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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 PMCID: PMC11285996 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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Hwang SH, Park D, Paeng S, Lee SW, Lee SH, Kim HF. Pneumatic tactile stimulus delivery system for studying brain responses evoked by active finger touch with fMRI. J Neurosci Methods 2023; 397:109938. [PMID: 37544383 DOI: 10.1016/j.jneumeth.2023.109938] [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: 04/18/2023] [Revised: 07/19/2023] [Accepted: 08/03/2023] [Indexed: 08/08/2023]
Abstract
BACKGROUND Primates use their hands to actively touch objects and collect information. To study tactile information processing, it is important for participants to experience tactile stimuli through active touch while monitoring brain activities. NEW METHOD Here, we developed a pneumatic tactile stimulus delivery system (pTDS) that delivers various tactile stimuli on a programmed schedule and allows voluntary finger touches during MRI scanning. The pTDS uses a pneumatic actuator to move tactile stimuli and place them in a finger hole. A photosensor detects the time when an index finger touches a tactile stimulus, enabling the analysis of the touch-elicited brain responses. RESULTS We examined brain responses while the participants actively touched braille objects presented by the pTDS. BOLD responses during tactile perception were significantly stronger in a finger touch area of the contralateral somatosensory cortex compared with that of visual perception. CONCLUSION The pTDS enables MR studies of brain mechanisms for tactile processes through natural finger touch.
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Affiliation(s)
- Seong-Hwan Hwang
- School of Biological Sciences, College of Natural Sciences, Seoul National University (SNU), Seoul 08826, Republic of Korea
| | - Doyoung Park
- Department of Bio and Brain Engineering, College of Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea; Institute of Psychological Sciences, Institute of Social Sciences, Seoul National University (SNU), Seoul 08826, Republic of Korea
| | - Somang Paeng
- School of Biological Sciences, College of Natural Sciences, Seoul National University (SNU), Seoul 08826, Republic of Korea
| | - Sang Wan Lee
- Department of Bio and Brain Engineering, College of Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea; Department of Brain and Cognitive Sciences, College of Life Science and Bioengineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Sue-Hyun Lee
- Department of Psychology, College of Social Sciences, Seoul National University (SNU), Seoul 08826, Republic of Korea.
| | - Hyoung F Kim
- School of Biological Sciences, College of Natural Sciences, Seoul National University (SNU), Seoul 08826, Republic of Korea.
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Brahimaj BC, Kochanski RB, Pearce JJ, Guryildirim M, Gerard CS, Kocak M, Sani S, Byrne RW. Structural and Functional Imaging in Glioma Management. Neurosurgery 2021; 88:211-221. [PMID: 33313852 DOI: 10.1093/neuros/nyaa360] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Accepted: 04/26/2020] [Indexed: 01/08/2023] Open
Abstract
The goal of glioma surgery is maximal safe resection in order to provide optimal tumor control and survival benefit to the patient. There are multiple imaging modalities beyond traditional contrast-enhanced magnetic resonance imaging (MRI) that have been incorporated into the preoperative workup of patients presenting with gliomas. The aim of these imaging modalities is to identify cortical and subcortical areas of eloquence, and their relationship to the lesion. In this article, multiple modalities are described with an emphasis on the underlying technology, clinical utilization, advantages, and disadvantages of each. functional MRI and its role in identifying hemispheric dominance and areas of language and motor are discussed. The nuances of magnetoencephalography and transcranial magnetic stimulation in localization of eloquent cortex are examined, as well as the role of diffusion tensor imaging in defining normal white matter tracts in glioma surgery. Lastly, we highlight the role of stimulated Raman spectroscopy in intraoperative histopathological diagnosis of tissue to guide tumor resection. Tumors may shift the normal arrangement of functional anatomy in the brain; thus, utilization of multiple modalities may be helpful in operative planning and patient counseling for successful surgery.
