151
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Sun K, Liu Z, Chen G, Zhou Z, Zhong S, Tang Z, Wang S, Zhou G, Zhou X, Shao L, Ye X, Zhang Y, Jia Y, Pan J, Huang L, Liu X, Liu J, Tian J, Wang Y. A two-center radiomic analysis for differentiating major depressive disorder using multi-modality MRI data under different parcellation methods. J Affect Disord 2022; 300:1-9. [PMID: 34942222 DOI: 10.1016/j.jad.2021.12.065] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 09/13/2021] [Accepted: 12/19/2021] [Indexed: 01/09/2023]
Abstract
BACKGROUND The present study aimed to explore the difference in the brain function and structure between patients with major depressive disorder (MDD) and healthy controls (HCs) using two-center and multi-modal MRI data, which would be helpful to investigate the pathogenesis of MDD. METHODS The subjects were collected from two hospitals. One including 140 patients with MDD and 138 HCs was used as primary cohort. Another one including 29 patients with MDD and 52 HCs was used as validation cohort. Functional and structural magnetic resonance images (MRI) were acquired to extract four types of features: functional connectivity (FC), amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), and gray matter volume (GMV). Then classifiers using different combinations among the four types of selected features were respectively built to discriminate patients from HCs. Different templates were applied and the results under different templates were compared. RESULTS The classifier built with the combination of FC, ALFF, and GMV under the AAL template discriminated patients from HCs with the best performance (AUC=0.916, ACC=84.8%). The regions selected in all the different templates were mainly located in the default mode network, affective network, prefrontal cortex. LIMITATIONS First, the sample size of the validation cohort was limited. Second, diffusion tensor imaging data were not collected. CONCLUSION The performance of classifier was improved by using multi-modal MRI imaging. Different templates would be suitable for different types of analysis. The regions selected in all the different templates are possibly the core regions to investigate the pathophysiology of MDD.
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Affiliation(s)
- Kai Sun
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China; CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, China
| | - Zhenyu Liu
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Science, Beijing, China
| | - Guanmao Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Zhifeng Zhou
- Shenzhen Institute of Mental Health, Shenzhen Kangning Hospital, Shenzhen, China
| | - Shuming Zhong
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Zhenchao Tang
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, China; Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine and Engineering, Beihang University, Beijing, China
| | - Shuo Wang
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, China; Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine and Engineering, Beihang University, Beijing, China
| | - Guifei Zhou
- School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China
| | - Xuezhi Zhou
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China; CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, China
| | - Lizhi Shao
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, China; School of Computer Science and Engineering, Southeast University, Nanjing, China
| | - Xiaoying Ye
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Yingli Zhang
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Yanbin Jia
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Jiyang Pan
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Li Huang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Xia Liu
- Shenzhen Institute of Mental Health, Shenzhen Kangning Hospital, Shenzhen, China.
| | - Jiangang Liu
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine and Engineering, Beihang University, Beijing, China; Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology.
| | - Jie Tian
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China; CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, China; Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine and Engineering, Beihang University, Beijing, China; Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology; School of Artificial Intelligence, University of Chinese Academy of Science, Beijing, China.
| | - Ying Wang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, China.
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152
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Liu S, Yin N, Li C, Li X, Ni J, Pan X, Ma R, Wu J, Feng J, Shen B. Topological Abnormalities of Pallido-Thalamo-Cortical Circuit in Functional Brain Network of Patients With Nonchemotherapy With Non-small Cell Lung Cancer. Front Neurol 2022; 13:821470. [PMID: 35211086 PMCID: PMC8860807 DOI: 10.3389/fneur.2022.821470] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Accepted: 01/07/2022] [Indexed: 12/11/2022] Open
Abstract
INTRODUCTION Some previous studies in patients with lung cancer have mainly focused on exploring the cognitive dysfunction and deficits of brain function associated with chemotherapy. However, little is known about functional brain alterations that might occur prior to chemotherapy. Therefore, this study aimed to evaluate brain functional changes in patients with nonchemotherapy before chemotherapy with non-small cell lung cancer (NSCLC). METHODS Resting-state functional MRI data of 35 patients with NSCLC and 46 matched healthy controls (HCs) were acquired to construct functional brain networks. Graph theoretical analysis was then applied to investigate the differences of the network and nodal measures between groups. Finally, the receiver operating characteristic (ROC) curve analysis was performed to distinguish between NSCLC and HC. RESULTS Decreased nodal strength was found in the left inferior frontal gyrus (opercular part), inferior frontal gyrus (triangular part), inferior occipital gyrus, and right inferior frontal gyrus (triangular part) of patients with NSCLC while increased nodal strength was found in the right pallidum and thalamus. NSCLC also showed decreased nodal betweenness in the right superior occipital gyrus. Different hub regions distribution was found between groups, however, no hub regions showed group differences in the nodal measures. Furthermore, the ROC curve analysis showed good performance in distinguishing NSCLC from HC. CONCLUSION These results suggested that topological abnormalities of pallido-thalamo-cortical circuit in functional brain network might be related to NSCLC prior to chemotherapy, which provided new insights concerning the pathophysiological mechanisms of NSCLC and could serve as promising biological markers for the identification of patients with NSCLC.
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Affiliation(s)
- Siwen Liu
- Research Center for Clinical Oncology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Na Yin
- Department of Radiology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Chenchen Li
- Department of Oncology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Xiaoyou Li
- Department of Oncology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Jie Ni
- Department of Oncology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Xuan Pan
- Department of Oncology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Rong Ma
- Research Center for Clinical Oncology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Jianzhong Wu
- Research Center for Clinical Oncology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Jifeng Feng
- Research Center for Clinical Oncology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China.,Department of Oncology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Bo Shen
- Department of Oncology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
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153
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Singh P, Wa Torek M, Ceglarek A, Fąfrowicz M, Lewandowska K, Marek T, Sikora-Wachowicz B, Oświȩcimka P. Analysis of fMRI Signals from Working Memory Tasks and Resting-State of Brain: Neutrosophic-Entropy-Based Clustering Algorithm. Int J Neural Syst 2022; 32:2250012. [PMID: 35179104 DOI: 10.1142/s0129065722500125] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
This study applies a neutrosophic-entropy-based clustering algorithm (NEBCA) to analyze the fMRI signals. We consider the data obtained from four different working memory tasks and the brain's resting state for the experimental purpose. Three non-overlapping clusters of data related to temporal brain activity are determined and statistically analyzed. Moreover, we used the Uniform Manifold Approximation and Projection (UMAP) method to reduce system dimensionality and present the effectiveness of NEBCA. The results show that using NEBCA, we are able to distinguish between different working memory tasks and resting-state and identify subtle differences in the related activity of brain regions. By analyzing the statistical properties of the entropy inside the clusters, the various regions of interest (ROIs), according to Automated Anatomical Labeling (AAL) atlas crucial for clustering procedure, are determined. The inferior occipital gyrus is established as an important brain region in distinguishing the resting state from the tasks. Moreover, the inferior occipital gyrus and superior parietal lobule are identified as necessary to correct the data discrimination related to the different memory tasks. We verified the statistical significance of the results through the two-sample t-test and analysis of surrogates performed by randomization of the cluster elements. The presented methodology is also appropriate to determine the influence of time of day on brain activity patterns. The differences between working memory tasks and resting-state in the morning are related to a lower index of small-worldness and sleep inertia in the first hours after waking. We also compared the performance of NEBCA to two existing algorithms, KMCA and FKMCA. We showed the advantage of the NEBCA over these algorithms that could not effectively accumulate fMRI signals with higher variability.
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Affiliation(s)
- Pritpal Singh
- Institute of Theoretical Physics, Jagiellonian University, Kraków 30-348, Poland
| | - Marcin Wa Torek
- Institute of Theoretical Physics, Jagiellonian University, Kraków 30-348, Poland.,Faculty of Computer Science and Telecommunications, Cracow University of Technology, Kraków 31-155, Poland
| | - Anna Ceglarek
- Department of Cognitive Neuroscience and Neuroergonomics, Jagiellonian University, Kraków 30-348, Poland
| | - Magdalena Fąfrowicz
- Department of Cognitive Neuroscience and Neuroergonomics, Jagiellonian University, Kraków 30-348, Poland
| | - Koryna Lewandowska
- Department of Cognitive Neuroscience and Neuroergonomics, Jagiellonian University, Kraków 30-348, Poland
| | - Tadeusz Marek
- Department of Cognitive Neuroscience and Neuroergonomics, Jagiellonian University, Kraków 30-348, Poland
| | - Barbara Sikora-Wachowicz
- Department of Cognitive Neuroscience and Neuroergonomics, Jagiellonian University, Kraków 30-348, Poland
| | - Paweł Oświȩcimka
- Institute of Theoretical Physics, Jagiellonian University, Kraków 30-348, Poland.,Complex Systems Theory Department, Institute of Nuclear Physics, Polish Academy of Sciences, Kraków 31-342, Poland
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154
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Kaplan S, Meyer D, Miranda-Dominguez O, Perrone A, Earl E, Alexopoulos D, Barch DM, Day TK, Dust J, Eggebrecht AT, Feczko E, Kardan O, Kenley JK, Rogers CE, Wheelock MD, Yacoub E, Rosenberg M, Elison JT, Fair DA, Smyser CD. Filtering respiratory motion artifact from resting state fMRI data in infant and toddler populations. Neuroimage 2022; 247:118838. [PMID: 34942363 PMCID: PMC8803544 DOI: 10.1016/j.neuroimage.2021.118838] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 11/30/2021] [Accepted: 12/18/2021] [Indexed: 11/24/2022] Open
Abstract
The importance of motion correction when processing resting state functional magnetic resonance imaging (rs-fMRI) data is well-established in adult cohorts. This includes adjustments based on self-limited, large amplitude subject head motion, as well as factitious rhythmic motion induced by respiration. In adults, such respiration artifact can be effectively removed by applying a notch filter to the motion trace, resulting in higher amounts of data retained after frame censoring (e.g., "scrubbing") and more reliable correlation values. Due to the unique physiological and behavioral characteristics of infants and toddlers, rs-fMRI processing pipelines, including methods to identify and remove colored noise due to subject motion, must be appropriately modified to accurately reflect true neuronal signal. These younger cohorts are characterized by higher respiration rates and lower-amplitude head movements than adults; thus, the presence and significance of comparable respiratory artifact and the subsequent necessity of applying similar techniques remain unknown. Herein, we identify and characterize the consistent presence of respiratory artifact in rs-fMRI data collected during natural sleep in infants and toddlers across two independent cohorts (aged 8-24 months) analyzed using different pipelines. We further demonstrate how removing this artifact using an age-specific notch filter allows for both improved data quality and data retention in measured results. Importantly, this work reveals the critical need to identify and address respiratory-driven head motion in fMRI data acquired in young populations through the use of age-specific motion filters as a mechanism to optimize the accuracy of measured results in this population.
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Affiliation(s)
- Sydney Kaplan
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.
| | - Dominique Meyer
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Oscar Miranda-Dominguez
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA,Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Anders Perrone
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA,Department of Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | - Eric Earl
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA,Department of Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | - Dimitrios Alexopoulos
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Deanna M. Barch
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA,Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA,Department of Psychological and Brain Sciences, Washington University School of Medicine, St. Louis, MO, USA
| | - Trevor K.M. Day
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
| | - Joseph Dust
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Adam T. Eggebrecht
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Eric Feczko
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA,Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Omid Kardan
- Department of Psychology, University of Chicago, Chicago, IL, USA
| | - Jeanette K. Kenley
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Cynthia E. Rogers
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, USA,Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Muriah D. Wheelock
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Essa Yacoub
- Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Monica Rosenberg
- Department of Psychology, University of Chicago, Chicago, IL, USA
| | - Jed T. Elison
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA,Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA,Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Damien A. Fair
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA,Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA,Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA,Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Christopher D. Smyser
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA,Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA,Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, USA
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155
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A hands-on tutorial on network and topological neuroscience. Brain Struct Funct 2022; 227:741-762. [PMID: 35142909 PMCID: PMC8930803 DOI: 10.1007/s00429-021-02435-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 11/23/2021] [Indexed: 02/08/2023]
Abstract
The brain is an extraordinarily complex system that facilitates the optimal integration of information from different regions to execute its functions. With the recent advances in technology, researchers can now collect enormous amounts of data from the brain using neuroimaging at different scales and from numerous modalities. With that comes the need for sophisticated tools for analysis. The field of network neuroscience has been trying to tackle these challenges, and graph theory has been one of its essential branches through the investigation of brain networks. Recently, topological data analysis has gained more attention as an alternative framework by providing a set of metrics that go beyond pairwise connections and offer improved robustness against noise. In this hands-on tutorial, our goal is to provide the computational tools to explore neuroimaging data using these frameworks and to facilitate their accessibility, data visualisation, and comprehension for newcomers to the field. We will start by giving a concise (and by no means complete) overview of the field to introduce the two frameworks and then explain how to compute both well-established and newer metrics on resting-state functional magnetic resonance imaging. We use an open-source language (Python) and provide an accompanying publicly available Jupyter Notebook that uses the 1000 Functional Connectomes Project dataset. Moreover, we would like to highlight one part of our notebook dedicated to the realistic visualisation of high order interactions in brain networks. This pipeline provides three-dimensional (3-D) plots of pairwise and higher-order interactions projected in a brain atlas, a new feature tailor-made for network neuroscience.
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156
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Li W, Kong X, Ma J. Effects of combat sports on cerebellar function in adolescents: a resting-state fMRI study. Br J Radiol 2022; 95:20210826. [PMID: 34918548 PMCID: PMC8822571 DOI: 10.1259/bjr.20210826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
OBJECTIVES To evaluate the effects of combat sports on cerebellar function in adolescents based on resting-state functional MRI (rs-fMRI). METHODS Rs-fMRI data were acquired from the combat sports (CS) group (n = 32, aged 14.2 ± 1.1 years) and non-athlete healthy control (HC) group (n = 29, aged 14.8 ± 0.9 years). The amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and functional connectivity (FC) within the cerebellum was calculated and then compared between the two groups. RESULTS None of these participants displayed intracranial lesions on conventional MRI and microhemorrhages on SWI. Compared with the HC group, the CS group showed decreased ALFF and ReHo in the bilateral cerebellum, mainly located in the inferior regions of the cerebellum (Cerebellum_8, Cerebellum_9, Cerebellum_7b, and Cerebellum_Crus2). While increased FC was found within the cerebellar network, mainly located in the superior regions near the midline (bilateral Cerebellum_6, Cerebellum_Crus1_R, and Vermis_6). There is no internetwork FC change between the CEN and other networks. CONCLUSION This study confirmed extensive effects of combat sports on cerebellar rs-fMRI in adolescents, which could enhance the understanding of cerebellar regulatory mechanism under combat conditions, and provide additional information about cerebellar protective inhibition and compensatory adaptation. ADVANCES IN KNOWLEDGE Adolescent combat participants are an ideal model to study training-induced brain plasticity and vulnerability. Relative to task-related fMRI, rs-fMRI can bring more information about cerebellar regulation and explain the Central Governor Model more comprehensively.
