual factors that, after decades of research, a unified understanding of its neural substrates is still elusive. In this study, following the recent best-practice guidelines, we conducted a coordinate-based meta-analysis of 95 carefully-selected neuroimaging papers of duration processing. We categorized the included papers into 14 classes of temporal features according to six categorical dimensions. Then, using the activation likelihood estimation (ALE) technique we investigated the convergent activation patterns of each class with a cluster-level family-wise error correction at p < 0.05. The regions most consistently activated across the various timing contexts were the pre-SMA and bilateral insula, consistent with an embodied theory of timing in which abstract representations of duration are rooted in sensorimotor and interoceptive experience, respectively. Moreover, class-specific patterns of activation could be roughly divided according to whether participants were timing auditory sequential stimuli, which additionally activated the dorsal striatum and SMA-proper, or visual single interval stimuli, which additionally activated the right middle frontal and inferior parietal cortices. We conclude that temporal cognition is so entangled with our everyday experience that timing stereotypically common combinations of stimulus characteristics reactivates the sensorimotor systems with which they were first experienced.
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Affiliation(s)
- Narges Naghibi
- Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran
| | - Nadia Jahangiri
- Faculty of Psychology & Education, Allameh Tabataba'i University, Tehran, Iran
| | - Reza Khosrowabadi
- Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran
| | - Claudia R Eickhoff
- Institute of Neuroscience and Medicine Research, Structural and functional organisation of the brain (INM-1), Jülich Research Center, Jülich, Germany
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine Research, Brain and Behaviour (INM-7), Jülich Research Center, Wilhelm-Johnen-Straße, Jülich, Germany
- Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany
| | - Jennifer T Coull
- Laboratoire de Neurosciences Cognitives (UMR 7291), Aix-Marseille Université & CNRS, Marseille, France
| | - Masoud Tahmasian
- Institute of Neuroscience and Medicine Research, Brain and Behaviour (INM-7), Jülich Research Center, Wilhelm-Johnen-Straße, Jülich, Germany.
- Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany.
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15
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Arrigoni E, Rappo E, Papagno C, Romero Lauro LJ, Pisoni A. Neural Correlates of Semantic Interference and Phonological Facilitation in Picture Naming: A Systematic Review and Coordinate-Based Meta-analysis. Neuropsychol Rev 2024:10.1007/s11065-024-09631-9. [PMID: 38319529 DOI: 10.1007/s11065-024-09631-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 01/04/2024] [Indexed: 02/07/2024]
Abstract
Semantic interference (SI) and phonological facilitation (PF) effects occur when multiple representations are co-activated simultaneously in complex naming paradigms, manipulating the context in which word production is set. Although the behavioral consequences of these psycholinguistic effects are well-known, the involved brain structures are still controversial. This paper aims to provide a systematic review and a coordinate-based meta-analysis of the available functional neuroimaging studies investigating SI and PF in picture naming paradigms. The included studies were fMRI experiments on healthy subjects, employing paradigms in which co-activations of representations were obtained by manipulating the naming context using semantically or phonologically related items. We examined the principal methodological aspects of the included studies, emphasizing the existing commonalities and discrepancies across single investigations. We then performed an exploratory coordinate-based meta-analysis of the reported activation peaks of neural response related to SI and PF. Our results consolidated previous findings regarding the involvement of the left inferior frontal gyrus and the left middle temporal gyrus in SI and brought out the role of bilateral inferior parietal regions in PF.
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Affiliation(s)
- Eleonora Arrigoni
- PhD Program in Neuroscience, School of Medicine and Surgery, University of Milano-Bicocca, via Cadore 48, 29100, Monza, MB, Italy
| | - Eleonora Rappo
- Department of Psychology, University of Milano-Bicocca, P.zza dell'Ateneo Nuovo 1, 20126, Milan, MI, Italy
| | - Costanza Papagno
- Center for Mind/Brain Sciences (CIMeC), Neurocognitive Rehabilitation Center (CeRiN), University of Trento, Via Matteo del Ben 5/b Bettini 31, 38068, Rovereto, TN, Italy
| | - Leonor J Romero Lauro
- Department of Psychology, University of Milano-Bicocca, P.zza dell'Ateneo Nuovo 1, 20126, Milan, MI, Italy
| | - Alberto Pisoni
- Department of Psychology, University of Milano-Bicocca, P.zza dell'Ateneo Nuovo 1, 20126, Milan, MI, Italy.
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16
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Garman A, Ash AM, Kokkinos EK, Nerland D, Winter L, Langreck CB, Forgette ML, Girgenti MJ, Banasr M, Duric V. Novel hippocampal genes involved in enhanced susceptibility to chronic pain-induced behavioral emotionality. Eur J Pharmacol 2024; 964:176273. [PMID: 38135263 DOI: 10.1016/j.ejphar.2023.176273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 12/08/2023] [Accepted: 12/11/2023] [Indexed: 12/24/2023]
Abstract
Altered mood and psychiatric disorders are commonly associated with chronic pain conditions; however, brain mechanisms linking pain and comorbid clinical depression are still largely unknown. In this study, we aimed to identify whether key genes/cellular mechanisms underlie susceptibility/resiliency to development of depressive-like behaviors during chronic pain state. Genome-wide RNA-seq analysis was used to examine the transcriptomic profile of the hippocampus, a limbic brain region that regulates mood and stress responses, from male rats exposed to chronic inflammatory pain. Pain-exposed animals were separated into either 'resilient' or 'susceptible' to development of enhanced behavioral emotionality based on behavioral testing. RNA-seq bioinformatic analysis, followed by validation using qPCR, revealed dysregulation of hippocampal genes involved in neuroinflammation, cell cycle/neurogenesis and blood-brain barrier integrity. Specifically, ADAM Metallopeptidase Domain 8 (Adam8) and Aurora Kinase B (Aurkb), genes with functional roles in activation of the NLRP3 inflammasome and microgliosis, respectively, were significantly upregulated in the hippocampus of 'susceptible' animals expressing increased behavioral emotionality. In addition, genes associated with blood-brain barrier integrity, such as the Claudin 4 (Cldn4), a tight junction protein and a known marker of astrocyte activation, were also significantly dysregulated between 'resilient' or 'susceptible' pain groups. Furthermore, differentially expressed genes (DEGs) were further characterized in rodents stress models to determine whether their hippocampal dysregulation is driven by common stress responses vs. affective pain processing. Altogether these results continue to strengthen the connection between dysregulation of hippocampal genes involved in neuroinflammatory and neurodegenerative processes with increased behavioral emotionality often expressed in chronic pain state.
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Affiliation(s)
- Adam Garman
- Department of Physiology and Pharmacology, Des Moines University, Des Moines, IA, 50312, USA
| | - Allison M Ash
- Department of Physiology and Pharmacology, Des Moines University, Des Moines, IA, 50312, USA
| | - Ellesavette K Kokkinos
- Department of Physiology and Pharmacology, Des Moines University, Des Moines, IA, 50312, USA
| | - Dakota Nerland
- Department of Physiology and Pharmacology, Des Moines University, Des Moines, IA, 50312, USA
| | - Lori Winter
- Department of Physiology and Pharmacology, Des Moines University, Des Moines, IA, 50312, USA
| | - Cory B Langreck
- Department of Physiology and Pharmacology, Des Moines University, Des Moines, IA, 50312, USA; Department of Molecular Pharmacology and Therapeutics, Columbia University, New York, NY, 10032, USA
| | - Morgan L Forgette
- Department of Physiology and Pharmacology, Des Moines University, Des Moines, IA, 50312, USA
| | - Matthew J Girgenti
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, 06508, USA
| | - Mounira Banasr
- Campbell Family Mental Health Research Institute of CAMH, Toronto, Canada; Department of Psychiatry, Pharmacology and Toxicology, University of Toronto, Toronto, Canada
| | - Vanja Duric
- Department of Physiology and Pharmacology, Des Moines University, Des Moines, IA, 50312, USA.
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17
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Zeng X, Han X, Zheng D, Jiang P, Yuan Z. Similarity and difference in large-scale functional network alternations between behavioral addictions and substance use disorder: a comparative meta-analysis. Psychol Med 2024; 54:473-487. [PMID: 38047402 DOI: 10.1017/s0033291723003434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
Behavioral addiction (BA) and substance use disorder (SUD) share similarities and differences in clinical symptoms, cognitive functions, and behavioral attributes. However, little is known about whether and how functional networks in the human brain manifest commonalities and differences between BA and SUD. Voxel-wise meta-analyses of resting-state functional connectivity (rs-FC) were conducted in BA and SUD separately, followed by quantitative conjunction analyses to identify the common and distinct alterations across both the BA and SUD groups. A total of 92 datasets with 2444 addicted patients and 2712 healthy controls (HCs) were eligible for the meta-analysis. Our findings demonstrated that BA and SUD exhibited common alterations in rs-FC between frontoparietal network (FPN) and other high-level neurocognitive networks (i.e. default mode network (DMN), affective network (AN), and salience network (SN)) as well as hyperconnectivity between SN seeds and the Rolandic operculum in SSN. In addition, compared with BA, SUD exhibited several distinct within- and between-network rs-FC alterations mainly involved in the DMN and FPN. Further, altered within- and between-network rs-FC showed significant association with clinical characteristics such as the severity of addiction in BA and duration of substance usage in SUD. The common rs-FC alterations in BA and SUD exhibited the relationship with consistent aberrant behaviors in both addiction groups, such as impaired inhibition control and salience attribution. By contrast, the distinct rs-FC alterations might suggest specific substance effects on the brain neural transmitter systems in SUD.
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Affiliation(s)
- Xinglin Zeng
- Centre for Cognitive and Brain Sciences, University of Macau, Macau SAR, 999078, China
- Faculty of Health Sciences, University of Macau, Macau SAR, 999078, China
| | - Xinyang Han
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, 999077, China
| | - Dong Zheng
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Ping Jiang
- West China Medical Publishers, West China Hospital of Sichuan University, Chengdu, 610041, People's Republic of China
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, Chengdu, China
| | - Zhen Yuan
- Centre for Cognitive and Brain Sciences, University of Macau, Macau SAR, 999078, China
- Faculty of Health Sciences, University of Macau, Macau SAR, 999078, China
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18
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Watanuki S. Identifying distinctive brain regions related to consumer choice behaviors on branded foods using activation likelihood estimation and machine learning. Front Comput Neurosci 2024; 18:1310013. [PMID: 38374888 PMCID: PMC10875973 DOI: 10.3389/fncom.2024.1310013] [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: 10/09/2023] [Accepted: 01/04/2024] [Indexed: 02/21/2024] Open
Abstract
Introduction Brand equity plays a crucial role in a brand's commercial success; however, research on the brain regions associated with brand equity has had mixed results. This study aimed to investigate key brain regions associated with the decision-making of branded and unbranded foods using quantitative neuroimaging meta-analysis and machine learning. Methods Quantitative neuroimaging meta-analysis was performed using the activation likelihood method. Activation of the ventral medial prefrontal cortex (VMPFC) overlapped between branded and unbranded foods. The lingual and parahippocampal gyri (PHG) were activated in the case of branded foods, whereas no brain regions were characteristically activated in response to unbranded foods. We proposed a novel predictive method based on the reported foci data, referencing the multi-voxel pattern analysis (MVPA) results. This approach is referred to as the multi-coordinate pattern analysis (MCPA). We conducted the MCPA, adopting the sparse partial least squares discriminant analysis (sPLS-DA) to detect unique brain regions associated with branded and unbranded foods based on coordinate data. The sPLS-DA is an extended PLS method that enables the processing of categorical data as outcome variables. Results We found that the lingual gyrus is a distinct brain region in branded foods. Thus, the VMPFC might be a core brain region in food categories in consumer behavior, regardless of whether they are branded foods. Moreover, the connection between the PHG and lingual gyrus might be a unique neural mechanism in branded foods. Discussion As this mechanism engages in imaging the feature-self based on emotionally subjective contextual associative memories, brand managers should create future-oriented relevancies between brands and consumers to build valuable brands.