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Affiliation(s)
- Bledi C Brahimaj
- Department of Neurosurgery, Rush University Medical Center, Chicago, Illinois
| | - Ryan B Kochanski
- Department of Neurosurgery, Rush University Medical Center, Chicago, Illinois
| | - John J Pearce
- Department of Neurosurgery, Rush University Medical Center, Chicago, Illinois
| | - Melike Guryildirim
- Department of Radiology and Radiological Science, Johns Hopkins Hospital, Baltimore, Maryland
| | - Carter S Gerard
- Swedish Neuroscience Institute, Swedish Medical Center, Seattle, Washington
| | - Mehmet Kocak
- Department of Diagnostic Radiology and Nuclear Medicine, Rush University Medical Center, Chicago, Illinois
| | - Sepehr Sani
- Department of Neurosurgery, Rush University Medical Center, Chicago, Illinois
| | - Richard W Byrne
- Department of Neurosurgery, Rush University Medical Center, Chicago, Illinois
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Utility of Preoperative Blood-Oxygen-Level-Dependent Functional MR Imaging in Patients with a Central Nervous System Neoplasm. Neuroimaging Clin N Am 2021; 31:93-102. [PMID: 33220831 PMCID: PMC10040207 DOI: 10.1016/j.nic.2020.09.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Functional neuroimaging provides means to understand the relationship between brain structure and associated functions. Functional MR (fMR) imaging can offer a unique insight into preoperative planning for central nervous system (CNS) neoplasms by identifying areas of the brain effected or spared by the neoplasm. BOLD (blood-oxygen-level-dependent) fMR imaging can be reliably used to map eloquent cortex presurgically and is sufficiently accurate for neurosurgical planning. In patients with brain tumors undergoing neurosurgical intervention, fMR imaging can decrease postoperative morbidity. This article discusses the applications, significance, and interpretation of BOLD fMR imaging, and its applications in presurgical planning for CNS neoplasms.
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Ades-Aron B, Lemberskiy G, Veraart J, Golfinos J, Fieremans E, Novikov DS, Shepherd T. Improved Task-based Functional MRI Language Mapping in Patients with Brain Tumors through Marchenko-Pastur Principal Component Analysis Denoising. Radiology 2020; 298:365-373. [PMID: 33289611 DOI: 10.1148/radiol.2020200822] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Background Functional MRI improves preoperative planning in patients with brain tumors, but task-correlated signal intensity changes are only 2%-3% above baseline. This makes accurate functional mapping challenging. Marchenko-Pastur principal component analysis (MP-PCA) provides a novel strategy to separate functional MRI signal from noise without requiring user input or prior data representation. Purpose To determine whether MP-PCA denoising improves activation magnitude for task-based functional MRI language mapping in patients with brain tumors. Materials and Methods In this Health Insurance Portability and Accountability Act-compliant study, MP-PCA performance was first evaluated by using simulated functional MRI data with a known ground truth. Right-handed, left-language-dominant patients with brain tumors who successfully performed verb generation, sentence completion, and finger tapping functional MRI tasks were retrospectively identified between January 2017 and August 2018. On the group level, for each task, histograms of z scores for original and MP-PCA denoised data were extracted from relevant regions and contralateral homologs were seeded by a neuroradiologist blinded to functional MRI findings. Z scores were compared with paired two-sided t tests, and distributions were compared with effect size measurements and the Kolmogorov-Smirnov test. The number of voxels with a z score greater than 3 was used to measure task sensitivity relative to task duration. Results Twenty-three patients (mean age ± standard deviation, 43 years ± 18; 13 women) were evaluated. MP-PCA denoising led to a higher median z score of task-based functional MRI voxel activation in left hemisphere cortical regions for verb generation (from 3.8 ± 1.0 to 4.5 ± 1.4; P < .001), sentence completion (from 3.7 ± 1.0 to 4.3 ± 1.4; P < .001), and finger tapping (from 6.9 ± 2.4 to 7.9 ± 2.9; P < .001). Median z scores did not improve in contralateral homolog regions for verb generation (from -2.7 ± 0.54 to -2.5 ± 0.40; P = .90), sentence completion (from -2.3 ± 0.21 to -2.4 ± 0.37; P = .39), or finger tapping (from -2.3 ± 1.20 to -2.7 ± 1.40; P = .07). Individual functional MRI task durations could be truncated by at least 40% after MP-PCA without degradation of clinically relevant correlations between functional cortex and functional MRI tasks. Conclusion Denoising with Marchenko-Pastur principal component analysis led to higher task correlations in relevant cortical regions during functional MRI language mapping in patients with brain tumors. © RSNA, 2020 Online supplemental material is available for this article.
