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Kumar VA, Lee J, Liu HL, Allen JW, Filippi CG, Holodny AI, Hsu K, Jain R, McAndrews MP, Peck KK, Shah G, Shimony JS, Singh S, Zeineh M, Tanabe J, Vachha B, Vossough A, Welker K, Whitlow C, Wintermark M, Zaharchuk G, Sair HI. Recommended Resting-State fMRI Acquisition and Preprocessing Steps for Preoperative Mapping of Language and Motor and Visual Areas in Adult and Pediatric Patients with Brain Tumors and Epilepsy. AJNR Am J Neuroradiol 2024; 45:139-148. [PMID: 38164572 DOI: 10.3174/ajnr.a8067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Accepted: 10/12/2023] [Indexed: 01/03/2024]
Abstract
Resting-state (rs) fMRI has been shown to be useful for preoperative mapping of functional areas in patients with brain tumors and epilepsy. However, its lack of standardization limits its widespread use and hinders multicenter collaboration. The American Society of Functional Neuroradiology, American Society of Pediatric Neuroradiology, and the American Society of Neuroradiology Functional and Diffusion MR Imaging Study Group recommend specific rs-fMRI acquisition approaches and preprocessing steps that will further support rs-fMRI for future clinical use. A task force with expertise in fMRI from multiple institutions provided recommendations on the rs-fMRI steps needed for mapping of language, motor, and visual areas in adult and pediatric patients with brain tumor and epilepsy. These were based on an extensive literature review and expert consensus.Following rs-fMRI acquisition parameters are recommended: minimum 6-minute acquisition time; scan with eyes open with fixation; obtain rs-fMRI before both task-based fMRI and contrast administration; temporal resolution of ≤2 seconds; scanner field strength of 3T or higher. The following rs-fMRI preprocessing steps and parameters are recommended: motion correction (seed-based correlation analysis [SBC], independent component analysis [ICA]); despiking (SBC); volume censoring (SBC, ICA); nuisance regression of CSF and white matter signals (SBC); head motion regression (SBC, ICA); bandpass filtering (SBC, ICA); and spatial smoothing with a kernel size that is twice the effective voxel size (SBC, ICA).The consensus recommendations put forth for rs-fMRI acquisition and preprocessing steps will aid in standardization of practice and guide rs-fMRI program development across institutions. Standardized rs-fMRI protocols and processing pipelines are essential for multicenter trials and to implement rs-fMRI as part of standard clinical practice.
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Affiliation(s)
- V A Kumar
- From the The University of Texas MD Anderson Cancer Center (V.A.K., J.L., H.-L.L., M.W.), Houston, Texas
| | - J Lee
- From the The University of Texas MD Anderson Cancer Center (V.A.K., J.L., H.-L.L., M.W.), Houston, Texas
| | - H-L Liu
- From the The University of Texas MD Anderson Cancer Center (V.A.K., J.L., H.-L.L., M.W.), Houston, Texas
| | - J W Allen
- Emory University (J.W.A.), Atlanta, Georgia
| | - C G Filippi
- Tufts University (C.G.F.), Boston, Massachusetts
| | - A I Holodny
- Memorial Sloan Kettering Cancer Center (A.I.H., K.K.P.), New York, New York
| | - K Hsu
- New York University (K.H., R.J.), New York, New York
| | - R Jain
- New York University (K.H., R.J.), New York, New York
| | - M P McAndrews
- University of Toronto (M.P.M.), Toronto, Ontario, Canada
| | - K K Peck
- Memorial Sloan Kettering Cancer Center (A.I.H., K.K.P.), New York, New York
| | - G Shah
- University of Michigan (G.S.), Ann Arbor, Michigan
| | - J S Shimony
- Washington University School of Medicine (J.S.S.), St. Louis, Missouri
| | - S Singh
- University of Texas Southwestern Medical Center (S.S.), Dallas, Texas
| | - M Zeineh
- Stanford University (M.Z., G.Z.), Palo Alto, California
| | - J Tanabe
- University of Colorado (J.T.), Aurora, Colorado
| | - B Vachha
- University of Massachusetts (B.V.), Worcester, Massachusetts
| | - A Vossough
- Children's Hospital of Philadelphia, University of Pennsylvania (A.V.), Philadelphia, Pennsylvania
| | - K Welker
- Mayo Clinic (K.W.), Rochester, Minnesota
| | - C Whitlow
- Wake Forest University (C.W.), Winston-Salem, North Carolina
| | - M Wintermark
- From the The University of Texas MD Anderson Cancer Center (V.A.K., J.L., H.-L.L., M.W.), Houston, Texas
| | - G Zaharchuk
- Stanford University (M.Z., G.Z.), Palo Alto, California
| | - H I Sair
- Johns Hopkins University (H.I.S.), Baltimore, Maryland
