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Zhang H, Liu Y, Xia D, Jiang M, Li Y, Sun J, Guan H, Zhu L, Song X, Wang J, Fan X, Zhou H. The insular cortex is not insular in thyroid eye disease: neuroimaging revelations of central-peripheral system interaction. J Neuroinflammation 2024; 21:51. [PMID: 38368427 PMCID: PMC10874024 DOI: 10.1186/s12974-024-03044-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 02/13/2024] [Indexed: 02/19/2024] Open
Abstract
BACKGROUND Thyroid eye disease (TED) is highly correlated with dysregulated immunoendocrine status. The insular cortex was found to regulate peripheral inflammation and immunomodulation in mice. This study aimed to explore whether the insular cortex in patients with TED played a modulatory role including the aberrant brain functional alteration and its association with immunoendocrine status. METHODS This study included 34 active patients (AP), 30 inactive patients (IP) with TED, and 45 healthy controls (HC) matched for age, sex, and educational level. Comprehensive clinical details (especially immunoendocrine markers) and resting-state functional magnetic resonance imaging data were collected from each participant. The amplitude of low-frequency fluctuation (ALFF) was used to probe the aberrant alterations of local neural activity. The seed-based functional connectivity (FC) analysis was used to explore the relationship between the insular cortex and each voxel throughout the whole brain. The correlation analysis was conducted to assess the association between insular neurobiomarkers and immunoendocrine parameters. RESULTS When compared with the IP and HC groups, the AP group displayed significantly higher ALFF values in the right insular cortex (INS.R) and lower FC values between the INS.R and the bilateral cerebellum. None of the neurobiomarkers differed between the IP and HC groups. Besides, correlations between insular neurobiomarkers and immunoendocrine markers (free thyroxine, the proportion of T cells, and natural killer cells) were identified in both AP and IP groups. CONCLUSIONS This study was novel in reporting that the dysregulation of the insular cortex activity in TED was associated with abnormal peripheral immunoendocrine status. The insular cortex might play a key role in central-peripheral system interaction in TED. Further research is crucial to enhance our understanding of the central-peripheral system interaction mechanisms involved in autoimmune diseases.
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Affiliation(s)
- Haiyang Zhang
- Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, China
| | - Yuting Liu
- Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, China
| | - Duojin Xia
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Mengda Jiang
- Department of Radiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yinwei Li
- Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, China
| | - Jing Sun
- Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, China
| | - Haixia Guan
- Department of Endocrinology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Ling Zhu
- Department of Radiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xuefei Song
- Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, China
| | - Jue Wang
- Institute of Sports Medicine and Health, Chengdu Sport University, Chengdu, China.
| | - Xianqun Fan
- Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, China.
| | - Huifang Zhou
- Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, China.
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Wang Z, Baeken C, Wu GR. Metabolic Covariance Connectivity of Posterior Cingulate Cortex Associated with Depression Symptomatology Level in Healthy Young Adults. Metabolites 2023; 13:920. [PMID: 37623864 PMCID: PMC10456574 DOI: 10.3390/metabo13080920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 08/01/2023] [Accepted: 08/02/2023] [Indexed: 08/26/2023] Open
Abstract
Early detection in the development of a Major Depressive Disorder (MDD) could guide earlier clinical interventions. Although MDD can begin at a younger age, most people have their first episode in young adulthood. The underlying pathophysiological mechanisms relating to such an increased risk are not clear. The posterior cingulate cortex (PCC), exhibiting high levels of brain connectivity and metabolic activity, plays a pivotal role in the pathological mechanism underlying MDD. In the current study, we used the (F-18) fluorodeoxyglucose (FDG) positron emission tomography (PET) to measure metabolic covariance connectivity of the PCC and investigated its association with depression symptomatology evaluated by the Centre for Epidemiological Studies Depression Inventory-Revised (CESD-R) among 27 healthy individuals aged between 18 and 23 years. A significant negative correlation has been observed between CESD-R scale scores and the PCC metabolic connectivity with the anterior cingulate, medial prefrontal cortex, inferior and middle frontal gyrus, as well as the insula. Overall, our findings suggest that the neural correlates of depressive symptomatology in healthy young adults without a formal diagnosis involve the metabolic connectivity of the PCC. Our findings may have potential implications for early identification and intervention in people at risk of developing depression.
