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Ashayeri H, Salehi-Pourmehr H, Ghojazadeh M. Letter to the editor. J Affect Disord 2024; 347:568. [PMID: 38092281 DOI: 10.1016/j.jad.2023.12.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2023] [Accepted: 12/08/2023] [Indexed: 01/08/2024]
Affiliation(s)
- Hamidreza Ashayeri
- Research Center for Evidence-Based Medicine, Iranian EBM Centre: A JBI Centre of Excellence, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Hanieh Salehi-Pourmehr
- Research Center for Evidence-Based Medicine, Iranian EBM Centre: A JBI Centre of Excellence, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Morteza Ghojazadeh
- Neurosciences Research Center (NSRC), Tabriz University of Medical Sciences, Tabriz, Iran.
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Rezaei S, Gharepapagh E, Rashidi F, Cattarinussi G, Sanjari Moghaddam H, Di Camillo F, Schiena G, Sambataro F, Brambilla P, Delvecchio G. Machine learning applied to functional magnetic resonance imaging in anxiety disorders. J Affect Disord 2023; 342:54-62. [PMID: 37683943 DOI: 10.1016/j.jad.2023.09.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 08/21/2023] [Accepted: 09/05/2023] [Indexed: 09/10/2023]
Abstract
BACKGROUND Brain functional abnormalities have been commonly reported in anxiety disorders, including generalized anxiety disorder, social anxiety disorder, panic disorder, agoraphobia, and specific phobias. The role of functional abnormalities in the discrimination of these disorders can be tested with machine learning (ML) techniques. Here, we aim to provide a comprehensive overview of ML studies exploring the potential discriminating role of functional brain alterations identified by functional magnetic resonance imaging (fMRI) in anxiety disorders. METHODS We conducted a search on PubMed, Web of Science, and Scopus of ML investigations using fMRI as features in patients with anxiety disorders. A total of 12 studies (resting-state fMRI n = 5, task-based fMRI n = 6, resting-state and task-based fMRI n=1) met our inclusion criteria. RESULTS Overall, the studies showed that, regardless of the classifiers, alterations in functional connectivity and aberrant neural activation involving the amygdala, anterior cingulate cortex, hippocampus, insula, orbitofrontal cortex, temporal pole, cerebellum, default mode network, dorsal attention network, sensory network, and affective network were able to discriminate patients with anxiety from controls, with accuracies spanning from 36 % to 94 %. LIMITATIONS The small sample size, different ML approaches and heterogeneity in the selection of regions included in the multivariate pattern analyses limit the conclusions of the present review. CONCLUSIONS ML methods using fMRI as features can distinguish patients with anxiety disorders from healthy controls, indicating that these techniques could be used as a helpful tool for the diagnosis and the development of more targeted treatments for these disorders.
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Affiliation(s)
- Sahar Rezaei
- Connective Tissue Diseases Research Center, Tabriz University of Medical Sciences, Tabriz, Iran; Department of Nuclear Medicine, Medical School, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Esmaeil Gharepapagh
- Connective Tissue Diseases Research Center, Tabriz University of Medical Sciences, Tabriz, Iran; Department of Nuclear Medicine, Medical School, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Fatemeh Rashidi
- Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Giulia Cattarinussi
- Department of Neuroscience (DNS), University of Padova, Padua, Italy; Padova Neuroscience Center, University of Padova, Padua, Italy
| | | | - Fabio Di Camillo
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
| | - Giandomenico Schiena
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Fabio Sambataro
- Department of Neuroscience (DNS), University of Padova, Padua, Italy; Padova Neuroscience Center, University of Padova, Padua, Italy
| | - Paolo Brambilla
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy; Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Giuseppe Delvecchio
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
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Alluri V, Toiviainen P. The naturalistic paradigm: An approach to studying individual variability in neural underpinnings of music perception. Ann N Y Acad Sci 2023; 1530:18-22. [PMID: 37847675 DOI: 10.1111/nyas.15075] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2023]
Abstract
Music listening is a dynamic process that entails complex interactions between sensory, cognitive, and emotional processes. The naturalistic paradigm provides a means to investigate these processes in an ecologically valid manner by allowing experimental settings that mimic real-life musical experiences. In this paper, we highlight the importance of the naturalistic paradigm in studying dynamic music processing and discuss how it allows for investigating both the segregation and integration of brain processes using model-based and model-free methods. We further suggest that studying individual difference-modulated music processing in this paradigm can provide insights into the mechanisms of brain plasticity, which can have implications for the development of interventions and therapies in a personalized way. Finally, despite the challenges that the naturalistic paradigm poses, we end with a discussion on future prospects of music and neuroscience research, especially with the continued development and refinement of naturalistic paradigms and the adoption of open science practices.