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Dressing A, Kaller CP, Nitschke K, Beume LA, Kuemmerer D, Schmidt CS, Bormann T, Umarova RM, Egger K, Rijntjes M, Weiller C, Martin M. Neural correlates of acute apraxia: Evidence from lesion data and functional MRI in stroke patients. Cortex 2019; 120:1-21. [DOI: 10.1016/j.cortex.2019.05.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2018] [Revised: 02/28/2019] [Accepted: 05/07/2019] [Indexed: 10/26/2022]
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Pfannmöller J, Strauss S, Langner I, Usichenko T, Lotze M. Investigations on maladaptive plasticity in the sensorimotor cortex of unilateral upper limb CRPS I patients. Restor Neurol Neurosci 2019; 37:143-153. [PMID: 30988242 DOI: 10.3233/rnn-180886] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
BACKGROUND Patients with a complex regional pain syndrome (CRPS) in the upper limb show a sensory and motor impairment of the hand. Decreased intra-cortical-inhibition (ICI) of the motor representation of the affected hand muscle and decreased somatosensory hand representation size were related to maladaptive plasticity. OBJECTIVE To achieve new insights about CRPS we examined whether these alterations were present in a single cohort. METHODS We used a multi-modal approach comprising behavioral testing, transcranial magnetic stimulation, and high resolution fMRI combined with a new analysis technique for improved neuronal specificity. RESULTS We found a decreased pinch-grip performance, two-point discrimination on the fingertips, ICI in the motor cortex, and representation size of the hand in Brodmann Area 3b (BA3b) in the somatosensory cortex. Our analysis further showed that correlations with ICI on the non-affected side were absent on the affected side. CONCLUSIONS This study is the first to gather behavioral, neurophysiologic and imaging measurements for one patient cohort and it therefore enables a comprehensive view of collapsed associations of function and representation focused on the hemisphere contralateral to the affected hand.
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Affiliation(s)
- J Pfannmöller
- Functional Imaging Unit, Center for Diagnostic Radiology, University of Greifswald, Germany
| | - S Strauss
- Functional Imaging Unit, Center for Diagnostic Radiology, University of Greifswald, Germany.,Neurology, University of Greifswald, Germany
| | - I Langner
- Department of Trauma and Reconstructive Surgery, Division of Hand Surgery and Functional Microsurgery, University Medicine Greifswald, Germany
| | - T Usichenko
- Department of Anesthesiology, University Medicine Greifswald, Germany
| | - M Lotze
- Functional Imaging Unit, Center for Diagnostic Radiology, University of Greifswald, Germany
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Fu S, Ma X, Wu Y, Bai Z, Yi Y, Liu M, Lan Z, Hua K, Huang S, Li M, Jiang G. Altered Local and Large-Scale Dynamic Functional Connectivity Variability in Posttraumatic Stress Disorder: A Resting-State fMRI Study. Front Psychiatry 2019; 10:234. [PMID: 31031661 PMCID: PMC6474202 DOI: 10.3389/fpsyt.2019.00234] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Accepted: 03/28/2019] [Indexed: 11/18/2022] Open
Abstract
Posttraumatic stress disorder (PTSD) is a psychiatric condition that can emerge after exposure to an exceedingly traumatic event. Previous neuroimaging studies have indicated that PTSD is characterized by aberrant resting-state functional connectivity (FC). However, few existing studies on PTSD have examined dynamic changes in resting-state FC related to network formation, interaction, and dissolution over time. In this study, we compared the dynamic resting-state local and large-scale FC between PTSD patients (n = 22) and healthy controls (HC; n = 22; conducted as standard deviation in resting-state local and large-scale FC over a series of sliding windows). Local dynamic FC was examined by calculating the dynamic regional homogeneity (dReHo), and large-scale dynamic FC (dFC) was investigated between regions with significant dReHo group differences. For the PTSD patients, we also investigated the relationship between symptom severity and dFC/dReHo. Our results showed that PTSD patients were characterized by I) increased dynamic (more variable) dReHo in left precuneus (PCu); II) increased dynamic (more variable) dFC between the left PCu and left insula; and III) decreased dFC between left PCu and left inferior parietal lobe (IPL), and decreased dFC between left PCu and right PCu. However, there is no significant correlation between the clinical indicators and dReHo/dFC after the family-wise-error (FWE) correction. These findings provided the initial evidence that PTSD is characterized by aberrant patterns of fluctuating communication within brain system such as the default mode network (DMN) and among different brain systems such as the salience network and the DMN.