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Affiliation(s)
- Zhixin Wang
- Key Laboratory of Cognition and Personality, Faculty of Psychology, Southwest University, Chongqing 400715, China;
| | - Chris Baeken
- Faculty of Medicine and Health Sciences, Department of Head and Skin, Ghent Experimental Psychiatry (GHEP) Lab, Ghent University, 9000 Ghent, Belgium;
| | - Guo-Rong Wu
- Key Laboratory of Cognition and Personality, Faculty of Psychology, Southwest University, Chongqing 400715, China;
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Bush KA, Calvert ML, Kilts CD. Lessons learned: A neuroimaging research center's transition to open and reproducible science. Front Big Data 2022; 5:988084. [PMID: 36105538 PMCID: PMC9464934 DOI: 10.3389/fdata.2022.988084] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 08/10/2022] [Indexed: 11/13/2022] Open
Abstract
Human functional neuroimaging has evolved dramatically in recent years, driven by increased technical complexity and emerging evidence that functional neuroimaging findings are not generally reproducible. In response to these trends, neuroimaging scientists have developed principles, practices, and tools to both manage this complexity as well as to enhance the rigor and reproducibility of neuroimaging science. We group these best practices under four categories: experiment pre-registration, FAIR data principles, reproducible neuroimaging analyses, and open science. While there is growing recognition of the need to implement these best practices there exists little practical guidance of how to accomplish this goal. In this work, we describe lessons learned from efforts to adopt these best practices within the Brain Imaging Research Center at the University of Arkansas for Medical Sciences over 4 years (July 2018-May 2022). We provide a brief summary of the four categories of best practices. We then describe our center's scientific workflow (from hypothesis formulation to result reporting) and detail how each element of this workflow maps onto these four categories. We also provide specific examples of practices or tools that support this mapping process. Finally, we offer a roadmap for the stepwise adoption of these practices, providing recommendations of why and what to do as well as a summary of cost-benefit tradeoffs for each step of the transition.
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Affiliation(s)
- Keith A. Bush
- Department of Psychiatry, Brain Imaging Research Center, University of Arkansas for Medical Sciences, Little Rock, AR, United States
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Voigt K, Liang EX, Misic B, Ward PGD, Egan GF, Jamadar SD. Metabolic and functional connectivity provide unique and complementary insights into cognition-connectome relationships. Cereb Cortex 2022; 33:1476-1488. [PMID: 35441214 PMCID: PMC9930619 DOI: 10.1093/cercor/bhac150] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Revised: 03/22/2022] [Accepted: 03/24/2022] [Indexed: 11/13/2022] Open
Abstract
A major challenge in current cognitive neuroscience is how functional brain connectivity gives rise to human cognition. Functional magnetic resonance imaging (fMRI) describes brain connectivity based on cerebral oxygenation dynamics (hemodynamic connectivity), whereas [18F]-fluorodeoxyglucose functional positron emission tomography (FDG-fPET) describes brain connectivity based on cerebral glucose uptake (metabolic connectivity), each providing a unique characterization of the human brain. How these 2 modalities differ in their contribution to cognition and behavior is unclear. We used simultaneous resting-state FDG-fPET/fMRI to investigate how hemodynamic connectivity and metabolic connectivity relate to cognitive function by applying partial least squares analyses. Results revealed that although for both modalities the frontoparietal anatomical subdivisions related the strongest to cognition, using hemodynamic measures this network expressed executive functioning, episodic memory, and depression, whereas for metabolic measures this network exclusively expressed executive functioning. These findings demonstrate the unique advantages that simultaneous FDG-PET/fMRI has to provide a comprehensive understanding of the neural mechanisms that underpin cognition and highlights the importance of multimodality imaging in cognitive neuroscience research.