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Affiliation(s)
- Benjamin Ades-Aron
- From the Center for Biomedical Imaging, Department of Radiology (B.A.A., G.L., J.V., E.F., D.S.N., T.S.) and Department of Neurosurgery (J.G.), New York University School of Medicine, 2nd Floor, 660 First Ave, New York, NY 10016; and Department of Electrical and Computer Engineering, New York University Tandon School of Engineering, New York, NY (B.A.A.)
| | - Gregory Lemberskiy
- From the Center for Biomedical Imaging, Department of Radiology (B.A.A., G.L., J.V., E.F., D.S.N., T.S.) and Department of Neurosurgery (J.G.), New York University School of Medicine, 2nd Floor, 660 First Ave, New York, NY 10016; and Department of Electrical and Computer Engineering, New York University Tandon School of Engineering, New York, NY (B.A.A.)
| | - Jelle Veraart
- From the Center for Biomedical Imaging, Department of Radiology (B.A.A., G.L., J.V., E.F., D.S.N., T.S.) and Department of Neurosurgery (J.G.), New York University School of Medicine, 2nd Floor, 660 First Ave, New York, NY 10016; and Department of Electrical and Computer Engineering, New York University Tandon School of Engineering, New York, NY (B.A.A.)
| | - John Golfinos
- From the Center for Biomedical Imaging, Department of Radiology (B.A.A., G.L., J.V., E.F., D.S.N., T.S.) and Department of Neurosurgery (J.G.), New York University School of Medicine, 2nd Floor, 660 First Ave, New York, NY 10016; and Department of Electrical and Computer Engineering, New York University Tandon School of Engineering, New York, NY (B.A.A.)
| | - Els Fieremans
- From the Center for Biomedical Imaging, Department of Radiology (B.A.A., G.L., J.V., E.F., D.S.N., T.S.) and Department of Neurosurgery (J.G.), New York University School of Medicine, 2nd Floor, 660 First Ave, New York, NY 10016; and Department of Electrical and Computer Engineering, New York University Tandon School of Engineering, New York, NY (B.A.A.)
| | - Dmitry S Novikov
- From the Center for Biomedical Imaging, Department of Radiology (B.A.A., G.L., J.V., E.F., D.S.N., T.S.) and Department of Neurosurgery (J.G.), New York University School of Medicine, 2nd Floor, 660 First Ave, New York, NY 10016; and Department of Electrical and Computer Engineering, New York University Tandon School of Engineering, New York, NY (B.A.A.)
| | - Timothy Shepherd
- From the Center for Biomedical Imaging, Department of Radiology (B.A.A., G.L., J.V., E.F., D.S.N., T.S.) and Department of Neurosurgery (J.G.), New York University School of Medicine, 2nd Floor, 660 First Ave, New York, NY 10016; and Department of Electrical and Computer Engineering, New York University Tandon School of Engineering, New York, NY (B.A.A.)