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Affiliation(s)
- Shishun Fu
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
- The Department of Medical Imaging of Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Xiaofen Ma
- The Department of Medical Imaging of Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Yunfan Wu
- The Department of Medical Imaging of Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Zhigang Bai
- The Department of Medical Imaging of Affiliated Hospital, Inner Mongolia University for Nationalities, Hohhot, China
| | - Yin Yi
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
- The Department of Medical Imaging of Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Mengchen Liu
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
- The Department of Medical Imaging of Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Zhihong Lan
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
- The Department of Medical Imaging of Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Kelei Hua
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
- The Department of Medical Imaging of Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Shumei Huang
- The Department of Medical Imaging of Guangdong Second Provincial General Hospital, Guangzhou, China
- Guangdong Medical University, Dongguan, China
| | - Meng Li
- The Department of Medical Imaging of Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Guihua Jiang
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
- The Department of Medical Imaging of Guangdong Second Provincial General Hospital, Guangzhou, China
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5
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Baxter L, Fitzgibbon S, Moultrie F, Goksan S, Jenkinson M, Smith S, Andersson J, Duff E, Slater R. Optimising neonatal fMRI data analysis: Design and validation of an extended dHCP preprocessing pipeline to characterise noxious-evoked brain activity in infants. Neuroimage 2019; 186:286-300. [PMID: 30414984 PMCID: PMC6347570 DOI: 10.1016/j.neuroimage.2018.11.006] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2018] [Revised: 10/16/2018] [Accepted: 11/06/2018] [Indexed: 11/21/2022] Open
Abstract
The infant brain is unlike the adult brain, with considerable differences in morphological, neurodynamic, and haemodynamic features. As the majority of current MRI analysis tools were designed for use in adults, a primary objective of the Developing Human Connectome Project (dHCP) is to develop optimised methodological pipelines for the analysis of neonatal structural, resting state, and diffusion MRI data. Here, in an independent neonatal dataset we have extended and optimised the dHCP fMRI preprocessing pipeline for the analysis of stimulus-response fMRI data. We describe and validate this extended dHCP fMRI preprocessing pipeline to analyse changes in brain activity evoked following an acute noxious stimulus applied to the infant's foot. We compare the results obtained from this extended dHCP pipeline to results obtained from a typical FSL FEAT-based analysis pipeline, evaluating the pipelines' outputs using a wide range of tests. We demonstrate that a substantial increase in spatial specificity and sensitivity to signal can be attained with a bespoke neonatal preprocessing pipeline through optimised motion and distortion correction, ICA-based denoising, and haemodynamic modelling. The improved sensitivity and specificity, made possible with this extended dHCP pipeline, will be paramount in making further progress in our understanding of the development of sensory processing in the infant brain.
