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Chan MMY, Choi CXT, Tsoi TCW, Zhong J, Han YMY. Clinical and neuropsychological correlates of theta-band functional excitation-inhibition ratio in autism: An EEG study. Clin Neurophysiol 2024; 163:56-67. [PMID: 38703700 DOI: 10.1016/j.clinph.2024.04.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 01/29/2024] [Accepted: 04/05/2024] [Indexed: 05/06/2024]
Abstract
OBJECTIVE How abnormal brain signaling impacts cognition in autism spectrum disorder (ASD) remained elusive. This study aimed to investigate the local and global brain signaling in ASD indicated by theta-band functional excitation-inhibition (fE/I) ratio and explored psychophysiological relationships between fE/I, cognitive deficits, and ASD symptomatology. METHODS A total of 83 ASD and typically developing (TD) individuals participated in this study. Participants' interference control and set-shifting abilities were assessed. Resting-state electroencephalography (EEG) was used for estimating theta-band fE/I ratio. RESULTS ASD individuals (n = 31 without visual EEG abnormality; n = 22 with visual EEG abnormality) generally performed slower in a cognitive task tapping interference control and set-maintenance abilities, but only ASD individuals with visually abnormal EEG performed significantly slower than their TD counterparts (Bonferroni-corrected ps < .001). Heightened theta-band fE/I ratios at the whole-head level, left and right hemispheres were observed in the ASD subgroup without visual EEG abnormality only (Bonferroni-corrected ps < .001), which remained highly significant when only data from medication-naïve participants were analyzed. In addition, higher left hemispheric fE/I ratios in ASD individuals without visual EEG abnormality were significantly correlated with faster interference control task performance, in turn faster reaction time was significantly associated with less severe restricted, repetitive behavior (Bonferroni-corrected ps ≤ .0017). CONCLUSIONS Differential theta-band fE/I within the ASD population. Heightened theta-band fE/I in ASD without visual EEG abnormality may be associated with more efficient filtering of distractors and a less severe ASD symptom manifestation. SIGNIFICANCE Brain signaling, indicated by theta-band fE/I, was different in ASD subgroups. Only ASD with visually-normal EEG showed heightened theta-band fE/I, which was associated with faster processing of visual distractors during a cognitive task. More efficient distractor filtering was associated with less restricted, repetitive behaviors.
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Affiliation(s)
- Melody M Y Chan
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region; Queensland Brain Institute, The University of Queensland, St Lucia QLD 4072, Australia
| | - Coco X T Choi
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region
| | - Tom C W Tsoi
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region
| | - Junpei Zhong
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region
| | - Yvonne M Y Han
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region; University Research Facility in Behavioral and Systems Neuroscience (UBSN), The Hong Kong Polytechnic University, Hong Kong Special Administrative Region.
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Ramduny J, Uddin LQ, Vanderwal T, Feczko E, Fair DA, Kelly C, Baskin-Sommers A. Increasing the representation of minoritized youth for inclusive and reproducible brain-behavior associations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.22.600221. [PMID: 38979302 PMCID: PMC11230295 DOI: 10.1101/2024.06.22.600221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Population neuroscience datasets allow researchers to estimate reliable effect sizes for brain-behavior associations because of their large sample sizes. However, these datasets undergo strict quality control to mitigate sources of noise, such as head motion. This practice often excludes a disproportionate number of minoritized individuals. We employ motion-ordering and motion-ordering+resampling (bagging) to test if these methods preserve functional MRI (fMRI) data in the Adolescent Brain Cognitive Development Study ( N = 5,733 ). Black and Hispanic youth exhibited excess head motion relative to data collected from White youth, and were discarded disproportionately when using conventional approaches. Both methods retained more than 99% of Black and Hispanic youth. They produced reproducible brain-behavior associations across low-/high-motion racial/ethnic groups based on motion-limited fMRI data. The motion-ordering and bagging methods are two feasible approaches that can enhance sample representation for testing brain-behavior associations and fulfill the promise of consortia datasets to produce generalizable effect sizes across diverse populations.