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Affiliation(s)
- Wei Li
- Department of Medical Imaging, Affiliated Hospital Of Yangzhou University, Yangzhou, China
| | - Xin Kong
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jun Ma
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
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157
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Towards reliable spinal cord fMRI: assessment of common imaging protocols. Neuroimage 2022; 250:118964. [DOI: 10.1016/j.neuroimage.2022.118964] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 01/07/2022] [Accepted: 02/01/2022] [Indexed: 01/29/2023] Open
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158
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Kulkarni PH, Merchant S, Awate SP. Mixed-Dictionary Models and Variational Inference in Task fMRI for Shorter Scans and Better Image Quality. Med Image Anal 2022; 78:102392. [DOI: 10.1016/j.media.2022.102392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 10/31/2021] [Accepted: 02/10/2022] [Indexed: 11/28/2022]
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159
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Nash K, Kleinert T, Leota J, Scott A, Schimel J. Resting-state networks of believers and non-believers: An EEG microstate study. Biol Psychol 2022; 169:108283. [PMID: 35114302 DOI: 10.1016/j.biopsycho.2022.108283] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 01/25/2022] [Accepted: 01/26/2022] [Indexed: 11/02/2022]
Abstract
Atheism and agnosticism are becoming increasingly popular, yet the neural processes underpinning individual differences in religious belief and non-belief remain poorly understood. In the current study, we examined differences between Believers and Non-Believers with regard to fundamental neural resting networks using EEG microstate analysis. Results demonstrated that Non-Believers show increased contribution from a resting-state network associated with deliberative or analytic processing (Microstate D), and Believers show increased contribution from a network associated with intuitive or automatic processing (Microstate C). Further, analysis of resting-state network communication suggested that Non-Believers may process visual information in a more deliberative or top-down manner, and Believers may process visual information in a more intuitive or bottom-up manner. These results support dual process explanations of individual differences in religious belief and add to the representation of non-belief as more than merely a lack of belief.
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Affiliation(s)
- Kyle Nash
- Department of Psychology, University of Alberta, Edmonton AB T6G 2R3, Canada.
| | - Tobias Kleinert
- Department of Psychology, University of Alberta, Edmonton AB T6G 2R3, Canada
| | - Josh Leota
- Department of Psychology, University of Alberta, Edmonton AB T6G 2R3, Canada
| | - Andy Scott
- Department of Psychology, University of Alberta, Edmonton AB T6G 2R3, Canada
| | - Jeff Schimel
- Department of Psychology, University of Alberta, Edmonton AB T6G 2R3, Canada
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160
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Tibon R, Tsvetanov KA. The "Neural Shift" of Sleep Quality and Cognitive Aging: A Resting-State MEG Study of Transient Neural Dynamics. Front Aging Neurosci 2022; 13:746236. [PMID: 35173599 PMCID: PMC8842663 DOI: 10.3389/fnagi.2021.746236] [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: 07/23/2021] [Accepted: 12/21/2021] [Indexed: 11/18/2022] Open
Abstract
Sleep quality changes dramatically from young to old age, but its effects on brain dynamics and cognitive functions are not yet fully understood. We tested the hypothesis that a shift in brain networks dynamics relates to sleep quality and cognitive performance across the lifespan. Network dynamics were assessed using Hidden Markov Models (HMMs) in resting-state MEG data from a large cohort of population-based adults (N = 564, aged 18-88). Using multivariate analyses of brain-sleep profiles and brain-cognition profiles, we found an age-related "neural shift," expressed as decreased occurrence of "lower-order" brain networks coupled with increased occurrence of "higher-order" networks. This "neural shift" was associated with both increased sleep dysfunction and decreased fluid intelligence, and this relationship was not explained by age, sex or other covariates. These results establish the link between poor sleep quality, as evident in aging, and a behavior-related shift in neural dynamics.
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Affiliation(s)
- Roni Tibon
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom
| | - Kamen A. Tsvetanov
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
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161
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What Can Resting-State fMRI Data Analysis Explain about the Functional Brain Connectivity in Glioma Patients? Tomography 2022; 8:267-280. [PMID: 35202187 PMCID: PMC8878995 DOI: 10.3390/tomography8010021] [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: 12/20/2021] [Revised: 01/12/2022] [Accepted: 01/14/2022] [Indexed: 11/24/2022] Open
Abstract
Resting-state functional MRI has been increasingly implemented in imaging protocols for the study of functional connectivity in glioma patients as a sequence able to capture the activity of brain networks and to investigate their properties without requiring the patients’ cooperation. The present review aims at describing the most recent results obtained through the analysis of resting-state fMRI data in different contexts of interest for brain gliomas: the identification and localization of functional networks, the characterization of altered functional connectivity, and the evaluation of functional plasticity in relation to the resection of the glioma. An analysis of the literature showed that significant and promising results could be achieved through this technique in all the aspects under investigation. Nevertheless, there is room for improvement, especially in terms of stability and generalizability of the outcomes. Further research should be conducted on homogeneous samples of glioma patients and at fixed time points to reduce the considerable variability in the results obtained across and within studies. Future works should also aim at establishing robust metrics for the assessment of the disruption of functional connectivity and its recovery at the single-subject level.
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162
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Bukkieva T, Pospelova M, Efimtsev A, Fionik O, Alekseeva T, Samochernych K, Gorbunova E, Krasnikova V, Makhanova A, Levchuk A, Trufanov G, Combs S, Shevtsov M. Functional Network Connectivity Reveals the Brain Functional Alterations in Breast Cancer Survivors. J Clin Med 2022; 11:jcm11030617. [PMID: 35160070 PMCID: PMC8837129 DOI: 10.3390/jcm11030617] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 12/29/2021] [Accepted: 01/10/2022] [Indexed: 02/04/2023] Open
Abstract
Different neurological and psychiatric disorders such as vertebrobasilar insufficiency, chronic pain syndrome, anxiety, and depression are observed in more than 90% of patients after treatment for breast cancer and may cause alterations in the functional connectivity of the default mode network. The purpose of the present study is to assess changes in the functional connectivity of the default mode network in patients after breast cancer treatment using resting state functional magnetic resonance imaging (rs-fMRI). Rs-fMRI was performed using a 3.0T MR-scanner on patients (N = 46, women) with neurological disorders (chronic pain, dizziness, headaches, and/or tinnitus) in the late postoperative period (>12 months) after Patey radical mastectomy for breast cancer. According to the intergroup statistical analysis, there were differences in the functional connectivity of the default mode network in all 46 patients after breast cancer treatment compared to the control group (p < 0.01). The use of rs-fMRI in in breast cancer survivors allowed us to identify changes in the functional connectivity in the brain caused by neurological disorders, which correlated with a decreased quality of life in these patients. The results indicate the necessity to improve treatment and rehabilitation methods in this group of patients.
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Affiliation(s)
- Tatyana Bukkieva
- Personalized Medicine Centre, Almazov National Medical Research Centre, 2 Akkuratova Str., 197341 Saint Petersburg, Russia; (T.B.); (M.P.); (A.E.); (O.F.); (T.A.); (K.S.); (E.G.); (V.K.); (A.M.); (A.L.); (G.T.)
| | - Maria Pospelova
- Personalized Medicine Centre, Almazov National Medical Research Centre, 2 Akkuratova Str., 197341 Saint Petersburg, Russia; (T.B.); (M.P.); (A.E.); (O.F.); (T.A.); (K.S.); (E.G.); (V.K.); (A.M.); (A.L.); (G.T.)
| | - Aleksandr Efimtsev
- Personalized Medicine Centre, Almazov National Medical Research Centre, 2 Akkuratova Str., 197341 Saint Petersburg, Russia; (T.B.); (M.P.); (A.E.); (O.F.); (T.A.); (K.S.); (E.G.); (V.K.); (A.M.); (A.L.); (G.T.)
| | - Olga Fionik
- Personalized Medicine Centre, Almazov National Medical Research Centre, 2 Akkuratova Str., 197341 Saint Petersburg, Russia; (T.B.); (M.P.); (A.E.); (O.F.); (T.A.); (K.S.); (E.G.); (V.K.); (A.M.); (A.L.); (G.T.)
| | - Tatyana Alekseeva
- Personalized Medicine Centre, Almazov National Medical Research Centre, 2 Akkuratova Str., 197341 Saint Petersburg, Russia; (T.B.); (M.P.); (A.E.); (O.F.); (T.A.); (K.S.); (E.G.); (V.K.); (A.M.); (A.L.); (G.T.)
| | - Konstantin Samochernych
- Personalized Medicine Centre, Almazov National Medical Research Centre, 2 Akkuratova Str., 197341 Saint Petersburg, Russia; (T.B.); (M.P.); (A.E.); (O.F.); (T.A.); (K.S.); (E.G.); (V.K.); (A.M.); (A.L.); (G.T.)
| | - Elena Gorbunova
- Personalized Medicine Centre, Almazov National Medical Research Centre, 2 Akkuratova Str., 197341 Saint Petersburg, Russia; (T.B.); (M.P.); (A.E.); (O.F.); (T.A.); (K.S.); (E.G.); (V.K.); (A.M.); (A.L.); (G.T.)
| | - Varvara Krasnikova
- Personalized Medicine Centre, Almazov National Medical Research Centre, 2 Akkuratova Str., 197341 Saint Petersburg, Russia; (T.B.); (M.P.); (A.E.); (O.F.); (T.A.); (K.S.); (E.G.); (V.K.); (A.M.); (A.L.); (G.T.)
| | - Albina Makhanova
- Personalized Medicine Centre, Almazov National Medical Research Centre, 2 Akkuratova Str., 197341 Saint Petersburg, Russia; (T.B.); (M.P.); (A.E.); (O.F.); (T.A.); (K.S.); (E.G.); (V.K.); (A.M.); (A.L.); (G.T.)
| | - Anatoliy Levchuk
- Personalized Medicine Centre, Almazov National Medical Research Centre, 2 Akkuratova Str., 197341 Saint Petersburg, Russia; (T.B.); (M.P.); (A.E.); (O.F.); (T.A.); (K.S.); (E.G.); (V.K.); (A.M.); (A.L.); (G.T.)
| | - Gennadiy Trufanov
- Personalized Medicine Centre, Almazov National Medical Research Centre, 2 Akkuratova Str., 197341 Saint Petersburg, Russia; (T.B.); (M.P.); (A.E.); (O.F.); (T.A.); (K.S.); (E.G.); (V.K.); (A.M.); (A.L.); (G.T.)
| | - Stephanie Combs
- Department of Radiation Oncology, Technishe Universität München (TUM), Klinikum rechts der Isar, Ismaningerstr. 22, 81675 Munich, Germany;
| | - Maxim Shevtsov
- Personalized Medicine Centre, Almazov National Medical Research Centre, 2 Akkuratova Str., 197341 Saint Petersburg, Russia; (T.B.); (M.P.); (A.E.); (O.F.); (T.A.); (K.S.); (E.G.); (V.K.); (A.M.); (A.L.); (G.T.)
- Department of Radiation Oncology, Technishe Universität München (TUM), Klinikum rechts der Isar, Ismaningerstr. 22, 81675 Munich, Germany;
- Laboratory of Biomedical Nanotechnologies, Institute of Cytology of the Russian Academy of Sciences (RAS), Tikhoretsky Ave. 4, 194064 Saint Petersburg, Russia
- Correspondence: ; Tel.: +7-981-829-4848
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Cauzzo S, Singh K, Stauder M, García-Gomar MG, Vanello N, Passino C, Staab J, Indovina I, Bianciardi M. Functional connectome of brainstem nuclei involved in autonomic, limbic, pain and sensory processing in living humans from 7 Tesla resting state fMRI. Neuroimage 2022; 250:118925. [PMID: 35074504 DOI: 10.1016/j.neuroimage.2022.118925] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 11/24/2021] [Accepted: 01/18/2022] [Indexed: 12/13/2022] Open
Abstract
Despite remarkable advances in mapping the functional connectivity of the cortex, the functional connectivity of subcortical regions is understudied in living humans. This is the case for brainstem nuclei that control vital processes, such as autonomic, limbic, nociceptive and sensory functions. This is because of the lack of precise brainstem nuclei localization, of adequate sensitivity and resolution in the deepest brain regions, as well as of optimized processing for the brainstem. To close the gap between the cortex and the brainstem, on 20 healthy subjects, we computed a correlation-based functional connectome of 15 brainstem nuclei involved in autonomic, limbic, nociceptive, and sensory function (superior and inferior colliculi, ventral tegmental area-parabrachial pigmented nucleus complex, microcellular tegmental nucleus-prabigeminal nucleus complex, lateral and medial parabrachial nuclei, vestibular and superior olivary complex, superior and inferior medullary reticular formation, viscerosensory motor nucleus, raphe magnus, pallidus, and obscurus, and parvicellular reticular nucleus - alpha part) with the rest of the brain. Specifically, we exploited 1.1mm isotropic resolution 7 Tesla resting-state fMRI, ad-hoc coregistration and physiological noise correction strategies, and a recently developed probabilistic template of brainstem nuclei. Further, we used 2.5mm isotropic resolution resting-state fMRI data acquired on a 3 Tesla scanner to assess the translatability of our results to conventional datasets. We report highly consistent correlation coefficients across subjects, confirming available literature on autonomic, limbic, nociceptive and sensory pathways, as well as high interconnectivity within the central autonomic network and the vestibular network. Interestingly, our results showed evidence of vestibulo-autonomic interactions in line with previous work. Comparison of 7 Tesla and 3 Tesla findings showed high translatability of results to conventional settings for brainstem-cortical connectivity and good yet weaker translatability for brainstem-brainstem connectivity. The brainstem functional connectome might bring new insight in the understanding of autonomic, limbic, nociceptive and sensory function in health and disease.
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Affiliation(s)
- Simone Cauzzo
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States; Life Sciences Institute, Sant'Anna School of Advanced Studies, Pisa, Italy.
| | - Kavita Singh
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Matthew Stauder
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - María Guadalupe García-Gomar
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Nicola Vanello
- Dipartimento di Ingegneria dell'Informazione, University of Pisa, Pisa, Italy
| | - Claudio Passino
- Life Sciences Institute, Sant'Anna School of Advanced Studies, Pisa, Italy; Dipartimento di Ingegneria dell'Informazione, University of Pisa, Pisa, Italy; Fondazione Toscana Gabriele Monasterio, Pisa, Italy
| | - Jeffrey Staab
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States; Department of Otorhinolaryngology - Head and Neck Surgery, Mayo Clinic, Rochester, MN, United States
| | - Iole Indovina
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Italy; Laboratory of Neuromotor Physiology, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Marta Bianciardi
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States; Division of Sleep Medicine, Harvard University, Boston, MA.
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164
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Singh K, Cauzzo S, García-Gomar MG, Stauder M, Vanello N, Passino C, Bianciardi M. Functional connectome of arousal and motor brainstem nuclei in living humans by 7 Tesla resting-state fMRI. Neuroimage 2022; 249:118865. [PMID: 35031472 DOI: 10.1016/j.neuroimage.2021.118865] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 11/30/2021] [Accepted: 12/27/2021] [Indexed: 01/21/2023] Open
Abstract
Brainstem nuclei play a pivotal role in many functions, such as arousal and motor control. Nevertheless, the connectivity of arousal and motor brainstem nuclei is understudied in living humans due to the limited sensitivity and spatial resolution of conventional imaging, and to the lack of atlases of these deep tiny regions of the brain. For a holistic comprehension of sleep, arousal and associated motor processes, we investigated in 20 healthy subjects the resting-state functional connectivity of 18 arousal and motor brainstem nuclei in living humans. To do so, we used high spatial-resolution 7 Tesla resting-state fMRI, as well as a recently developed in-vivo probabilistic atlas of these nuclei in stereotactic space. Further, we verified the translatability of our brainstem connectome approach to conventional (e.g. 3 Tesla) fMRI. Arousal brainstem nuclei displayed high interconnectivity, as well as connectivity to the thalamus, hypothalamus, basal forebrain and frontal cortex, in line with animal studies and as expected for arousal regions. Motor brainstem nuclei showed expected connectivity to the cerebellum, basal ganglia and motor cortex, as well as high interconnectivity. Comparison of 3 Tesla to 7 Tesla connectivity results indicated good translatability of our brainstem connectome approach to conventional fMRI, especially for cortical and subcortical (non-brainstem) targets and to a lesser extent for brainstem targets. The functional connectome of 18 arousal and motor brainstem nuclei with the rest of the brain might provide a better understanding of arousal, sleep and accompanying motor function in living humans in health and disease.