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Affiliation(s)
- Shinya Watanuki
- Department of Marketing, Faculty of Commerce, University of Marketing and Distribution Sciences, Kobe, Hyogo, Japan
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19
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Zheng J, Womer FY, Tang L, Guo H, Zhang X, Tang Y, Wang F. Integrative omics analysis reveals epigenomic and transcriptomic signatures underlying brain structural deficits in major depressive disorder. Transl Psychiatry 2024; 14:17. [PMID: 38195555 PMCID: PMC10776753 DOI: 10.1038/s41398-023-02724-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 12/11/2023] [Accepted: 12/19/2023] [Indexed: 01/11/2024] Open
Abstract
Several lines of evidence support the involvement of transcriptomic and epigenetic mechanisms in the brain structural deficits of major depressive disorder (MDD) separately. However, research in these two areas has remained isolated. In this study, we proposed an integrative strategy that combined neuroimaging, brain-wide gene expression, and peripheral DNA methylation data to investigate the genetic basis of gray matter abnormalities in MDD. The MRI T1-weighted images and Illumina 850 K DNA methylation microarrays were obtained from 269 patients and 416 healthy controls, and brain-wide transcriptomic data were collected from Allen Human Brain Atlas. The between-group differences in gray matter volume (GMV) and differentially methylated CpG positions (DMPs) were examined. The genes with their expression patterns spatially related to GMV changes and genes with DMPs were overlapped and selected. Using principal component regression, the associations between DMPs in overlapped genes and GMV across individual patients were investigated, and the region-specific correlations between methylation status and gene expression were examined. We found significant associations between the decreased GMV and DMPs methylation status in the anterior cingulate cortex, inferior frontal cortex, and fusiform face cortex regions. These DMPs genes were primarily enriched in the neurodevelopmental and synaptic transmission process. There was a significant negative correlation between DNA methylation and gene expression in genes associated with GMV changes of the frontal cortex in MDD. Our findings suggest that GMV abnormalities in MDD may have a transcriptomic and epigenetic basis. This imaging-transcriptomic-epigenetic integrative analysis provides spatial and biological links between cortical morphological deficits and peripheral epigenetic signatures in MDD.
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Affiliation(s)
- Junjie Zheng
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
| | - Fay Y Womer
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lili Tang
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
| | - Huiling Guo
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Xizhe Zhang
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Yanqing Tang
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China.
- Brain Function Research Section, The First Hospital of China Medical University, Shenyang, China.
- Department of Gerontology, The First Hospital of China Medical University, Shenyang, China.
- Shengjing Hospital of China Medical University, Shenyang, China.
| | - Fei Wang
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
- Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China.
- Department of Mental Health, School of Public Health, Nanjing Medical University, Nanjing, China.
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20
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Acar F, Maumet C, Heuten T, Vervoort M, Bossier H, Seurinck R, Moerkerke B. Improving the Eligibility of Task-Based fMRI Studies for Meta-Analysis: A Review and Reporting Recommendations. Neuroinformatics 2024; 22:5-22. [PMID: 37924428 DOI: 10.1007/s12021-023-09643-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/09/2023] [Indexed: 11/06/2023]
Abstract
Decisions made during the analysis or reporting of an fMRI study influence the eligibility of that study to be entered into a meta-analysis. In a meta-analysis, results of different studies on the same topic are combined. To combine the results, it is necessary that all studies provide equivalent pieces of information. However, in task-based fMRI studies we see a large variety in reporting styles. Several specific meta-analysis methods have been developed to deal with the reporting practices occurring in task-based fMRI studies, therefore each requiring a specific type of input. In this manuscript we provide an overview of the meta-analysis methods and the specific input they require. Subsequently we discuss how decisions made during the study influence the eligibility of a study for a meta-analysis and finally we formulate some recommendations about how to report an fMRI study so that it complies with as many meta-analysis methods as possible.
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Affiliation(s)
- Freya Acar
- Department of Data-Analysis, Faculty of Psychology and Educational Science, Ghent University, Ghent, Belgium.
| | - Camille Maumet
- Inria, Univ Rennes, CNRS, Inserm, IRISA UMR 6074, Empenn ERL U 1228, Rennes, F-35000, France
| | - Talia Heuten
- Department of Data-Analysis, Faculty of Psychology and Educational Science, Ghent University, Ghent, Belgium
| | - Maya Vervoort
- Department of Data-Analysis, Faculty of Psychology and Educational Science, Ghent University, Ghent, Belgium
| | - Han Bossier
- Department of Data-Analysis, Faculty of Psychology and Educational Science, Ghent University, Ghent, Belgium
| | - Ruth Seurinck
- Department of Data-Analysis, Faculty of Psychology and Educational Science, Ghent University, Ghent, Belgium
| | - Beatrijs Moerkerke
- Department of Data-Analysis, Faculty of Psychology and Educational Science, Ghent University, Ghent, Belgium
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21
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Wiener M. Coordinate-Based Meta-Analyses of the Time Perception Network. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1455:215-226. [PMID: 38918354 DOI: 10.1007/978-3-031-60183-5_12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/27/2024]
Abstract
The study of time perception has advanced over the past three decades to include numerous neuroimaging studies, most notably including the use of functional Magnetic Resonance Imaging (fMRI). Yet, with this increase in studies, there comes the desire to draw broader conclusions across datasets about the nature and instantiation of time in the human brain. In the absence of collating individual studies together, the field has employed the use of Coordinate-Based Meta-Analyses (CBMA), in which foci from individual studies are modeled as probability distributions within the brain, from which common areas of activation-likelihood are determined. This chapter provides an overview of these CBMA studies, the methods they employ, the conclusions drawn by them, and where future areas of inquiry lie. The result of this survey suggests the existence of a domain-general "timing network" that can be used both as a guide for individual neuroimaging studies and as a template for future meta-analyses.
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22
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Joo SW, Jo YT, Ahn S, Choi YJ, Choi W, Kim SK, Joe S, Lee J. Structural impairment in superficial and deep white matter in schizophrenia. Acta Neuropsychiatr 2023:1-10. [PMID: 37620164 DOI: 10.1017/neu.2023.44] [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] [Indexed: 08/26/2023]
Abstract
OBJECTIVE Although disconnectivity among brain regions has been one of the main hypotheses for schizophrenia, the superficial white matter (SWM) has received less attention in schizophrenia research than the deep white matter (DWM) owing to the challenge of consistent reconstruction across subjects. METHODS We obtained the diffusion magnetic resonance imaging (dMRI) data of 223 healthy controls and 143 patients with schizophrenia. After harmonising the raw dMRIs from three different studies, we performed whole-brain two-tensor tractography and fibre clustering on the tractography data. We compared the fractional anisotropy (FA) of white matter tracts between healthy controls and patients with schizophrenia. Spearman's rho was adopted for the associations with clinical symptoms measured by the Positive and Negative Syndrome Scale (PANSS). The Bonferroni correction was used to adjust multiple testing. RESULTS Among the 33 DWM and 8 SWM tracts, patients with schizophrenia had a lower FA in 14 DWM and 4 SWM tracts than healthy controls, with small effect sizes. In the patient group, the FA deviations of the corticospinal and superficial-occipital tracts were negatively correlated with the PANSS negative score; however, this correlation was not evident after adjusting for multiple testing. CONCLUSION We observed the structural impairments of both the DWM and SWM tracts in patients with schizophrenia. The SWM could be a potential target of interest in future research on neural biomarkers for schizophrenia.
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Affiliation(s)
- Sung Woo Joo
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Young Tak Jo
- Department of Psychiatry, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Republic of Korea
| | - Soojin Ahn
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Young Jae Choi
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Woohyeok Choi
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Sang Kyoung Kim
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Soohyun Joe
- Brain Laboratory, Department of Psychiatry, University of California San Diego, School of Medicine, San Diego, CA, USA
| | - Jungsun Lee
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
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23
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Lv Q, Zeljic K, Zhao S, Zhang J, Zhang J, Wang Z. Dissecting Psychiatric Heterogeneity and Comorbidity with Core Region-Based Machine Learning. Neurosci Bull 2023; 39:1309-1326. [PMID: 37093448 PMCID: PMC10387015 DOI: 10.1007/s12264-023-01057-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 02/17/2023] [Indexed: 04/25/2023] Open
Abstract
Machine learning approaches are increasingly being applied to neuroimaging data from patients with psychiatric disorders to extract brain-based features for diagnosis and prognosis. The goal of this review is to discuss recent practices for evaluating machine learning applications to obsessive-compulsive and related disorders and to advance a novel strategy of building machine learning models based on a set of core brain regions for better performance, interpretability, and generalizability. Specifically, we argue that a core set of co-altered brain regions (namely 'core regions') comprising areas central to the underlying psychopathology enables the efficient construction of a predictive model to identify distinct symptom dimensions/clusters in individual patients. Hypothesis-driven and data-driven approaches are further introduced showing how core regions are identified from the entire brain. We demonstrate a broadly applicable roadmap for leveraging this core set-based strategy to accelerate the pursuit of neuroimaging-based markers for diagnosis and prognosis in a variety of psychiatric disorders.
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Affiliation(s)
- Qian Lv
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, IDG/McGovern Institute for Brain Research, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China.
| | - Kristina Zeljic
- School of Health and Psychological Sciences, City, University of London, London, EC1V 0HB, UK
| | - Shaoling Zhao
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, 101408, China
| | - Jiangtao Zhang
- Tongde Hospital of Zhejiang Province (Zhejiang Mental Health Center), Zhejiang Office of Mental Health, Hangzhou, 310012, China
| | - Jianmin Zhang
- Tongde Hospital of Zhejiang Province (Zhejiang Mental Health Center), Zhejiang Office of Mental Health, Hangzhou, 310012, China
| | - Zheng Wang
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, IDG/McGovern Institute for Brain Research, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China.
- School of Biomedical Engineering, Hainan University, Haikou, 570228, China.