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Affiliation(s)
- Jivesh Ramduny
- Department of Psychology, Yale University, New Haven, CT, USA
- Kavli Institute for Neuroscience, Yale University, New Haven, CT, USA
| | - Lucina Q Uddin
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
- Department of Psychology, University of California Los Angeles, Los Angeles, CA, USA
| | - Tamara Vanderwal
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Eric Feczko
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Damien A Fair
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
| | - Clare Kelly
- School of Psychology, Trinity College Dublin, Dublin, Ireland
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Arielle Baskin-Sommers
- Department of Psychology, Yale University, New Haven, CT, USA
- Department of Psychiatry, Yale University, New Haven, CT, USA
- Wu Tsai Institute, Yale University, New Haven, CT, USA
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Smith MJ, Phillips RV, Luque-Fernandez MA, Maringe C. Application of targeted maximum likelihood estimation in public health and epidemiological studies: a systematic review. Ann Epidemiol 2023; 86:34-48.e28. [PMID: 37343734 DOI: 10.1016/j.annepidem.2023.06.004] [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: 03/03/2023] [Revised: 05/24/2023] [Accepted: 06/06/2023] [Indexed: 06/23/2023]
Abstract
PURPOSE The targeted maximum likelihood estimation (TMLE) statistical data analysis framework integrates machine learning, statistical theory, and statistical inference to provide a least biased, efficient, and robust strategy for estimation and inference of a variety of statistical and causal parameters. We describe and evaluate the epidemiological applications that have benefited from recent methodological developments. METHODS We conducted a systematic literature review in PubMed for articles that applied any form of TMLE in observational studies. We summarized the epidemiological discipline, geographical location, expertize of the authors, and TMLE methods over time. We used the Roadmap of Targeted Learning and Causal Inference to extract key methodological aspects of the publications. We showcase the contributions to the literature of these TMLE results. RESULTS Of the 89 publications included, 33% originated from the University of California at Berkeley, where the framework was first developed by Professor Mark van der Laan. By 2022, 59% of the publications originated from outside the United States and explored up to seven different epidemiological disciplines in 2021-2022. Double-robustness, bias reduction, and model misspecification were the main motivations that drew researchers toward the TMLE framework. Through time, a wide variety of methodological, tutorial, and software-specific articles were cited, owing to the constant growth of methodological developments around TMLE. CONCLUSIONS There is a clear dissemination trend of the TMLE framework to various epidemiological disciplines and to increasing numbers of geographical areas. The availability of R packages, publication of tutorial papers, and involvement of methodological experts in applied publications have contributed to an exponential increase in the number of studies that understood the benefits and adoption of TMLE.
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Affiliation(s)
- Matthew J Smith
- Inequalities in Cancer Outcomes Network, London School of Hygiene and Tropical Medicine, London, UK.
| | - Rachael V Phillips
- Division of Biostatistics, School of Public Health, University of California at Berkeley, Berkeley, CA
| | - Miguel Angel Luque-Fernandez
- Inequalities in Cancer Outcomes Network, London School of Hygiene and Tropical Medicine, London, UK; Department of Statistics and Operations Research, University of Granada, Granada, Spain
| | - Camille Maringe
- Inequalities in Cancer Outcomes Network, London School of Hygiene and Tropical Medicine, London, UK
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Wu CH, Hsu TW, Lai KL, Wang YF, Fuh JL, Wu HM, Lirng JF, Wang SJ, Chen SP. Disrupted Brain Functional Status in Patients with Reversible Cerebral Vasoconstriction Syndrome. Ann Neurol 2023; 94:772-784. [PMID: 37345341 DOI: 10.1002/ana.26724] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 06/11/2023] [Accepted: 06/15/2023] [Indexed: 06/23/2023]
Abstract
OBJECTIVES The aim of this study was to investigate the functional networks in subjects with reversible cerebral vasoconstriction syndrome (RCVS) using resting-state functional magnetic resonance imaging (rs-fMRI). METHODS We prospectively recruited patients with RCVS and healthy controls (HCs) between February 2017 and April 2021. The rs-fMRI data were analyzed using graph theory methods. We compared node-based global and regional topological metrics (Bundle 1) and network-based intranetwork and internetwork connectivity (Bundle 2) between RCVS patients and HCs. We also explored the associations of clinical and vascular (ie, the Lindegaard index, LI) parameters with significant rs-fMRI metrics. RESULTS A total of 104 RCVS patients and 93 HCs were included in the final analysis. We identified significantly decreased local efficiency of the left dorsal anterior insula (dAI; p = 0.0005) in RCVS patients within 30 days after disease onset as compared to HCs, which improved 1 month later. RCVS patients also had increased global efficiency (p = 0.009) and decreased average degree centrality (p = 0.045), clustering coefficient (p = 0.033), and assortativity values (p = 0.003) in node-based analysis. In addition, patients with RCVS had increased internetwork connectivity of the default mode network (DMN) with the salience (p = 0.027) and dorsal attention (p = 0.016) networks. Significant correlations between LI and regional local efficiency in left dAI (rs = -0.418, p = 0.042) was demonstrated. INTERPRETATION The significantly lower local efficiency of the left dAI, suggestive of impaired central autonomic modulation, was negatively correlated with vasoconstriction severity, which is highly plausible for the pathogenesis of RCVS. ANN NEUROL 2023;94:772-784.