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Affiliation(s)
- Kavita Singh
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
| | - Simone Cauzzo
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States; Institute of Life Sciences, Sant'Anna School of Advanced Studies, Pisa, Italy
| | - María Guadalupe García-Gomar
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Matthew Stauder
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Nicola Vanello
- Dipartimento di Ingegneria dell'Informazione, University of Pisa, Pisa, Italy
| | - Claudio Passino
- Institute of Life Sciences, Sant'Anna School of Advanced Studies, Pisa, Italy; Fondazione Toscana Gabriele Monasterio, Pisa, Italy
| | - Marta Bianciardi
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States; Division of Sleep Medicine, Harvard University, Boston, MA.
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165
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Hou J, Mohanty R, Chu D, Nair VA, Danilov Y, Kaczmarek KA, Meyerand B, Tyler M, Prabhakaran V. Translingual neural stimulation affects resting-state functional connectivity in mild-moderate traumatic brain injury. J Neuroimaging 2022; 32:1193-1200. [PMID: 35906713 PMCID: PMC9649856 DOI: 10.1111/jon.13029] [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: 05/19/2022] [Revised: 07/11/2022] [Accepted: 07/12/2022] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND AND PURPOSE Traumatic brain injury (TBI) can lead to movement and balance deficits. In addition to physical therapy, brain-based neurorehabilitation efforts have begun to show promise in improving these deficits. The present study investigated the effectiveness of translingual neural stimulation (TLNS) on patients with mild-to-moderate TBI (mmTBI) and related brain connectivity using a resting-state functional connectivity (RSFC) approach. METHODS Resting-state images with 5-min on GE750 3T scanner were acquired from nine participants with mmTBI. Paired t-test was used for calculating changes in RSFC and behavioral scores before and after the TLNS intervention. The balance and movement performances related to mmTBI were evaluated by Sensory Organization Test (SOT) and Dynamic Gait Index (DGI). RESULTS Compared to pre-TLNS intervention, significant behavioral changes in SOT and DGI were observed. The analysis revealed increased RSFC between the left postcentral gyrus and left inferior parietal lobule and left Brodmann Area 40, as well as the increased RSFC between the right culmen and right declive, indicating changes due to TLNS treatment. However, there were no correlations between the sensory/somatomotor (or visual or cerebellar) network and SOT/DGI behavioral performance. CONCLUSIONS Although the limited sample size may have led to lack of significant correlations with functional assessments, these results provide preliminary evidence that TLNS in conjunction with physical therapy can induce brain plasticity in TBI patients with balance and movement deficits.
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Affiliation(s)
- Jiancheng Hou
- Research Center for Cross‐Straits Cultural DevelopmentFujian Normal UniversityFuzhouChina,Department of Radiology, School of Medicine and Public HealthUniversity of Wisconsin–MadisonMadisonWisconsinUSA
| | | | - Daniel Chu
- Department of Radiology, School of Medicine and Public HealthUniversity of Wisconsin–MadisonMadisonWisconsinUSA
| | - Veena A. Nair
- Department of Radiology, School of Medicine and Public HealthUniversity of Wisconsin–MadisonMadisonWisconsinUSA
| | - Yuri Danilov
- Department of KinesiologyUniversity of Wisconsin–MadisonMadisonWisconsinUSA
| | - Kurt A. Kaczmarek
- Department of KinesiologyUniversity of Wisconsin–MadisonMadisonWisconsinUSA
| | - Beth Meyerand
- Department of Biomedical EngineeringUniversity of Wisconsin–MadisonMadisonWisconsinUSA
| | - Mitchell Tyler
- Department of KinesiologyUniversity of Wisconsin–MadisonMadisonWisconsinUSA,Department of Biomedical EngineeringUniversity of Wisconsin–MadisonMadisonWisconsinUSA
| | - Vivek Prabhakaran
- Department of Radiology, School of Medicine and Public HealthUniversity of Wisconsin–MadisonMadisonWisconsinUSA
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166
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Hassanzadeh R, Silva RF, Abrol A, Salman M, Bonkhoff A, Du Y, Fu Z, DeRamus T, Damaraju E, Baker B, Calhoun VD. Individualized spatial network predictions using Siamese convolutional neural networks: A resting-state fMRI study of over 11,000 unaffected individuals. PLoS One 2022; 17:e0249502. [PMID: 35061657 PMCID: PMC8782493 DOI: 10.1371/journal.pone.0249502] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Accepted: 12/07/2021] [Indexed: 11/20/2022] Open
Abstract
Individuals can be characterized in a population according to their brain measurements and activity, given the inter-subject variability in brain anatomy, structure-function relationships, or life experience. Many neuroimaging studies have demonstrated the potential of functional network connectivity patterns estimated from resting functional magnetic resonance imaging (fMRI) to discriminate groups and predict information about individual subjects. However, the predictive signal present in the spatial heterogeneity of brain connectivity networks is yet to be extensively studied. In this study, we investigate, for the first time, the use of pairwise-relationships between resting-state independent spatial maps to characterize individuals. To do this, we develop a deep Siamese framework comprising three-dimensional convolution neural networks for contrastive learning based on individual-level spatial maps estimated via a fully automated fMRI independent component analysis approach. The proposed framework evaluates whether pairs of spatial networks (e.g., visual network and auditory network) are capable of subject identification and assesses the spatial variability in different network pairs' predictive power in an extensive whole-brain analysis. Our analysis on nearly 12,000 unaffected individuals from the UK Biobank study demonstrates that the proposed approach can discriminate subjects with an accuracy of up to 88% for a single network pair on the test set (best model, after several runs), and 82% average accuracy at the subcortical domain level, notably the highest average domain level accuracy attained. Further investigation of our network's learned features revealed a higher spatial variability in predictive accuracy among younger brains and significantly higher discriminative power among males. In sum, the relationship among spatial networks appears to be both informative and discriminative of individuals and should be studied further as putative brain-based biomarkers.
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Affiliation(s)
- Reihaneh Hassanzadeh
- Department of Computer Science, Georgia State University, Atlanta, GA, United States of America
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United States of America
- * E-mail:
| | - Rogers F. Silva
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United States of America
| | - Anees Abrol
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United States of America
| | - Mustafa Salman
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United States of America
- School of Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States of America
| | - Anna Bonkhoff
- J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States of America
| | - Yuhui Du
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United States of America
| | - Zening Fu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United States of America
| | - Thomas DeRamus
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United States of America
| | - Eswar Damaraju
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United States of America
| | - Bradley Baker
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United States of America
- School of Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States of America
| | - Vince D. Calhoun
- Department of Computer Science, Georgia State University, Atlanta, GA, United States of America
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United States of America
- School of Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States of America
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Yang YC, Zeng K, Wang W, Gong ZG, Chen YL, Cheng JM, Zhang M, Huang YW, Men XB, Wang JW, Zhan S, Tan WL. The Changes of Brain Function After Spinal Manipulation Therapy in Patients with Chronic Low Back Pain: A Rest BOLD fMRI Study. Neuropsychiatr Dis Treat 2022; 18:187-199. [PMID: 35153482 PMCID: PMC8828077 DOI: 10.2147/ndt.s339762] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 01/22/2022] [Indexed: 12/16/2022] Open
Abstract
OBJECTIVE To investigate the changes of regional homogeneity (Reho) values before and after spinal manipulative therapy (SMT) in patients with chronic low back pain (CLBP) through rest blood-oxygen-level-dependent functional magnetic resonance imaging (BOLD fMRI). METHODS Patients with CLBP (Group 1, n = 20) and healthy control subjects (Group 2, n = 20) were recruited. The fMRI was performed three times in Group 1 before SMT (time point 1, TP1), after the first SMT (time point 2, TP2), after the sixth SMT (time point 3, TP3), and for one time in Group 2, which received no intervention. The clinical scales were finished in Group 1 every time before fMRI was performed. The Reho values were compared among Group 1 at different time points, and between Group 1 and Group 2. The correlation between Reho values with the statistical differences and the clinical scale scores were calculated. RESULTS The bilateral precuneus and right mid-frontal gyrus in Group 1 had different Reho values compared with Group 2 at TP1. The Reho values were increased in the left precuneus and decreased in the left superior frontal gyrus in Group 1 at TP2 compared with TP1. The Reho values were increased in the left postcentral gyrus and decreased in the left posterior cingulate cortex and the superior frontal gyrus in Group 1 at TP3 compared with TP1. The ReHo values of the left precuneus in Group 1 at TP1 were negatively correlated with the pain degree at TP1 and TP2 (r = -0.549, -0.453; p = 0.012, 0.045). The Reho values of the middle temporal gyrus in Group 1 at TP3 were negatively correlated with the changes of clinical scale scores between TP3 and TP1 (r = 0.454, 0.559; p = 0.044, 0.01). CONCLUSION Patients with CLBP showed abnormal brain function activity, which was altered after SMT. The Reho values of the left precuneus could predict the immediate analgesic effect of SMT.
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Affiliation(s)
- Yu-Chan Yang
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People's Republic of China
| | - Ke Zeng
- Department of Massage, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People's Republic of China
| | - Wei Wang
- Department of Massage, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People's Republic of China
| | - Zhi-Gang Gong
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People's Republic of China
| | - Yi-Lei Chen
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People's Republic of China
| | - Jian-Ming Cheng
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People's Republic of China
| | - Min Zhang
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People's Republic of China
| | - Yan-Wen Huang
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People's Republic of China
| | - Xin-Bo Men
- Department of Massage, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People's Republic of China
| | - Jian-Wei Wang
- Department of Massage, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People's Republic of China
| | - Songhua Zhan
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People's Republic of China
| | - Wen-Li Tan
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People's Republic of China
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McCulloch DEW, Madsen MK, Stenbæk DS, Kristiansen S, Ozenne B, Jensen PS, Knudsen GM, Fisher PM. Lasting effects of a single psilocybin dose on resting-state functional connectivity in healthy individuals. J Psychopharmacol 2022; 36:74-84. [PMID: 34189985 PMCID: PMC8801642 DOI: 10.1177/02698811211026454] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
Abstract
BACKGROUND Psilocybin is a psychedelic drug that has shown lasting positive effects on clinical symptoms and self-reported well-being following a single dose. There has been little research into the long-term effects of psilocybin on brain connectivity in humans. AIM Evaluate changes in resting-state functional connectivity (RSFC) at 1 week and 3 months after one psilocybin dose in 10 healthy psychedelic-naïve volunteers and explore associations between change in RSFC and related measures. METHODS Participants received 0.2-0.3 mg/kg psilocybin in a controlled setting. Participants completed resting-state functional magnetic resonance imaging (fMRI) scans at baseline, 1-week and 3-month post-administration and [11C]Cimbi-36 PET scans at baseline and 1 week. We examined changes in within-network, between-network and region-to-region RSFC. We explored associations between changes in RSFC and psilocybin-induced phenomenology as well as changes in psychological measures and neocortex serotonin 2A receptor binding. RESULTS Psilocybin was well tolerated and produced positive changes in well-being. At 1 week only, executive control network (ECN) RSFC was significantly decreased (Cohen's d = -1.73, pFWE = 0.010). We observed no other significant changes in RSFC at 1 week or 3 months, nor changes in region-to-region RSFC. Exploratory analyses indicated that decreased ECN RSFC at 1 week predicted increased mindfulness at 3 months (r = -0.65). CONCLUSIONS These findings in a small cohort indicate that psilocybin affects ECN function within the psychedelic 'afterglow' period. Our findings implicate ECN modulation as mediating psilocybin-induced, long-lasting increases in mindfulness. Although our findings implicate a neural pathway mediating lasting psilocybin effects, it is notable that changes in neuroimaging measures at 3 months, when personality changes are observed, remain to be identified.
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Affiliation(s)
| | - Martin Korsbak Madsen
- Neurobiology Research Unit and NeuroPharm, Rigshospitalet, Copenhagen, Denmark,Institute of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Dea Siggaard Stenbæk
- Neurobiology Research Unit and NeuroPharm, Rigshospitalet, Copenhagen, Denmark,Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Sara Kristiansen
- Neurobiology Research Unit and NeuroPharm, Rigshospitalet, Copenhagen, Denmark
| | - Brice Ozenne
- Neurobiology Research Unit and NeuroPharm, Rigshospitalet, Copenhagen, Denmark,Section of Biostatistics, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Peter Steen Jensen
- Neurobiology Research Unit and NeuroPharm, Rigshospitalet, Copenhagen, Denmark
| | - Gitte Moos Knudsen
- Neurobiology Research Unit and NeuroPharm, Rigshospitalet, Copenhagen, Denmark,Institute of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Patrick MacDonald Fisher
- Neurobiology Research Unit and NeuroPharm, Rigshospitalet, Copenhagen, Denmark,Patrick MacDonald Fisher, Neurobiology Research Unit, Rigshospitalet Building 8057, 8 Inge Lehmanns Vej, Copenhagen 2100, Denmark.
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169
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Nenning KH, Langs G. Machine learning in neuroimaging: from research to clinical practice. RADIOLOGIE (HEIDELBERG, GERMANY) 2022; 62:1-10. [PMID: 36044070 PMCID: PMC9732070 DOI: 10.1007/s00117-022-01051-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 07/07/2022] [Indexed: 12/14/2022]
Abstract
Neuroimaging is critical in clinical care and research, enabling us to investigate the brain in health and disease. There is a complex link between the brain's morphological structure, physiological architecture, and the corresponding imaging characteristics. The shape, function, and relationships between various brain areas change during development and throughout life, disease, and recovery. Like few other areas, neuroimaging benefits from advanced analysis techniques to fully exploit imaging data for studying the brain and its function. Recently, machine learning has started to contribute (a) to anatomical measurements, detection, segmentation, and quantification of lesions and disease patterns, (b) to the rapid identification of acute conditions such as stroke, or (c) to the tracking of imaging changes over time. As our ability to image and analyze the brain advances, so does our understanding of its intricate relationships and their role in therapeutic decision-making. Here, we review the current state of the art in using machine learning techniques to exploit neuroimaging data for clinical care and research, providing an overview of clinical applications and their contribution to fundamental computational neuroscience.
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Affiliation(s)
- Karl-Heinz Nenning
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, USA
- Department of Biomedical Imaging and Image-guided Therapy, Computational Imaging Research Lab, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
| | - Georg Langs
- Department of Biomedical Imaging and Image-guided Therapy, Computational Imaging Research Lab, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.
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170
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Kok TE, Domingo D, Hassan J, Vuong A, Hordacre B, Clark C, Katrakazas P, Shekhawat GS. Resting-state Networks in Tinnitus : A Scoping Review. Clin Neuroradiol 2022; 32:903-922. [PMID: 35556148 PMCID: PMC9744700 DOI: 10.1007/s00062-022-01170-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 04/07/2022] [Indexed: 12/16/2022]
Abstract
Chronic subjective tinnitus is the constant perception of a sound that has no physical source. Brain imaging studies show alterations in tinnitus patients' resting-state networks (RSNs). This scoping review aims to provide an overview of resting-state fMRI studies in tinnitus, and to evaluate the evidence for changes in different RSNs. A total of 29 studies were included, 26 of which found alterations in networks such as the auditory network, default mode network, attention networks, and visual network; however, there is a lack of reproducibility in the field which can be attributed to the use of different regions of interest and analytical methods per study, and tinnitus heterogeneity. Future studies should focus on replication by using the same regions of interest in their analysis of resting-state data, and by controlling adequately for potential confounds. These efforts could potentially lead to the identification of a biomarker for tinnitus in the future.