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Affiliation(s)
- Luke Baxter
- Department of Paediatrics, University of Oxford, Oxford, United Kingdom
| | - Sean Fitzgibbon
- FMRIB, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Fiona Moultrie
- Department of Paediatrics, University of Oxford, Oxford, United Kingdom
| | - Sezgi Goksan
- Department of Paediatrics, University of Oxford, Oxford, United Kingdom
| | - Mark Jenkinson
- FMRIB, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Stephen Smith
- FMRIB, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Jesper Andersson
- FMRIB, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Eugene Duff
- Department of Paediatrics, University of Oxford, Oxford, United Kingdom
| | - Rebeccah Slater
- Department of Paediatrics, University of Oxford, Oxford, United Kingdom.
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6
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Kellmeyer P, Berkemeier R, Ball T. P 33 Different spatial observation scales in the analysis of an fMRI language task lead to substantially differing functional interpretations. Clin Neurophysiol 2017. [DOI: 10.1016/j.clinph.2017.06.112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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Abstract
Abstract:Currently, many scientific fields such as psychology or biomedicine face a methodological crisis concerning the reproducibility, replicability, and validity of their research. In neuroimaging, similar methodological concerns have taken hold of the field, and researchers are working frantically toward finding solutions for the methodological problems specific to neuroimaging. This article examines some ethical and legal implications of this methodological crisis in neuroimaging. With respect to ethical challenges, the article discusses the impact of flawed methods in neuroimaging research in cognitive and clinical neuroscience, particularly with respect to faulty brain-based models of human cognition, behavior, and personality. Specifically examined is whether such faulty models, when they are applied to neurological or psychiatric diseases, could put patients at risk, and whether this places special obligations on researchers using neuroimaging. In the legal domain, the actual use of neuroimaging as evidence in United States courtrooms is surveyed, followed by an examination of ways that the methodological problems may create challenges for the criminal justice system. Finally, the article reviews and promotes some promising ideas and initiatives from within the neuroimaging community for addressing the methodological problems.
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8
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Fiederer LDJ, Vorwerk J, Lucka F, Dannhauer M, Yang S, Dümpelmann M, Schulze-Bonhage A, Aertsen A, Speck O, Wolters CH, Ball T. The role of blood vessels in high-resolution volume conductor head modeling of EEG. Neuroimage 2016; 128:193-208. [PMID: 26747748 PMCID: PMC5225375 DOI: 10.1016/j.neuroimage.2015.12.041] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2015] [Revised: 11/27/2015] [Accepted: 12/22/2015] [Indexed: 12/18/2022] Open
Abstract
Reconstruction of the electrical sources of human EEG activity at high spatio-temporal accuracy is an important aim in neuroscience and neurological diagnostics. Over the last decades, numerous studies have demonstrated that realistic modeling of head anatomy improves the accuracy of source reconstruction of EEG signals. For example, including a cerebro-spinal fluid compartment and the anisotropy of white matter electrical conductivity were both shown to significantly reduce modeling errors. Here, we for the first time quantify the role of detailed reconstructions of the cerebral blood vessels in volume conductor head modeling for EEG. To study the role of the highly arborized cerebral blood vessels, we created a submillimeter head model based on ultra-high-field-strength (7T) structural MRI datasets. Blood vessels (arteries and emissary/intraosseous veins) were segmented using Frangi multi-scale vesselness filtering. The final head model consisted of a geometry-adapted cubic mesh with over 17×10(6) nodes. We solved the forward model using a finite-element-method (FEM) transfer matrix approach, which allowed reducing computation times substantially and quantified the importance of the blood vessel compartment by computing forward and inverse errors resulting from ignoring the blood vessels. Our results show that ignoring emissary veins piercing the skull leads to focal localization errors of approx. 5 to 15mm. Large errors (>2cm) were observed due to the carotid arteries and the dense arterial vasculature in areas such as in the insula or in the medial temporal lobe. Thus, in such predisposed areas, errors caused by neglecting blood vessels can reach similar magnitudes as those previously reported for neglecting white matter anisotropy, the CSF or the dura - structures which are generally considered important components of realistic EEG head models. Our findings thus imply that including a realistic blood vessel compartment in EEG head models will be helpful to improve the accuracy of EEG source analyses particularly when high accuracies in brain areas with dense vasculature are required.