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Affiliation(s)
- Chia-Hung Wu
- Department of Radiology, Taipei Veterans General Hospital, Taipei, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Tun-Wei Hsu
- Department of Radiology, Taipei Veterans General Hospital, Taipei, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Nuclear Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Kuan-Lin Lai
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan
- Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Yen-Feng Wang
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan
- Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Jong-Ling Fuh
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan
- Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Hsiu-Mei Wu
- Department of Radiology, Taipei Veterans General Hospital, Taipei, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Jiing-Feng Lirng
- Department of Radiology, Taipei Veterans General Hospital, Taipei, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Shuu-Jiun Wang
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan
- Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Shih-Pin Chen
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan
- Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Division of Translational Research, Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan
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Gao P, Wang YS, Lu QY, Rong MJ, Fan XR, Holmes AJ, Dong HM, Li HF, Zuo XN. Brief mock-scan training reduces head motion during real scanning for children: A growth curve study. Dev Cogn Neurosci 2023; 61:101244. [PMID: 37062244 PMCID: PMC10139901 DOI: 10.1016/j.dcn.2023.101244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 03/14/2023] [Accepted: 04/11/2023] [Indexed: 04/18/2023] Open
Abstract
Pediatric neuroimaging datasets are rapidly increasing in scales. Despite strict protocols in data collection and preprocessing focused on improving data quality, the presence of head motion still impedes our understanding of neurodevelopmental mechanisms. Large head motion can lead to severe noise and artifacts in magnetic resonance imaging (MRI) studies, inflating correlations between adjacent brain areas and decreasing correlations between spatial distant territories, especially in children and adolescents. Here, by leveraging mock-scans of 123 Chinese children and adolescents, we demonstrated the presence of increased head motion in younger participants. Critically, a 5.5-minute training session in an MRI mock scanner was found to effectively suppress the head motion in the children and adolescents. Therefore, we suggest that mock scanner training should be part of the quality assurance routine prior to formal MRI data collection, particularly in large-scale population-level neuroimaging initiatives for pediatrics.
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Affiliation(s)
- Peng Gao
- College of Information and Computer, Taiyuan University of Technology, No. 79 West Street Yingze, Taiyuan, Shanxi 030024, China
| | - Yin-Shan Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Faculty of Psychology, Beijing Normal University, No 19 Xinjiekouwai Street, Haidian District, Beijing 100875, China; Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, No 19 Xinjiekouwai Street, Haidian District, Beijing 100875, China
| | - Qiu-Yu Lu
- State Key Laboratory of Cognitive Neuroscience and Learning, Faculty of Psychology, Beijing Normal University, No 19 Xinjiekouwai Street, Haidian District, Beijing 100875, China; Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, No 19 Xinjiekouwai Street, Haidian District, Beijing 100875, China
| | - Meng-Jie Rong
- State Key Laboratory of Cognitive Neuroscience and Learning, Faculty of Psychology, Beijing Normal University, No 19 Xinjiekouwai Street, Haidian District, Beijing 100875, China; Institute of Psychology, Chinese Academy of Sciences, No 16 Lincui Road, Chaoyang District, Beijing 100101, China
| | - Xue-Ru Fan
- State Key Laboratory of Cognitive Neuroscience and Learning, Faculty of Psychology, Beijing Normal University, No 19 Xinjiekouwai Street, Haidian District, Beijing 100875, China; Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, No 19 Xinjiekouwai Street, Haidian District, Beijing 100875, China; Institute of Psychology, Chinese Academy of Sciences, No 16 Lincui Road, Chaoyang District, Beijing 100101, China
| | - Avram J Holmes
- Department of Psychology, Yale University, 1 Prospect Street, New Haven, CT 06511, USA
| | - Hao-Ming Dong
- State Key Laboratory of Cognitive Neuroscience and Learning, Faculty of Psychology, Beijing Normal University, No 19 Xinjiekouwai Street, Haidian District, Beijing 100875, China; Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, No 19 Xinjiekouwai Street, Haidian District, Beijing 100875, China.