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Affiliation(s)
- Tori Elyssa Kok
- grid.83440.3b0000000121901201Ear Institute, University College London, London, UK
| | - Deepti Domingo
- grid.1014.40000 0004 0367 2697College of Medicine and Public Health, Flinders University, Adelaide, Australia
| | - Joshua Hassan
- grid.1014.40000 0004 0367 2697College of Medicine and Public Health, Flinders University, Adelaide, Australia
| | - Alysha Vuong
- grid.1014.40000 0004 0367 2697College of Medicine and Public Health, Flinders University, Adelaide, Australia
| | - Brenton Hordacre
- grid.1026.50000 0000 8994 5086Innovation, IMPlementation and Clinical Translation (IIMPACT) in Health, Allied Health and Human Performance, University of South Australia, Adelaide, Australia
| | - Chris Clark
- grid.83440.3b0000000121901201Great Ormond Street Institute of Child Health, Department of Developmental Imaging and Biophysics, University College London, London, UK
| | | | - Giriraj Singh Shekhawat
- grid.83440.3b0000000121901201Ear Institute, University College London, London, UK ,grid.1014.40000 0004 0367 2697College of Medicine and Public Health, Flinders University, Adelaide, Australia ,Tinnitus Research Initiative, Regensburg, Germany
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171
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Du Y, Yang W, Zhang J, Liu J. Changes in ALFF and ReHo values in methamphetamine abstinent individuals based on the Harvard-Oxford atlas: A longitudinal resting-state fMRI study. Addict Biol 2022; 27:e13080. [PMID: 34427375 PMCID: PMC9286454 DOI: 10.1111/adb.13080] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 05/24/2021] [Accepted: 07/14/2021] [Indexed: 01/10/2023]
Abstract
Methamphetamine (MA) abuse has become a global public health problem due to damage to various systems throughout the body, especially the central nervous system. However, the differences in resting‐state brain function between short‐term and long‐term abstinence, the pros and cons of treatments, and the relationship between resting‐state brain function and behavioral tests are unknown. Sixty‐three MA abstinent individuals were followed up for nearly 1 year and treated with three different methods. The amplitude of low‐frequency fluctuation (ALFF) and regional homogeneity (ReHo) based on the Harvard‐Oxford atlas (HOA) were measured by resting‐state functional magnetic resonance imaging (fMRI). Impulsivity was evaluated by the Barratt Impulsivity Scale‐11 (BIS‐11). Brain regions with significant increases in ALFF and ReHo values in the long‐term abstinent group compared to the short‐term abstinent group were around the right frontal pole (McKetin et al., 2012, https://doi.org/10.1111/j.1360-0443.2012.03933.x) and right middle frontal gyrus (Wang et al., 2015, https://doi.org/10.1371/journal.pone.0133431). There were no significant differences among the three groups that experienced long‐term abstinence. The changes in ALFF and ReHo in the right middle frontal gyrus were significantly associated with BIS total scores, BIS attention scores, and BIS nonplanning scores. The right middle frontal gyrus is a critical region in MA long‐term abstinent individuals exposed to therapeutic intervention, and this region may be useful, when combined with BIS‐11, as a potential biomarker to identify the effect of abstinence with therapeutic intervention in MA individuals.
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Affiliation(s)
- Yanyao Du
- Department of Radiology Second Xiangya Hospital of Central South University Changsha China
| | - Wenhan Yang
- Department of Radiology Second Xiangya Hospital of Central South University Changsha China
| | - Jun Zhang
- Department of Detoxification Treatment Technology Hunan Judicial Police Vocational College Changsha China
| | - Jun Liu
- Department of Radiology Second Xiangya Hospital of Central South University Changsha China
- Clinical Research Center for Medical Imaging in Hunan Province Changsha China
- Department of Radiology Quality Control Center Changsha China
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172
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Li C, Liu Y, Yang N, Lan Z, Huang S, Wu Y, Ma X, Jiang G. Functional Connectivity Disturbances of the Locus Coeruleus in Chronic Insomnia Disorder. Nat Sci Sleep 2022; 14:1341-1350. [PMID: 35942365 PMCID: PMC9356738 DOI: 10.2147/nss.s366234] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 07/14/2022] [Indexed: 11/25/2022] Open
Abstract
INTRODUCTION In recent years, people have gained a profound understanding of chronic insomnia disorder (CID), but the pathophysiological mechanism of CID is still unclear. There is some evidence that the locus coeruleus (LC) is involved in the regulation of wakefulness in CID, but there have been few studies using brain functional imaging. The purpose of this study was to evaluate the resting-state functional connectivity (FC) between the LC and other brain voxels in CID and whether these abnormal FC are involved in the regulation of wakefulness. METHODS A total of 49 patients with chronic insomnia disorder and 47 healthy controls (HC) matched for gender, age, and education were examined with rs-fMRI in this study. The LC was selected as the region of interest, and then seed-based analysis was conducted on the LC and other voxels to obtain the brain regions with abnormal FC. The correlation between the FC value of the abnormal connection area and the clinical scale score was analyzed. RESULTS Compared with the HC, the FC between the LC and right precuneus, right posterior cingulate cortex, left middle temporal gyrus, left calcarine, and right superior orbitofrontal cortex was significantly enhanced (p < 0.05, FDR correction), and the functional connectivity signal value between the locus coeruleus and left middle temporal gyrus was positively correlated with the Self-Rating Depression Scale (p = 0.021). CONCLUSION The abnormal FC between the LC and multiple brain regions may contribute to a better understanding of the neurobiological mechanism of CID.
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Affiliation(s)
- Chunlong Li
- Department of Medical Imaging, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People' s Republic of China
| | - Yuexia Liu
- Department of Ultrasound, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, People' s Republic of China
| | - Ning Yang
- Department of Medical Imaging, Guangdong Second Provincial General Hospital, Guangzhou, People's Republic of China
| | - Zhihong Lan
- Department of Medical Imaging, Zhuhai City People's Hospital, Zhuhai, People's Republic of China
| | - Shumei Huang
- Department of Medical Imaging, Guangdong Second Provincial General Hospital, Guangzhou, People's Republic of China
| | - Yunfan Wu
- Department of Medical Imaging, Guangdong Second Provincial General Hospital, Guangzhou, People's Republic of China
| | - Xiaofen Ma
- Department of Medical Imaging, Guangdong Second Provincial General Hospital, Guangzhou, People's Republic of China
| | - Guihua Jiang
- Department of Medical Imaging, Guangdong Second Provincial General Hospital, Guangzhou, People's Republic of China
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173
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Chen B. A Preliminary Study of Abnormal Centrality of Cortical Regions and Subsystems in Whole Brain Functional Connectivity of Autism Spectrum Disorder Boys. Clin EEG Neurosci 2022; 53:3-11. [PMID: 34152841 DOI: 10.1177/15500594211026282] [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: 11/17/2022]
Abstract
The abnormal cortices of autism spectrum disorder (ASD) brains are uncertain. However, the pathological alterations of ASD brains are distributed throughout interconnected cortical systems. Functional connections (FCs) methodology identifies cooperation and separation characteristics of information process in macroscopic cortical activity patterns under the context of network neuroscience. Embracing the graph theory concepts, this paper introduces eigenvector centrality index (EC score) ground on the FCs, and further develops a new framework for researching the dysfunctional cortex of ASD in holism significance. The important process is to uncover noticeable regions and subsystems endowed with antagonistic stance in EC-scores of 26 ASD boys and 28 matched healthy controls (HCs). For whole brain regional EC scores of ASD boys, orbitofrontal superior medial cortex, insula R, posterior cingulate gyrus L, and cerebellum 9 L are endowed with different EC scores significantly. In the brain subsystems level, EC scores of DMN, prefrontal lobe, and cerebellum are aberrant in the ASD boys. Generally, the EC scores display widespread distribution of diseased regions in ASD brains. Meanwhile, the discovered regions and subsystems, such as MPFC, AMYG, INS, prefrontal lobe, and DMN, are engaged in social processing. Meanwhile, the CBCL externalizing problem scores are associated with EC scores.
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Affiliation(s)
- Bo Chen
- 12626Hangzhou Dianzi University, Hangzhou, Zhejiang, PR China
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174
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Langenecker SA, Westlund Schreiner M, Thomas LR, Bessette KL, DelDonno SR, Jenkins LM, Easter RE, Stange JP, Pocius SL, Dillahunt A, Love TM, Phan KL, Koppelmans V, Paulus M, Lindquist MA, Caffo B, Mickey BJ, Welsh RC. Using Network Parcels and Resting-State Networks to Estimate Correlates of Mood Disorder and Related Research Domain Criteria Constructs of Reward Responsiveness and Inhibitory Control. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2022; 7:76-84. [PMID: 34271215 PMCID: PMC8748287 DOI: 10.1016/j.bpsc.2021.06.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 05/14/2021] [Accepted: 06/13/2021] [Indexed: 01/03/2023]
Abstract
BACKGROUND Resting-state graph-based network edges can be powerful tools for identification of mood disorders. We address whether these edges can be integrated with Research Domain Criteria (RDoC) constructs for accurate identification of mood disorder-related markers, while minimizing active symptoms of disease. METHODS We compared 132 individuals with currently remitted or euthymic mood disorder with 65 healthy comparison participants, ages 18-30 years. Subsets of smaller brain parcels, combined into three prominent networks and one network of parcels overlapping across these networks, were used to compare edge differences between groups. Consistent with the RDoC framework, we evaluated individual differences with performance measure regressors of inhibitory control and reward responsivity. Within an omnibus regression model, we predicted edges related to diagnostic group membership, performance within both RDoC domains, and relevant interactions. RESULTS There were several edges of mood disorder group, predominantly of greater connectivity across networks, different than those related to individual differences in inhibitory control and reward responsivity. Edges related to diagnosis and inhibitory control did not align well with prior literature, whereas edges in relation to reward responsivity constructs showed greater alignment with prior literature. Those edges in interaction between RDoC constructs and diagnosis showed a divergence for inhibitory control (negative interactions in default mode) relative to reward (positive interactions with salience and emotion network). CONCLUSIONS In conclusion, there is evidence that prior simple network models of mood disorders are currently of insufficient biological or diagnostic clarity or that parcel-based edges may be insufficiently sensitive for these purposes.
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Affiliation(s)
| | | | - Leah R Thomas
- Department of Psychiatry, University of Utah, Salt Lake City, Utah; Department of Psychology, University of Utah, Salt Lake City, Utah
| | - Katie L Bessette
- Department of Psychiatry, University of Utah, Salt Lake City, Utah; Department of Psychiatry & Psychology, University of Illinois at Chicago, Chicago, Illinois
| | - Sophia R DelDonno
- Department of Psychiatry & Psychology, University of Illinois at Chicago, Chicago, Illinois
| | - Lisanne M Jenkins
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Evanston, Illinois
| | - Rebecca E Easter
- Department of Psychiatry & Psychology, University of Illinois at Chicago, Chicago, Illinois
| | - Jonathan P Stange
- Department of Psychiatry & Psychology, University of Illinois at Chicago, Chicago, Illinois; Department of Psychology, University of Southern California, Los Angeles, California
| | | | - Alina Dillahunt
- Department of Psychiatry, University of Utah, Salt Lake City, Utah
| | - Tiffany M Love
- Department of Psychiatry, University of Utah, Salt Lake City, Utah
| | - K Luan Phan
- Department of Psychiatry and Behavioral Health, The Ohio State University, Columbus, Ohio
| | | | - Martin Paulus
- Laureate Institute for Brain Research, Tulsa, Oklahoma
| | | | - Brian Caffo
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Brian J Mickey
- Department of Psychiatry, University of Utah, Salt Lake City, Utah
| | - Robert C Welsh
- Department of Psychiatry, University of Utah, Salt Lake City, Utah
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175
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Resting-State Functional Magnetic Resonance Imaging for Surgical Neuro-Oncology Planning: Towards a Standardization in Clinical Settings. Brain Sci 2021; 11:brainsci11121613. [PMID: 34942915 PMCID: PMC8699779 DOI: 10.3390/brainsci11121613] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 11/26/2021] [Accepted: 12/02/2021] [Indexed: 02/03/2023] Open
Abstract
Resting-state functional magnetic resonance imaging (rest-f-MRI) is a neuroimaging technique that has demonstrated its potential in providing new insights into brain physiology. rest-f-MRI can provide useful information in pre-surgical mapping aimed to balancing long-term survival by maximizing the extent of resection of brain neoplasms, while preserving the patient’s functional connectivity. Rest-fMRI may replace or can be complementary to task-driven fMRI (t-fMRI), particularly in patients unable to cooperate with the task paradigm, such as children or sedated, paretic, aphasic patients. Although rest-fMRI is still under standardization, this technique has been demonstrated to be feasible and valuable in the routine clinical setting for neurosurgical planning, along with intraoperative electrocortical mapping. In the literature, there is growing evidence that rest-fMRI can provide valuable information for the depiction of glioma-related functional brain network impairment. Accordingly, rest-fMRI could allow a tailored glioma surgery improving the surgeon’s ability to increase the extent of resection (EOR), and simultaneously minimize the risk of damage of eloquent brain structures and neuronal networks responsible for the integrity of executive functions. In this article, we present a review of the literature and illustrate the feasibility of rest-fMRI in the clinical setting for presurgical mapping of eloquent networks in patients affected by brain tumors, before and after tumor resection.
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176
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Sims JR, Chen AM, Sun Z, Deng W, Colwell NA, Colbert MK, Zhu J, Sainulabdeen A, Faiq MA, Bang JW, Chan KC. Role of Structural, Metabolic, and Functional MRI in Monitoring Visual System Impairment and Recovery. J Magn Reson Imaging 2021; 54:1706-1729. [PMID: 33009710 PMCID: PMC8099039 DOI: 10.1002/jmri.27367] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Revised: 08/24/2020] [Accepted: 08/27/2020] [Indexed: 12/13/2022] Open
Abstract
The visual system, consisting of the eyes and the visual pathways of the brain, receives and interprets light from the environment so that we can perceive the world around us. A wide variety of disorders can affect human vision, ranging from ocular to neurologic to systemic in nature. While other noninvasive imaging techniques such as optical coherence tomography and ultrasound can image particular sections of the visual system, magnetic resonance imaging (MRI) offers high resolution without depth limitations. MRI also gives superior soft-tissue contrast throughout the entire pathway compared to computed tomography. By leveraging different imaging sequences, MRI is uniquely capable of unveiling the intricate processes of ocular anatomy, tissue physiology, and neurological function in the human visual system from the microscopic to macroscopic levels. In this review we discuss how structural, metabolic, and functional MRI can be used in the clinical assessment of normal and pathologic states in the anatomic structures of the visual system, including the eyes, optic nerves, optic chiasm, optic tracts, visual brain nuclei, optic radiations, and visual cortical areas. We detail a selection of recent clinical applications of MRI at each position along the visual pathways, including the evaluation of pathology, plasticity, and the potential for restoration, as well as its limitations and key areas of ongoing exploration. Our discussion of the current and future developments in MR ocular and neuroimaging highlights its potential impact on our ability to understand visual function in new detail and to improve our protection and treatment of anatomic structures that are integral to this fundamental sensory system. LEVEL OF EVIDENCE 3: TECHNICAL EFFICACY STAGE 3: .
