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  Effect of temporal resolution and serial autocorrelations in event-related functional MRI

Sahib, A., Mathiak, K., Erb, M., Elshahabi, K., Klamer, S., Scheffler, K., et al. (2016). Effect of temporal resolution and serial autocorrelations in event-related functional MRI. Magnetic Resonance in Medicine, 76(6), 1805-1813. doi:10.1002/mrm.26073.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0000-793B-7 Version Permalink: http://hdl.handle.net/21.11116/0000-0000-793C-6
Genre: Journal Article

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Sahib, AK, Author
Mathiak, K, Author
Erb, M1, 2, Author              
Elshahabi, K, Author
Klamer, S, Author
Scheffler, K1, 2, Author              
Focke, NK, Author
Ethofer, T, Author
Affiliations:
1Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
2Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497796              

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 Abstract: Purpose To assess the impact of colored noise on statistics in event-related functional MRI (fMRI) (visual stimulation using checkerboards) acquired by simultaneous multislice imaging enabling repetition times (TRs) between 2.64 to 0.26 s. Methods T-values within the visual cortex obtained with analysis tools that assume a first-order autoregressive plus white noise process (AR(1)+w) with a fixed AR coefficient versus higher-order AR models with spatially varying AR coefficients were compared. In addition, dependency of T-values on correction of physiological noise (respiration, heart rate) was evaluated. Results Optimal statistical power was obtained for a TR of 0.33 s, but T-values as obtained by AR(1)+w models were strongly dependent on the predefined AR coefficients in fMRI with short TRs which required higher-order AR models to achieve stable statistics. Direct estimation of AR coefficients revealed the highest values within the default mode network while physiological noise had little influence on statistics in cortical structures. Conclusion Colored noise in event-related fMRI obtained at short TRs originates mainly from neural sources and calls for more sophisticated correction of serial autocorrelations which cannot be achieved with standard methods relying on AR(1)+w models with globally fixed AR coefficients.

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 Dates: 2016-12
 Publication Status: Published in print
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 Identifiers: DOI: 10.1002/mrm.26073
BibTex Citekey: SahibMEEKSFE2016
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Title: Magnetic Resonance in Medicine
Source Genre: Journal
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Pages: - Volume / Issue: 76 (6) Sequence Number: - Start / End Page: 1805 - 1813 Identifier: -