| | - Hai-Fang Li
- College of Information and Computer, Taiyuan University of Technology, No. 79 West Street Yingze, Taiyuan, Shanxi 030024, China.
| | - Xi-Nian Zuo
- State Key Laboratory of Cognitive Neuroscience and Learning, Faculty of Psychology, Beijing Normal University, No 19 Xinjiekouwai Street, Haidian District, Beijing 100875, China; Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, No 19 Xinjiekouwai Street, Haidian District, Beijing 100875, China; Institute of Psychology, Chinese Academy of Sciences, No 16 Lincui Road, Chaoyang District, Beijing 100101, China; National Basic Science Data Center, No 2 Dongsheng South Road, Haidian District, Beijing 100190, China.
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6
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Tupitsa E, Egbuniwe I, Lloyd WK, Puertollano M, Macdonald B, Joanknecht K, Sakaki M, van Reekum CM. Heart Rate Variability Covaries with Amygdala Functional Connectivity During Voluntary Emotion Regulation. Neuroimage 2023; 274:120136. [PMID: 37116768 DOI: 10.1016/j.neuroimage.2023.120136] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 03/19/2023] [Accepted: 04/25/2023] [Indexed: 04/30/2023] Open
Abstract
The Neurovisceral Integration Model posits that shared neural networks support the effective regulation of emotions and heart rate, with heart rate variability (HRV) serving as an objective, peripheral index of prefrontal inhibitory control. Prior neuroimaging studies have predominantly examined both HRV and associated neural functional connectivity at rest, as opposed to contexts that require active emotion regulation. The present study sought to extend upon previous resting-state functional connectivity findings, examining task-related HRV and corresponding amygdala functional connectivity during a cognitive reappraisal task. Seventy adults (52 older and 18 younger adults, 18-84 years, 51% male) received instructions to cognitively reappraise negative affective images during functional MRI scanning. HRV measures were derived from a finger pulse signal throughout the scan. During the task, younger adults exhibited a significant inverse association between HRV and amygdala-medial prefrontal cortex (mPFC) functional connectivity, in which higher task-related HRV was correlated with weaker amygdala-mPFC coupling, whereas older adults displayed a slight positive, albeit non-significant correlation. Furthermore, voxelwise whole-brain functional connectivity analyses showed that higher task-based HRV was linked to weaker right amygdala-posterior cingulate cortex connectivity across older and younger adults, and in older adults, higher task-related HRV correlated positively with stronger right amygdala-right ventrolateral prefrontal cortex connectivity. Collectively, these findings highlight the importance of assessing HRV and neural functional connectivity during active regulatory contexts to further identify neural concomitants of HRV and adaptive emotion regulation.