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Affiliation(s)
- Jeffrey R. Sims
- Department of Ophthalmology, NYU Grossman School of Medicine, NYU Langone Health, New York University, New York, New York, USA
| | - Anna M. Chen
- Department of Ophthalmology, NYU Grossman School of Medicine, NYU Langone Health, New York University, New York, New York, USA
- Sackler Institute of Graduate Biomedical Sciences, NYU Grossman School of Medicine, NYU Langone Health, New York University, New York, New York, USA
| | - Zhe Sun
- Department of Ophthalmology, NYU Grossman School of Medicine, NYU Langone Health, New York University, New York, New York, USA
- Sackler Institute of Graduate Biomedical Sciences, NYU Grossman School of Medicine, NYU Langone Health, New York University, New York, New York, USA
| | - Wenyu Deng
- Department of Ophthalmology, NYU Grossman School of Medicine, NYU Langone Health, New York University, New York, New York, USA
| | - Nicole A. Colwell
- Department of Ophthalmology, NYU Grossman School of Medicine, NYU Langone Health, New York University, New York, New York, USA
| | - Max K. Colbert
- Department of Ophthalmology, NYU Grossman School of Medicine, NYU Langone Health, New York University, New York, New York, USA
| | - Jingyuan Zhu
- Department of Ophthalmology, NYU Grossman School of Medicine, NYU Langone Health, New York University, New York, New York, USA
- Department of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Anoop Sainulabdeen
- Department of Ophthalmology, NYU Grossman School of Medicine, NYU Langone Health, New York University, New York, New York, USA
- Department of Surgery and Radiology, College of Veterinary and Animal Sciences, Kerala Veterinary and Animal Sciences University, Thrissur, India
| | - Muneeb A. Faiq
- Department of Ophthalmology, NYU Grossman School of Medicine, NYU Langone Health, New York University, New York, New York, USA
| | - Ji Won Bang
- Department of Ophthalmology, NYU Grossman School of Medicine, NYU Langone Health, New York University, New York, New York, USA
| | - Kevin C. Chan
- Department of Ophthalmology, NYU Grossman School of Medicine, NYU Langone Health, New York University, New York, New York, USA
- Sackler Institute of Graduate Biomedical Sciences, NYU Grossman School of Medicine, NYU Langone Health, New York University, New York, New York, USA
- Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, New York University, New York, New York, USA
- Neuroscience Institute, NYU Grossman School of Medicine, NYU Langone Health, New York University, New York, New York, USA
- Center for Neural Science, College of Arts and Science, New York University, New York, New York, USA
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177
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Li ZY, Si LH, Shen B, Yang X. Altered brain network functional connectivity patterns in patients with vestibular migraine diagnosed according to the diagnostic criteria of the Bárány Society and the International Headache Society. J Neurol 2021; 269:3026-3036. [PMID: 34792633 PMCID: PMC9119883 DOI: 10.1007/s00415-021-10868-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 10/12/2021] [Accepted: 10/20/2021] [Indexed: 11/29/2022]
Abstract
Background Vestibular migraine (VM) is considered one of the most common causes of episodic central vestibular disorders, the mechanism of VM is currently still unclear. The development of functional nuclear magnetic resonance (fMRI) in recent years offers the possibility to explore the altered functional connectivity patterns in patients with VM in depth. The study aimed to investigate altered patterns of brain network functional connectivity in patients with VM diagnosed based on the diagnostic criteria of the Bárány Society and the International Headache Society, and hope to provide a scientific theoretical basis for understanding whether VM is a no-structural central vestibular disease, i.e., functional central vestibular disease with altered brain function. Methods Seventeen patients with VM who received treatment in our hospital from December 2018 to December 2020 were enrolled. Eight patients with migraine and 17 health controls (HCs) were also included. Clinical data of all patients were collected. Blood pressure, blood routine tests and electrocardiography were conducted to exclude other diseases associated with chronic dizziness. Videonystagmography, the vestibular caloric test, the video head impulse test and vestibular-evoked myogenic potentials were measured to exclude peripheral vestibular lesions. MRI was utilized to exclude focal lesions and other neurological diseases. All subjects underwent fMRI. The independent component analysis was performed to explore changes in intra- and inter-network functional connectivity in patients with VM. Results Among 17 patients with VM, there were 7 males and 10 females with an average age of 39.47 ± 9.78 years old. All patients had a history of migraine. Twelve (70.6%) patients had recurrent spontaneous vertigo, 2 (11.7%) patients had visually induced vertigo, and 3 (17.6%) patients had head motion-induced vertigo. All 17 patients with VM reported worsening of dizziness vertigo during visual stimulation. The migraine-like symptoms were photophobia or phonophobia (n = 15, 88.2%), migraine-like headache (n = 8, 47.1%), visual aura during VM onset (n = 7, 41.2%). 5 (29.4%) patients with VM had hyperactive response during the caloric test, and 12 (70.6%) patients had caloric test intolerance. Eleven (64.7%) patients had a history of motion sickness. Totally 13 independent components were identified. Patients with VM showed decreased functional connectivity in the bilateral medial cingulate gyrus and paracingulate gyrus within sensorimotor network (SMN) compared with HCs. They also showed weakened functional connectivity between auditory network (AN) and anterior default mode network (aDMN) compared with HCs, and enhanced functional connectivity between AN and the salience network (SN) compared with patients with migraine. Conclusion Patients with vestibular migraine showed obvious altered functional connectivity in the bilateral medial cingulate gyrus and paracingulate gyrus within the SMN. The median cingulate and paracingulate gyri may be impaired, the disinhibition of sensorimotor network and vestibular cortical network may result in a hypersensitivity state (photophobia/phonophobia). Altered functional connectivity between AN and DMN, SN may lead to increased sensitivity to vestibular sensory processing.
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Affiliation(s)
- Zhe-Yuan Li
- Department of Neurology, Aerospace Center Hospital, Peking University Aerospace School of Clinical Medicine, Beijing, 100049, People's Republic of China
| | - Li-Hong Si
- Department of Neurology, Aerospace Center Hospital, Peking University Aerospace School of Clinical Medicine, Beijing, 100049, People's Republic of China
| | - Bo Shen
- Department of Neurology, Aerospace Center Hospital, Peking University Aerospace School of Clinical Medicine, Beijing, 100049, People's Republic of China
| | - Xu Yang
- Department of Neurology, Aerospace Center Hospital, Peking University Aerospace School of Clinical Medicine, Beijing, 100049, People's Republic of China.
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178
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Yu XM, Qiu LL, Huang HX, Zuo X, Zhou ZH, Wang S, Liu HS, Tian L. Comparison of resting-state spontaneous brain activity between treatment-naive schizophrenia and obsessive-compulsive disorder. BMC Psychiatry 2021; 21:544. [PMID: 34732149 PMCID: PMC8565005 DOI: 10.1186/s12888-021-03554-y] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Accepted: 10/18/2021] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Schizophrenia (SZ) and obsessive-compulsive disorder (OCD) share many demographic characteristics and severity of clinical symptoms, genetic risk factors, pathophysiological underpinnings, and brain structure and function. However, the differences in the spontaneous brain activity patterns between the two diseases remain unclear. Here this study aimed to compare the features of intrinsic brain activity in treatment-naive participants with SZ and OCD and to explore the relationship between spontaneous brain activity and the severity of symptoms. METHODS In this study, 22 treatment-naive participants with SZ, 27 treatment-naive participants with OCD, and sixty healthy controls (HC) underwent a resting-state functional magnetic resonance imaging (fMRI) scan. The amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo) and degree of centrality (DC) were performed to examine the intrinsic brain activity of participants. Additionally, the relationships among spontaneous brain activity, the severity of symptoms, and the duration of illness were explored in SZ and OCD groups. RESULTS Compared with SZ group and HC group, participants with OCD had significantly higher ALFF in the right angular gyrus and the left middle frontal gyrus/precentral gyrus and significantly lower ALFF in the left superior temporal gyrus/insula/rolandic operculum and the left postcentral gyrus, while there was no significant difference in ALFF between SZ group and HC group. Compared with HC group, lower ALFF in the right supramarginal gyrus/inferior parietal lobule and lower DC in the right lingual gyrus/calcarine fissure and surrounding cortex of the two patient groups, higher ReHo in OCD group and lower ReHo in SZ group in the right angular gyrus/middle occipital gyrus brain region were documented in the present study. DC in SZ group was significantly higher than that in HC group in the right inferior parietal lobule/angular gyrus, while there were no significant DC differences between OCD group and HC group. In addition, ALFF in the left postcentral gyrus were positively correlated with positive subscale score (r = 0.588, P = 0.013) and general psychopathology subscale score (r = 0.488, P = 0.047) respectively on the Positive and Negative Syndrome Scale (PANSS) in SZ group. ALFF in the left superior temporal gyrus/insula/rolandic operculum of participants with OCD were positively correlated with compulsion subscale score (r = 0.463, P = 0.030) on the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS). The longer the illness duration in SZ group, the smaller the ALFF of the left superior temporal gyrus/insula/rolandic operculum (Rho = 0.-492, P = 0.020). The longer the illness duration in OCD group, the higher the ALFF of the right supramarginal gyrus/inferior parietal lobule (Rho = 0.392, P = 0.043) and the left postcentral gyrus (Rho = 0.385, P = 0.048), and the lower the DC of the right inferior parietal lobule/angular gyrus (Rho = - 0.518, P = 0.006). CONCLUSION SZ and OCD show some similarities in spontaneous brain activity in parietal and occipital lobes, but exhibit different patterns of spontaneous brain activity in frontal, temporal, parietal, occipital, and insula brain regions, which might imply different underlying neurobiological mechanisms in the two diseases. Compared with OCD, SZ implicates more significant abnormalities in the functional connections among brain regions.
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Affiliation(s)
- Xiao-Man Yu
- grid.89957.3a0000 0000 9255 8984Department of Psychiatry, the Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi, Jiangsu 214151 People’s Republic of China
| | - Lin-Lin Qiu
- grid.186775.a0000 0000 9490 772XSchool of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, Anhui 230032 People’s Republic of China ,grid.186775.a0000 0000 9490 772XAnhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders & Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, Anhui 230032 People’s Republic of China
| | - Hai-Xia Huang
- Department of Medical Imaging, Huadong Sanatorium, Wuxi, Jiangsu 214065 People’s Republic of China
| | - Xiang Zuo
- Department of Medical Imaging, Huadong Sanatorium, Wuxi, Jiangsu 214065 People’s Republic of China
| | - Zhen-He Zhou
- Department of Psychiatry, the Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi, Jiangsu, 214151, People's Republic of China.
| | - Shuai Wang
- grid.89957.3a0000 0000 9255 8984Department of Psychiatry, the Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi, Jiangsu 214151 People’s Republic of China
| | - Hai-Sheng Liu
- grid.89957.3a0000 0000 9255 8984Department of Psychiatry, the Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi, Jiangsu 214151 People’s Republic of China
| | - Lin Tian
- Department of Psychiatry, the Affiliated Wuxi Mental Health Center of Nanjing Medical University, Wuxi, Jiangsu, 214151, People's Republic of China.
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179
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Huang S, Zeng W, Shi Y. Internet-like brain hierarchical network model: Alzheimer's disease study as an example. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021; 211:106393. [PMID: 34551380 DOI: 10.1016/j.cmpb.2021.106393] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 08/30/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND AND OBJECTIVE The modular structure and hierarchy are important topological characteristics in real complex networks such as brain networks on temporal scale. However, there are few studies investigating the hierarchical structure at the spatial scale of brain networks, the application of which still remains to be further studied. METHODS In this study, a novel model of brain hierarchical network based on the hierarchical characteristic of Internet topology is proposed for the first time, which is called Internet-like brain hierarchical network (IBHN). In this model, the whole brain network is partitioned into multiple levels: brain wide area network (Brain-WAN), brain metropolitan network (Brain-MAN), and brain local area network (Brain-LAN). A Brain-MAN is formed by the interconnection of multiple Brain-LANs, and the interconnection of multiple Brain-MANs forms a Brain-WAN. A multivariate analysis method is employed to measure overall functional connectivity between two brain networks at the same network level rather than detecting the change of each node pair's functional connection. Furthermore, we demonstrate the utility of IBHN model with application to a practical case-control study involving 64 patients with Alzheimer's disease and 75 healthy controls. RESULTS The proposed model identified enhanced functional connectivity (P-value<0.05) at Brain-WAN level and reduced functional connectivity (P-value=0.004) at Brain-LAN level of Alzheimer's disease patients, which can be used as a multi-dimension functional reference for AD's diagnosis. CONCLUSIONS This study not only provides insight into AD pathophysiology, but also further proves the effectiveness of the proposed IBHN model. In addition, the IBHN model makes it possible to explore the brain's functional organization from multiple dimensions and offers a multi-level perspective for the research of complex brain network.
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Affiliation(s)
- Shaojun Huang
- College of Information Engineering, Shanghai Maritime University, 1550 Harbor Avenue, Pudong, Shanghai, 201306, China
| | - Weiming Zeng
- College of Information Engineering, Shanghai Maritime University, 1550 Harbor Avenue, Pudong, Shanghai, 201306, China.
| | - Yuhu Shi
- College of Information Engineering, Shanghai Maritime University, 1550 Harbor Avenue, Pudong, Shanghai, 201306, China
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180
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Lunkova E, Guberman GI, Ptito A, Saluja RS. Noninvasive magnetic resonance imaging techniques in mild traumatic brain injury research and diagnosis. Hum Brain Mapp 2021; 42:5477-5494. [PMID: 34427960 PMCID: PMC8519871 DOI: 10.1002/hbm.25630] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 08/06/2021] [Accepted: 08/07/2021] [Indexed: 12/13/2022] Open
Abstract
Mild traumatic brain injury (mTBI), frequently referred to as concussion, is one of the most common neurological disorders. The underlying neural mechanisms of functional disturbances in the brains of concussed individuals remain elusive. Novel forms of brain imaging have been developed to assess patients postconcussion, including functional magnetic resonance imaging (fMRI), susceptibility-weighted imaging (SWI), diffusion MRI (dMRI), and perfusion MRI [arterial spin labeling (ASL)], but results have been mixed with a more common utilization in the research environment and a slower integration into the clinical setting. In this review, the benefits and drawbacks of the methods are described: fMRI is an effective method in the diagnosis of concussion but it is expensive and time-consuming making it difficult for regular use in everyday practice; SWI allows detection of microhemorrhages in acute and chronic phases of concussion; dMRI is primarily used for the detection of white matter abnormalities, especially axonal injury, specific for mTBI; and ASL is an alternative to the BOLD method with its ability to track cerebral blood flow alterations. Thus, the absence of a universal diagnostic neuroimaging method suggests a need for the adoption of a multimodal approach to the neuroimaging of mTBI. Taken together, these methods, with their underlying functional and structural features, can contribute from different angles to a deeper understanding of mTBI mechanisms such that a comprehensive diagnosis of mTBI becomes feasible for the clinician.