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Affiliation(s)
- L D J Fiederer
- Intracranial EEG and Brain Imaging Lab, Epilepsy Center, University Hospital Freiburg, Germany; Neurobiology and Biophysics, Faculty of Biology, University of Freiburg, Germany; BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Germany; Bernstein Center Freiburg, University of Freiburg, Germany.
| | - J Vorwerk
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Germany
| | - F Lucka
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Germany; Institute for Computational and Applied Mathematics, University of Münster, Germany; Department of Computer Science, University College London, WC1E 6BT London, UK
| | - M Dannhauer
- Scientific Computing and Imaging Institute, 72 So. Central Campus Drive, Salt Lake City, Utah 84112, USA; Center for Integrative Biomedical Computing, University of Utah, 72 S. Central Campus Drive, 84112, Salt Lake City, UT, USA
| | - S Yang
- Dept. of Biomedical Magnetic Resonance, Otto-von-Guericke University Magdeburg, Germany
| | - M Dümpelmann
- Intracranial EEG and Brain Imaging Lab, Epilepsy Center, University Hospital Freiburg, Germany; BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Germany
| | - A Schulze-Bonhage
- BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Germany; Bernstein Center Freiburg, University of Freiburg, Germany
| | - A Aertsen
- Neurobiology and Biophysics, Faculty of Biology, University of Freiburg, Germany; Bernstein Center Freiburg, University of Freiburg, Germany
| | - O Speck
- Dept. of Biomedical Magnetic Resonance, Otto-von-Guericke University Magdeburg, Germany; Leibniz Institute for Neurobiology, Magdeburg, Germany; German Center for Neurodegenerative Diseases (DZNE), Site Magdeburg, Germany; Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - C H Wolters
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Germany
| | - T Ball
- Intracranial EEG and Brain Imaging Lab, Epilepsy Center, University Hospital Freiburg, Germany; BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Germany; Bernstein Center Freiburg, University of Freiburg, Germany
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9
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Neural representation of swallowing is retained with age. A functional neuroimaging study validated by classical and Bayesian inference. Behav Brain Res 2015; 286:308-17. [PMID: 25771712 DOI: 10.1016/j.bbr.2015.03.009] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2015] [Revised: 02/27/2015] [Accepted: 03/04/2015] [Indexed: 11/20/2022]
Abstract
We investigated the neural representation of swallowing in two age groups for a total of 51 healthy participants (seniors: average age 64 years; young adults: average age 24 years) using high spatial resolution functional magnetic resonance imaging (fMRI). Two statistical comparisons (classical and Bayesian inference) revealed no significant differences between subject groups, apart from higher cortical activation for the seniors in the frontal pole 1 of Brodmann's Area 10 using Bayesian inference. Seniors vs. young participants showed longer reaction times and higher skin conductance response (SCR) during swallowing. We found a positive association of SCR and fMRI-activation only among seniors in areas processing sensorimotor performance, arousal and emotional perception. The results indicate that the highly automated swallowing network retains its functionality with age. However, seniors with higher SCR during swallowing appear to also engage areas involved in attention control and emotional regulation, possibly suggesting increased attention and emotional demands during task performance.
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10
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Lin JA, Zhu H, Mihye A, Sun W, Ibrahim JG. Functional-mixed effects models for candidate genetic mapping in imaging genetic studies. Genet Epidemiol 2014; 38:680-91. [PMID: 25270690 PMCID: PMC4236266 DOI: 10.1002/gepi.21854] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2014] [Revised: 07/29/2014] [Accepted: 08/13/2014] [Indexed: 01/09/2023]
Abstract
The aim of this paper is to develop a functional-mixed effects modeling (FMEM) framework for the joint analysis of high-dimensional imaging data in a large number of locations (called voxels) of a three-dimensional volume with a set of genetic markers and clinical covariates. Our FMEM is extremely useful for efficiently carrying out the candidate gene approaches in imaging genetic studies. FMEM consists of two novel components including a mixed effects model for modeling nonlinear genetic effects on imaging phenotypes by introducing the genetic random effects at each voxel and a jumping surface model for modeling the variance components of the genetic random effects and fixed effects as piecewise smooth functions of the voxels. Moreover, FMEM naturally accommodates the correlation structure of the genetic markers at each voxel, while the jumping surface model explicitly incorporates the intrinsically spatial smoothness of the imaging data. We propose a novel two-stage adaptive smoothing procedure to spatially estimate the piecewise smooth functions, particularly the irregular functional genetic variance components, while preserving their edges among different piecewise-smooth regions. We develop weighted likelihood ratio tests and derive their exact approximations to test the effect of the genetic markers across voxels. Simulation studies show that FMEM significantly outperforms voxel-wise approaches in terms of higher sensitivity and specificity to identify regions of interest for carrying out candidate genetic mapping in imaging genetic studies. Finally, FMEM is used to identify brain regions affected by three candidate genes including CR1, CD2AP, and PICALM, thereby hoping to shed light on the pathological interactions between these candidate genes and brain structure and function.