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Affiliation(s)
- Emma Tupitsa
- Centre for Integrative Neuroscience and Neurodynamics, School of Psychology and Clinical Language Sciences, University of Reading, Reading, UK
| | - Ifeoma Egbuniwe
- Centre for Integrative Neuroscience and Neurodynamics, School of Psychology and Clinical Language Sciences, University of Reading, Reading, UK
| | - William K Lloyd
- Centre for Integrative Neuroscience and Neurodynamics, School of Psychology and Clinical Language Sciences, University of Reading, Reading, UK; School of Health Sciences, University of Manchester, Manchester, UK
| | - Marta Puertollano
- Centre for Integrative Neuroscience and Neurodynamics, School of Psychology and Clinical Language Sciences, University of Reading, Reading, UK
| | - Birthe Macdonald
- Centre for Integrative Neuroscience and Neurodynamics, School of Psychology and Clinical Language Sciences, University of Reading, Reading, UK; URPP Dynamics of Healthy Ageing, University of Zurich, Zurich, Switzerland
| | - Karin Joanknecht
- Centre for Integrative Neuroscience and Neurodynamics, School of Psychology and Clinical Language Sciences, University of Reading, Reading, UK
| | - Michiko Sakaki
- Hector Research Institute of Education Sciences and Psychology, University of Tübingen, Tübingen, Germany; Research Institute, Kochi University of Technology, Kochi, Japan
| | - Carien M van Reekum
- Centre for Integrative Neuroscience and Neurodynamics, School of Psychology and Clinical Language Sciences, University of Reading, Reading, UK.
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Kim J, De Asis‐Cruz J, Kapse K, Limperopoulos C. Systematic evaluation of head motion on resting-state functional connectivity MRI in the neonate. Hum Brain Mapp 2023; 44:1934-1948. [PMID: 36576333 PMCID: PMC9980896 DOI: 10.1002/hbm.26183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 11/18/2022] [Accepted: 12/01/2022] [Indexed: 12/29/2022] Open
Abstract
Reliability and robustness of resting state functional connectivity MRI (rs-fcMRI) relies, in part, on minimizing the influence of head motion on measured brain signals. The confounding effects of head motion on functional connectivity have been extensively studied in adults, but its impact on newborn brain connectivity remains unexplored. Here, using a large newborn data set consisting of 159 rs-fcMRI scans acquired in the Developing Brain Institute at Children's National Hospital and 416 scans from The Developing Human Connectome Project (dHCP), we systematically investigated associations between head motion and rs-fcMRI. Head motion during the scan significantly affected connectivity at sensory-related networks and default mode networks, and at the whole brain scale; the direction of motion effects varied across the whole brain. Comparing high- versus low-head motion groups suggested that head motion can impact connectivity estimates across the whole brain. Censoring of high-motion volumes using frame-wise displacement significantly reduced the confounding effects of head motion on neonatal rs-fcMRI. Lastly, in the dHCP data set, we demonstrated similar persistent associations between head motion and network connectivity despite implementing a standard denoising strategy. Collectively, our results highlight the importance of using rigorous head motion correction in preprocessing neonatal rs-fcMRI to yield reliable estimates of brain activity.
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Affiliation(s)
- Jung‐Hoon Kim
- Developing Brain Institute, Children's NationalWashingtonDistrict of ColumbiaUSA
| | | | - Kushal Kapse
- Developing Brain Institute, Children's NationalWashingtonDistrict of ColumbiaUSA
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Di X, Biswal BB. A functional MRI pre-processing and quality control protocol based on statistical parametric mapping (SPM) and MATLAB. FRONTIERS IN NEUROIMAGING 2023; 1:1070151. [PMID: 37555150 PMCID: PMC10406300 DOI: 10.3389/fnimg.2022.1070151] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 12/19/2022] [Indexed: 08/10/2023]
Abstract
Functional MRI (fMRI) has become a popular technique to study brain functions and their alterations in psychiatric and neurological conditions. The sample sizes for fMRI studies have been increasing steadily, and growing studies are sourced from open-access brain imaging repositories. Quality control becomes critical to ensure successful data processing and valid statistical results. Here, we outline a simple protocol for fMRI data pre-processing and quality control based on statistical parametric mapping (SPM) and MATLAB. The focus of this protocol is not only to identify and remove data with artifacts and anomalies, but also to ensure the processing has been performed properly. We apply this protocol to the data from fMRI Open quality control (QC) Project, and illustrate how each quality control step can help to identify potential issues. We also show that simple steps such as skull stripping can improve coregistration between the functional and anatomical images.