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Chaudhry AA, Naim S, Gul M, Chaudhry A, Chen M, Jandial R, Badie B. Utility of Preoperative Blood-Oxygen-Level-Dependent Functional MR Imaging in Patients with a Central Nervous System Neoplasm. Radiol Clin North Am 2019; 57:1189-1198. [PMID: 31582044 DOI: 10.1016/j.rcl.2019.07.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Functional neuroimaging provides means to understand the relationship between brain structure and associated functions. Functional MR (fMR) imaging can offer a unique insight into preoperative planning for central nervous system (CNS) neoplasms by identifying areas of the brain effected or spared by the neoplasm. BOLD (blood-oxygen-level-dependent) fMR imaging can be reliably used to map eloquent cortex presurgically and is sufficiently accurate for neurosurgical planning. In patients with brain tumors undergoing neurosurgical intervention, fMR imaging can decrease postoperative morbidity. This article discusses the applications, significance, and interpretation of BOLD fMR imaging, and its applications in presurgical planning for CNS neoplasms.
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Affiliation(s)
- Ammar A Chaudhry
- Precision Imaging Lab, Department of Diagnostic Radiology, City of Hope National Cancer Center, 1500 East Duarte Road, Los Angeles, CA 91010, USA.
| | - Sohaib Naim
- Department of Diagnostic Radiology, City of Hope National Cancer Center, 1500 East Duarte Road, Los Angeles, CA 91010, USA
| | - Maryam Gul
- Department of Diagnostic Radiology, City of Hope National Cancer Center, 1500 East Duarte Road, Los Angeles, CA 91010, USA
| | - Abbas Chaudhry
- Department of Diagnostic Radiology, City of Hope National Cancer Center, 1500 East Duarte Road, Los Angeles, CA 91010, USA
| | - Mike Chen
- Department of Neurosurgery, City of Hope National Cancer Center, 1500 East Duarte Road, Los Angeles, CA 91010, USA
| | - Rahul Jandial
- Department of Neurosurgery, City of Hope National Cancer Center, 1500 East Duarte Road, Los Angeles, CA 91010, USA
| | - Behnam Badie
- Department of Neurosurgery, City of Hope National Cancer Center, 1500 East Duarte Road, Los Angeles, CA 91010, USA
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Rabany L, Brocke S, Calhoun VD, Pittman B, Corbera S, Wexler BE, Bell MD, Pelphrey K, Pearlson GD, Assaf M. Dynamic functional connectivity in schizophrenia and autism spectrum disorder: Convergence, divergence and classification. Neuroimage Clin 2019; 24:101966. [PMID: 31401405 PMCID: PMC6700449 DOI: 10.1016/j.nicl.2019.101966] [Citation(s) in RCA: 73] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Revised: 05/15/2019] [Accepted: 07/31/2019] [Indexed: 01/16/2023]
Abstract
BACKGROUND Over the recent years there has been a growing debate regarding the extent and nature of the overlap in neuropathology between schizophrenia (SZ) and autism spectrum disorder (ASD). Dynamic functional network connectivity (dFNC) is a recent analysis method that explores temporal patterns of functional connectivity (FC). We compared resting-state dFNC in SZ, ASD and healthy controls (HC), characterized the associations between temporal patterns and symptoms, and performed a three-way classification analysis based on dFNC indices. METHODS Resting-state fMRI was collected from 100 young adults: 33 SZ, 33 ASD, 34 HC. Independent component analysis (ICA) was performed, followed by dFNC analysis (window = 33 s, step = 1TR, k-means clustering). Temporal patterns were compared between groups, correlated with symptoms, and classified via cross-validated three-way discriminant analysis. RESULTS Both clinical groups displayed an increased fraction of time (FT) spent in a state of weak, intra-network connectivity [p < .001] and decreased FT in a highly-connected state [p < .001]. SZ further showed decreased number of transitions between states [p < .001], decreased FT in a widely-connected state [p < .001], increased dwell time (DT) in the weakly-connected state [p < .001], and decreased DT in the highly-connected state [p = .001]. Social behavior scores correlated with DT in the widely-connected state in SZ [r = 0.416, p = .043], but not ASD. Classification correctly identified SZ at high rates (81.8%), while ASD and HC at lower rates. CONCLUSIONS Results indicate a severe and pervasive pattern of temporal aberrations in SZ (specifically, being "stuck" in a state of weak connectivity), that distinguishes SZ participants from both ASD and HC, and is associated with clinical symptoms.