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24
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Manuello J, Liloia D, Crocetta A, Cauda F, Costa T. CBMAT: a MATLAB toolbox for data preparation and post hoc analyses in neuroimaging meta-analyses. Behav Res Methods 2023:10.3758/s13428-023-02185-3. [PMID: 37528293 DOI: 10.3758/s13428-023-02185-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/28/2023] [Indexed: 08/03/2023]
Abstract
Coordinate-based meta-analysis (CBMA) is a powerful technique in the field of human brain imaging research. Due to its intense usage, several procedures for data preparation and post hoc analyses have been proposed so far. However, these steps are often performed manually by the researcher, and are therefore potentially prone to error and time-consuming. We hence developed the Coordinate-Based Meta-Analyses Toolbox (CBMAT) to provide a suite of user-friendly and automated MATLAB® functions allowing one to perform all these procedures in a fast, reproducible and reliable way. Besides the description of the code, in the present paper we also provide an annotated example of using CBMAT on a dataset including 34 experiments. CBMAT can therefore substantially improve the way data are handled when performing CBMAs. The code can be downloaded from https://github.com/Jordi-Manuello/CBMAT.git .
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Affiliation(s)
- Jordi Manuello
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
- FOCUS Lab, Department of Psychology, University of Turin, Turin, Italy
- Move'N'Brains Lab, Department of Psychology, University of Turin, Turin, Italy
| | - Donato Liloia
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy.
- FOCUS Lab, Department of Psychology, University of Turin, Turin, Italy.
| | - Annachiara Crocetta
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
- FOCUS Lab, Department of Psychology, University of Turin, Turin, Italy
| | - Franco Cauda
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
- FOCUS Lab, Department of Psychology, University of Turin, Turin, Italy
- Neuroscience Institute of Turin (NIT), Turin, Italy
| | - Tommaso Costa
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
- FOCUS Lab, Department of Psychology, University of Turin, Turin, Italy
- Neuroscience Institute of Turin (NIT), Turin, Italy
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25
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Cao Y, Tian F, Zeng J, Gong Q, Yang X, Jia Z. The brain activity pattern in alcohol-use disorders under inhibition response Task. J Psychiatr Res 2023; 163:127-134. [PMID: 37209618 DOI: 10.1016/j.jpsychires.2023.05.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 04/18/2023] [Accepted: 05/01/2023] [Indexed: 05/22/2023]
Abstract
BACKGROUND Inhibitory control impairment in alcohol use disorder (AUD) may indicate detrimental effects of chronic alcohol use on different functional systems in the brain, but the current studies lack consistency. This study aims to identify the most consistent response inhibition-related brain dysfunction based on existing data. METHODS We performed systematic searches of the PubMed, Embase, Web of Science, and PsychINFO databases for available studies. Anisotropic effect-size signed differential mapping was used to quantitatively analyze the differences in response inhibition-related brain activation between AUD patients and HCs. Meta regression was used to explore the relationship between brain alterations and clinical variables. RESULTS The brain hypoactivation or hyperactivation in AUD patients compared with HCs during the response inhibition tasks was mainly located in the prefrontal cortex including the superior frontal gyrus, inferior frontal gyrus, and middle frontal gyrus, anterior cingulate gyrus (ACC), superior temporal gyrus, occipital gyrus, and somatosensory areas including postcentral gyrus and supramarginal gyrus. The meta-regression revealed that older patients were more likely to present activation in the left superior frontal gyrus when performing the response inhibition tasks. CONCLUSIONS The response inhibitive dysfunctions in a distinct prefrontal-cingulate cortices may presumably reflect the core impairment in cognitive control abilities. Dysfunction in the occipital gyrus and somatosensory areas may indicate an abnormal motor-sensory and visual function in AUD. Such functional abnormalities may represent neurophysiological correlates of the executive deficits observed in AUD patients. This study has been registered in PROSPERO (number CRD42022339384).
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Affiliation(s)
- Yuan Cao
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, 610041, PR China
| | - Fangfang Tian
- Department of Nuclear Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, PR China
| | - Jianguang Zeng
- School of Economics and Business Administration, Chongqing University, Chongqing, 400044, PR China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, PR China; Psychoradiology Research Unit of the Chinese Academy of Medical Sciences (2018RU011), West China Hospital of Sichuan University, Chengdu, Sichuan, PR China
| | - Xun Yang
- School of Public Affairs, Chongqing University, Chongqing, 400044, PR China
| | - Zhiyun Jia
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, 610041, PR China; Psychoradiology Research Unit of the Chinese Academy of Medical Sciences (2018RU011), West China Hospital of Sichuan University, Chengdu, Sichuan, PR China.
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26
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Hiew S, Roothans J, Eldebakey H, Volkmann J, Zeller D, Reich MM. Imaging the Spin: Disentangling the Core Processes Underlying Mental Rotation by Network Mapping of Data From Meta-analysis. Neurosci Biobehav Rev 2023; 150:105187. [PMID: 37086933 DOI: 10.1016/j.neubiorev.2023.105187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 04/05/2023] [Accepted: 04/16/2023] [Indexed: 04/24/2023]
Abstract
Research on the mental rotation task has sparked debate regarding the specific processes that underly the capability of humans to mentally rotate objects. The spread of reported brain activations suggests that mental rotation is subserved by a neural network circle. However, no common network has yet been found that uncovers the crucial processes underlying this ability. We aimed to identify the common network crucial for mental rotation by coordinate-based network mapping of previous neuroimaging findings in mental rotation. A meta-analysis revealed 710 peak activation coordinates from 42 fMRI studies in mental rotation, which include a total 844 participants. The coordinates were mapped to a normative functional connectome (n = 1000) to identify a network of connected regions. To account for experimental factors, we examined this network against two control tasks, action imitation and symbolic number processing. A common and crucial network for mental rotation, centring on dorsal premotor, superior parietal and inferior temporal lobes was revealed. This network, separated from other experimental aspects, suggests that the crucial processes underlying mental rotation are motor rotation, visuospatial processing, and higher order visual object recognition.
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Affiliation(s)
- Shawn Hiew
- Department of Neurology, University Hospital of Würzburg, Germany.
| | - Jonas Roothans
- Department of Neurology, University Hospital of Würzburg, Germany
| | - Hazem Eldebakey
- Department of Neurology, University Hospital of Würzburg, Germany
| | - Jens Volkmann
- Department of Neurology, University Hospital of Würzburg, Germany
| | - Daniel Zeller
- Department of Neurology, University Hospital of Würzburg, Germany
| | - Martin M Reich
- Department of Neurology, University Hospital of Würzburg, Germany
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27
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MacLean MW, Hadid V, Spreng RN, Lepore F. Revealing robust neural correlates of conscious and unconscious visual processing: activation likelihood estimation meta-analyses. Neuroimage 2023; 273:120088. [PMID: 37030413 DOI: 10.1016/j.neuroimage.2023.120088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 03/30/2023] [Accepted: 04/03/2023] [Indexed: 04/09/2023] Open
Abstract
Our ability to consciously perceive information from the visual scene relies on a myriad of intrinsic neural mechanisms. Functional neuroimaging studies have sought to identify the neural correlates of conscious visual processing and to further dissociate from those pertaining to preconscious and unconscious visual processing. However, delineating what core brain regions are involved in eliciting a conscious percept remains a challenge, particularly regarding the role of prefrontal-parietal regions. We performed a systematic search of the literature that yielded a total of 54 functional neuroimaging studies. We conducted two quantitative meta-analyses using activation likelihood estimation to identify reliable patterns of activation engaged by i. conscious (n = 45 studies, comprising 704 participants) and ii. unconscious (n = 16 studies, comprising 262 participants) visual processing during various task performances. Results of the meta-analysis specific to conscious percepts quantitatively revealed reliable activations across a constellation of regions comprising the bilateral inferior frontal junction, intraparietal sulcus, dorsal anterior cingulate, angular gyrus, temporo-occipital cortex and anterior insula. Neurosynth reverse inference revealed conscious visual processing to be intertwined with cognitive terms related to attention, cognitive control and working memory. Results of the meta-analysis on unconscious percepts revealed consistent activations in the lateral occipital complex, intraparietal sulcus and precuneus. These findings highlight the notion that conscious visual processing readily engages higher-level regions including the inferior frontal junction and unconscious processing reliably recruits posterior regions, mainly the lateral occipital complex.
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28
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Pisani S, Gunasekera B, Lu Y, Vignando M, Ffytche D, Aarsland D, Chaudhuri KR, Ballard C, Lee JY, Kim YK, Velayudhan L, Bhattacharyya S. Grey matter volume loss in Parkinson's disease psychosis and its relationship with serotonergic gene expression: A meta-analysis. Neurosci Biobehav Rev 2023; 147:105081. [PMID: 36775084 DOI: 10.1016/j.neubiorev.2023.105081] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 01/14/2023] [Accepted: 02/05/2023] [Indexed: 02/12/2023]
Abstract
BACKGROUND Neuroanatomical alterations underlying psychosis in Parkinson's Disease (PDP) remain unclear. We carried out a meta-analysis of MRI studies investigating the neural correlates of PDP and examined its relation with dopaminergic and serotonergic receptor gene expression. METHODS PubMed, Web of Science and Embase were searched for MRI studies (k studies = 10) of PDP compared to PD patients without psychosis (PDnP). Seed-based d Mapping with Permutation of Subject Images and multiple linear regression analyses was used to examine the relationship between pooled estimates of grey matter volume (GMV) loss in PDP and D1/D2 and 5-HT1a/5-HT2a receptor gene expression estimates from Allen Human Brain Atlas. RESULTS We observed lower grey matter volume in parietal-temporo-occipital regions (PDP n = 211, PDnP, n = 298). GMV loss in PDP was associated with local expression of 5-HT1a (b = 0.109, p = 0.012) and 5-HT2a receptors (b= -0.106, p = 0.002) but not dopaminergic receptors. CONCLUSION Widespread GMV loss in the parieto-temporo-occipital regions may underlie PDP. Association between grey matter volume and local expression of serotonergic receptor genes may suggest a role for serotonergic receptors in PDP.
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Affiliation(s)
- Sara Pisani
- Division of Academic Psychiatry, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, United Kingdom.
| | - Brandon Gunasekera
- Division of Academic Psychiatry, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, United Kingdom.
| | - Yining Lu
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, United Kingdom.
| | - Miriam Vignando
- Centre for Neuroimaging Science, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, United Kingdom.
| | - Dominic Ffytche
- Division of Academic Psychiatry, Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, United Kingdom.
| | - Dag Aarsland
- Division of Academic Psychiatry, Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, United Kingdom; Centre for Age-Related Medicine (SESAM), Stavanger University Hospital, Stavanger, Norway.
| | - K Ray Chaudhuri
- Department of Neurosciences, Institute of Psychiatry, Psychology and Neuroscience, and Parkinson's Foundation Centre of Excellence, King's College Hospital, London, United Kingdom.
| | - Clive Ballard
- Medical School, Medical School Building, St Luke's Campus, Magdalen Road, University of Exeter, Exeter EX1 2LU, United Kingdom.
| | - Jee-Young Lee
- Department of Neurology, Seoul National University-Seoul Metropolitan Government, Boramae Medical Center, 20, Boramae-ro 5-gil, Dongjak-gu, Seoul 07061, Republic of Korea.
| | - Yu Kyeong Kim
- Department of Nuclear Medicine, Seoul National University-Seoul Metropolitan Government, Boramae Medical Center, 20, Boramae-ro 5-gil, Dongjak-gu, Seoul 07061, Republic of Korea.
| | - Latha Velayudhan
- Division of Academic Psychiatry, Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, United Kingdom; Department of Population Health Sciences, University of Leicester, United Kingdom.
| | - Sagnik Bhattacharyya
- Division of Academic Psychiatry, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, United Kingdom.