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Affiliation(s)
- Katharina Voigt
- Corresponding author: Turner Institute for Brain and Mental Health, Monash Biomedical Imaging, 770 Blackburn Road, Clayton, VIC 3800, Australia.
| | - Emma X Liang
- Monash Biomedical Imaging, Monash University, 770 Blackburn Road, 3800 Clayton VIC, Australia
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, 3801 University Street Montréal, Quebec H3A 2B4, Canada
| | - Phillip G D Ward
- Monash Biomedical Imaging, Monash University, 770 Blackburn Road, 3800 Clayton VIC, Australia
| | - Gary F Egan
- School of Psychological Sciences Turner and Turner Institute for Brain and Mental Health, Monash University, 18 Innovation Walk, 3800 Clayton VIC, Australia,Monash Biomedical Imaging, Monash University, 770 Blackburn Road, 3800 Clayton VIC, Australia
| | - Sharna D Jamadar
- School of Psychological Sciences Turner and Turner Institute for Brain and Mental Health, Monash University, 18 Innovation Walk, 3800 Clayton VIC, Australia,Monash Biomedical Imaging, Monash University, 770 Blackburn Road, 3800 Clayton VIC, Australia
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Jamadar SD, Ward PGD, Liang EX, Orchard ER, Chen Z, Egan GF. Metabolic and Hemodynamic Resting-State Connectivity of the Human Brain: A High-Temporal Resolution Simultaneous BOLD-fMRI and FDG-fPET Multimodality Study. Cereb Cortex 2021; 31:2855-2867. [PMID: 33529320 DOI: 10.1093/cercor/bhaa393] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 10/26/2020] [Accepted: 11/30/2020] [Indexed: 12/12/2022] Open
Abstract
Simultaneous [18F]-fluorodeoxyglucose positron emission tomography functional magnetic resonance imaging (FDG-PET/fMRI) provides the capacity to image 2 sources of energetic dynamics in the brain-glucose metabolism and the hemodynamic response. fMRI connectivity has been enormously useful for characterizing interactions between distributed brain networks in humans. Metabolic connectivity based on static FDG-PET has been proposed as a biomarker for neurological disease, but FDG-sPET cannot be used to estimate subject-level measures of "connectivity," only across-subject "covariance." Here, we applied high-temporal resolution constant infusion functional positron emission tomography (fPET) to measure subject-level metabolic connectivity simultaneously with fMRI connectivity. fPET metabolic connectivity was characterized by frontoparietal connectivity within and between hemispheres. fPET metabolic connectivity showed moderate similarity with fMRI primarily in superior cortex and frontoparietal regions. Significantly, fPET metabolic connectivity showed little similarity with FDG-sPET metabolic covariance, indicating that metabolic brain connectivity is a nonergodic process whereby individual brain connectivity cannot be inferred from group-level metabolic covariance. Our results highlight the complementary strengths of fPET and fMRI in measuring the intrinsic connectivity of the brain and open up the opportunity for novel fundamental studies of human brain connectivity as well as multimodality biomarkers of neurological diseases.