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Affiliation(s)
- Vinoo Alluri
- Cognitive Science Lab, International Institute of Information Technology, Hyderabad, India
| | - Petri Toiviainen
- Department of Music, Art and Culture Studies, Centre of Excellence in Music, Mind, Body and Brain, University of Jyväskylä, Jyväskylä, Finland
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Hu Z, Di X, Yang Z. Editorial: Shared responses and individual differences in the human brain during naturalistic stimulations. Front Hum Neurosci 2023; 17:1201728. [PMID: 37213928 PMCID: PMC10198652 DOI: 10.3389/fnhum.2023.1201728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 04/20/2023] [Indexed: 05/23/2023] Open
Affiliation(s)
- Zhishan Hu
- Neuroimaging Core, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xin Di
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, United States
| | - Zhi Yang
- Neuroimaging Core, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
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Mahrukh R, Shakil S, Malik AS. Sentiments analysis of fMRI using automatically generated stimuli labels under naturalistic paradigm. Sci Rep 2023; 13:7267. [PMID: 37142654 PMCID: PMC10160115 DOI: 10.1038/s41598-023-33734-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 04/18/2023] [Indexed: 05/06/2023] Open
Abstract
Our emotions and sentiments are influenced by naturalistic stimuli such as the movies we watch and the songs we listen to, accompanied by changes in our brain activation. Comprehension of these brain-activation dynamics can assist in identification of any associated neurological condition such as stress and depression, leading towards making informed decision about suitable stimuli. A large number of open-access functional magnetic resonance imaging (fMRI) datasets collected under naturalistic conditions can be used for classification/prediction studies. However, these datasets do not provide emotion/sentiment labels, which limits their use in supervised learning studies. Manual labeling by subjects can generate these labels, however, this method is subjective and biased. In this study, we are proposing another approach of generating automatic labels from the naturalistic stimulus itself. We are using sentiment analyzers (VADER, TextBlob, and Flair) from natural language processing to generate labels using movie subtitles. Subtitles generated labels are used as the class labels for positive, negative, and neutral sentiments for classification of brain fMRI images. Support vector machine, random forest, decision tree, and deep neural network classifiers are used. We are getting reasonably good classification accuracy (42-84%) for imbalanced data, which is increased (55-99%) for balanced data.
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Affiliation(s)
| | - Sadia Shakil
- Institute of Space Technology, Islamabad, Pakistan.
- Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic.
- Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia.
| | - Aamir Saeed Malik
- Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic.
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Jin S, Liu W, Hu Y, Liu Z, Xia Y, Zhang X, Ding Y, Zhang L, Xie S, Ma C, Kang Y, Hu Z, Cheng W, Yang Z. Aberrant functional connectivity of the bed nucleus of the stria terminalis and its age dependence in children and adolescents with social anxiety disorder. Asian J Psychiatr 2023; 82:103498. [PMID: 36758449 DOI: 10.1016/j.ajp.2023.103498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 01/03/2023] [Accepted: 01/30/2023] [Indexed: 02/04/2023]
Abstract
BACKGROUND Social anxiety disorder (SAD) is a prevalent and impairing mental disorder among children and adolescents. The bed nucleus of the stria terminalis (BNST) plays a critical role in anxiety disorders, including valence surveillance and hypervigilance for potential threats. However, the role of BNST and its related functional network in children and adolescents with SAD has not been fully investigated. This study examined the aberration of BNST's functional connectivity and its age dependence in adolescents with SAD. METHODS Using a sample of 75 SAD patients and 75 healthy controls (HCs) children aged 9-18 years old, we delineated the group-by-age interaction of BNST-seeded functional connectivity (FC) during resting state and movie-watching. The relationships between BNST-seeded FC and clinical scores were also examined. RESULTS During movie viewing, the FC between the right BNST and the left amygdala, bilateral posterior cingulate cortex (PCC), bilateral superior temporal cortex, and right pericalcarine cortex showed a diagnostic group-by-age interaction. Compared to HCs, SAD patients showed a significant enhancement of the above FC at younger ages. Meanwhile, they showed an age-dependent decrease in FC between the right BNST and left amygdala. Furthermore, for SAD patients, FC between the right BNST and left amygdala during movie viewing was positively correlated with separation anxiety scores. CONCLUSIONS The right BNST plays an essential role in the aberrant brain functioning in children and adolescents with SAD. The atypicality of BNST's FC has remarkable age dependence in SAD, suggesting an association of SAD with neurodevelopmental traits.
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Affiliation(s)
- Shuyu Jin
- Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Wenjing Liu
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Yang Hu
- Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Zhen Liu
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Yufeng Xia
- Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Xiaochen Zhang
- Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Yue Ding
- Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Lei Zhang
- Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Shuqi Xie
- Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Changminghao Ma
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Yinzhi Kang
- Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Zhishan Hu
- Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Wenhong Cheng
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Zhi Yang
- Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Institute of Psychological and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai, China; Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, China.
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