Spin‐history artifact during functional MRI: Potential for adaptive correction

Yancey, Sadie; Rotenberg, David; Tam, Fred; Chiew, Mark; Ranieri, Shawn; Biswas, Labonny; Anderson, K.M.; Baker, Shawn; Wright, Graham A.; Graham, Simon J.

doi:10.1118/1.3583814

Cited by 48 publications

(50 citation statements)

References 37 publications

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“…Furthermore, many studies of white matter activation have mitigated the risk of motion-related activations by including the estimated motion parameters (output by the motion correction) as regressors of no interest in the analysis model (Mazerolle et al, 2008; Yarkoni et al, 2009; Gawryluk et al, 2011a,b). Even with this approach, it is possible that nonlinear spin history effects caused by motion are not corrected (Yancey et al, 2011). However, spin history effects are likely to be most severe near regions of large magnetic gradients (i.e., susceptibility induced field gradients near the sinuses) and would not be expected to result in white matter-specific effects.…”

Section: Understanding Why Reports Of White Matter Fmri Activation Armentioning

confidence: 99%

Does functional MRI detect activation in white matter? A review of emerging evidence, issues, and future directions

2014

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Functional magnetic resonance imaging (fMRI) is a non-invasive technique that allows for visualization of activated brain regions. Until recently, fMRI studies have focused on gray matter. There are two main reasons white matter fMRI remains controversial: (1) the blood oxygen level dependent (BOLD) fMRI signal depends on cerebral blood flow and volume, which are lower in white matter than gray matter and (2) fMRI signal has been associated with post-synaptic potentials (mainly localized in gray matter) as opposed to action potentials (the primary type of neural activity in white matter). Despite these observations, there is no direct evidence against measuring fMRI activation in white matter and reports of fMRI activation in white matter continue to increase. The questions underlying white matter fMRI activation are important. White matter fMRI activation has the potential to greatly expand the breadth of brain connectivity research, as well as improve the assessment and diagnosis of white matter and connectivity disorders. The current review provides an overview of the motivation to investigate white matter fMRI activation, as well as the published evidence of this phenomenon. We speculate on possible neurophysiologic bases of white matter fMRI signals, and discuss potential explanations for why reports of white matter fMRI activation are relatively scarce. We end with a discussion of future basic and clinical research directions in the study of white matter fMRI.

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Section: Understanding Why Reports Of White Matter Fmri Activation Armentioning

confidence: 99%

Does functional MRI detect activation in white matter? A review of emerging evidence, issues, and future directions

2014

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“…This allows for correction of both intra‐ and intervolume motion, while conventional RMC implementations only correct for intervolume motion. Second, accurate coupling of the acquisition box to the participant's head removes spin history effects and preserves edge voxels (Yancey et al, 2011). This allows for a higher confidence in voxel‐wise registration across volumes and ensures that the entire acquisition volume can be used for model fitting.…”

Section: Introductionmentioning

confidence: 99%

Prospective motion correction improves the sensitivity of fMRI pattern decoding

Huang

Carlin

Alink

et al. 2018

Human Brain Mapping

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We evaluated the effectiveness of prospective motion correction (PMC) on a simple visual task when no deliberate subject motion was present. The PMC system utilizes an in‐bore optical camera to track an external marker attached to the participant via a custom‐molded mouthpiece. The study was conducted at two resolutions (1.5 mm vs 3 mm) and under three conditions (PMC On and Mouthpiece On vs PMC Off and Mouthpiece On vs PMC Off and Mouthpiece Off). Multiple data analysis methods were conducted, including univariate and multivariate approaches, and we demonstrated that the benefit of PMC is most apparent for multi‐voxel pattern decoding at higher resolutions. Additional testing on two participants showed that our inexpensive, commercially available mouthpiece solution produced comparable results to a dentist‐molded mouthpiece. Our results showed that PMC is increasingly important at higher resolutions for analyses that require accurate voxel registration across time.

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“…These motion correction techniques assume that motion affects the entire volume in a similar fashion and attempt to address first-order motion effects; however, they do not address potential slice-to-slice out of plane motion effects or other second order motion effects. Such motion effects may arise from primarily spin history effects (out of plane motion (Friston et al, 1996; Muresan et al, 2005; Yancey et al, 2011), but also B1 inhomogeneity, and B0 inhomogeneity. Semi-prospective (e.g., SimPACE, (Beall and Lowe, 2014)) and retrospective (e.g., SLOMOCO, (Beall and Lowe, 2014) correction methods exist which attempt to address second order motion effects.…”

Section: Motion Correction During Data Processingmentioning

confidence: 99%

Minimizing noise in pediatric task-based functional MRI; Adolescents with developmental disabilities and typical development

2017

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Functional Magnetic Resonance Imaging (fMRI) represents a powerful tool with which to examine brain functioning and development in typically developing pediatric groups as well as children and adolescents with clinical disorders. However, fMRI data can be highly susceptible to misinterpretation due to the effects of excessive levels of noise, often related to head motion. Imaging children, especially with developmental disorders, requires extra considerations related to hyperactivity, anxiety and the ability to perform and maintain attention to the fMRI paradigm. We discuss a number of methods that can be employed to minimize noise, in particular movement-related noise. To this end we focus on strategies prior to, during and following the data acquisition phase employed primarily within our own laboratory. We discuss the impact of factors such as experimental design, screening of potential participants and pre-scan training on head motion in our adolescents with developmental disorders and typical development. We make some suggestions that may minimize noise during data acquisition itself and finally we briefly discuss some current processing techniques that may help to identify and remove noise in the data. Many advances have been made in the field of pediatric imaging, particularly with regard to research involving children with developmental disorders. Mindfulness of issues such as those discussed here will ensure continued progress and greater consistency across studies.

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Spin‐history artifact during functional MRI: Potential for adaptive correction

Abstract: Overall, this work suggests that adaptive correction, especially when implemented with minimal lag between motion measurement and scan plane update, may help to expand the populations for which fMRI can be performed robustly.

Cited by 48 publications

References 37 publications

Does functional MRI detect activation in white matter? A review of emerging evidence, issues, and future directions

Does functional MRI detect activation in white matter? A review of emerging evidence, issues, and future directions

Prospective motion correction improves the sensitivity of fMRI pattern decoding

Minimizing noise in pediatric task-based functional MRI; Adolescents with developmental disabilities and typical development

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