Optimal repetition time reduction for single subject event‐related functional magnetic resonance imaging
Purpose Short TRs are increasingly used for fMRI as fast sequences such as simultaneous multislice excitation become available. These have been associated with apparent sensitivity improvements, although greater temporal autocorrelation at shorter TRs can inflate sensitivity measurements leading to...
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Published in | Magnetic resonance in medicine Vol. 81; no. 3; pp. 1890 - 1897 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
United States
Wiley Subscription Services, Inc
01.03.2019
John Wiley and Sons Inc |
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Abstract | Purpose
Short TRs are increasingly used for fMRI as fast sequences such as simultaneous multislice excitation become available. These have been associated with apparent sensitivity improvements, although greater temporal autocorrelation at shorter TRs can inflate sensitivity measurements leading to uncertainty regarding the optimal approach.
Methods
In volunteers (n = 10), the optimal TR was assessed at the single subject level for event‐related designs (visual stimulation) with 4 frequencies of presentation at 4 TR values (412‐2550 ms). T‐values in the visual cortex localized in each individual were obtained and receiver operating characteristics (ROC) analysis was performed by counting voxels within and outside expected task active regions at different thresholds. This analysis was repeated using 4 different autoregressive (AR) models; SPM AR(1) and SPM AR(fast) which globally estimate autocorrelation, and fMRIstat AR(1) and AR(5) that use a local estimate.
Results
The use of modest multiband factors of 2 or 3 with a reduction in TR to 1000 ± 200 ms had greater sensitivity and specificity as shown by higher T‐values in visual cortex and ROC analysis. At these TRs, the ROC analysis demonstrated that a local AR model fit improved performance while high order AR models were unnecessary.
Conclusions
Modest TR reductions (to 1000 ± 200 ms) optimally improved event‐related fMRI performance independent of design frequency. Autoregressive models with a local as opposed to global fit performed better, while low order autoregressive models were sufficient at the optimal TR. |
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AbstractList | PurposeShort TRs are increasingly used for fMRI as fast sequences such as simultaneous multislice excitation become available. These have been associated with apparent sensitivity improvements, although greater temporal autocorrelation at shorter TRs can inflate sensitivity measurements leading to uncertainty regarding the optimal approach.MethodsIn volunteers (n = 10), the optimal TR was assessed at the single subject level for event‐related designs (visual stimulation) with 4 frequencies of presentation at 4 TR values (412‐2550 ms). T‐values in the visual cortex localized in each individual were obtained and receiver operating characteristics (ROC) analysis was performed by counting voxels within and outside expected task active regions at different thresholds. This analysis was repeated using 4 different autoregressive (AR) models; SPM AR(1) and SPM AR(fast) which globally estimate autocorrelation, and fMRIstat AR(1) and AR(5) that use a local estimate.ResultsThe use of modest multiband factors of 2 or 3 with a reduction in TR to 1000 ± 200 ms had greater sensitivity and specificity as shown by higher T‐values in visual cortex and ROC analysis. At these TRs, the ROC analysis demonstrated that a local AR model fit improved performance while high order AR models were unnecessary.ConclusionsModest TR reductions (to 1000 ± 200 ms) optimally improved event‐related fMRI performance independent of design frequency. Autoregressive models with a local as opposed to global fit performed better, while low order autoregressive models were sufficient at the optimal TR. Short TRs are increasingly used for fMRI as fast sequences such as simultaneous multislice excitation become available. These have been associated with apparent sensitivity improvements, although greater temporal autocorrelation at shorter TRs can inflate sensitivity measurements leading to uncertainty regarding the optimal approach. In volunteers (n = 10), the optimal TR was assessed at the single subject level for event-related designs (visual stimulation) with 4 frequencies of presentation at 4 TR values (412-2550 ms). T-values in the visual cortex localized in each individual were obtained and receiver operating characteristics (ROC) analysis was performed by counting voxels within and outside expected task active regions at different thresholds. This analysis was repeated using 4 different