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Neuroscientific applications of high-field MRI in humans

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Turner,  Robert
Department Neurophysics, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Citation

Turner, R. (2012). Neuroscientific applications of high-field MRI in humans. In J. Hennig (Ed.), High-field MR imaging (pp. 137-149). Berlin: Springer. doi:10.1007/174_2010_103.


Cite as: https://hdl.handle.net/21.11116/0000-0003-42A8-5
Abstract
The chief advantages of using high-field MRI for neuroscientific research are the improvements in spatial resolution and contrast that become available. Neuroscientists are interested in the spatial organisation of brain grey matter, in cortex and deep brain structures, and in the connectivity of white matter neuronal fibres. At lower field, it is very hard to distinguish cortical areas purely by their anatomical differences, or to discriminate subcomponents of basal ganglia and thalamus. This has led to a widely accepted method of functional image analysis involving warping of individual brains to a standardised template, together with significant image smoothing, which eliminates the possibility of detailed MRI-based mapping of human brain, and severely handicaps the exploration of individual differences and monitoring of brain changes over time. Even at a field of 3 T, the spatial resolution of MR tractography is limited to about 1.5 mm isotropic, hindering discrimination of crossing fibres. However, at fields of 7 T and above, the available high isotropic resolution of 0.4 mm and the varying myelin content of grey matter allow several cortical areas to be quite easily distinguished, and the varying iron content of deeper brain structures reveals their internal features. Higher spatial isotropic resolution in tractography can also be achieved, of 1 mm or better. Because blood oxygenation-dependent contrast (BOLD) also improves at high field, functional maps with submillimetre resolution can be acquired, showing columnar structures such as ocular dominance and orientation columns. These results will enable a much more precise correlation of brain functions with the neural tissue that supports them, and is likely to bring about major conceptual changes in systems neuroscience, especially in analysis methodology.