Physiological noise in human cerebellar fMRI

Zwaag, Wietske van der; Jorge, João; Butticaz, Denis; Gruetter, Rolf

doi:10.1007/s10334-015-0483-6

Cited by 19 publications

(13 citation statements)

References 38 publications

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“…In addition, the locations close to the lung may benefit from our approach, because such a location is more sensitive to respiratory-induced B 0 fluctuations. 22 Second, the qualitative and quantitative relationship between the state of respiration and the fluctuations of B 0 / B 1 1 field is unknown, because we monitored only the success of breath holding using the respiratory belt. Third, only the GRE sequence was examined for clinical images in this study.…”

Section: Discussionmentioning

confidence: 99%

“…[16][17][18][19][20][21] These B 0 fluctuations are mainly induced by susceptibility changes caused by lung and chest motion during breathing, as well as by other physiological noises, such as cardiac function, and blood and cerebrospinal fluid (CSF) pulsation. 22 B 0 mapping, which uses the difference between two phase images, is affected by the respiration-induced phase variations. 23 In addition, these B 0 changes have an impact on B 1 1 mapping of the BS method, because this technique uses the phase images with two different off-resonance pulses.…”

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confidence: 99%

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Improvement of the repeatability of parallel transmission at 7T using interleaved acquisition in the calibration scan

Kameda

Kudo

Matsuda

et al. 2017

Magnetic Resonance Imaging

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

Improvement of the repeatability of parallel transmission at 7T using interleaved acquisition in the calibration scan

Kameda

Kudo

Matsuda

et al. 2017

Magnetic Resonance Imaging

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“…Effects due to temporal autocorrelation of the acquired time series data, which can invalidate assumptions of normality, were minimised by prewhitening (Woolrich, Ripley, Brady, & Smith, 2001). It has been demonstrated that the cerebellum, like the brainstem, suffers from issues relating to increased physiological noise, for example, due to pulsatile flow of CSF through the fourth ventricle (Brooks et al, 2008;Brooks, Faull, Pattinson, & Jenkinson, 2013;van der Zwaag, Jorge, Butticaz, & Gruetter, 2015). Hence, a physiological noise model, which attempts to model signal fluctuation in the fMRI time series produced by cardiac and respiratory processes (Brooks et al, 2008) was incorporated into the GLM.…”

Section: Model Estimation Was Performed Using Feat (Fmrib's Expertmentioning

confidence: 99%

Sensorimotor, language, and working memory representation within the human cerebellum

Ashida

Cerminara

Edwards

et al. 2019

Human Brain Mapping

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The cerebellum is involved in a wide range of behaviours. A key organisational principle from animal studies is that somatotopically corresponding sensory input and motor output reside in the same cerebellar cortical areas. However, compelling evidence for a similar arrangement in humans and whether it extends to cognitive functions is lacking. To address this, we applied cerebellar optimised whole‐brain functional MRI in 20 healthy subjects. To assess spatial overlap within the sensorimotor and cognitive domains, we recorded activity to a sensory stimulus (vibrotactile) and a motor task; the Sternberg verbal working memory (VWM) task; and a verb generation paradigm. Consistent with animal data, sensory and motor activity overlapped with a somatotopic arrangement in ipsilateral areas of the anterior and posterior cerebellum. During the maintenance phase of the Sternberg task, a positive linear relationship between VWM load and activity was observed in right Lobule VI, extending into Crus I bilaterally. Articulatory movement gave rise to bilateral activity in medial Lobule VI. A conjunction of two independent language tasks localised activity during verb generation in right Lobule VI‐Crus I, which overlapped with activity during VWM. These results demonstrate spatial compartmentalisation of sensorimotor and cognitive function in the human cerebellum, with each area involved in more than one aspect of a given behaviour, consistent with an integrative function. Sensorimotor localisation was uniform across individuals, but the representation of cognitive tasks was more variable, highlighting the importance of individual scans for mapping higher order functions within the cerebellum.

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“…Multishot sequences are particularly prone to physiological noise, because different segments will be affected differently by respiration, cardiac rate, and more generally, motion. Physiological noise correction on 3D data led to small improvements in BOLD detection compared with standard 2D EPI for nonaccelerated 3D EPI at 7 T (19,29) and accelerated 3D EPI at 3T (20). Because segmented 3D EPI approaches are more susceptible to physiological fluctuations than 2D sequences, the advantage of using 3D accelerated sequences may not directly translate into a higher image SNR.…”

Section: Introductionmentioning

confidence: 99%

Influence of physiological noise on accelerated 2D and 3D resting state functional MRI data at 7 T

Reynaud

Jorge

Gruetter

et al. 2017

Magnetic Resonance in Med

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Purpose: Physiological noise often dominates the bloodoxygen level-dependent (BOLD) signal fluctuations in high-field functional MRI (fMRI) data. Therefore, to optimize fMRI protocols, it becomes crucial to investigate how physiological signal fluctuations impact various acquisition and reconstruction schemes at different acquisition speeds. In particular, further differences can arise between 2D and 3D fMRI acquisitions due to different encoding strategies, thereby impacting fMRI sensitivity in potentially significant ways. Methods: The amount of physiological noise to be removed from the BOLD fMRI signal acquired at 7 T was quantified for different sampling rates (repetition time from 3300 to 350 ms, acceleration 1 to 8) and techniques dedicated to fast fMRI (simultaneous multislice echo planar imaging [EPI] and 3D EPI). Resting state fMRI (rsfMRI) performances were evaluated using temporal signal-tonoise ratio (tSNR) and network characterization based on seed correlation and independent component analysis. Results: Overall, acceleration enhanced tSNR and rsfMRI metrics. 3D EPI benefited the most from physiological noise removal at long repetition times. Differences between 2D and 3D encoding strategies disappeared at high acceleration factors (6-to 8-fold). Conclusion: After physiological noise correction, 2D-and 3D-accelerated sequences provide similar performances at high fields, both in terms of tSNR and resting state network identification and characterization. Magn Reson Med 78:888-896,

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Physiological noise in human cerebellar fMRI

Abstract: likely to improve the temporal signal-to-noise ratio (SNR) for cerebellar fMRI at 7T, even at high spatial resolution.

Cited by 19 publications

References 38 publications

Improvement of the repeatability of parallel transmission at 7T using interleaved acquisition in the calibration scan

Improvement of the repeatability of parallel transmission at 7T using interleaved acquisition in the calibration scan

Sensorimotor, language, and working memory representation within the human cerebellum

Influence of physiological noise on accelerated 2D and 3D resting state functional MRI data at 7 T

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