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Affiliation(s)
- Ekaterina Lunkova
- Department of Neurology & NeurosurgeryMcGill UniversityMontrealQuebecCanada
| | - Guido I. Guberman
- Department of Neurology & NeurosurgeryMcGill UniversityMontrealQuebecCanada
| | - Alain Ptito
- Department of Neurology & NeurosurgeryMcGill UniversityMontrealQuebecCanada
- Montreal Neurological InstituteMontrealQuebecCanada
- Department of PsychologyMcGill University Health CentreMontrealQuebecCanada
| | - Rajeet Singh Saluja
- Department of Neurology & NeurosurgeryMcGill UniversityMontrealQuebecCanada
- McGill University Health Centre Research InstituteMontrealQuebecCanada
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181
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Ahmadi ZZ, DiBacco ML, Pearl PL. Speech Motor Function and Auditory Perception in Succinic Semialdehyde Dehydrogenase Deficiency: Toward Pre-Supplementary Motor Area (SMA) and SMA-Proper Dysfunctions. J Child Neurol 2021; 36:1210-1217. [PMID: 33757330 DOI: 10.1177/08830738211001210] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
This study reviews the fundamental roles of pre-supplementary motor area (SMA) and SMA-proper responsible for speech-motor functions and auditory perception in succinic semialdehyde dehydrogenase (SSADH) deficiency. We comprehensively searched the databases of PubMed, Google Scholar, and the electronic journals Springer, PreQuest, and Science Direct associated with keywords SSADHD, SMA, auditory perception, speech, and motor with AND operator. Transcranial magnetic stimulation emerged for assessing excitability/inhibitory M1 functions, but its role in pre-SMA and SMA proper dysfunction remains unknown. There was a lack of data on resting-state and task-based functional magnetic resonance imaging (MRI), with a focus on passive and active tasks for both speech and music, in terms of analysis of SMA-related cortex and its connections. Children with SSADH deficiency likely experience a dysfunction in connectivity between SMA portions with cortical and subcortical areas contributing to disabilities in speech-motor functions and auditory perception. Early diagnosis of auditory-motor disabilities in children with SSADH deficiency by neuroimaging techniques invites opportunities for utilizing sensory-motor integration as future interventional strategies.
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Affiliation(s)
- Zohreh Ziatabar Ahmadi
- Department of Speech Therapy, School of Rehabilitation, Babol University of Medical Sciences, Babol, I.R. Iran
| | - Melissa L DiBacco
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Phillip L Pearl
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
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182
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Resting-state functional connectivity predictors of treatment response in schizophrenia - A systematic review and meta-analysis. Schizophr Res 2021; 237:153-165. [PMID: 34534947 DOI: 10.1016/j.schres.2021.09.004] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 08/18/2021] [Accepted: 09/06/2021] [Indexed: 11/21/2022]
Abstract
We aimed to systematically synthesize and quantify the utility of pre-treatment resting-state functional magnetic resonance imaging (rs-fMRI) in predicting antipsychotic response in schizophrenia. We searched the PubMed/MEDLINE database for studies that examined the magnitude of association between baseline rs-fMRI assessment and subsequent response to antipsychotic treatment in persons with schizophrenia. We also performed meta-analyses for quantifying the magnitude and accuracy of predicting response defined continuously and categorically. Data from 22 datasets examining 1280 individuals identified striatal and default mode network functional segregation and integration metrics as consistent determinants of treatment response. The pooled correlation coefficient for predicting improvement in total symptoms measured continuously was ~0.47 (12 datasets; 95% CI: 0.35 to 0.59). The pooled odds ratio of predicting categorically defined treatment response was 12.66 (nine datasets; 95% CI: 7.91-20.29), with 81% sensitivity and 76% specificity. rs-fMRI holds promise as a predictive biomarker of antipsychotic treatment response in schizophrenia. Future efforts need to focus on refining feature characterization to improve prediction accuracy, validate prediction models, and evaluate their implementation in clinical practice.
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183
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Larsson DEO, Esposito G, Critchley HD, Dienes Z, Garfinkel SN. Sensitivity to changes in rate of heartbeats as a measure of interoceptive ability. J Neurophysiol 2021; 126:1799-1813. [PMID: 34669507 DOI: 10.1152/jn.00059.2021] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
Individuals vary in their ability to perceive, as conscious sensations, signals like the beating of the heart. Tests of such interoceptive ability are, however, constrained in nature and reliability. Performance of the heartbeat tracking task, a widely used test of cardiac interoception, often corresponds well with individual differences in emotion and cognition, yet is susceptible to reporting bias and influenced by higher-order knowledge, e.g., of expected heart rate. The present study introduces a new way of assessing cardiac interoceptive ability, focusing on sensitivity to short-term, naturalistic changes in frequency of heartbeats. At rest, such heart rate variability typically reflects the dominant influence of respiration on vagus parasympathetic control of the sinoatrial pacemaker. We observed an overall tendency of healthy participants to report feeling fewer heartbeats during increases in heart rate, which we speculate reflects a reduction in heartbeat strength and salience during inspiratory periods when heart rate typically increases to maintain a stable cardiac output. Within-participant performance was more variable on this measure of cardiac interoceptive sensitivity relative to the "classic" heartbeat tracking task. Our findings indicate that cardiac interoceptive ability, rather than reflecting the veridical monitoring of subtle variations in physiology, appears to involve more interpolation wherein interoceptive decisions are informed by dynamic working estimates derived from the integration of afferent signaling and higher-order predictions.NEW & NOTEWORTHY This study presents a new method for evaluating cardiac interoceptive ability, measuring sensitivity to naturalistic changes in the number of heartbeats over time periods. Results show participants have an overall tendency toward sensing fewer heartbeats during higher heart rates. This likely reflects the influence of changing heartbeat strength on cardiac interoception at rest, which should be taken into account when evaluating cardiac interoceptive ability and its relationship to anxiety and psychosomatic conditions.
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Affiliation(s)
- Dennis E O Larsson
- Department of Psychology, grid.12082.39University of Sussex, Falmer, United Kingdom.,Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer, United Kingdom
| | - Giulia Esposito
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer, United Kingdom.,Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium
| | - Hugo D Critchley
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer, United Kingdom.,Sackler Centre for Consciousness Science, University of Sussex, Falmer, United Kingdom.,Sussex Partnership NHS Foundation Trust, Swandean, Worthing, West Sussex, United Kingdom
| | - Zoltan Dienes
- Department of Psychology, grid.12082.39University of Sussex, Falmer, United Kingdom.,Sackler Centre for Consciousness Science, University of Sussex, Falmer, United Kingdom
| | - Sarah N Garfinkel
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer, United Kingdom.,Sussex Partnership NHS Foundation Trust, Swandean, Worthing, West Sussex, United Kingdom.,Institute of Cognitive Neuroscience, University College London, London, United Kingdom
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184
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Liang X, Koh CL, Yeh CH, Goodin P, Lamp G, Connelly A, Carey LM. Predicting Post-Stroke Somatosensory Function from Resting-State Functional Connectivity: A Feasibility Study. Brain Sci 2021; 11:brainsci11111388. [PMID: 34827387 PMCID: PMC8615819 DOI: 10.3390/brainsci11111388] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 10/07/2021] [Accepted: 10/18/2021] [Indexed: 12/02/2022] Open
Abstract
Accumulating evidence shows that brain functional deficits may be impacted by damage to remote brain regions. Recent advances in neuroimaging suggest that stroke impairment can be better predicted based on disruption to brain networks rather than from lesion locations or volumes only. Our aim was to explore the feasibility of predicting post-stroke somatosensory function from brain functional connectivity through the application of machine learning techniques. Somatosensory impairment was measured using the Tactile Discrimination Test. Functional connectivity was employed to model the global brain function. Behavioral measures and MRI were collected at the same timepoint. Two machine learning models (linear regression and support vector regression) were chosen to predict somatosensory impairment from disrupted networks. Along with two feature pools (i.e., low-order and high-order functional connectivity, or low-order functional connectivity only) engineered, four predictive models were built and evaluated in the present study. Forty-three chronic stroke survivors participated this study. Results showed that the regression model employing both low-order and high-order functional connectivity can predict outcomes based on correlation coefficient of r = 0.54 (p = 0.0002). A machine learning predictive approach, involving high- and low-order modelling, is feasible for the prediction of residual somatosensory function in stroke patients using functional brain networks.
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Affiliation(s)
- Xiaoyun Liang
- Neurorehabilitation and Recovery, Florey Institute of Neuroscience and Mental Health, Melbourne, VIC 3084, Australia; (C.-L.K.); (P.G.); (G.L.); (L.M.C.)
- Victorian Infant Brain Studies (VIBeS) Group, Murdoch Children’s Research Institute, Melbourne, VIC 3052, Australia
- Correspondence:
| | - Chia-Lin Koh
- Neurorehabilitation and Recovery, Florey Institute of Neuroscience and Mental Health, Melbourne, VIC 3084, Australia; (C.-L.K.); (P.G.); (G.L.); (L.M.C.)
- Department of Occupational Therapy, Social Work and Social Policy, School of Allied Health Human Services and Sport, La Trobe University, Melbourne, VIC 3086, Australia
- Department of Occupational Therapy, College of Medicine, National Cheng Kung University, Tainan 701, Taiwan
| | - Chun-Hung Yeh
- Imaging Division, Florey Institute of Neuroscience and Mental Health, Melbourne, VIC 3084, Australia; (C.-H.Y.); (A.C.)
- Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital, Taoyuan 33302, Taiwan
- Department of Psychiatry, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan 33305, Taiwan
| | - Peter Goodin
- Neurorehabilitation and Recovery, Florey Institute of Neuroscience and Mental Health, Melbourne, VIC 3084, Australia; (C.-L.K.); (P.G.); (G.L.); (L.M.C.)
| | - Gemma Lamp
- Neurorehabilitation and Recovery, Florey Institute of Neuroscience and Mental Health, Melbourne, VIC 3084, Australia; (C.-L.K.); (P.G.); (G.L.); (L.M.C.)
- Department of Psychology and Counselling, School of Psychology and Public Health, La Trobe University, Melbourne, VIC 3086, Australia
| | - Alan Connelly
- Imaging Division, Florey Institute of Neuroscience and Mental Health, Melbourne, VIC 3084, Australia; (C.-H.Y.); (A.C.)
| | - Leeanne M. Carey
- Neurorehabilitation and Recovery, Florey Institute of Neuroscience and Mental Health, Melbourne, VIC 3084, Australia; (C.-L.K.); (P.G.); (G.L.); (L.M.C.)
- Department of Occupational Therapy, Social Work and Social Policy, School of Allied Health Human Services and Sport, La Trobe University, Melbourne, VIC 3086, Australia
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185
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Xing Y, Yang J, Zhou A, Wang F, Tang Y, Jia J. Altered brain activity mediates the relationship between white matter hyperintensity severity and cognition in older adults. Brain Imaging Behav 2021; 16:899-908. [PMID: 34671890 DOI: 10.1007/s11682-021-00564-y] [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: 09/24/2021] [Indexed: 11/26/2022]
Abstract
White matter hyperintensities (WMHs) on magnetic resonance imaging are commonly found in older adults. The mechanisms underpinning the dose-dependent association between WMH severity and cognition are not well understood. This study aimed to investigate how brain activity changes with WMH severity, and if altered brain activity mediates the relationship between WMH and cognitive function. A total of 35 participants with moderate to severe WMHs (Fazekas grade 2 or 3) and 34 participants with mild WMHs (Fazekas grade 1), who were cognitively normal, were included. Resting-state brain function was analyzed using the amplitude of low-frequency fluctuation (ALFF). A mean fractional anisotropy (FA) value of 20 tract-specific regions of interest was calculated. Mediation analysis was used to assess whether ALFF values mediated the relationship between WMH and cognition. The results showed that compared to those with mild WMHs, participants with confluent WMHs had worse memory and naming ability and also had increased ALFF in the right middle frontal gyrus and decreased ALFF in the left middle occipital gyrus. After controlling for age, gender, education and apolipoprotein E (ApoE) ε4 status, increased ALFF in the right prefrontal cortex was associated with worse immediate recall and recognition, and ALFF values mediated the relationships between both Fazekas scores and FA values and memory. In conclusion, our study suggests that cognitively normal adults with high WMH load exhibit subclinical cognitive dysfunction and altered spontaneous brain activity. The mediating effects of brain activity help to shed light on our understanding of the relationship between WMHs and cognition.
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Affiliation(s)
- Yi Xing
- Innovation Center for Neurological Disorders, Department of Neurology, Xuanwu Hospital, National Clinical Research Center for Geriatric Disorders, Capital Medical University, 45 Changchun Street, Beijing, 100053, China
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education of the People's Republic of China, Beijing, China
| | - Jianwei Yang
- Innovation Center for Neurological Disorders, Department of Neurology, Xuanwu Hospital, National Clinical Research Center for Geriatric Disorders, Capital Medical University, 45 Changchun Street, Beijing, 100053, China
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education of the People's Republic of China, Beijing, China
| | - Aihong Zhou
- Innovation Center for Neurological Disorders, Department of Neurology, Xuanwu Hospital, National Clinical Research Center for Geriatric Disorders, Capital Medical University, 45 Changchun Street, Beijing, 100053, China
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education of the People's Republic of China, Beijing, China
| | - Fen Wang
- Innovation Center for Neurological Disorders, Department of Neurology, Xuanwu Hospital, National Clinical Research Center for Geriatric Disorders, Capital Medical University, 45 Changchun Street, Beijing, 100053, China
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education of the People's Republic of China, Beijing, China
| | - Yi Tang
- Innovation Center for Neurological Disorders, Department of Neurology, Xuanwu Hospital, National Clinical Research Center for Geriatric Disorders, Capital Medical University, 45 Changchun Street, Beijing, 100053, China.
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education of the People's Republic of China, Beijing, China.
| | - Jianping Jia
- Innovation Center for Neurological Disorders, Department of Neurology, Xuanwu Hospital, National Clinical Research Center for Geriatric Disorders, Capital Medical University, 45 Changchun Street, Beijing, 100053, China.
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education of the People's Republic of China, Beijing, China.
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186
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Horstman LI, Riem MME, Alyousefi-van Dijk K, Lotz AM, Bakermans-Kranenburg MJ. Fathers' Involvement in Early Childcare is Associated with Amygdala Resting-State Connectivity. Soc Cogn Affect Neurosci 2021; 17:198-205. [PMID: 34651177 PMCID: PMC8847902 DOI: 10.1093/scan/nsab086] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 06/18/2021] [Accepted: 10/13/2021] [Indexed: 11/18/2022] Open
Abstract
Becoming a parent requires new skills and frequent task switching during daily childcare. Little is known about the paternal brain during the transition to fatherhood. The present study examined intrinsic neuronal network connectivity in a group of first-time expectant and new fathers (total N = 131) using amygdala seed-based resting-state functional connectivity analysis. Furthermore, we examined the association between paternal involvement (i.e. hours spent in childcare and real-time push notifications on smartphone) and connectivity within the parental brain network in new fathers. There were no significant differences in functional connectivity between expectant and new fathers. However, results show that in new fathers, time spent in childcare was positively related to amygdala connectivity with the supramarginal gyrus, postcentral gyrus and the superior parietal lobule—all regions within the cognition/mentalizing network that have been associated with empathy and social cognition. Our results suggest that fathers’ time investment in childcare is related to connectivity networks in the parental brain.