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29
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Wen J, Gao Y, Li M, Hu S, Zhao M, Su C, Wang Q, Xi H, Zhan L, Lv Y, Antwi CO, Ren J, Jia X. Regional abnormalities of spontaneous brain activity in migraine: A coordinate‐based meta‐analysis. J Neurosci Res 2023. [DOI: 10.1002/jnr.25191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 02/17/2023] [Accepted: 03/13/2023] [Indexed: 04/03/2023]
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30
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Atzil S, Satpute AB, Zhang J, Parrish MH, Shablack H, MacCormack JK, Leshin J, Goel S, Brooks JA, Kang J, Xu Y, Cohen M, Lindquist KA. The impact of sociality and affective valence on brain activation: A meta-analysis. Neuroimage 2023; 268:119879. [PMID: 36642154 DOI: 10.1016/j.neuroimage.2023.119879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Revised: 01/07/2023] [Accepted: 01/11/2023] [Indexed: 01/15/2023] Open
Abstract
Thirty years of neuroimaging reveal the set of brain regions consistently associated with pleasant and unpleasant affect in humans-or the neural reference space for valence. Yet some of humans' most potent affective states occur in the context of other humans. Prior work has yet to differentiate how the neural reference space for valence varies as a product of the sociality of affective stimuli. To address this question, we meta-analyzed across 614 social and non-social affective neuroimaging contrasts, summarizing the brain regions that are consistently activated for social and non-social affective information. We demonstrate that across the literature, social and non-social affective stimuli yield overlapping activations within regions associated with visceromotor control, including the amygdala, hypothalamus, anterior cingulate cortex and insula. However, we find that social processing differs from non-social affective processing in that it involves additional cortical activations in the medial prefrontal and posterior cingulum that have been associated with mentalizing and prediction. A Bayesian classifier was able to differentiate unpleasant from pleasant affect, but not social from non-social affective states. Moreover, it was not able to classify unpleasantness from pleasantness at the highest levels of sociality. These findings suggest that highly social scenarios may be equally salient to humans, regardless of their valence.
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Affiliation(s)
- Shir Atzil
- The Hebrew University of Jerusalem, Jerusalem, Israel.
| | | | - Jiahe Zhang
- Northeastern University, Boston, MA, United States
| | | | - Holly Shablack
- Washington and Lee University, Lexington, VA, United States
| | | | - Joseph Leshin
- University of North Carolina, Chapel Hill, NC, United States
| | | | - Jeffrey A Brooks
- Hume AI, New York, NY, United States; University of California, Berkeley, CA, United States
| | - Jian Kang
- University of Michigan, Ann Arbor, MI, United States
| | - Yuliang Xu
- University of Michigan, Ann Arbor, MI, United States
| | - Matan Cohen
- The Hebrew University of Jerusalem, Jerusalem, Israel
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31
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Ma H, Cao Y, Li M, Zhan L, Xie Z, Huang L, Gao Y, Jia X. Abnormal amygdala functional connectivity and deep learning classification in multifrequency bands in autism spectrum disorder: A multisite functional magnetic resonance imaging study. Hum Brain Mapp 2023; 44:1094-1104. [PMID: 36346215 PMCID: PMC9875923 DOI: 10.1002/hbm.26141] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Revised: 10/19/2022] [Accepted: 10/25/2022] [Indexed: 11/11/2022] Open
Abstract
Previous studies have explored resting-state functional connectivity (rs-FC) of the amygdala in patients with autism spectrum disorder (ASD). However, it remains unclear whether there are frequency-specific FC alterations of the amygdala in ASD and whether FC in specific frequency bands can be used to distinguish patients with ASD from typical controls (TCs). Data from 306 patients with ASD and 314 age-matched and sex-matched TCs were collected from 28 sites in the Autism Brain Imaging Data Exchange database. The bilateral amygdala, defined as the seed regions, was used to perform seed-based FC analyses in the conventional, slow-5, and slow-4 frequency bands at each site. Image-based meta-analyses were used to obtain consistent brain regions across 28 sites in the three frequency bands. By combining generative adversarial networks and deep neural networks, a deep learning approach was applied to distinguish patients with ASD from TCs. The meta-analysis results showed frequency band specificity of FC in ASD, which was reflected in the slow-5 frequency band instead of the conventional and slow-4 frequency bands. The deep learning results showed that, compared with the conventional and slow-4 frequency bands, the slow-5 frequency band exhibited a higher accuracy of 74.73%, precision of 74.58%, recall of 75.05%, and area under the curve of 0.811 to distinguish patients with ASD from TCs. These findings may help us to understand the pathological mechanisms of ASD and provide preliminary guidance for the clinical diagnosis of ASD.
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Affiliation(s)
- Huibin Ma
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Yikang Cao
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Mengting Li
- College of Teacher Education, Zhejiang Normal University, Jinhua, China.,Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China
| | - Linlin Zhan
- Faculty of Western Languages, Heilongjiang University, Harbin, China
| | - Zhou Xie
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Lina Huang
- Department of Radiology, Changshu No. 2 People's Hospital, The Affiliated Changshu Hospital of Xuzhou Medical University, Changshu, China
| | - Yanyan Gao
- College of Teacher Education, Zhejiang Normal University, Jinhua, China.,Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China
| | - Xize Jia
- Department of Radiology, Changshu No. 2 People's Hospital, The Affiliated Changshu Hospital of Xuzhou Medical University, Changshu, China
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32
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Fiorito AM, Aleman A, Blasi G, Bourque J, Cao H, Chan RCK, Chowdury A, Conrod P, Diwadkar VA, Goghari VM, Guinjoan S, Gur RE, Gur RC, Kwon JS, Lieslehto J, Lukow PB, Meyer-Lindenberg A, Modinos G, Quarto T, Spilka MJ, Shivakumar V, Venkatasubramanian G, Villarreal M, Wang Y, Wolf DH, Yun JY, Fakra E, Sescousse G. Are Brain Responses to Emotion a Reliable Endophenotype of Schizophrenia? An Image-Based Functional Magnetic Resonance Imaging Meta-analysis. Biol Psychiatry 2023; 93:167-177. [PMID: 36085080 DOI: 10.1016/j.biopsych.2022.06.013] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 06/07/2022] [Accepted: 06/07/2022] [Indexed: 11/02/2022]
Abstract
BACKGROUND Impaired emotion processing constitutes a key dimension of schizophrenia and a possible endophenotype of this illness. Empirical studies consistently report poorer emotion recognition performance in patients with schizophrenia as well as in individuals at enhanced risk of schizophrenia. Functional magnetic resonance imaging studies also report consistent patterns of abnormal brain activation in response to emotional stimuli in patients, in particular, decreased amygdala activation. In contrast, brain-level abnormalities in at-risk individuals are more elusive. We address this gap using an image-based meta-analysis of the functional magnetic resonance imaging literature. METHODS Functional magnetic resonance imaging studies investigating brain responses to negative emotional stimuli and reporting a comparison between at-risk individuals and healthy control subjects were identified. Frequentist and Bayesian voxelwise meta-analyses were performed separately, by implementing a random-effect model with unthresholded group-level T-maps from individual studies as input. RESULTS In total, 17 studies with a cumulative total of 677 at-risk individuals and 805 healthy control subjects were included. Frequentist analyses did not reveal significant differences between at-risk individuals and healthy control subjects. Similar results were observed with Bayesian analyses, which provided strong evidence for the absence of meaningful brain activation differences across the entire brain. Region of interest analyses specifically focusing on the amygdala confirmed the lack of group differences in this region. CONCLUSIONS These results suggest that brain activation patterns in response to emotional stimuli are unlikely to constitute a reliable endophenotype of schizophrenia. We suggest that future studies instead focus on impaired functional connectivity as an alternative and promising endophenotype.
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Affiliation(s)
- Anna M Fiorito
- Lyon Neuroscience Research Center, INSERM U1028, CNRS UMR 5292, PSYR2 Team, University of Lyon, Lyon, France; Department of Psychiatry, University Hospital of Saint-Etienne, Saint-Etienne, France.
| | - André Aleman
- University of Groningen, University Medical Center Groningen, Department of Biomedical Sciences of Cells & Systems, Groningen, The Netherlands
| | - Giuseppe Blasi
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Josiane Bourque
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Hengyi Cao
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, New York
| | - Raymond C K Chan
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, Chinese Academy of Sciences Key Laboratory of Mental Health, Institute of Psychology, Beijing, China
| | - Asadur Chowdury
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University, Detroit, Michigan
| | - Patricia Conrod
- CHU Sainte-Justine Research Center, Department of Psychiatry and Addiction, University of Montréal, Montreal, Quebec, Canada
| | - Vaibhav A Diwadkar
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University, Detroit, Michigan
| | - Vina M Goghari
- Department of Psychological Clinical Science, University of Toronto, Toronto, Ontario, Canada
| | | | - Raquel E Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Ruben C Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Jun Soo Kwon
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Johannes Lieslehto
- University of Eastern Finland, Department of Forensic Psychiatry, Niuvanniemi Hospital, Kuopio, Finland
| | - Paulina B Lukow
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Andreas Meyer-Lindenberg
- Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
| | - Gemma Modinos
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | | | - Michael J Spilka
- Department of Psychology, University of Georgia, Athens, Georgia
| | - Venkataram Shivakumar
- Department of Integrative Medicine, National Institute of Mental Health and Neuro Sciences, Bengaluru, India
| | | | - Mirta Villarreal
- Instituto de Neurociencias FLENI-CONICET, Facultad de Ciencias Exactas y Naturales, UBA, Buenos Aires, Argentina
| | - Yi Wang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, Chinese Academy of Sciences Key Laboratory of Mental Health, Institute of Psychology, Beijing, China
| | - Daniel H Wolf
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Je-Yeon Yun
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Eric Fakra
- Lyon Neuroscience Research Center, INSERM U1028, CNRS UMR 5292, PSYR2 Team, University of Lyon, Lyon, France; Department of Psychiatry, University Hospital of Saint-Etienne, Saint-Etienne, France
| | - Guillaume Sescousse
- Lyon Neuroscience Research Center, INSERM U1028, CNRS UMR 5292, PSYR2 Team, University of Lyon, Lyon, France; Centre Hospitalier Le Vinatier, Bron, France
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33
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Dugré JR, Orban P, Potvin S. Disrupted functional connectivity of the brain reward system in substance use problems: A meta-analysis of functional neuroimaging studies. Addict Biol 2023; 28:e13257. [PMID: 36577728 DOI: 10.1111/adb.13257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 09/12/2022] [Accepted: 11/08/2022] [Indexed: 11/25/2022]
Abstract
Extensive literature suggests that the brain reward system is crucial in understanding the neurobiology of substance use disorders. However, evidence of reliable deficits in functional connectivity across studies on substance use problems remains limited. Therefore, a voxel-wise seed-based meta-analysis using brain regions of the reward system as seeds of interest was conducted on 96 studies representing 5757 subjects with substance use problems. The ventromedial prefrontal cortex exhibited hyperconnectivity with the ventral striatum and hypoconnectivity with the amygdala and hippocampus. The executive striatum showed hyperconnectivity with the motor thalamus and dorsolateral prefrontal cortex and hypoconnectivity with the anterior cingulate cortex and anterior insula. Finally, the limbic striatum was found to be hyperconnected to the orbitofrontal cortex and hypoconnected to the precuneus compared with healthy subjects. The current study provided meta-analytical evidence of deficient functional connectivity between brain regions of the reward system and cortico-striato-thalamocortical loops in addiction. These results are consistent with deficits in motivation and habit formation occurring in addiction, and they highlight alterations in brain regions involved in socio-emotional processing and attention salience.