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Affiliation(s)
- Liron Rabany
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA.
| | - Sophy Brocke
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA
| | - Vince D Calhoun
- Mind Research Network, Albuquerque, NM, USA; University of New Mexico, Department of ECE, Albuquerque, NM, USA; Yale University, School of Medicine, Department of Psychiatry, New Haven, CT, USA
| | - Brian Pittman
- Yale University, School of Medicine, Department of Psychiatry, New Haven, CT, USA
| | - Silvia Corbera
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA; Central Connecticut State University, Department of Psychological Science, New Britain, CT, USA
| | - Bruce E Wexler
- Yale University, School of Medicine, Department of Psychiatry, New Haven, CT, USA
| | - Morris D Bell
- Yale University, School of Medicine, Department of Psychiatry, New Haven, CT, USA; VA Connecticut Healthcare System West Haven, CT, USA
| | - Kevin Pelphrey
- Autism and Neurodevelopment Disorders Institute, George Washington University and Children's National Medical Center, DC, USA
| | - Godfrey D Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA; Yale University, School of Medicine, Department of Psychiatry, New Haven, CT, USA; Yale University School of Medicine, Department of Neuroscience, New Haven, CT, USA
| | - Michal Assaf
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA; Yale University, School of Medicine, Department of Psychiatry, New Haven, CT, USA
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Walsh MJM, Baxter LC, Smith CJ, Braden BB. Age Group Differences in Executive Network Functional Connectivity and Relationships with Social Behavior in Men with Autism Spectrum Disorder. RESEARCH IN AUTISM SPECTRUM DISORDERS 2019; 63:63-77. [PMID: 32405319 PMCID: PMC7220036 DOI: 10.1016/j.rasd.2019.02.008] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
BACKGROUND Research suggests adults with autism spectrum disorder (ASD) may use executive functions to compensate for social difficulties. Given hallmark age-related declines in executive functioning and the executive brain network in normal aging, there is concern that older adults with ASD may experience further declines in social functioning as they age. In a male-only sample, we hypothesized: 1) older adults with ASD would demonstrate greater ASD-related social behavior than young adults with ASD, 2) adults with ASD would demonstrate a greater age group reduction in connectivity of the executive brain network than neurotypical (NT) adults, and 3) that behavioral and neural mechanisms of executive functioning would predict ASD-related social difficulties in adults with ASD. METHODS Participants were a cross-sectional sample of non-intellectually disabled young (ages 18-25) and middle-aged (ages 40-70) adult men with ASD and NT development (young adult ASD: n=24; middle-age ASD: n=25; young adult NT: n=15; middle-age NT: n=21). We assessed ASD-related social behavior via the self-report Social Responsiveness Scale-2 (SRS-2) Total Score, with exploratory analyses of the Social Cognition Subscale. We assessed neural executive function via connectivity of the resting-state executive network (EN) as measured by independent component analysis. Correlations were investigated between SRS-2 Total Scores (with exploratory analyses of the Social Cognition Subscale), EN functional connectivity of the dorsolateral prefrontal cortex (dlPFC), and a behavioral measure of executive function, Tower of London (ToL) Total Moves. RESULTS We did not confirm a significant age group difference for adults with ASD on the SRS-2 Total Score; however, exploratory analysis revealed middle-age men with ASD had higher scores on the SRS-2 Social Cognition Subscale than young adult men with ASD. Exacerbated age group reductions in EN functional connectivity were confirmed (left dlPFC) in men with ASD compared to NT, such that older adults with ASD demonstrated the greatest levels of hypoconnectivity. A significant correlation was confirmed between dlPFC connectivity and the SRS-2 Total Score in middle-age men with ASD, but not young adult men with ASD. Furthermore, exploratory analysis revealed a significant correlation with the SRS-2 Social Cognition Subscale for young and middle-aged ASD groups and ToL Total Moves. CONCLUSIONS Our findings suggest that ASD-related difficulties in social cognition and EN hypoconnectivity may get worse with age in men with ASD and is related to executive functioning. Further, exacerbated EN hypoconnectivity associated with older age in ASD may be a mechanism of increased ASD-related social cognition difficulties in older adults with ASD. Given the cross-sectional nature of this sample, longitudinal replication is needed.