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Affiliation(s)
- Lisa I Horstman
- Clinical Child & Family Studies, Faculty of Behavioral and Movement Sciences, Vrije Universiteit, Amsterdam, the Netherlands.,Leiden Institute for Brain and Cognition, Leiden University Medical Center, Leiden, the Netherlands
| | - Madelon M E Riem
- Clinical Child & Family Studies, Faculty of Behavioral and Movement Sciences, Vrije Universiteit, Amsterdam, the Netherlands.,Behavioral Science Institute, Radboud University, The Netherlands
| | - Kim Alyousefi-van Dijk
- Clinical Child & Family Studies, Faculty of Behavioral and Movement Sciences, Vrije Universiteit, Amsterdam, the Netherlands.,Leiden Institute for Brain and Cognition, Leiden University Medical Center, Leiden, the Netherlands
| | - Anna M Lotz
- Clinical Child & Family Studies, Faculty of Behavioral and Movement Sciences, Vrije Universiteit, Amsterdam, the Netherlands.,Leiden Institute for Brain and Cognition, Leiden University Medical Center, Leiden, the Netherlands
| | - Marian J Bakermans-Kranenburg
- Clinical Child & Family Studies, Faculty of Behavioral and Movement Sciences, Vrije Universiteit, Amsterdam, the Netherlands.,Leiden Institute for Brain and Cognition, Leiden University Medical Center, Leiden, the Netherlands
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187
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Safari A, Moretti P, Diez I, Cortes JM, Muñoz MA. Persistence of hierarchical network organization and emergent topologies in models of functional connectivity. Neurocomputing 2021. [DOI: 10.1016/j.neucom.2021.02.096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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188
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Liang D, Xia S, Zhang X, Zhang W. Analysis of Brain Functional Connectivity Neural Circuits in Children With Autism Based on Persistent Homology. Front Hum Neurosci 2021; 15:745671. [PMID: 34588970 PMCID: PMC8473898 DOI: 10.3389/fnhum.2021.745671] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 08/19/2021] [Indexed: 11/24/2022] Open
Abstract
Autism spectrum disorder (ASD) is a complex neuropsychiatric disorder with a complex and unknown etiology. Statistics demonstrate that the number of people diagnosed with ASD is increasing in countries around the world. Currently, although many neuroimaging studies indicate that ASD is characterized by abnormal functional connectivity (FC) patterns within brain networks rather than local functional or structural abnormalities, the FC characteristics of ASD are still poorly understood. In this study, a Vietoris-Rips (VR) complex filtration model of the brain functional network was established by using resting-state functional magnetic resonance imaging (fMRI) data of children aged 6–13 years old [including 54 ASD patients and 52 typical development (TD) controls] from the Autism Brain Imaging Data Exchange (ABIDE) public database. VR complex filtration barcodes are calculated by using persistent homology to describe the changes in the FC neural circuits of brain networks. The number of FC neural circuits with different length ranges at different threshold values is calculated by using the barcodes, the different brain regions participating in FC neural circuits are discussed, and the connectivity characteristics of brain FC neural circuits in the two groups are compared and analyzed. Our results show that the number of FC neural circuits with lengths of 8–12 is significantly decreased in the ASD group compared with the TD control group at threshold values of 0.7, 0.8 and 0.9, and there is no significant difference in the number of FC neural circuits with lengths of 4–7 and 13–16 and lengths 16. When the thresholds are 0.7, 0.8, and 0.9, the number of FC neural circuits in some brain regions, such as the right orbital part of the superior frontal gyrus, the left supplementary motor area, the left hippocampus, and the right caudate nucleus, involved in the study is significantly decreased in the ASD group compared with the TD control group. The results of this study indicate that there are significant differences in the FC neural circuits of brain networks in the ASD group compared with the TD control group.
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Affiliation(s)
- Di Liang
- School of Science, Shandong Jianzhu University, Jinan, China
| | - Shengxiang Xia
- School of Science, Shandong Jianzhu University, Jinan, China
| | - Xianfu Zhang
- School of Control Science and Engineering, Shandong University, Jinan, China
| | - Weiwei Zhang
- School of Science, Shandong Jianzhu University, Jinan, China
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189
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Kajimura S, Ito A, Izuma K. Brain Knows Who Is on the Same Wavelength: Resting-State Connectivity Can Predict Compatibility of a Female-Male Relationship. Cereb Cortex 2021; 31:5077-5089. [PMID: 34145453 PMCID: PMC8491675 DOI: 10.1093/cercor/bhab143] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Revised: 04/15/2021] [Accepted: 05/03/2021] [Indexed: 12/03/2022] Open
Abstract
Prediction of the initial compatibility of heterosexual individuals based on self-reported traits and preferences has not been successful, even with significantly developed information technology. To overcome the limitations of self-reported measures and predict compatibility, we used functional connectivity profiles from resting-state functional magnetic resonance imaging (fMRI) data that carry rich individual-specific information sufficient to predict psychological constructs and activation patterns during social cognitive tasks. Several days after collecting data from resting-state fMRIs, participants undertook a speed-dating experiment in which they had a 3-min speed date with every other opposite-sex participant. Our machine learning algorithm successfully predicted whether pairs in the experiment were compatible or not using (dis)similarity of functional connectivity profiles obtained before the experiment. The similarity and dissimilarity of functional connectivity between individuals and these multivariate relationships contributed to the prediction, hence suggesting the importance of complementarity (observed as dissimilarity) as well as the similarity between an individual and a potential partner during the initial attraction phase. The result indicates that the salience network, limbic areas, and cerebellum are especially important for the feeling of compatibility. This research emphasizes the utility of neural information to predict complex phenomena in a social environment that behavioral measures alone cannot predict.
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Affiliation(s)
- Shogo Kajimura
- Faculty of Information and Human Sciences, Kyoto Institute of Technology, Kyoto 606-8585, Japan
| | - Ayahito Ito
- Research Institute for Future Design, Kochi University of Technology, Kochi 780-8515, Japan
- Department of Psychology, University of Southampton, Southampton SO17 1BJ, United Kingdom
- Faculty of Health Sciences, Hokkaido University, Hokkaido 060-0812, Japan
| | - Keise Izuma
- Research Institute for Future Design, Kochi University of Technology, Kochi 780-8515, Japan
- Department of Psychology, University of Southampton, Southampton SO17 1BJ, United Kingdom
- School of Economics & Management, Kochi University of Technology, Kochi 780-8515, Japan
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190
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Prospective study on resting state functional connectivity in adolescents with major depressive disorder after antidepressant treatment. J Psychiatr Res 2021; 142:369-375. [PMID: 34425489 DOI: 10.1016/j.jpsychires.2021.08.026] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 06/26/2021] [Accepted: 08/17/2021] [Indexed: 11/24/2022]
Abstract
Recent advances in functional magnetic resonance imaging (fMRI) have resulted in many studies on resting-state functional connectivity (rsFC) in depressed patients. Previous studies have shown alterations between multiple brain areas, such as the prefrontal cortex, anterior cingulate cortex, and basal ganglia, but there are very few prospective studies with a longitudinal design on adolescent depression patients. We therefore investigated the change in positive rsFC in a homogeneous drug-naïve adolescent group after 12 weeks of antidepressant treatment. Functional neuroimaging data were collected and analyzed from 32 patients and 27 healthy controls. Based on previous literature, the amygdala, anterior cingulate cortex (ACC), insula, hippocampus, and dorsolateral prefrontal cortex (DLPFC) were selected as seed regions. Seed-to-voxel analyses were performed between pre- and post-treatment states as well as between the patients and controls at baseline. The positive rsFC between the right DLPFC and the left putamen/right frontal operculum were shown to be higher in patients than in the controls. The positive rsFC between the left DLPFC and left putamen/left lingual gyrus was also higher in the patients than in the controls. The positive rsFC between the right dorsal ACC and the left precentral gyrus had reduced after the 12-week antidepressant treatment. Regions involved in the frontolimbic circuit showed changes in the positive rsFC in the depressed adolescents as compared to in the healthy controls. There were also significant changes in the positive rsFC after 12-weeks of antidepressant treatment. The involved regions were associated with emotional regulation, cognitive functioning, impulse control, and visual processing.
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191
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Leota J, Kleinert T, Tran A, Nash K. Neural signatures of heterogeneity in risk-taking and strategic consistency. Eur J Neurosci 2021; 54:7214-7230. [PMID: 34561929 PMCID: PMC9292925 DOI: 10.1111/ejn.15476] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 08/23/2021] [Accepted: 09/20/2021] [Indexed: 12/28/2022]
Abstract
People display a high degree of heterogeneity in risk-taking behaviour, but this heterogeneity remains poorly understood. Here, we use a neural trait approach to examine if task-independent, brain-based differences can help uncover the sources of heterogeneity in risky decision-making. We extend prior research in two key ways. First, we disentangled risk-taking and strategic consistency using novel measures afforded by the Balloon Analogue Risk Task. Second, we applied a personality neuroscience framework to explore why personality traits are typically only weakly related to risk-taking behaviour. We regressed participants' (N = 104) source localized resting-state electroencephalographic activity on risk-taking and strategic consistency. Results revealed that higher levels of resting-state delta-band current density (reflecting reduced cortical activation) in the left dorsal anterior cingulate cortex and the left dorsolateral prefrontal cortex were associated with increased risk-taking and decreased strategic consistency, respectively. These results suggest that heterogeneity in risk-taking behaviour is associated with neural dispositions related to sensitivity to the risk of loss, whereas heterogeneity in strategic consistency is associated with neural dispositions related to strategic decision-making. Finally, extraversion, neuroticism, openness, and self-control were broadly associated with both of the identified neural traits, which in turn mediated indirect associations between personality traits and behavioural measures. These results provide an explanation for the weak direct relationships between personality traits and risk-taking behaviour, supporting a personality neuroscience framework of traits and decision-making.
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Affiliation(s)
- Josh Leota
- Department of Psychology, University of Alberta, Edmonton, Alberta, Canada
| | - Tobias Kleinert
- Department of Psychology, University of Alberta, Edmonton, Alberta, Canada
| | - Alex Tran
- Institute for Mental Health Policy Research, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada
| | - Kyle Nash
- Department of Psychology, University of Alberta, Edmonton, Alberta, Canada
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192
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Li D, Zhang H, Liu Y, Liang X, Chen Y, Zheng Y, Qiu S, Cui Y. Abnormal Functional Connectivity of Posterior Cingulate Cortex Correlates With Phonemic Verbal Fluency Deficits in Major Depressive Disorder. Front Neurol 2021; 12:724874. [PMID: 34512534 PMCID: PMC8427063 DOI: 10.3389/fneur.2021.724874] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 07/30/2021] [Indexed: 12/27/2022] Open
Abstract
Background: Major depressive disorder (MDD) patients face an increased risk of developing cognitive impairments. One of the prominent cognitive impairments in MDD patients is verbal fluency deficit. Nonetheless, it is not clear which vulnerable brain region in MDD is interactively linked to verbal fluency deficit. It is important to gain an improved understanding for verbal fluency deficit in MDD. Methods: Thirty-four MDD patients and 34 normal controls (NCs) completed resting-state fMRI (rs-fMRI) scan and a set of verbal fluency tests (semantic VFT and phonemic VFT). Fourteen brain regions from five brain networks/systems (central executive network, default mode network, salience network, limbic system, cerebellum) based on their vital role in MDD neuropathology were selected as seeds for functional connectivity (FC) analyses with the voxels in the whole brain. Finally, correlations between the z-score of the FCs from clusters showing significant between-group difference and z-score of the VFTs were calculated using Pearson correlation analyses. Results: Increased FCs in MDD patients vs. NCs were identified between the bilateral posterior cingulate cortex (PCC) and the right inferior frontal gyrus (triangular part), in which the increased FC between the right PCC and the right inferior frontal gyrus (triangular part) was positively correlated with the z score of phonemic VFT in the MDD patients. Moreover, decreased FCs were identified between the right hippocampal gyrus and PCC, as well as left cerebellum Crus II and right parahippocampal gyrus in MDD patients vs. NCs. Conclusions: The MDD patients have altered FCs among key brain regions in the default mode network, the central executive network, the limbic system, and the cerebellum. The increased FC between the right PCC and the right inferior frontal gyrus (triangular part) may be useful to better characterize pathophysiology of MDD and functional correlates of the phonemic verbal fluency deficit in MDD.
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Affiliation(s)
- Danian Li
- Cerebropathy Center, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Hanyue Zhang
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yujie Liu
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.,Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Xinyu Liang
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yaoping Chen
- Department of Radiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Yanting Zheng
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.,Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Shijun Qiu
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Ying Cui
- Cerebropathy Center, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
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193
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Marciano L, Camerini AL, Morese R. The Developing Brain in the Digital Era: A Scoping Review of Structural and Functional Correlates of Screen Time in Adolescence. Front Psychol 2021; 12:671817. [PMID: 34512437 PMCID: PMC8432290 DOI: 10.3389/fpsyg.2021.671817] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 08/06/2021] [Indexed: 12/12/2022] Open
Abstract
The widespread diffusion of screen-based devices in adolescence has fueled a debate about the beneficial and detrimental effects on adolescents’ well-being and development. With the aim of summarizing the existing literature on the associations between screen time (including Internet-related addictions) and adolescent brain development, the present scoping review summarized evidence from 16 task-unrelated and task-related neuroimaging studies, published between 2010 and 2020. Results highlight three important key messages: (i) a frequent and longer duration of screen-based media consumption (including Internet-related addictive behaviors) is related to a less efficient cognitive control system in adolescence, including areas of the Default Mode Network and the Central Executive Network; (ii) online activities act as strong rewards to the brain and repeated screen time augments the tendency to seek short-term gratifications; and (iii) neuroscientific research on the correlates between screen time and adolescent brain development is still at the beginning and in urgent need for further evidence, especially on the underlying causality mechanisms. Methodological, theoretical, and conceptual implications are discussed.
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Affiliation(s)
- Laura Marciano
- Institute of Public Health, Università della Svizzera italiana, Lugano, Switzerland
| | - Anne-Linda Camerini
- Institute of Public Health, Università della Svizzera italiana, Lugano, Switzerland
| | - Rosalba Morese
- Faculty of Biomedical Sciences, Università della Svizzera italiana, Lugano, Switzerland.,Faculty of Communication, Culture and Society, Università della Svizzera italiana, Lugano, Switzerland.,Department of Business Economics, Health and Social Care, University of Applied Sciences and Arts of Southern Switzerland, Manno, Switzerland
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194
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Kanno S, Ogawa KI, Kikuchi H, Toyoshima M, Abe N, Sato K, Miyazawa K, Oshima R, Ohtomo S, Arai H, Shibuya S, Suzuki K. Reduced default mode network connectivity relative to white matter integrity is associated with poor cognitive outcomes in patients with idiopathic normal pressure hydrocephalus. BMC Neurol 2021; 21:353. [PMID: 34517828 PMCID: PMC8436532 DOI: 10.1186/s12883-021-02389-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 09/06/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The aim of this study was to investigate whether default mode network (DMN) connectivity and brain white matter integrity at baseline were associated with severe cognitive impairments at baseline and poor cognitive outcomes after shunt placement in patients with idiopathic normal pressure hydrocephalus (iNPH). METHODS Twenty consecutive patients with iNPH whose symptoms were followed for 6 months after shunt placement and 10 healthy controls (HCs) were enrolled. DMN connectivity and brain white matter integrity at baseline in the patients with iNPH and HCs were detected by using resting-state functional magnetic resonance imaging (MRI) with independent component analysis and diffusion tensor imaging, respectively, and these MRI indexes were compared between the patients with iNPH and HCs. Performance on neuropsychological tests for memory and executive function and on the gait test was assessed in the patients with iNPH at baseline and 6 months after shunt placement. We divided the patients with iNPH into the relatively preserved and reduced DMN connectivity groups using the MRI indexes for DMN connectivity and brain white matter integrity, and the clinical measures were compared between the relatively preserved and reduced DMN connectivity groups. RESULTS Mean DMN connectivity in the iNPH group was significantly lower than that in the HC group and was significantly positively correlated with Rey auditory verbal learning test (RAVLT) immediate recall scores and frontal assessment battery (FAB) scores. Mean fractional anisotropy of the whole-brain white matter skeleton in the iNPH group was significantly lower than that in the HC group. The reduced DMN connectivity group showed significantly worse performance on the RAVLT at baseline and significantly worse improvement in the RAVLT immediate recall and recognition scores and the FAB scores than the preserved DMN connectivity group. Moreover, the RAVLT recognition score highly discriminated patients with relatively preserved DMN connectivity from those with relatively reduced DMN connectivity. CONCLUSIONS Our findings indicated that iNPH patients with reduced DMN connectivity relative to the severity of brain white matter disruption have severe memory deficits at baseline and poorer cognitive outcomes after shunt placement. However, further larger-scale studies are needed to confirm these findings.