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Affiliation(s)
- Ja-An Lin
- Departments of Biostatistics, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Hongtu Zhu
- Departments of Biostatistics, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Biomedical Research Imaging Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Ahn Mihye
- Departments of Biostatistics, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Wei Sun
- Departments of Biostatistics, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Departments of Biostatistics Genetics, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Joseph G Ibrahim
- Departments of Biostatistics, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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11
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Pajula J, Tohka J. Effects of spatial smoothing on inter-subject correlation based analysis of FMRI. Magn Reson Imaging 2014; 32:1114-24. [DOI: 10.1016/j.mri.2014.06.001] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2013] [Revised: 04/06/2014] [Accepted: 06/15/2014] [Indexed: 10/25/2022]
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12
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Di Pietro F, Stanton TR, Moseley GL, Lotze M, McAuley JH. Interhemispheric somatosensory differences in chronic pain reflect abnormality of the healthy side. Hum Brain Mapp 2014; 36:508-18. [PMID: 25256887 DOI: 10.1002/hbm.22643] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2014] [Revised: 09/14/2014] [Accepted: 09/15/2014] [Indexed: 11/07/2022] Open
Abstract
It is widely accepted that complex regional pain syndrome (CRPS) is associated with shrinkage of the primary somatosensory cortex (S1) representation of the affected limb. However, supporting evidence is surprisingly limited and may be compromised by high risk of bias. This study compared the S1 spatial representation of the hand in 17 patients with upper-limb CRPS to 16 healthy controls, using functional MRI. Innocuous vibration was delivered to digits one (D1) and five (D5) in a block-design. Resultant activation maxima were located within a bilateral S1 mask, determined a priori. Distance between D1 and D5 activation maxima, calculated for both hands, was used as a measure of S1 representation. Analyses were blinded to group and hand. In patients, S1 representation was smaller for the affected hand than it was for the healthy hand (t(11) = 2.02, P = 0.03), as predicted. However, S1 representation of the affected hand was no different to that of either hand in controls. Critically, S1 representation of the healthy hand of patients was larger than that of controls' hands. CRPS seems to be associated with an enlarged representation of the healthy hand, not a smaller representation of the affected hand. These findings raise important questions about neuroplasticity in CRPS.
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Affiliation(s)
- Flavia Di Pietro
- Neuroscience Research Australia, Sydney, Australia ; Faculty of Medicine, University of New South Wales, Sydney, Australia; Department of Anatomy and Histology, Sydney Medical School, University of Sydney
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Hyun JW, Li Y, Gilmore JH, Lu Z, Styner M, Zhu H. SGPP: spatial Gaussian predictive process models for neuroimaging data. Neuroimage 2014; 89:70-80. [PMID: 24269800 PMCID: PMC4134945 DOI: 10.1016/j.neuroimage.2013.11.018] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2013] [Revised: 10/22/2013] [Accepted: 11/11/2013] [Indexed: 11/29/2022] Open
Abstract
The aim of this paper is to develop a spatial Gaussian predictive process (SGPP) framework for accurately predicting neuroimaging data by using a set of covariates of interest, such as age and diagnostic status, and an existing neuroimaging data set. To achieve a better prediction, we not only delineate spatial association between neuroimaging data and covariates, but also explicitly model spatial dependence in neuroimaging data. The SGPP model uses a functional principal component model to capture medium-to-long-range (or global) spatial dependence, while SGPP uses a multivariate simultaneous autoregressive model to capture short-range (or local) spatial dependence as well as cross-correlations of different imaging modalities. We propose a three-stage estimation procedure to simultaneously estimate varying regression coefficients across voxels and the global and local spatial dependence structures. Furthermore, we develop a predictive method to use the spatial correlations as well as the cross-correlations by employing a cokriging technique, which can be useful for the imputation of missing imaging data. Simulation studies and real data analysis are used to evaluate the prediction accuracy of SGPP and show that SGPP significantly outperforms several competing methods, such as voxel-wise linear model, in prediction. Although we focus on the morphometric variation of lateral ventricle surfaces in a clinical study of neurodevelopment, it is expected that SGPP is applicable to other imaging modalities and features.
