Exploring structure and function of sensory cortex with 7 T MRI

Schluppeck, Denis; S�nchez-Panchuelo, Rosa-Maria; Francis, Susan T.

Abstract

In this paper, we present an overview of 7 Tesla magnetic resonance imaging (MRI) studies of the detailed function and anatomy of sensory areas of the human brain. We discuss the motivation for the studies, with particular emphasis on increasing the spatial resolution of functional MRI (fMRI) using reduced field-of-view (FOV) data acquisitions. MRI at ultra-high-field (UHF) – defined here as 7 T and above – has several advantages over lower field strengths. The intrinsic signal-to-noise ratio (SNR) of images is higher at UHF, and coupled with the increased blood-oxygen-level-dependent (BOLD) signal change, this results in increased BOLD contrast-to-noise ratio (CNR), which can be exploited to improve spatial resolution or detect weaker signals. Additionally, the BOLD signal from the intra-vascular (IV) compartment is relatively diminished compared to lower field strengths. Together, these properties make 7 T functional MRI an attractive proposition for high spatial specificity measures. But with the advantages come some challenges. For example, increased vulnerability to susceptibility-induced geometric distortions and signal loss in EPI acquisitions tend to be much larger. Some of these technical issues can be addressed with currently available tools and will be discussed. We highlight the key methodological considerations for high resolution functional and structural imaging at 7 T. We then present recent data using the high spatial resolution available at UHF in studies of the visual and somatosensory cortex to highlight promising developments in this area.

Citation

Schluppeck, D., Sánchez-Panchuelo, R.-M., & Francis, S. T. (2018). Exploring structure and function of sensory cortex with 7 T MRI. NeuroImage, 164, https://doi.org/10.1016/j.neuroimage.2017.01.081

• Journal Article Type: Article
• Acceptance Date: Jan 31, 2017
• Online Publication Date: Feb 2, 2017
• Publication Date: Jan 1, 2018
• Deposit Date: Feb 6, 2017
• Publicly Available Date: Feb 6, 2017
• Journal: NeuroImage
• Print ISSN: 1053-8119
• Electronic ISSN: 1095-9572
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 164
• DOI: https://doi.org/10.1016/j.neuroimage.2017.01.081
• Public URL: https://nottingham-repository.worktribe.com/output/902294
• Publisher URL: http://www.sciencedirect.com/science/article/pii/S1053811917301039
• Contract Date: Feb 6, 2017