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Affiliation(s)
- Sharna D Jamadar
- Monash Biomedical Imaging, Melbourne, Vic, 3800 Australia.,Turner Institute for Brain and Mental Health, Monash University, Melbourne, Vic, 3800 Australia.,Australian Research Council Centre of Excellence for Integrative Brain Function, Melbourne 3800, Australia
| | - Phillip G D Ward
- Monash Biomedical Imaging, Melbourne, Vic, 3800 Australia.,Turner Institute for Brain and Mental Health, Monash University, Melbourne, Vic, 3800 Australia.,Australian Research Council Centre of Excellence for Integrative Brain Function, Melbourne 3800, Australia
| | - Emma X Liang
- Monash Biomedical Imaging, Melbourne, Vic, 3800 Australia
| | - Edwina R Orchard
- Monash Biomedical Imaging, Melbourne, Vic, 3800 Australia.,Turner Institute for Brain and Mental Health, Monash University, Melbourne, Vic, 3800 Australia.,Australian Research Council Centre of Excellence for Integrative Brain Function, Melbourne 3800, Australia
| | - Zhaolin Chen
- Monash Biomedical Imaging, Melbourne, Vic, 3800 Australia.,Department of Electrical and Computer Systems Engineering, Monash University, Melbourne, Vic, 3800 Australia
| | - Gary F Egan
- Monash Biomedical Imaging, Melbourne, Vic, 3800 Australia.,Turner Institute for Brain and Mental Health, Monash University, Melbourne, Vic, 3800 Australia.,Australian Research Council Centre of Excellence for Integrative Brain Function, Melbourne 3800, Australia
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Altered Global Brain Signal during Physiologic, Pharmacologic, and Pathologic States of Unconsciousness in Humans and Rats. Anesthesiology 2020; 132:1392-1406. [PMID: 32205548 DOI: 10.1097/aln.0000000000003197] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND Consciousness is supported by integrated brain activity across widespread functionally segregated networks. The functional magnetic resonance imaging-derived global brain signal is a candidate marker for a conscious state, and thus the authors hypothesized that unconsciousness would be accompanied by a loss of global temporal coordination, with specific patterns of decoupling between local regions and global activity differentiating among various unconscious states. METHODS Functional magnetic resonance imaging global signals were studied in physiologic, pharmacologic, and pathologic states of unconsciousness in human natural sleep (n = 9), propofol anesthesia (humans, n = 14; male rats, n = 12), and neuropathological patients (n = 21). The global signal amplitude as well as the correlation between global signal and signals of local voxels were quantified. The former reflects the net strength of global temporal coordination, and the latter yields global signal topography. RESULTS A profound reduction of global signal amplitude was seen consistently across the various unconscious states: wakefulness (median [1st, 3rd quartile], 0.46 [0.21, 0.50]) versus non-rapid eye movement stage 3 of sleep (0.30 [0.24, 0.32]; P = 0.035), wakefulness (0.36 [0.31, 0.42]) versus general anesthesia (0.25 [0.21, 0.28]; P = 0.001), healthy controls (0.30 [0.27, 0.37]) versus unresponsive wakefulness syndrome (0.22 [0.15, 0.24]; P < 0.001), and low dose (0.07 [0.06, 0.08]) versus high dose of propofol (0.04 [0.03, 0.05]; P = 0.028) in rats. Furthermore, non-rapid eye movement stage 3 of sleep was characterized by a decoupling of sensory and attention networks from the global network. General anesthesia and unresponsive wakefulness syndrome were characterized by a dissociation of the majority of functional networks from the global network. This decoupling, however, was dominated by distinct neuroanatomic foci (e.g., precuneus and anterior cingulate cortices). CONCLUSIONS The global temporal coordination of various modules across the brain may distinguish the coarse-grained state of consciousness versus unconsciousness, while the relationship between the global and local signals may define the particular qualities of a particular unconscious state.
