Over the last 2 years, my laboratoary has been deeply involved in the development of new MRI techniques for the study of human brain anatomy and function. During 2001-2002, significant progress was made in the development of new techniques for multi-channel MRI, resulting in improved spatial and temporal resolution. In addition to the design of multi-channel MRI signal detectors, a receiver system was developed to allow signal reception simultaneously through 16 channels. This system is currently being tested for 3.0T magnets, and will also be adapted for the 7.0T system. Preliminary results with 4-channel signal detection show that sensitivity gains allow the detection of cortical layers in human V1. Multi-channel technology was combined with parallel imaging techniques to facilitate image acquisition. Novel parallel imaging strategies were designed and evaluated in BOLD fMRI studies, demonstrating the feasibility of improving temporal or spatial resolution, or alternatively reduce acoustic noise and hardware stress during the MRI acquisition process. A technique to measure perfusion and BOLD changes during brain activation was evaluated and used to perform high resolution somatotopy and retinotopy studies. These studies indicated that the ultimately achievable functional resolution in V1 and S1 is limited by vascular artifacts, suggesting that additional methodologies need to be developed to remove these artifacts. One possibility is that the attenuation of vessels at higher magnetic field (7.0T) will be adequate to accomplish this. A new method to investigate temporal aspects of brain activation was developed in collaboration with NHLBI. Non-linear system analysis was performed in the human visual system to investigate non-linear aspects of temporal summation. This required separation of neuronal and hemodynamic effects. We found that, despite the seconds-long temporal blurring of the fMRI contrast mechanism, temporal non-linearities on neuronal time-scales of 10's of millisecond could be detected and mapped.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Intramural Research (Z01)
Project #
1Z01NS002990-03
Application #
6659619
Study Section
(LFMI)
Project Start
Project End
Budget Start
Budget End
Support Year
3
Fiscal Year
2002
Total Cost
Indirect Cost
City
State
Country
United States
Zip Code
van Gelderen, Peter; Jiang, Xu; Duyn, Jeff H (2017) Rapid measurement of brain macromolecular proton fraction with transient saturation transfer MRI. Magn Reson Med 77:2174-2185
Duyn, Jeff (2011) Spontaneous fMRI activity during resting wakefulness and sleep. Prog Brain Res 193:295-305
Li, Tie-Qiang; Yao, Bing; van Gelderen, Peter et al. (2009) Characterization of T(2)* heterogeneity in human brain white matter. Magn Reson Med 62:1652-7
Bianciardi, Marta; Fukunaga, Masaki; van Gelderen, Peter et al. (2009) Sources of functional magnetic resonance imaging signal fluctuations in the human brain at rest: a 7 T study. Magn Reson Imaging 27:1019-29
Horovitz, Silvina G; Fukunaga, Masaki; de Zwart, Jacco A et al. (2008) Low frequency BOLD fluctuations during resting wakefulness and light sleep: a simultaneous EEG-fMRI study. Hum Brain Mapp 29:671-82
Duyn, Jeff H; van Gelderen, Peter; Li, Tie-Qiang et al. (2007) High-field MRI of brain cortical substructure based on signal phase. Proc Natl Acad Sci U S A 104:11796-801
Shmueli, Karin; van Gelderen, Peter; de Zwart, Jacco A et al. (2007) Low-frequency fluctuations in the cardiac rate as a source of variance in the resting-state fMRI BOLD signal. Neuroimage 38:306-20
van Gelderen, P; de Zwart, J A; Starewicz, P et al. (2007) Real-time shimming to compensate for respiration-induced B0 fluctuations. Magn Reson Med 57:362-8
Silva, Afonso C; Koretsky, Alan P; Duyn, Jeff H (2007) Functional MRI impulse response for BOLD and CBV contrast in rat somatosensory cortex. Magn Reson Med 57:1110-8
Deckers, Roel H R; van Gelderen, Peter; Ries, Mario et al. (2006) An adaptive filter for suppression of cardiac and respiratory noise in MRI time series data. Neuroimage 33:1072-81

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