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Peter van Gelderen

Researcher at National Institutes of Health

Publications -  116
Citations -  12706

Peter van Gelderen is an academic researcher from National Institutes of Health. The author has contributed to research in topics: Magnetic resonance imaging & Functional magnetic resonance imaging. The author has an hindex of 57, co-authored 111 publications receiving 11782 citations.

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Magnetodendrimers allow endosomal magnetic labeling and in vivo tracking of stem cells

TL;DR: It is shown here that NSC-derived (and LacZ-transfected), magnetically labeled oligodendroglial progenitors can be readily detected in vivo at least as long as six weeks after transplantation, with an excellent correlation between the obtained MR contrast and staining for β-galactosidase expression.
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High-field MRI of brain cortical substructure based on signal phase

TL;DR: In MRI of the human brain, large improvements in contrast to noise in high-resolution images are possible by exploiting the MRI signal phase at high magnetic field strength, an almost 10-fold improvement over conventional MRI techniques that do not use image phase.
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Functional Properties of Brain Areas Associated With Motor Execution and Imagery

TL;DR: Functional MRI is used to compare the functional neuroanatomy of motor execution and imagery using a task that objectively assesses imagery performance, including the effects of imagery performance and stimulus-dependency on brain activity.
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Low frequency BOLD fluctuations during resting wakefulness and light sleep: a simultaneous EEG-fMRI study.

TL;DR: The results suggest that activity in areas such as the default‐mode network and primary sensory cortex, as measured from BOLD fMRI fluctuations, does not require a level of consciousness typical of wakefulness.
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Low Frequency Fluctuations in the Cardiac Rate as a Source of Variance in the Resting-State fMRI BOLD Signal

TL;DR: Time-sh shifted cardiac rate timecourses were included as regressors in addition to established physiological regressors to suggest that including such time-shifted cardiac rate regressors will be beneficial for explaining physiological noise variance and will improve the statistical power in future task-based and resting-state fMRI studies.