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Affiliation(s)
- Jules R Dugré
- Research Center of the Institut Universitaire en Santé Mentale de Montréal, Montreal, Canada.,Department of Psychiatry and Addictology, Faculty of Medicine, University of Montreal, Montreal, Canada
| | - Pierre Orban
- Research Center of the Institut Universitaire en Santé Mentale de Montréal, Montreal, Canada.,Department of Psychiatry and Addictology, Faculty of Medicine, University of Montreal, Montreal, Canada
| | - Stéphane Potvin
- Research Center of the Institut Universitaire en Santé Mentale de Montréal, Montreal, Canada.,Department of Psychiatry and Addictology, Faculty of Medicine, University of Montreal, Montreal, Canada
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34
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Henn AT, Larsen B, Frahm L, Xu A, Adebimpe A, Scott JC, Linguiti S, Sharma V, Basbaum AI, Corder G, Dworkin RH, Edwards RR, Woolf CJ, Habel U, Eickhoff SB, Eickhoff CR, Wagels L, Satterthwaite TD. Structural imaging studies of patients with chronic pain: an anatomical likelihood estimate meta-analysis. Pain 2023; 164:e10-e24. [PMID: 35560117 PMCID: PMC9653511 DOI: 10.1097/j.pain.0000000000002681] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 05/09/2022] [Indexed: 01/09/2023]
Abstract
ABSTRACT Neuroimaging is a powerful tool to investigate potential associations between chronic pain and brain structure. However, the proliferation of studies across diverse chronic pain syndromes and heterogeneous results challenges data integration and interpretation. We conducted a preregistered anatomical likelihood estimate meta-analysis on structural magnetic imaging studies comparing patients with chronic pain and healthy controls. Specifically, we investigated a broad range of measures of brain structure as well as specific alterations in gray matter and cortical thickness. A total of 7849 abstracts of experiments published between January 1, 1990, and April 26, 2021, were identified from 8 databases and evaluated by 2 independent reviewers. Overall, 103 experiments with a total of 5075 participants met the preregistered inclusion criteria. After correction for multiple comparisons using the gold-standard family-wise error correction ( P < 0.05), no significant differences associated with chronic pain were found. However, exploratory analyses using threshold-free cluster enhancement revealed several spatially distributed clusters showing structural alterations in chronic pain. Most of the clusters coincided with regions implicated in nociceptive processing including the amygdala, thalamus, hippocampus, insula, anterior cingulate cortex, and inferior frontal gyrus. Taken together, these results suggest that chronic pain is associated with subtle, spatially distributed alterations of brain structure.
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Affiliation(s)
- Alina T. Henn
- Department of Psychiatry, Psychotherapy and Psychosomatics, School of Medicine, RWTH Aachen University, Aachen, Germany
| | - Bart Larsen
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, US
- Lifespan Informatics and Neuroimaging Center, Perelman School of Medicine, University of Pennsylvania
| | - Lennart Frahm
- Institute of Neuroscience and Medicine (INM7), Forschungszentrum Jülich, Jülich, Germany
| | - Anna Xu
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, US
- Lifespan Informatics and Neuroimaging Center, Perelman School of Medicine, University of Pennsylvania
- Department of Psychology, Stanford University, Stanford, Carlifornia, US
| | - Azeez Adebimpe
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, US
- Lifespan Informatics and Neuroimaging Center, Perelman School of Medicine, University of Pennsylvania
| | - J. Cobb Scott
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, US
- VISN4 Mental Illness Research, Education, and Clinical Center at the Corporal Michael J. Crescenz VA (Veterans Affairs) Medical Center, Philadelphia, Pennsylvania, US
| | - Sophia Linguiti
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, US
- Lifespan Informatics and Neuroimaging Center, Perelman School of Medicine, University of Pennsylvania
| | - Vaishnavi Sharma
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, US
- Lifespan Informatics and Neuroimaging Center, Perelman School of Medicine, University of Pennsylvania
| | - Allan I. Basbaum
- Department of Anatomy, University of California, San Francisco, US
| | - Gregory Corder
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, US
| | - Robert H. Dworkin
- Department of Anesthesiology and Perioperative Medicine, University of Rochester School of Medicine and Dentistry, Rochester, New York, US
| | - Robert R. Edwards
- Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, US
| | - Clifford J. Woolf
- FM Kirby Neurobiology Center, Boston Children’s Hospital, Boston, Massachusetts, US
- Department of Neurobiology, Harvard Medical School, Boston, Massachusetts, US
| | - Ute Habel
- Department of Psychiatry, Psychotherapy and Psychosomatics, School of Medicine, RWTH Aachen University, Aachen, Germany
- JARA-Institute Brain Structure Function Relationship (INM 10), Research Center Jülich, Jülich, Germany
| | - Simon B. Eickhoff
- Institute of Neuroscience and Medicine (INM7), Forschungszentrum Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany
| | - Claudia R. Eickhoff
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine-University, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM1), Forschungszentrum Jülich, Jülich, Germany
| | - Lisa Wagels
- Department of Psychiatry, Psychotherapy and Psychosomatics, School of Medicine, RWTH Aachen University, Aachen, Germany
- JARA-Institute Brain Structure Function Relationship (INM 10), Research Center Jülich, Jülich, Germany
| | - Theodore D. Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, US
- Lifespan Informatics and Neuroimaging Center, Perelman School of Medicine, University of Pennsylvania
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35
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Pintos Lobo R, Bottenhorn KL, Riedel MC, Toma AI, Hare MM, Smith DD, Moor AC, Cowan IK, Valdes JA, Bartley JE, Salo T, Boeving ER, Pankey B, Sutherland MT, Musser ED, Laird AR. Neural systems underlying RDoC social constructs: An activation likelihood estimation meta-analysis. Neurosci Biobehav Rev 2023; 144:104971. [PMID: 36436737 PMCID: PMC9843621 DOI: 10.1016/j.neubiorev.2022.104971] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 10/13/2022] [Accepted: 11/21/2022] [Indexed: 11/27/2022]
Abstract
Neuroscientists have sought to identify the underlying neural systems supporting social processing that allow interaction and communication, forming social relationships, and navigating the social world. Through the use of NIMH's Research Domain Criteria (RDoC) framework, we evaluated consensus among studies that examined brain activity during social tasks to elucidate regions comprising the "social brain". We examined convergence across tasks corresponding to the four RDoC social constructs, including Affiliation and Attachment, Social Communication, Perception and Understanding of Self, and Perception and Understanding of Others. We performed a series of coordinate-based meta-analyses using the activation likelihood estimate (ALE) method. Meta-analysis was performed on whole-brain coordinates reported from 864 fMRI contrasts using the NiMARE Python package, revealing convergence in medial prefrontal cortex, anterior cingulate cortex, posterior cingulate cortex, temporoparietal junction, bilateral insula, amygdala, fusiform gyrus, precuneus, and thalamus. Additionally, four separate RDoC-based meta-analyses revealed differential convergence associated with the four social constructs. These outcomes highlight the neural support underlying these social constructs and inform future research on alterations among neurotypical and atypical populations.
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Affiliation(s)
| | - Katherine L Bottenhorn
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - Michael C Riedel
- Department of Physics, Florida International University, Miami, FL, USA
| | - Afra I Toma
- Department of Biomedical Engineering, Emory University, Atlanta, GA, USA
| | - Megan M Hare
- Department of Psychology, Florida International University, Miami, FL, USA
| | - Donisha D Smith
- Department of Psychology, Florida International University, Miami, FL, USA
| | - Alexandra C Moor
- Department of Psychology, Florida International University, Miami, FL, USA
| | - Isis K Cowan
- Department of Psychology, Old Dominion University, Norfolk, VA, USA
| | - Javier A Valdes
- College of Medicine, Florida International University, Miami, FL, USA
| | - Jessica E Bartley
- Department of Physics, Florida International University, Miami, FL, USA
| | - Taylor Salo
- Department of Psychology, Florida International University, Miami, FL, USA
| | - Emily R Boeving
- Department of Psychology, Florida International University, Miami, FL, USA
| | - Brianna Pankey
- Department of Psychology, Florida International University, Miami, FL, USA
| | | | - Erica D Musser
- Department of Psychology, Florida International University, Miami, FL, USA
| | - Angela R Laird
- Department of Physics, Florida International University, Miami, FL, USA
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36
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Wang M, Zhang S, Suo T, Mao T, Wang F, Deng Y, Eickhoff S, Pan Y, Jiang C, Rao H. Risk-taking in the human brain: An activation likelihood estimation meta-analysis of the balloon analog risk task (BART). Hum Brain Mapp 2022; 43:5643-5657. [PMID: 36441844 PMCID: PMC9704781 DOI: 10.1002/hbm.26041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 05/25/2022] [Accepted: 07/15/2022] [Indexed: 01/15/2023] Open
Abstract
The Balloon Analog Risk Task (BART) is increasingly used to assess risk-taking behavior and brain function. However, the brain networks underlying risk-taking during the BART and its reliability remain controversial. Here, we combined the activation likelihood estimation (ALE) meta-analysis with both task-based and task-free functional connectivity (FC) analysis to quantitatively synthesize brain networks involved in risk-taking during the BART, and compared the differences between adults and adolescents studies. Based on 22 pooled publications, the ALE meta-analysis revealed multiple brain regions in the reward network, salience network, and executive control network underlying risk-taking during the BART. Compared with adult risk-taking, adolescent risk-taking showed greater activation in the insula, putamen, and prefrontal regions. The combination of meta-analytic connectivity modeling with task-free FC analysis further confirmed the involvement of the reward, salience, and cognitive control networks in the BART. These findings demonstrate the core brain networks for risk-taking during the BART and support the utility of the BART for future neuroimaging and developmental research.