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Affiliation(s)
- Melissa J. M. Walsh
- Department of Speech and Hearing Science, Arizona State University, 976 S Forest Mall, Tempe, AZ 85281
| | - Leslie C. Baxter
- Department of Neuroimaging Research, Barrow Neurological Institute, St. Joseph’s Hospital and Medical Center, 350 W Thomas Rd, Phoenix, AZ 85013
| | - Christopher J. Smith
- Southwest Autism Research & Resource Center, 2225 N 16th Street, Phoenix, AZ 85006
| | - B. Blair Braden
- Department of Speech and Hearing Science, Arizona State University, 976 S Forest Mall, Tempe, AZ 85281
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Mayer AR, Ling JM, Dodd AB, Shaff NA, Wertz CJ, Hanlon FM. A comparison of denoising pipelines in high temporal resolution task-based functional magnetic resonance imaging data. Hum Brain Mapp 2019; 40:3843-3859. [PMID: 31119818 DOI: 10.1002/hbm.24635] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2018] [Revised: 03/15/2019] [Accepted: 05/06/2019] [Indexed: 11/08/2022] Open
Abstract
It has been known for decades that head motion/other artifacts affect the blood oxygen level-dependent signal. Recent recommendations predominantly focus on denoising resting state data, which may not apply to task data due to the different statistical relationships that exist between signal and noise sources. Several blind-source denoising strategies (FIX and AROMA) and more standard motion parameter (MP) regression (0, 12, or 24 parameters) analyses were therefore compared across four sets of event-related functional magnetic resonance imaging (erfMRI) and block-design (bdfMRI) datasets collected with multiband 32- (repetition time [TR] = 460 ms) or older 12-channel (TR = 2,000 ms) head coils. The amount of motion varied across coil designs and task types. Quality control plots indicated small to moderate relationships between head motion estimates and percent signal change in both signal and noise regions. Blind-source denoising strategies eliminated signal as well as noise relative to MP24 regression; however, the undesired effects on signal depended both on algorithm (FIX > AROMA) and design (bdfMRI > erfMRI). Moreover, in contrast to previous results, there were minimal differences between MP12/24 and MP0 pipelines in both erfMRI and bdfMRI designs. MP12/24 pipelines were detrimental for a task with both longer block length (30 ± 5 s) and higher correlations between head MPs and design matrix. In summary, current results suggest that there does not appear to be a single denoising approach that is appropriate for all fMRI designs. However, even nonaggressive blind-source denoising approaches appear to remove signal as well as noise from task-related data at individual subject and group levels.
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Affiliation(s)
- Andrew R Mayer
- The Mind Research Network/Lovelace Biomedical and Environmental Research Institute, Albuquerque, New Mexico.,Departments of Neurology and Psychiatry, University of New Mexico School of Medicine, Albuquerque, New Mexico.,Department of Psychology, University of New Mexico, Albuquerque, New Mexico
| | - Josef M Ling
- The Mind Research Network/Lovelace Biomedical and Environmental Research Institute, Albuquerque, New Mexico
| | - Andrew B Dodd
- The Mind Research Network/Lovelace Biomedical and Environmental Research Institute, Albuquerque, New Mexico
| | - Nicholas A Shaff
- The Mind Research Network/Lovelace Biomedical and Environmental Research Institute, Albuquerque, New Mexico
| | - Christopher J Wertz
- The Mind Research Network/Lovelace Biomedical and Environmental Research Institute, Albuquerque, New Mexico
| | - Faith M Hanlon
- The Mind Research Network/Lovelace Biomedical and Environmental Research Institute, Albuquerque, New Mexico
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