autoregressive (AR) models; SPM AR(1) and SPM AR(fast) which globally estimate autocorrelation, and fMRIstat AR(1) and AR(5) that use a local estimate. The use of modest multiband factors of 2 or 3 with a reduction in TR to 1000 ± 200 ms had greater sensitivity and specificity as shown by higher T-values in visual cortex and ROC analysis. At these TRs, the ROC analysis demonstrated that a local AR model fit improved performance while high order AR models were unnecessary. Modest TR reductions (to 1000 ± 200 ms) optimally improved event-related fMRI performance independent of design frequency. Autoregressive models with a local as opposed to global fit performed better, while low order autoregressive models were sufficient at the optimal TR. Short TRs are increasingly used for fMRI as fast sequences such as simultaneous multislice excitation become available. These have been associated with apparent sensitivity improvements, although greater temporal autocorrelation at shorter TRs can inflate sensitivity measurements leading to uncertainty regarding the optimal approach.PURPOSEShort TRs are increasingly used for fMRI as fast sequences such as simultaneous multislice excitation become available. These have been associated with apparent sensitivity improvements, although greater temporal autocorrelation at shorter TRs can inflate sensitivity measurements leading to uncertainty regarding the optimal approach.In volunteers (n = 10), the optimal TR was assessed at the single subject level for event-related designs (visual stimulation) with 4 frequencies of presentation at 4 TR values (412-2550 ms). T-values in the visual cortex localized in each individual were obtained and receiver operating characteristics (ROC) analysis was performed by counting voxels within and outside expected task active regions at different thresholds. This analysis was repeated using 4 different autoregressive (AR) models; SPM AR(1) and SPM AR(fast) which globally estimate autocorrelation, and fMRIstat AR(1) and AR(5) that use a local estimate.METHODSIn volunteers (n = 10), the optimal TR was assessed at the single subject level for event-related designs (visual stimulation) with 4 frequencies of presentation at 4 TR values (412-2550 ms). T-values in the visual cortex localized in each individual were obtained and receiver operating characteristics (ROC) analysis was performed by counting voxels within and outside expected task active regions at different thresholds. This analysis was repeated using 4 different autoregressive (AR) models; SPM AR(1) and SPM AR(fast) which globally estimate autocorrelation, and fMRIstat AR(1) and AR(5) that use a local estimate.The use of modest multiband factors of 2 or 3 with a reduction in TR to 1000 ± 200 ms had greater sensitivity and specificity as shown by higher T-values in visual cortex and ROC analysis. At these TRs, the ROC analysis demonstrated that a local AR model fit improved performance while high order AR models were unnecessary.RESULTSThe use of modest multiband factors of 2 or 3 with a reduction in TR to 1000 ± 200 ms had greater sensitivity and specificity as shown by higher T-values in visual cortex and ROC analysis. At these TRs, the ROC analysis demonstrated that a local AR model fit improved performance while high order AR models were unnecessary.Modest TR reductions (to 1000 ± 200 ms) optimally improved event-related fMRI performance independent of design frequency. Autoregressive models with a local as opposed to global fit performed better, while low order autoregressive models were sufficient at the optimal TR.CONCLUSIONSModest TR reductions (to 1000 ± 200 ms) optimally improved event-related fMRI performance independent of design frequency. Autoregressive models with a local as opposed to global fit performed better, while low order autoregressive models were sufficient at the optimal TR. Purpose Short TRs are increasingly used for fMRI as fast sequences such as simultaneous multislice excitation become available. These have been associated with apparent sensitivity improvements, although greater temporal autocorrelation at shorter TRs can inflate sensitivity measurements leading to uncertainty regarding the optimal approach. Methods In volunteers (n = 10), the optimal TR was assessed at the single subject level for event‐related designs (visual stimulation) with 4 frequencies of presentation at 4 TR values (412‐2550 ms). T‐values in the visual cortex localized in each individual were obtained and receiver operating characteristics (ROC) analysis was performed by counting voxels within and outside expected task active regions at different thresholds. This analysis was repeated using 4 different autoregressive (AR) models; SPM AR(1) and SPM AR(fast) which globally estimate autocorrelation, and fMRIstat AR(1) and AR(5) that use a local estimate. Results The use of modest multiband factors of 2 or 3 with a reduction in TR to 1000 ± 200 ms had greater sensitivity and specificity as shown by higher T‐values in visual cortex and ROC analysis. At these TRs, the ROC analysis demonstrated that a local AR model fit improved performance while high order AR models were unnecessary. Conclusions Modest TR reductions (to 1000 ± 200 ms) optimally improved event‐related fMRI performance independent of design frequency. Autoregressive models with a local as opposed to global fit performed better, while low order autoregressive models were sufficient at the optimal TR. |