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Affiliation(s)
- Mengmeng Wang
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Applied Brain and Cognitive Sciences, School of Business and ManagementShanghai International Studies UniversityShanghaiChina
| | - Shunmin Zhang
- Department of Psychology and Behavioral SciencesZhejiang UniversityHangzhouZhejiangChina
| | - Tao Suo
- School of Education, Institute of Cognition, Brain, and Health, Institute of Psychology and BehaviorHenan UniversityKaifengHenanChina
| | - Tianxin Mao
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Applied Brain and Cognitive Sciences, School of Business and ManagementShanghai International Studies UniversityShanghaiChina
| | - Fenghua Wang
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Applied Brain and Cognitive Sciences, School of Business and ManagementShanghai International Studies UniversityShanghaiChina
| | - Yao Deng
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Applied Brain and Cognitive Sciences, School of Business and ManagementShanghai International Studies UniversityShanghaiChina
- Center for Functional Neuroimaging, Department of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Simon Eickhoff
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM‐7), Research Centre JülichJülichGermany
- Institute of Systems Neuroscience, Medical FacultyHeinrich Heine University DüsseldorfDüsseldorfGermany
| | - Yu Pan
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Applied Brain and Cognitive Sciences, School of Business and ManagementShanghai International Studies UniversityShanghaiChina
| | - Caihong Jiang
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Applied Brain and Cognitive Sciences, School of Business and ManagementShanghai International Studies UniversityShanghaiChina
| | - Hengyi Rao
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Applied Brain and Cognitive Sciences, School of Business and ManagementShanghai International Studies UniversityShanghaiChina
- Center for Functional Neuroimaging, Department of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
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37
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Cui Y, Li C, Liu B, Sui J, Song M, Chen J, Chen Y, Guo H, Li P, Lu L, Lv L, Ning Y, Wan P, Wang H, Wang H, Wu H, Yan H, Yan J, Yang Y, Zhang H, Zhang D, Jiang T. Consistent brain structural abnormalities and multisite individualised classification of schizophrenia using deep neural networks. Br J Psychiatry 2022; 221:732-739. [PMID: 35144702 DOI: 10.1192/bjp.2022.22] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
BACKGROUND Previous analyses of grey and white matter volumes have reported that schizophrenia is associated with structural changes. Deep learning is a data-driven approach that can capture highly compact hierarchical non-linear relationships among high-dimensional features, and therefore can facilitate the development of clinical tools for making a more accurate and earlier diagnosis of schizophrenia. AIMS To identify consistent grey matter abnormalities in patients with schizophrenia, 662 people with schizophrenia and 613 healthy controls were recruited from eight centres across China, and the data from these independent sites were used to validate deep-learning classifiers. METHOD We used a prospective image-based meta-analysis of whole-brain voxel-based morphometry. We also automatically differentiated patients with schizophrenia from healthy controls using combined grey matter, white matter and cerebrospinal fluid volumetric features, incorporated a deep neural network approach on an individual basis, and tested the generalisability of the classification models using independent validation sites. RESULTS We found that statistically reliable schizophrenia-related grey matter abnormalities primarily occurred in regions that included the superior temporal gyrus extending to the temporal pole, insular cortex, orbital and middle frontal cortices, middle cingulum and thalamus. Evaluated using leave-one-site-out cross-validation, the performance of the classification of schizophrenia achieved by our findings from eight independent research sites were: accuracy, 77.19-85.74%; sensitivity, 75.31-89.29% and area under the receiver operating characteristic curve, 0.797-0.909. CONCLUSIONS These results suggest that, by using deep-learning techniques, multidimensional neuroanatomical changes in schizophrenia are capable of robustly discriminating patients with schizophrenia from healthy controls, findings which could facilitate clinical diagnosis and treatment in schizophrenia.
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Affiliation(s)
- Yue Cui
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, China, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China and University of Chinese Academy of Sciences, China
| | - Chao Li
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, China, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China and University of Chinese Academy of Sciences, China
| | - Bing Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, China and Chinese Institute for Brain Research, China
| | - Jing Sui
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, China
| | - Ming Song
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, China, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China and University of Chinese Academy of Sciences, China
| | - Jun Chen
- Department of Radiology, Renmin Hospital of Wuhan University, China
| | - Yunchun Chen
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, China
| | - Hua Guo
- Zhumadian Psychiatric Hospital, China
| | - Peng Li
- Peking University Sixth Hospital/Institute of Mental Health, China and Key Laboratory of Mental Health, Ministry of Health (Peking University), China
| | - Lin Lu
- Peking University Sixth Hospital/Institute of Mental Health, China, Key Laboratory of Mental Health, Ministry of Health (Peking University), China and Center for Life Sciences/PKU-IDG/McGovern Institute for Brain Research, Peking University, China
| | - Luxian Lv
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, China and Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, China
| | - Yuping Ning
- Guangzhou Brain Hospital, Guangzhou Hui-Ai Hospital, The Affiliated Brain Hospital of Guangzhou Medical University, China
| | - Ping Wan
- Zhumadian Psychiatric Hospital, China
| | - Huaning Wang
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, China
| | - Huiling Wang
- Department of Psychiatry, Renmin Hospital of Wuhan University, China
| | - Huawang Wu
- Guangzhou Brain Hospital, Guangzhou Hui-Ai Hospital, The Affiliated Brain Hospital of Guangzhou Medical University, China
| | - Hao Yan
- Peking University Sixth Hospital/Institute of Mental Health, China and Key Laboratory of Mental Health, Ministry of Health (Peking University), China
| | - Jun Yan
- Peking University Sixth Hospital/Institute of Mental Health, China and Key Laboratory of Mental Health, Ministry of Health (Peking University), China
| | - Yongfeng Yang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, China, Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, China and CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, China
| | - Hongxing Zhang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, China, Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, China and Department of Psychology, Xinxiang Medical University, China
| | - Dai Zhang
- Peking University Sixth Hospital/Institute of Mental Health, China, Key Laboratory of Mental Health, Ministry of Health (Peking University), China and Center for Life Sciences/PKU-IDG/McGovern Institute for Brain Research, Peking University, China
| | - Tianzi Jiang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, China, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China and University of Chinese Academy of Sciences, China, CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, China; Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, China and Queensland Brain Institute, University of Queensland, Australia
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38
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Huang C, Zhu H. Functional hybrid factor regression model for handling heterogeneity in imaging studies. Biometrika 2022; 109:1133-1148. [PMID: 36531154 PMCID: PMC9754099 DOI: 10.1093/biomet/asac007] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2023] Open
Abstract
This paper develops a functional hybrid factor regression modelling framework to handle the heterogeneity of many large-scale imaging studies, such as the Alzheimer's disease neuroimaging initiative study. Despite the numerous successes of those imaging studies, such heterogeneity may be caused by the differences in study environment, population, design, protocols or other hidden factors, and it has posed major challenges in integrative analysis of imaging data collected from multicentres or multistudies. We propose both estimation and inference procedures for estimating unknown parameters and detecting unknown factors under our new model. The asymptotic properties of both estimation and inference procedures are systematically investigated. The finite-sample performance of our proposed procedures is assessed by using Monte Carlo simulations and a real data example on hippocampal surface data from the Alzheimer's disease study.
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Affiliation(s)
- C Huang
- Department of Statistics, Florida State University, 117 N. Woodward Ave., Tallahassee, Florida 32304, U.S.A
| | - H Zhu
- Department of Biostatistics, The University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, North Carolina 27599, U.S.A
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39
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Watanuki S. Neural mechanisms of brand love relationship dynamics: Is the development of brand love relationships the same as that of interpersonal romantic love relationships? Front Neurosci 2022; 16:984647. [PMID: 36440289 PMCID: PMC9686448 DOI: 10.3389/fnins.2022.984647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Accepted: 10/24/2022] [Indexed: 01/25/2023] Open
Abstract
Brand love is a relationship between brands and consumers. Managing the relationship is an important issue for marketing strategy since it changes according to temporal flow. Brand love theories, including their dynamics, have been developed based on interpersonal romantic love theories. Although many brand love studies have provided useful findings, the neural mechanism of brand love remains unclear. Especially, its dynamics have not been considered from a neuroscience perspective. The present study addressed the commonalities and differentiations of activated brain regions between brand love and interpersonal romantic love relationships using a quantitative neuroimaging meta-analytic approach, from the view of brain connectivity. Regarding the mental processes of each love relationship related to these activated brain regions, decoding analysis was conducted using the NeuroQuery platform to prevent reverse inference. The results revealed that different neural mechanisms and mental processes were distinctively involved in the dynamics of each love relationship, although the anterior insula overlapped across all stages and the reinforcement learning system was driven between both love relationships in the early stage. Remarkably, regarding the distinctive mental processes, although prosocial aspects were involved in the mental processes of interpersonal romantic love relationships across all stages, they were not involved in the mental processes of brand love relationships. Conclusively, although common brain regions and mental processes between both love relationships were observed, neural mechanisms and mental processes in brand love relationship dynamics might be innately different from those in the interpersonal romantic love relationship dynamics. As this finding indicates essential distinctiveness between both these relationships, theories concerning interpersonal romantic love should be applied cautiously when investigating brand love relationship dynamics.
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Affiliation(s)
- Shinya Watanuki
- Department of Marketing, Faculty of Commerce, University of Marketing and Distribution Sciences, Kobe, Japan
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40
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Cai M, Wang R, Liu M, Du X, Xue K, Ji Y, Wang Z, Zhang Y, Guo L, Qin W, Zhu W, Fu J, Liu F. Disrupted local functional connectivity in schizophrenia: An updated and extended meta-analysis. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2022; 8:93. [PMID: 36347874 PMCID: PMC9643538 DOI: 10.1038/s41537-022-00311-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 10/31/2022] [Indexed: 06/06/2023]
Abstract
Neuroimaging studies have shown that schizophrenia is associated with disruption of resting-state local functional connectivity. However, these findings vary considerably, which hampers our understanding of the underlying pathophysiological mechanisms of schizophrenia. Here, we performed an updated and extended meta-analysis to identify the most consistent changes of local functional connectivity measured by regional homogeneity (ReHo) in schizophrenia. Specifically, a systematic search of ReHo studies in patients with schizophrenia in PubMed, Embase, and Web of Science identified 18 studies (20 datasets), including 652 patients and 596 healthy controls. In addition, we included three whole-brain statistical maps of ReHo differences calculated based on independent datasets (163 patients and 194 controls). A voxel-wise meta-analysis was then conducted to investigate ReHo alterations and their relationship with clinical characteristics using the newly developed seed-based d mapping with permutation of subject images (SDM-PSI) meta-analytic approach. Compared with healthy controls, patients with schizophrenia showed significantly higher ReHo in the bilateral medial superior frontal gyrus, while lower ReHo in the bilateral postcentral gyrus, right precentral gyrus, and right middle occipital gyrus. The following sensitivity analyses including jackknife analysis, subgroup analysis, heterogeneity test, and publication bias test demonstrated that our results were robust and highly reliable. Meta-regression analysis revealed that illness duration was negatively correlated with ReHo abnormalities in the right precentral/postcentral gyrus. This comprehensive meta-analysis not only identified consistent and reliably aberrant local functional connectivity in schizophrenia but also helped to further deepen our understanding of its pathophysiology.