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Affiliation(s)
- Jung Won Hyun
- Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Yimei Li
- Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Zhaohua Lu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Martin Styner
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Hongtu Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
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Kushnir T, Arzouan Y, Karni A, Manor D. Brain activation associated with practiced left hand mirror writing. BRAIN AND LANGUAGE 2013; 125:38-46. [PMID: 23454072 DOI: 10.1016/j.bandl.2012.12.015] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2012] [Revised: 12/10/2012] [Accepted: 12/15/2012] [Indexed: 06/01/2023]
Abstract
Mirror writing occurs in healthy children, in various pathologies and occasionally in healthy adults. There are only scant experimental data on the underlying brain processes. Eight, right-handed, healthy young adults were scanned (BOLD-fMRI) before and after practicing left-hand mirror-writing (lh-MW) over seven sessions. They wrote dictated words, using either the right hand with regularly oriented writing or lh-MW. An MRI compatible stylus-point recording system was used and online visual feedback was provided. Practice resulted in increased speed and readability of lh-MW but the number of movement segments was unchanged. Post-training signal increases occurred in visual, right lateral and medial premotor areas, and in right anterior and posterior peri-sylvian areas corresponding to language areas. These results suggest that lh-MW may constitute a latent ability that can be reinstated by a relatively brief practice experience. Concurrently, right hemisphere language processing areas may emerge, reflecting perhaps a reduction in trans-hemispheric suppression.
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Affiliation(s)
- T Kushnir
- Dept. of Diagnostic Imaging, MRI Unit, The Sheba Medical Center, Tel Hashomer 52621, Israel.
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Multiscale adaptive generalized estimating equations for longitudinal neuroimaging data. Neuroimage 2013; 72:91-105. [PMID: 23357075 DOI: 10.1016/j.neuroimage.2013.01.034] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2012] [Revised: 01/14/2013] [Accepted: 01/19/2013] [Indexed: 12/29/2022] Open
Abstract
Many large-scale longitudinal imaging studies have been or are being widely conducted to better understand the progress of neuropsychiatric and neurodegenerative disorders and normal brain development. The goal of this article is to develop a multiscale adaptive generalized estimation equation (MAGEE) method for spatial and adaptive analysis of neuroimaging data from longitudinal studies. MAGEE is applicable to making statistical inference on regression coefficients in both balanced and unbalanced longitudinal designs and even in twin and familial studies, whereas standard software platforms have several major limitations in handling these complex studies. Specifically, conventional voxel-based analyses in these software platforms involve Gaussian smoothing imaging data and then independently fitting a statistical model at each voxel. However, the conventional smoothing methods suffer from the lack of spatial adaptivity to the shape and spatial extent of region of interest and the arbitrary choice of smoothing extent, while independently fitting statistical models across voxels does not account for the spatial properties of imaging observations and noise distribution. To address such drawbacks, we adapt a powerful propagation-separation (PS) procedure to sequentially incorporate the neighboring information of each voxel and develop a new novel strategy to solely update a set of parameters of interest, while fixing other nuisance parameters at their initial estimators. Simulation studies and real data analysis show that MAGEE significantly outperforms voxel-based analysis.
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