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Affiliation(s)
- Shigenori Kanno
- Department of Behavioral Neurology and Cognitive Neuroscience, Tohoku University Graduate School of Medicine, 2-1, Seiryo-machi, Aoba-ku, Miyagi, 980-8575, Sendai, Japan. .,Department of Neurology, South Miyagi Medical Center, Shibata, Japan.
| | - Kun-Ichi Ogawa
- Department of Radiology, South Miyagi Medical Center, Shibata, Japan
| | - Hiroaki Kikuchi
- Healthcare Center, South Miyagi Medical Center, Shibata, Japan
| | - Masako Toyoshima
- Department of Rehabilitation, South Miyagi Medical Center, Shibata, Japan
| | - Nobuhito Abe
- Kokoro Research Center, Kyoto University, Kyoto, Japan
| | - Kazushi Sato
- Department of Radiology, South Miyagi Medical Center, Shibata, Japan
| | - Koichi Miyazawa
- Department of Neurology, South Miyagi Medical Center, Shibata, Japan.,Department of Neurology, Tohoku Medical and Pharmaceutical University, Sendai, Japan
| | - Ryuji Oshima
- Department of Neurology, South Miyagi Medical Center, Shibata, Japan
| | - Satoru Ohtomo
- Department of Neurosurgery, South Miyagi Medical Center, Shibata, Japan
| | - Hiroaki Arai
- Department of Neurosurgery, South Miyagi Medical Center, Shibata, Japan
| | - Satoshi Shibuya
- Department of Neurology, South Miyagi Medical Center, Shibata, Japan.,Department of Neurology, Moriyama Memorial Hospital, Edogawa, Japan
| | - Kyoko Suzuki
- Department of Behavioral Neurology and Cognitive Neuroscience, Tohoku University Graduate School of Medicine, 2-1, Seiryo-machi, Aoba-ku, Miyagi, 980-8575, Sendai, Japan
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195
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Ma J, Wu JJ, Hua XY, Zheng MX, Huo BB, Xing XX, Feng SY, Li B, Xu J. Alterations in brain structure and function in patients with osteonecrosis of the femoral head: a multimodal MRI study. PeerJ 2021; 9:e11759. [PMID: 34484979 PMCID: PMC8381875 DOI: 10.7717/peerj.11759] [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: 12/17/2020] [Accepted: 06/21/2021] [Indexed: 11/30/2022] Open
Abstract
Background Pain, a major symptom of osteonecrosis of the femoral head (ONFH), is a complex sensory and emotional experience that presents therapeutic challenges. Pain can cause neuroplastic changes at the cortical level, leading to central sensitization and difficulties with curative treatments; however, whether changes in structural and functional plasticity occur in patients with ONFH remains unclear. Methods A total of 23 ONFH inpatients who did not undergo surgery (14 males, nine females; aged 55.61 ± 13.79 years) and 20 controls (12 males, eight females; aged 47.25 ± 19.35 years) were enrolled. Functional indices of the amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and a structural index of tract-based spatial statistics (TBSS) were calculated for each participant. The probability distribution of fiber direction was determined according to the ALFF results. Results ONFH patients demonstrated increased ALFF in the bilateral dorsolateral superior frontal gyrus, right medial superior frontal gyrus, right middle frontal gyrus, and right supplementary motor area. In contrast, ONFH patients showed decreased ReHo in the left superior parietal gyrus and right inferior temporal gyrus. There were no significant differences in TBSS or probabilistic tractography. Conclusion These results indicate cerebral pain processing in ONFH patients. It is advantageous to use functional magnetic resonance imaging to better understand pain pathogenesis and identify new therapeutic targets in ONFH patients.
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Affiliation(s)
- Jie Ma
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jia-Jia Wu
- Center of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xu-Yun Hua
- Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), Tongji University, Shanghai, China.,Department of Traumatology and Orthopedics, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Mou-Xiong Zheng
- Department of Traumatology and Orthopedics, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Bei-Bei Huo
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xiang-Xin Xing
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Sheng-Yi Feng
- Department of Traumatology and Orthopedics, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Bo Li
- Department of Traumatology and Orthopedics, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jianguang Xu
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
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196
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Raimondo L, Oliveira ĹAF, Heij J, Priovoulos N, Kundu P, Leoni RF, van der Zwaag W. Advances in resting state fMRI acquisitions for functional connectomics. Neuroimage 2021; 243:118503. [PMID: 34479041 DOI: 10.1016/j.neuroimage.2021.118503] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 08/16/2021] [Accepted: 08/22/2021] [Indexed: 01/21/2023] Open
Abstract
Resting state functional magnetic resonance imaging (rs-fMRI) is based on spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal, which occur simultaneously in different brain regions, without the subject performing an explicit task. The low-frequency oscillations of the rs-fMRI signal demonstrate an intrinsic spatiotemporal organization in the brain (brain networks) that may relate to the underlying neural activity. In this review article, we briefly describe the current acquisition techniques for rs-fMRI data, from the most common approaches for resting state acquisition strategies, to more recent investigations with dedicated hardware and ultra-high fields. Specific sequences that allow very fast acquisitions, or multiple echoes, are discussed next. We then consider how acquisition methods weighted towards specific parts of the BOLD signal, like the Cerebral Blood Flow (CBF) or Volume (CBV), can provide more spatially specific network information. These approaches are being developed alongside the commonly used BOLD-weighted acquisitions. Finally, specific applications of rs-fMRI to challenging regions such as the laminae in the neocortex, and the networks within the large areas of subcortical white matter regions are discussed. We finish the review with recommendations for acquisition strategies for a range of typical applications of resting state fMRI.
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Affiliation(s)
- Luisa Raimondo
- Spinoza Centre for Neuroimaging, Amsterdam, the Netherlands; Experimental and Applied Psychology, VU University, Amsterdam, the Netherlands
| | - Ĺcaro A F Oliveira
- Spinoza Centre for Neuroimaging, Amsterdam, the Netherlands; Experimental and Applied Psychology, VU University, Amsterdam, the Netherlands
| | - Jurjen Heij
- Spinoza Centre for Neuroimaging, Amsterdam, the Netherlands; Experimental and Applied Psychology, VU University, Amsterdam, the Netherlands
| | | | - Prantik Kundu
- Hyperfine Research Inc, Guilford, CT, United States; Icahn School of Medicine at Mt. Sinai, New York, United States
| | - Renata Ferranti Leoni
- InBrain, Department of Physics, FFCLRP, University of São Paulo, Ribeirão Preto, Brazil
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197
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Automated eloquent cortex localization in brain tumor patients using multi-task graph neural networks. Med Image Anal 2021; 74:102203. [PMID: 34474216 DOI: 10.1016/j.media.2021.102203] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 06/04/2021] [Accepted: 06/08/2021] [Indexed: 11/20/2022]
Abstract
Localizing the eloquent cortex is a crucial part of presurgical planning. While invasive mapping is the gold standard, there is increasing interest in using noninvasive fMRI to shorten and improve the process. However, many surgical patients cannot adequately perform task-based fMRI protocols. Resting-state fMRI has emerged as an alternative modality, but automated eloquent cortex localization remains an open challenge. In this paper, we develop a novel deep learning architecture to simultaneously identify language and primary motor cortex from rs-fMRI connectivity. Our approach uses the representational power of convolutional neural networks alongside the generalization power of multi-task learning to find a shared representation between the eloquent subnetworks. We validate our method on data from the publicly available Human Connectome Project and on a brain tumor dataset acquired at the Johns Hopkins Hospital. We compare our method against feature-based machine learning approaches and a fully-connected deep learning model that does not account for the shared network organization of the data. Our model achieves significantly better performance than competing baselines. We also assess the generalizability and robustness of our method. Our results clearly demonstrate the advantages of our graph convolution architecture combined with multi-task learning and highlight the promise of using rs-fMRI as a presurgical mapping tool.
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198
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Tibon R, Tsvetanov KA, Price D, Nesbitt D, Can C, Henson R. Transient neural network dynamics in cognitive ageing. Neurobiol Aging 2021; 105:217-228. [PMID: 34118787 PMCID: PMC8345312 DOI: 10.1016/j.neurobiolaging.2021.01.035] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Revised: 12/15/2020] [Accepted: 01/06/2021] [Indexed: 01/03/2023]
Abstract
It is important to maintain cognitive function in old age, yet the neural substrates that support successful cognitive ageing remain unclear. One factor that might be crucial, but has been overlooked due to limitations of previous data and methods, is the ability of brain networks to flexibly reorganize and coordinate over a millisecond time-scale. Magnetoencephalography (MEG) provides such temporal resolution, and can be combined with Hidden Markov Models (HMMs) to characterise transient neural states. We applied HMMs to resting-state MEG data from a large cohort (N=595) of population-based adults (aged 18-88), who also completed a range of cognitive tasks. Using multivariate analysis of neural and cognitive profiles, we found that decreased occurrence of "lower-order" brain networks, coupled with increased occurrence of "higher-order" networks, was associated with both increasing age and decreased fluid intelligence. These results favour theories of age-related reductions in neural efficiency over current theories of age-related functional compensation, and suggest that this shift might reflect a stable property of the ageing brain.
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Affiliation(s)
- Roni Tibon
- MRC Cognition & Brain Sciences Unit, University of Cambridge, Cambridge, UK.
| | - Kamen A Tsvetanov
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK; Department of Psychology, University of Cambridge, Cambridge, UK
| | - Darren Price
- MRC Cognition & Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - David Nesbitt
- MRC Cognition & Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Cam Can
- Cambridge Centre for Ageing and Neuroscience (Cam-CAN), University of Cambridge and MRC Cognition and Brain Sciences Unit, Cambridge, UK
| | - Richard Henson
- MRC Cognition & Brain Sciences Unit, University of Cambridge, Cambridge, UK; Department of Psychiatry, University of Cambridge, Cambridge, UK
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199
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Kuhn T, Becerra S, Duncan J, Spivak N, Dang BH, Habelhah B, Mahdavi KD, Mamoun M, Whitney M, Pereles FS, Bystritsky A, Jordan SE. Translating state-of-the-art brain magnetic resonance imaging (MRI) techniques into clinical practice: multimodal MRI differentiates dementia subtypes in a traditional clinical setting. Quant Imaging Med Surg 2021; 11:4056-4073. [PMID: 34476189 PMCID: PMC8339641 DOI: 10.21037/qims-20-1355] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2020] [Accepted: 04/25/2021] [Indexed: 11/06/2022]
Abstract
BACKGROUND This study sought to validate the clinical utility of multimodal magnetic resonance imaging (MRI) techniques in the assessment of neurodegenerative disorders. We intended to demonstrate that advanced neuroimaging techniques commonly used in research can effectively be employed in clinical practice to accurately differentiate heathy aging and dementia subtypes. METHODS Twenty patients with dementia of the Alzheimer's type (DAT) and 18 patients with Parkinson's disease dementia (PDD) were identified using gold-standard techniques. Twenty-three healthy, age and sex matched control participants were also recruited. All participants underwent multimodal MRI including T1 structural, diffusion tensor imaging (DTI), arterial spin labeling (ASL), and magnetic resonance spectroscopy (MRS). MRI modalities were evaluated by trained neuroimaging readers and were separately assessed using cross-validated, iterative discriminant function analyses with subsequent feature reduction techniques. In this way, each modality was evaluated for its ability to differentiate patients with dementia from healthy controls as well as to differentiate dementia subtypes. RESULTS Following individual and group feature reduction, each of the multimodal MRI metrics except MRS successfully differentiated healthy aging from dementia and also demonstrated distinct dementia subtypes. Using the following ten metrics, excellent separation (95.5% accuracy, 92.3% sensitivity; 100.0% specificity) was achieved between healthy aging and neurodegenerative conditions: volume of the left frontal pole, left occipital pole, right posterior superior temporal gyrus, left posterior cingulate gyrus, right planum temporale; perfusion of the left hippocampus and left occipital lobe; fractional anisotropy (FA) of the forceps major and bilateral anterior thalamic radiation. Using volume of the left frontal pole, right posterior superior temporal gyrus, left posterior cingulate gyrus, perfusion of the left hippocampus and left occipital lobe; FA of the forceps major and bilateral anterior thalamic radiation, neurodegenerative subtypes were accurately differentiated as well (87.8% accuracy, 95.2% sensitivity; 85.0% specificity). CONCLUSIONS Regional volumetrics, DTI metrics, and ASL successfully differentiated dementia patients from controls with sufficient sensitivity to differentiate dementia subtypes. Similarly, feature reduction results suggest that advanced analyses can meaningfully identify brain regions with the most positive predictive value and discriminant validity. Together, these advanced neuroimaging techniques can contribute significantly to diagnosis and treatment planning for individual patients.
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Affiliation(s)
- Taylor Kuhn
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, USA
| | - Sergio Becerra
- Neurology Management Associates, Los Angeles, California, USA
| | - John Duncan
- Neurology Management Associates, Los Angeles, California, USA
| | - Norman Spivak
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, USA
| | - Bianca Huan Dang
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, USA
| | | | | | | | | | | | - Alexander Bystritsky
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, USA
| | - Sheldon E. Jordan
- Neurology Management Associates, Los Angeles, California, USA
- Department of Neurology, University of California, Los Angeles, Los Angeles, California, USA
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200
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Csukly G, Szabó Á, Polgár P, Farkas K, Gyebnár G, Kozák LR, Stefanics G. Fronto-thalamic structural and effective connectivity and delusions in schizophrenia: a combined DTI/DCM study. Psychol Med 2021; 51:2083-2093. [PMID: 32329710 PMCID: PMC8426148 DOI: 10.1017/s0033291720000859] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Revised: 02/07/2020] [Accepted: 03/20/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND Schizophrenia (SZ) is a complex disorder characterized by a range of behavioral and cognitive symptoms as well as structural and functional alterations in multiple cortical and subcortical structures. SZ is associated with reduced functional network connectivity involving core regions such as the anterior cingulate cortex (ACC) and the thalamus. However, little is known whether effective coupling, the directed influence of one structure over the other, is altered during rest in the ACC-thalamus network. METHODS We collected resting-state fMRI and diffusion-weighted MRI data from 18 patients and 20 healthy controls. We analyzed fronto-thalamic effective connectivity using dynamic causal modeling for cross-spectral densities in a network consisting of the ACC and the left and right medio-dorsal thalamic regions. We studied structural connectivity using fractional anisotropy (FA). RESULTS We found decreased coupling strength from the right thalamus to the ACC and from the right thalamus to the left thalamus, as well as increased inhibitory intrinsic connectivity in the right thalamus in patients relative to controls. ACC-to-left thalamus coupling strength correlated with the Positive and Negative Syndrome Scale (PANSS) total positive syndrome score and with delusion score. Whole-brain structural analysis revealed several tracts with reduced FA in patients, with a maximum decrease in white matter tracts containing fronto-thalamic and cingulo-thalamic fibers. CONCLUSIONS We found altered effective and structural connectivity within the ACC-thalamus network in SZ. Our results indicate that ACC-thalamus network activity at rest is characterized by reduced thalamus-to-ACC coupling. We suggest that positive symptoms may arise as a consequence of compensatory measures to imbalanced fronto-thalamic coupling.
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Affiliation(s)
- Gábor Csukly
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Ádám Szabó
- Magnetic Resonance Research Centre, Semmelweis University, Budapest, Hungary
| | - Patrícia Polgár
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Kinga Farkas
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Gyula Gyebnár
- Magnetic Resonance Research Centre, Semmelweis University, Budapest, Hungary
| | - Lajos R. Kozák
- Magnetic Resonance Research Centre, Semmelweis University, Budapest, Hungary
| | - Gábor Stefanics
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Wilfriedstrasse 6, 8032, Zurich, Switzerland
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