Optimizing the detection of white matter fMRI using asymmetric spin echo spiral

Gawryluk, Jodie R.; Brewer, Kimberly; Beyea, Steven; D’Arcy, Ryan C.N.

doi:10.1016/j.neuroimage.2008.11.005

Cited by 49 publications

(73 citation statements)

References 29 publications

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“…The analysis of percent signal change in gray and white matter supports previous claims that white matter fMRI activation is weaker than that of gray matter ( [Gawryluk et al, 2009a], [Mazerolle et al, 2008], [Tettamanti et al, 2002] and [Yarkoni et al, 2009]). Sensitivity remains a major hurdle to potential applications of white matter fMRI.…”

Section: Discussionsupporting

confidence: 83%

“…The previous study employed a more typical T2 weighted fMRI acquisition and reported a considerably lower percentage of individuals with CC activation (21% versus the 80% reported here; Mazerolle et al, 2008). It is possible that the increased sensitivity provided by ASE spiral fMRI acquisition and increased T2 weighting ( and [Gawryluk et al, 2009a]) allowed detection of white matter activation not only in more subjects, but also across a larger region of the corpus callosum. Given what is known about inter-individual functional anatomy differences in gray matter (e.g., Brett, 2002), such variability in white matter fMRI activation is not surprising.…”

Section: Discussionmentioning

confidence: 49%

“…Sensitivity remains a major hurdle to potential applications of white matter fMRI. Previous work has demonstrated improved sensitivity to white matter fMRI activation through increased T2 weighting of fMRI pulse sequences (Gawryluk et al, 2009a). Ongoing work investigating the mechanisms of the effect of T2 weighting may provide additional insight that can be applied to further optimize sensitivity to white matter fMRI activation.…”

Section: Discussionmentioning

confidence: 96%

“…The co-localization of white matter fMRI activation with tracts connected to regions of gray matter fMRI activation provides strong evidence that the white matter fMRI activation is not only functionally significant (e.g., [Gawryluk et al, 2009a], [Mazerolle et al, 2008], [Tettamanti et al, 2002] and [Yarkoni et al, 2009]), but also structurally connected to the activated gray matter network. White matter accounts for 40-45% of brain parenchyma (e.g., Black, 2007) and it is known that connections play a critical role in brain function.…”

Section: Discussionmentioning

confidence: 96%

“…In order to increase the overall T2 weighting of the combined image, the three ASE images were combined using an inverted signal weighted averaging algorithm (Gawryluk et al, 2009a). Statistical analyses were performed using the general linear model with fMRI expert analysis tool (FEAT) version 5.3 in FMRIB Software Library (FSL) (Smith et al, 2004).…”

Section: Fmri Analysismentioning

confidence: 99%

See 4 more Smart Citations

Confirming white matter fMRI activation in the corpus callosum: Co-localization with DTI tractography

et al. 2010

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Section: Discussionsupporting

confidence: 83%

Section: Discussionmentioning

confidence: 49%

Section: Discussionmentioning

confidence: 96%

Section: Discussionmentioning

confidence: 96%

Section: Fmri Analysismentioning

confidence: 99%

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Confirming white matter fMRI activation in the corpus callosum: Co-localization with DTI tractography

et al. 2010

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Changes in white matter functional networks during wakefulness and sleep

Yang

Wang

Liu

et al. 2022

Human Brain Mapping

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Blood oxygenation level‐dependent (BOLD) signals in the white matter (WM) have been demonstrated to encode neural activities by showing structure‐specific temporal correlations during resting‐state and task‐specific imaging of fiber pathways with various degrees of correlations in strength and time delay. Previous neuroimaging studies have shown state‐dependent functional connectivity and regional amplitude of signal fluctuations in brain gray matter across wakefulness and nonrapid eye movement (NREM) sleep cycles. However, the functional characteristics of WM during sleep remain unknown. Using simultaneous electroencephalography and functional magnetic resonance imaging data during wakefulness and NREM sleep collected from 66 healthy participants, we constructed 10 stable WM functional networks using clustering analysis. Functional connectivity between these WM functional networks and regional amplitude of WM signal fluctuations across multiple low‐frequency bands were evaluated. In general, decreased WM functional connectivity between superficial and middle layer WM functional networks was observed from wakefulness to sleep. In addition, functional connectivity between the deep and cerebellar networks was higher during light sleep and lower during both wakefulness and deep sleep. The regional fluctuation amplitude was always higher during light sleep and lower during deep sleep. Importantly, slow‐wave activity during deep sleep negatively correlated with functional connectivity between WM functional networks but positively correlated with fluctuation strength in the WM. These observations provide direct physiological evidence that neural activities in the WM are modulated by the sleep–wake cycle. This study provided the initial mapping of functional changes in WM during sleep.

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Asymmetric spin‐echo (ASE) spiral improves BOLD fMRI in inhomogeneous regions

et al. 2009

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Functional MRI (fMRI) is of limited use in areas such as the orbitofrontal and inferior temporal lobes due to the presence of local susceptibility-induced field gradients (SFGs), which result in severe image artifacts. Several techniques have been developed to reduce these artifacts, the most common being the dual-echo spiral sequences (spiral-in/out and spiral-in/in). In this study, a new multiple spiral acquisition technique was developed, in which the later spiral acquisitions are acquired asymmetrically with the peak of a spin-echo causing increased R(2)-weighting but matched R(2)'-weighting. This sequence, called asymmetric spin-echo (ASE) spiral, has demonstrated significant improvements in minimizing the signal loss and increasing the image quality as well as optimal blood-oxygen-level-dependent (BOLD)-weighting. The ASE spiral is compared to conventional spiral-out using both signal-to-noise ratio (SNR) and whole brain fMRI activation volumes from a breath-hold task acquired at 4 Tesla. The ASE dual spiral has exhibited SNR increases of up to 300% in areas where strong SFGs are present. As a result, the ASE spiral is highly efficient for recovering lost activation in areas of SFGs, as demonstrated by a 16% increase in the total number of activated voxels over the whole brain. Post spin-echo ASE spiral images have decreasing SNR due to R(2) signal losses, however the increase in R(2)-weighting leads to a higher percentage of signal changes producing ASE spiral images with equivalent contrast-to-noise ratio (CNR) for each echo. The use of this sequence allows for recovery of BOLD activation in areas of SFG without sacrificing the CNR over the whole brain.

show abstract

Optimizing the detection of white matter fMRI using asymmetric spin echo spiral

Cited by 49 publications

References 29 publications

Confirming white matter fMRI activation in the corpus callosum: Co-localization with DTI tractography

Confirming white matter fMRI activation in the corpus callosum: Co-localization with DTI tractography

Changes in white matter functional networks during wakefulness and sleep

Asymmetric spin‐echo (ASE) spiral improves BOLD fMRI in inhomogeneous regions

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