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Affiliation(s)
- Mengjing Cai
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Rui Wang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
- School of Medical Imaging, Tianjin Medical University, Tianjin, 300070, China
- Department of Radiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Mengge Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Xiaotong Du
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Kaizhong Xue
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Yuan Ji
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Zirui Wang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Yijing Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Lining Guo
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Wen Qin
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Wenshuang Zhu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China.
| | - Jilian Fu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China.
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China.
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Ferraro S, Klugah-Brown B, Tench CR, Bazinet V, Bore MC, Nigri A, Demichelis G, Bruzzone MG, Palermo S, Zhao W, Yao S, Jiang X, Kendrick KM, Becker B. The central autonomic system revisited – Convergent evidence for a regulatory role of the insular and midcingulate cortex from neuroimaging meta-analyses. Neurosci Biobehav Rev 2022; 142:104915. [DOI: 10.1016/j.neubiorev.2022.104915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 09/28/2022] [Accepted: 10/09/2022] [Indexed: 11/17/2022]
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Hill-Bowen LD, Riedel MC, Salo T, Flannery JS, Poudel R, Laird AR, Sutherland MT. Convergent gray matter alterations across drugs of abuse and network-level implications: A meta-analysis of structural MRI studies. Drug Alcohol Depend 2022; 240:109625. [PMID: 36115222 DOI: 10.1016/j.drugalcdep.2022.109625] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 09/01/2022] [Accepted: 09/06/2022] [Indexed: 01/06/2023]
Abstract
BACKGROUND Neuroimaging studies often consider brain alterations linked with substance abuse within the context of individual drugs (e.g., nicotine), while neurobiological theories of addiction emphasize common brain network-level alterations across drug classes. Using emergent meta-analytic techniques, we identified common structural brain alterations across drugs and characterized the functionally-connected networks with which such structurally altered regions interact. METHODS We identified 82 articles characterizing gray matter (GM) volume differences for substance users vs. controls. Using the anatomical likelihood estimation algorithm, we identified convergent GM reductions across drug classes. Next, we performed resting-state and meta-analytic functional connectivity analyses using each structurally altered region as a seed and computed whole-brain functional connectivity profiles as the union of both maps. We characterized an "extended network" by identifying brain areas demonstrating the highest degree of functional coupling with structurally impacted regions. Finally, hierarchical clustering was performed leveraging extended network nodes' functional connectivity profiles to delineate subnetworks. RESULTS Across drug classes, we identified medial frontal/ventromedial prefrontal, and multiple regions in anterior cingulate (ACC) and insula as regions displaying convergent GM reductions among users. Overlap of these regions' functional connectivity profiles identified ACC, inferior frontal, PCC, insula, superior temporal, and putamen as regions of an impacted extended network. Hierarchical clustering revealed 3 subnetworks closely corresponding to default mode (PCC, angular), salience (dACC, caudate), and executive control networks (dlPFC and parietal). CONCLUSIONS These outcomes suggest that substance-related structural brain alterations likely have implications for the functioning of canonical large-scale networks and the perpetuation of substance use and neurocognitive alterations.
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Affiliation(s)
- Lauren D Hill-Bowen
- Department of Psychology, Florida International University, 11200 SW 8th Street, Miami, FL 33199, United States
| | - Michael C Riedel
- Department of Physics, Florida International University, 11200 SW 8th Street, Miami, FL 33199, United States
| | - Taylor Salo
- Department of Psychology, Florida International University, 11200 SW 8th Street, Miami, FL 33199, United States
| | - Jessica S Flannery
- Department of Psychology and Neuroscience, University of North Carolina, Chapel Hill, NC, United States
| | - Ranjita Poudel
- Department of Psychology, Florida International University, 11200 SW 8th Street, Miami, FL 33199, United States
| | - Angela R Laird
- Department of Physics, Florida International University, 11200 SW 8th Street, Miami, FL 33199, United States
| | - Matthew T Sutherland
- Department of Psychology, Florida International University, 11200 SW 8th Street, Miami, FL 33199, United States.
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Liloia D, Crocetta A, Cauda F, Duca S, Costa T, Manuello J. Seeking Overlapping Neuroanatomical Alterations between Dyslexia and Attention-Deficit/Hyperactivity Disorder: A Meta-Analytic Replication Study. Brain Sci 2022; 12:brainsci12101367. [PMID: 36291301 PMCID: PMC9599506 DOI: 10.3390/brainsci12101367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 09/23/2022] [Accepted: 09/29/2022] [Indexed: 01/18/2023] Open
Abstract
The present work is a replication article based on the paper “Are there shared neural correlates between dyslexia and ADHD? A meta-analysis of voxel-based morphometry studies” by McGrath and Stoodley (2019). In the original research, the authors used activation likelihood estimation (ALE), a technique to perform coordinate-based meta-analysis (CBMA), to investigate the existence of brain regions undergoing gray matter alteration in association with both attention-deficit/hyper-activity disorder (ADHD) and dyslexia. Here, the same voxel-based morphometry dataset was analyzed, while using the permutation-subject images version of signed differential mapping (PSI-SDM) in place of ALE. Overall, the replication converged with the original paper in showing a limited overlap between the two conditions. In particular, no significant effect was found for dyslexia, therefore precluding any form of comparison between the two disorders. The possible influences of biological sex, age, and medication status were also ruled out. Our findings are in line with literature about gray matter alteration associated with ADHD and dyslexia, often showing conflicting results. Therefore, although neuropsychological and clinical evidence suggest some convergence between ADHD and dyslexia, more future research is sorely needed to reach a consensus on the neuroimaging domain in terms of patterns of gray matter alteration.
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Affiliation(s)
- Donato Liloia
- GCS fMRI Koelliker Group, Koelliker Hospital and University of Turin, 10124 Turin, Italy
- FOCUS Laboratory, Department of Psychology, University of Turin, 10124 Turin, Italy
| | - Annachiara Crocetta
- FOCUS Laboratory, Department of Psychology, University of Turin, 10124 Turin, Italy
| | - Franco Cauda
- GCS fMRI Koelliker Group, Koelliker Hospital and University of Turin, 10124 Turin, Italy
- FOCUS Laboratory, Department of Psychology, University of Turin, 10124 Turin, Italy
- Neuroscience Institute of Turin, 10043 Turin, Italy
- Correspondence: ; Tel.: +39-011-670-29-80; Fax: +39-011-814-62-31
| | - Sergio Duca
- GCS fMRI Koelliker Group, Koelliker Hospital and University of Turin, 10124 Turin, Italy
- FOCUS Laboratory, Department of Psychology, University of Turin, 10124 Turin, Italy
| | - Tommaso Costa
- GCS fMRI Koelliker Group, Koelliker Hospital and University of Turin, 10124 Turin, Italy
- FOCUS Laboratory, Department of Psychology, University of Turin, 10124 Turin, Italy
| | - Jordi Manuello
- GCS fMRI Koelliker Group, Koelliker Hospital and University of Turin, 10124 Turin, Italy
- FOCUS Laboratory, Department of Psychology, University of Turin, 10124 Turin, Italy
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Cai M, Liu J, Wang X, Ma J, Ma L, Liu M, Zhao Y, Wang H, Fu D, Wang W, Xu Q, Guo L, Liu F. Spontaneous brain activity abnormalities in migraine: A meta-analysis of functional neuroimaging. Hum Brain Mapp 2022; 44:571-584. [PMID: 36129066 PMCID: PMC9842892 DOI: 10.1002/hbm.26085] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Revised: 08/21/2022] [Accepted: 09/02/2022] [Indexed: 01/25/2023] Open
Abstract
Neuroimaging studies have demonstrated that migraine is accompanied by spontaneous brain activity alterations in specific regions. However, these findings are inconsistent, thus hindering our understanding of the potential neuropathology. Hence, we performed a quantitative whole-brain meta-analysis of relevant resting-state functional imaging studies to identify brain regions consistently involved in migraine. A systematic search of studies that investigated the differences in spontaneous brain activity patterns between migraineurs and healthy controls up to April 2022 was conducted. We then performed a whole-brain voxel-wise meta-analysis using the anisotropic effect size version of seed-based d mapping software. Complementary analyses including jackknife sensitivity analysis, heterogeneity test, publication bias test, subgroup analysis, and meta-regression analysis were conducted as well. In total, 24 studies that reported 31 datasets were finally eligible for our meta-analysis, including 748 patients and 690 controls. In contrast to healthy controls, migraineurs demonstrated consistent and robust decreased spontaneous brain activity in the angular gyrus, visual cortex, and cerebellum, while increased activity in the caudate, thalamus, pons, and prefrontal cortex. Results were robust and highly replicable in the following jackknife sensitivity analysis and subgroup analysis. Meta-regression analyses revealed that a higher visual analog scale score in the patient sample was associated with increased spontaneous brain activity in the left thalamus. These findings provided not only a comprehensive overview of spontaneous brain activity patterns impairments, but also useful insights into the pathophysiology of dysfunction in migraine.
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Affiliation(s)
- Mengjing Cai
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Jiawei Liu
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Xuexiang Wang
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina,Department of RadiologyTianjin Hongqiao HospitalTianjinChina
| | - Juanwei Ma
- Department of RadiologyTianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for CancerTianjinChina
| | - Lin Ma
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Mengge Liu
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Yao Zhao
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - He Wang
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Dianxun Fu
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Wenqin Wang
- School of Mathematical SciencesTiangong UniversityTianjinChina
| | - Qiang Xu
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Lining Guo
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
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Deming P, Heilicher M, Koenigs M. How reliable are amygdala findings in psychopathy? A systematic review of MRI studies. Neurosci Biobehav Rev 2022; 142:104875. [PMID: 36116578 DOI: 10.1016/j.neubiorev.2022.104875] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 08/31/2022] [Accepted: 09/13/2022] [Indexed: 10/31/2022]
Abstract
The amygdala is a key component in predominant neural circuitry models of psychopathy. Yet, after two decades of neuroimaging research on psychopathy, the reproducibility of amygdala findings is questionable. We systematically reviewed MRI studies (81 of adults, 53 of juveniles) to determine the consistency of amygdala findings across studies, as well as within specific types of experimental tasks, community versus forensic populations, and the lowest- versus highest-powered studies. Three primary findings emerged. First, the majority of studies found null relationships between psychopathy and amygdala structure and function, even in the context of theoretically relevant tasks. Second, findings of reduced amygdala activity were more common in studies with low compared to high statistical power. Third, the majority of peak coordinates of reduced amygdala activity did not fall primarily within the anatomical bounds of the amygdala. Collectively, these findings demonstrate significant gaps in the empirical support for the theorized role of the amygdala in psychopathy and indicate the need for novel research perspectives and approaches in this field.