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Tong Y, Hocke LM, Frederick BB. Low Frequency Systemic Hemodynamic "Noise" in Resting State BOLD fMRI: Characteristics, Causes, Implications, Mitigation Strategies, and Applications. Front Neurosci 2019; 13:787. [PMID: 31474815 PMCID: PMC6702789 DOI: 10.3389/fnins.2019.00787] [Citation(s) in RCA: 88] [Impact Index Per Article: 17.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Accepted: 07/15/2019] [Indexed: 01/06/2023] Open
Abstract
Advances in functional magnetic resonance imaging (fMRI) acquisition have improved signal to noise to the point where the physiology of the subject is the dominant noise source in resting state fMRI data (rsfMRI). Among these systemic, non-neuronal physiological signals, respiration and to some degree cardiac fluctuations can be removed through modeling, or in the case of newer, faster acquisitions such as simultaneous multislice acquisition, simple spectral filtering. However, significant low frequency physiological oscillation (∼0.01-0.15 Hz) remains in the signal. This is problematic, as it is the precise frequency band occupied by the neuronally modulated hemodynamic responses used to study brain connectivity, precluding its removal by spectral filtering. The source of this signal, and its method of production and propagation in the body, have not been conclusively determined. Here, we summarize the defining characteristics of the systemic low frequency noise signal, and review some current theories about the signal source and the evidence supporting them. The strength and distribution of the systemic LFO signal make characterizing and removing it essential for accurate quantification, especially for resting state connectivity, when no stimulation can be compared with the signal. Widespread correlated non-neuronal signals obscure and distort the more localized patterns of neuronal correlations between interacting brain regions; they may even cause apparent connectivity between regions with no neuronal interaction. Here, we discuss a simple method we have developed to parse the global, moving, blood-borne signal from the stationary, neuronal connectivity signals, substantially reducing the negative correlations that result from global signal regression. Finally, we will discuss some of the uses to which the moving systemic low frequency oscillation can be put if we consider it a "signal" carrying information, rather than simply "noise" complicating the interpretation of resting state connectivity. Properly utilizing this signal may offer insights into subtle hemodynamic alterations that can be used as early indicators of circulatory dysfunction in a number of neuropsychiatric conditions, such as prodromal stroke, moyamoya, and Alzheimer's disease.
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Affiliation(s)
- Yunjie Tong
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States
| | - Lia M. Hocke
- McLean Imaging Center, McLean Hospital, Belmont, MA, United States
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States
| | - Blaise B. Frederick
- McLean Imaging Center, McLean Hospital, Belmont, MA, United States
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States
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Achterberg M, van der Meulen M. Genetic and environmental influences on MRI scan quantity and quality. Dev Cogn Neurosci 2019; 38:100667. [PMID: 31170550 PMCID: PMC6969338 DOI: 10.1016/j.dcn.2019.100667] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Revised: 05/14/2019] [Accepted: 05/20/2019] [Indexed: 01/24/2023] Open
Abstract
The current study provides an overview of quantity and quality of MRI data in a large developmental twin sample (N = 512, aged 7–9), and investigated to what extent scan quantity and quality were influenced by genetic and environmental factors. This was examined in a fixed scan protocol consisting of two functional MRI tasks, high resolution structural anatomy (3DT1) and connectivity (DTI) scans, and a resting state scan. Overall, scan quantity was high (88% of participants completed all runs), while scan quality decreased with increasing session length. Scanner related distress was negatively associated with scan quantity (i.e., completed runs), but not with scan quality (i.e., included runs). In line with previous studies, behavioral genetic analyses showed that genetics explained part of the variation in head motion, with heritability estimates of 29% for framewise displacement and 65% for absolute displacement. Additionally, our results revealed that subtle head motion (after exclusion of excessive head motion) showed lower heritability estimates (0–14%), indicating that findings of motion-corrected and quality-controlled MRI data may be less confounded by genetic factors. These findings provide insights in factors contributing to scan quality in children, an issue that is highly relevant for the field of developmental neuroscience.
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Affiliation(s)
- Michelle Achterberg
- Leiden Consortium on Individual Development, Leiden University, the Netherlands; Institute of Psychology, Leiden University, the Netherlands; Leiden Institute for Brain and Cognition, Leiden University, the Netherlands.
| | - Mara van der Meulen
- Leiden Consortium on Individual Development, Leiden University, the Netherlands; Institute of Psychology, Leiden University, the Netherlands; Leiden Institute for Brain and Cognition, Leiden University, the Netherlands
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