Author | Carmichael, David W McDowell, Amy R. |
AuthorAffiliation | 1 UCL GOS Institute of Child Health London UK 2 EPSCRC / Wellcome Centre for Medical Engineering Kings College London UK |
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BackLink | https://www.ncbi.nlm.nih.gov/pubmed/30230635$$D View this record in MEDLINE/PubMed |
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CitedBy_id | crossref_primary_10_1016_j_neuroimage_2019_02_008 crossref_primary_10_1016_j_bspc_2020_102099 crossref_primary_10_1016_j_neuroimage_2019_116223 crossref_primary_10_1080_0954898X_2023_2215860 crossref_primary_10_1002_hbm_25698 crossref_primary_10_1002_jnr_25121 crossref_primary_10_1038_s41598_024_51694_4 crossref_primary_10_1155_2021_9965756 crossref_primary_10_52294_001c_91292 crossref_primary_10_1002_jmri_28836 crossref_primary_10_1016_j_pneurobio_2021_102171 crossref_primary_10_3389_fneur_2021_645974 |
Cites_doi | 10.1006/nimg.2001.1044 10.1006/nimg.2001.0933 10.1371/journal.pone.0015710 10.1006/nimg.2002.1091 10.1016/j.neuroimage.2015.08.056 10.1016/j.neuroimage.2012.06.033 10.1371/journal.pone.0149048 10.1002/1522-2586(200102)13:2<313::AID-JMRI1045>3.0.CO;2-W 10.1002/ana.25003 10.1002/mrm.26073 10.1002/mrm.23097 10.1002/(SICI)1522-2586(199904)9:4<531::AID-JMRI4>3.0.CO;2-L |
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Copyright | 2018 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine 2018 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. 2019 International Society for Magnetic Resonance in Medicine |
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Keywords | event related fMRI multiband EEG-fMRI autoregressive model simultaneous multislice |
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Notes | Funding information by EPSRC grant EP/M001393/1. David Carmichael was supported by the Wellcome/EPSRC Centre for Medical Engineering [WT 203148/Z/16/Z]. We thank Dr. Sahib from Tübingen University for his fMRISTAT script. The University of Minnesota and E. Yacoub provided the SMS EPI sequence used in this study. This research was supported by the NIHR Great Ormond Street Hospital Biomedical Research Centre. The views expressed are those of the authors and not necessarily reflect those of the NHS, the NIHR, or the Department of Health. ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
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References | 2016; 76 2016; 124 2002; 16 2006 2002; 15 2017; 82 2001; 13 2010; 5 2012; 67 2012; 63 2016; 11 1999; 9 e_1_2_5_14_1 e_1_2_5_9_1 e_1_2_5_8_1 e_1_2_5_11_1 e_1_2_5_7_1 e_1_2_5_10_1 e_1_2_5_6_1 e_1_2_5_13_1 e_1_2_5_5_1 e_1_2_5_12_1 e_1_2_5_4_1 e_1_2_5_3_1 e_1_2_5_2_1 |
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Short TRs are increasingly used for fMRI as fast sequences such as simultaneous multislice excitation become available. These have been associated with... Short TRs are increasingly used for fMRI as fast sequences such as simultaneous multislice excitation become available. These have been associated with... PurposeShort TRs are increasingly used for fMRI as fast sequences such as simultaneous multislice excitation become available. These have been associated with... |
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SubjectTerms | Adult Algorithms Autocorrelation autoregressive model Autoregressive models Autoregressive processes Brain Mapping - methods Data processing EEG‐fMRI event related Female fMRI Functional magnetic resonance imaging Healthy Volunteers Humans Image Processing, Computer-Assisted - methods Magnetic resonance imaging Magnetic Resonance Imaging - methods Male Middle Aged multiband Neuroimaging Notes—Imaging Methodology Optimization Photic Stimulation Reduction Regression Analysis ROC Curve Sensitivity simultaneous multislice Temporal lobe Time Factors Visual cortex Visual Cortex - diagnostic imaging Visual Cortex - physiology Visual stimuli Young Adult |
Title | Optimal repetition time reduction for single subject event‐related functional magnetic resonance imaging |
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