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Affiliation(s)
- Xin Di
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, United States
| | - Bharat B. Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, United States
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9
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Lu B, Yan CG. Demonstrating quality control procedures for fMRI in DPABI. Front Neurosci 2023; 17:1069639. [PMID: 36895416 PMCID: PMC9989208 DOI: 10.3389/fnins.2023.1069639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 02/01/2023] [Indexed: 02/25/2023] Open
Abstract
Quality control (QC) is an important stage for functional magnetic resonance imaging (fMRI) studies. The methods for fMRI QC vary in different fMRI preprocessing pipelines. The inflating sample size and number of scanning sites for fMRI studies further add to the difficulty and working load of the QC procedure. Therefore, as a constituent part of the Demonstrating Quality Control Procedures in fMRI research topic in Frontiers, we preprocessed a well-organized open-available dataset using DPABI pipelines to illustrate the QC procedure in DPABI. Six categories of DPABI-derived reports were used to eliminate images without adequate quality. After the QC procedure, twelve participants (8.6%) were categorized as excluded and eight participants (5.8%) were categorized as uncertain. More automatic QC tools were needed in the big-data era while visually inspecting images was still indispensable now.
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Affiliation(s)
- Bin Lu
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Chao-Gan Yan
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.,International Big-Data Center for Depression Research, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
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10
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Henry TR, Fogleman ND, Nugiel T, Cohen JR. Effect of methylphenidate on functional controllability: a preliminary study in medication-naïve children with ADHD. Transl Psychiatry 2022; 12:518. [PMID: 36528602 PMCID: PMC9759578 DOI: 10.1038/s41398-022-02283-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 11/18/2022] [Accepted: 12/05/2022] [Indexed: 12/23/2022] Open
Abstract
Methylphenidate (MPH) is the recommended first-line treatment for attention-deficit/hyperactivity disorder (ADHD). While MPH's mechanism of action as a dopamine and noradrenaline transporter blocker is well known, how this translates to ADHD-related symptom mitigation is still unclear. As functional connectivity is reliably altered in ADHD, with recent literature indicating dysfunctional connectivity dynamics as well, one possible mechanism is through altering brain network dynamics. In a double-blind, placebo-controlled MPH crossover trial, 19 medication-naïve children with ADHD underwent two functional MRI scanning sessions (one on MPH and one on placebo) that included a resting state scan and two inhibitory control tasks; 27 typically developing (TD) children completed the same protocol without medication. Network control theory, which quantifies how brain activity reacts to system inputs based on underlying connectivity, was used to assess differences in average and modal functional controllability during rest and both tasks between TD children and children with ADHD (on and off MPH) and between children with ADHD on and off MPH. Children with ADHD on placebo exhibited higher average controllability and lower modal controllability of attention, reward, and somatomotor networks than TD children. Children with ADHD on MPH were statistically indistinguishable from TD children on almost all controllability metrics. These findings suggest that MPH may stabilize functional network dynamics in children with ADHD, both reducing reactivity of brain organization and making it easier to achieve brain states necessary for cognitively demanding tasks.
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Affiliation(s)
- Teague R Henry
- Department of Psychology and School of Data Science, University of Virginia, Charlottesville, VA, USA.
| | - Nicholas D Fogleman
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Tehila Nugiel
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jessica R Cohen
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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11
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Recent Developments in Autism Genetic Research: A Scientometric Review from 2018 to 2022. Genes (Basel) 2022; 13:genes13091646. [PMID: 36140813 PMCID: PMC9498399 DOI: 10.3390/genes13091646] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 09/12/2022] [Accepted: 09/12/2022] [Indexed: 12/13/2022] Open
Abstract
Genetic research in Autism Spectrum Disorder (ASD) has progressed tremendously in recent decades. Dozens of genetic loci and hundreds of alterations in the genetic sequence, expression, epigenetic transformation, and interactions with other physiological and environmental systems have been found to increase the likelihood of developing ASD. There is therefore a need to represent this wide-ranging yet voluminous body of literature in a systematic manner so that this information can be synthesised and understood at a macro level. Therefore, this study made use of scientometric methods, particularly document co-citation analysis (DCA), to systematically review literature on ASD genetic research from 2018 to 2022. A total of 14,818 articles were extracted from Scopus and analyzed with CiteSpace. An optimized DCA analysis revealed that recent literature on ASD genetic research can be broadly organised into 12 major clusters representing various sub-topics. These clusters are briefly described in the manuscript and potential applications of this study are discussed.
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