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Affiliation(s)
- Philip Deming
- Department of Psychology, Northeastern University, 360 Huntington Ave., Boston, MA 02115, USA.
| | - Mickela Heilicher
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Blvd., Madison, WI 53719, USA
| | - Michael Koenigs
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Blvd., Madison, WI 53719, USA
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Pankey BS, Riedel MC, Cowan I, Bartley JE, Pintos Lobo R, Hill-Bowen LD, Salo T, Musser ED, Sutherland MT, Laird AR. Extended functional connectivity of convergent structural alterations among individuals with PTSD: a neuroimaging meta-analysis. Behav Brain Funct 2022; 18:9. [PMID: 36100907 PMCID: PMC9472396 DOI: 10.1186/s12993-022-00196-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Accepted: 08/27/2022] [Indexed: 02/04/2023] Open
Abstract
Background Post-traumatic stress disorder (PTSD) is a debilitating disorder defined by the onset of intrusive, avoidant, negative cognitive or affective, and/or hyperarousal symptoms after witnessing or experiencing a traumatic event. Previous voxel-based morphometry studies have provided insight into structural brain alterations associated with PTSD with notable heterogeneity across these studies. Furthermore, how structural alterations may be associated with brain function, as measured by task-free and task-based functional connectivity, remains to be elucidated. Methods Using emergent meta-analytic techniques, we sought to first identify a consensus of structural alterations in PTSD using the anatomical likelihood estimation (ALE) approach. Next, we generated functional profiles of identified convergent structural regions utilizing resting-state functional connectivity (rsFC) and meta-analytic co-activation modeling (MACM) methods. Finally, we performed functional decoding to examine mental functions associated with our ALE, rsFC, and MACM brain characterizations. Results We observed convergent structural alterations in a single region located in the medial prefrontal cortex. The resultant rsFC and MACM maps identified functional connectivity across a widespread, whole-brain network that included frontoparietal and limbic regions. Functional decoding revealed overlapping associations with attention, memory, and emotion processes. Conclusions Consensus-based functional connectivity was observed in regions of the default mode, salience, and central executive networks, which play a role in the tripartite model of psychopathology. Taken together, these findings have important implications for understanding the neurobiological mechanisms associated with PTSD. Supplementary Information The online version contains supplementary material available at 10.1186/s12993-022-00196-2.
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Gao Y, Sun J, Cheng L, Yang Q, Li J, Hao Z, Zhan L, Shi Y, Li M, Jia X, Li H. Altered resting state dynamic functional connectivity of amygdala subregions in patients with autism spectrum disorder: A multi-site fMRI study. J Affect Disord 2022; 312:69-77. [PMID: 35710036 DOI: 10.1016/j.jad.2022.06.011] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 05/31/2022] [Accepted: 06/08/2022] [Indexed: 10/18/2022]
Abstract
BACKGROUND Autism spectrum disorder (ASD) is associated with altered brain connectivity. Previous studies have focused on the static functional connectivity pattern from amygdala subregions in ASD while ignoring its dynamics. Considering that dynamic functional connectivity (dFC) can provide different perspectives, the present study aims to investigate the dFC pattern of the amygdala subregions in ASD patients. METHODS Data of 618 ASD patients and 836 typical controls (TCs) of 30 sites were obtained from the Autism Brain Imaging Data Exchange (ABIDE) database. The sliding window approach was applied to conduct seed-based dFC analysis. The seed regions were bilateral basolateral (BLA) and centromedial-superficial amygdala (CSA). A two-sample t-test was done at each site. Image-based meta-analysis (IBMA) based on the results from all sites was performed. Correlation analysis was conducted between the dFC values and the clinical scores. RESULTS The ASD patients showed lower dFC between the left BLA and the bilateral inferior temporal (ITG)/left superior frontal gyrus, between the right BLA and right ITG/right thalamus/left superior temporal gyrus, and between the right CSA and middle temporal gyrus. The ASD patients showed higher dFC between the left BLA and temporal lobe/right supramarginal gyrus, between the right BLA and left calcarine gyrus, and between the left CSA and left calcarine gyrus. Correlation analysis revealed that the symptom severity was positively correlated with the dFC between the bilateral BLA and ITG in ASD. CONCLUSIONS Abnormal dFC of the specific amygdala subregions may provide new insights into the pathological mechanisms of ASD.
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Affiliation(s)
- Yanyan Gao
- College of Teacher Education, Zhejiang Normal University, Jinhua, China; Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China
| | - Jiawei Sun
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Lulu Cheng
- School of Foreign Studies, China University of Petroleum, Qingdao, China; Shanghai Center for Research in English Language Education, Shanghai International Studies University, Shanghai, China
| | - Qihang Yang
- College of Foreign Language, Zhejiang Normal University, Jinhua, China
| | - Jing Li
- College of Teacher Education, Zhejiang Normal University, Jinhua, China; Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China
| | - Zeqi Hao
- College of Teacher Education, Zhejiang Normal University, Jinhua, China; Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China
| | - Linlin Zhan
- Faculty of Western Languages, Heilongjiang University, Harbin, China
| | - Yuyu Shi
- College of Teacher Education, Zhejiang Normal University, Jinhua, China; Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China
| | - Mengting Li
- College of Teacher Education, Zhejiang Normal University, Jinhua, China; Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China
| | - Xize Jia
- College of Teacher Education, Zhejiang Normal University, Jinhua, China; Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China.
| | - Huayun Li
- College of Teacher Education, Zhejiang Normal University, Jinhua, China; Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China.
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Hao Z, Shi Y, Huang L, Sun J, Li M, Gao Y, Li J, Wang Q, Zhan L, Ding Q, Jia X, Li H. The Atypical Effective Connectivity of Right Temporoparietal Junction in Autism Spectrum Disorder: A Multi-Site Study. Front Neurosci 2022; 16:927556. [PMID: 35924226 PMCID: PMC9340667 DOI: 10.3389/fnins.2022.927556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Accepted: 06/21/2022] [Indexed: 11/13/2022] Open
Abstract
Social function impairment is the core deficit of autism spectrum disorder (ASD). Although many studies have investigated ASD through a variety of neuroimaging tools, its brain mechanism of social function remains unclear due to its complex and heterogeneous symptoms. The present study aimed to use resting-state functional magnetic imaging data to explore effective connectivity between the right temporoparietal junction (RTPJ), one of the key brain regions associated with social impairment of individuals with ASD, and the whole brain to further deepen our understanding of the neuropathological mechanism of ASD. This study involved 1,454 participants from 23 sites from the Autism Brain Imaging Data Exchange (ABIDE) public dataset, which included 618 individuals with ASD and 836 with typical development (TD). First, a voxel-wise Granger causality analysis (GCA) was conducted with the RTPJ selected as the region of interest (ROI) to investigate the differences in effective connectivity between the ASD and TD groups in every site. Next, to obtain further accurate and representative results, an image-based meta-analysis was implemented to further analyze the GCA results of each site. Our results demonstrated abnormal causal connectivity between the RTPJ and the widely distributed brain regions and that the connectivity has been associated with social impairment in individuals with ASD. The current study could help to further elucidate the pathological mechanisms of ASD and provides a new perspective for future research.
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Affiliation(s)
- Zeqi Hao
- School of Teacher Education, Zhejiang Normal University, Jinhua, China
- Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China
| | - Yuyu Shi
- School of Teacher Education, Zhejiang Normal University, Jinhua, China
- Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China
| | - Lina Huang
- Department of Radiology, Changshu No. 2 People's Hospital, The Affiliated Changshu Hospital of Xuzhou Medical University, Changshu, China
| | - Jiawei Sun
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Mengting Li
- School of Teacher Education, Zhejiang Normal University, Jinhua, China
- Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China
| | - Yanyan Gao
- School of Teacher Education, Zhejiang Normal University, Jinhua, China
- Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China
| | - Jing Li
- School of Teacher Education, Zhejiang Normal University, Jinhua, China
- Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China
| | - Qianqian Wang
- School of Teacher Education, Zhejiang Normal University, Jinhua, China
- Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China
| | - Linlin Zhan
- School of Western Languages, Heilongjiang University, Harbin, China
| | - Qingguo Ding
- Department of Radiology, Changshu No. 2 People's Hospital, The Affiliated Changshu Hospital of Xuzhou Medical University, Changshu, China
| | - Xize Jia
- School of Teacher Education, Zhejiang Normal University, Jinhua, China
- Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China
| | - Huayun Li
- School of Teacher Education, Zhejiang Normal University, Jinhua, China
- Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, China
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Affiliation(s)
- Shannon E. Grogans
- Department of Psychology, University of Maryland, College Park, MD 20742 USA
| | - Andrew S. Fox
- Department of Psychology, University of California, Davis, CA 95616 USA,California National Primate Research Center, University of California, Davis, CA 95616 USA
| | - Alexander J. Shackman
- Department of Psychology, University of Maryland, College Park, MD 20742 USA.,Department of Neuroscience and Cognitive Science Program, University of Maryland, College Park, MD 20742 USA.,Maryland Neuroimaging Center, University of Maryland, College Park, MD 20742 USA
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50
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Evidence for non-selective response inhibition in uncertain contexts revealed by combined meta-analysis and Bayesian analysis of fMRI data. Sci Rep 2022; 12:10137. [PMID: 35710930 PMCID: PMC9203582 DOI: 10.1038/s41598-022-14221-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Accepted: 06/02/2022] [Indexed: 11/24/2022] Open
Abstract
Response inhibition is typically considered a brain mechanism selectively triggered by particular “inhibitory” stimuli or events. Based on recent research, an alternative non-selective mechanism was proposed by several authors. Presumably, the inhibitory brain activity may be triggered not only by the presentation of “inhibitory” stimuli but also by any imperative stimuli, including Go stimuli, when the context is uncertain. Earlier support for this notion was mainly based on the absence of a significant difference between neural activity evoked by equiprobable Go and NoGo stimuli. Equiprobable Go/NoGo design with a simple response time task limits potential confounds between response inhibition and accompanying cognitive processes while not preventing prepotent automaticity. However, previous neuroimaging studies used classical null hypothesis significance testing, making it impossible to accept the null hypothesis. Therefore, the current research aimed to provide evidence for the practical equivalence of neuronal activity in the Go and NoGo trials using Bayesian analysis of functional magnetic resonance imaging (fMRI) data. Thirty-four healthy participants performed a cued Go/NoGo task with an equiprobable presentation of Go and NoGo stimuli. To independently localize brain areas associated with response inhibition in similar experimental conditions, we performed a meta-analysis of fMRI studies using equal-probability Go/NoGo tasks. As a result, we observed overlap between response inhibition areas and areas that demonstrate the practical equivalence of neuronal activity located in the right dorsolateral prefrontal cortex, parietal cortex, premotor cortex, and left inferior frontal gyrus. Thus, obtained results favour the existence of non-selective response inhibition, which can act in settings of contextual uncertainty induced by the equal probability of Go and NoGo stimuli.
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