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Neuroimage. 2018 Mar;168:366-382. doi: 10.1016/j.neuroimage.2017.03.060. Epub 2017 Apr 8.

The impact of ultra-high field MRI on cognitive and computational neuroimaging.

Author information

1
Department of Cognitive Neurosciences, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 ER Maastricht, The Netherlands; Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, 2021 sixth street SE, 55455 Minneapolis, MN, USA. Electronic address: f.demartino@maastrichtuniversity.nl.
2
Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, 2021 sixth street SE, 55455 Minneapolis, MN, USA.
3
Department of Cognitive Neurosciences, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 ER Maastricht, The Netherlands.
4
Department of Cognitive Neurosciences, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 ER Maastricht, The Netherlands; Maastricht Center for System Biology, Maastricht University, Universiteitssingel 60, 6229 ER Maastricht, The Netherlands.

Abstract

The ability to measure functional brain responses non-invasively with ultra high field MRI (7 T and above) represents a unique opportunity in advancing our understanding of the human brain. Compared to lower fields (3 T and below), ultra high field MRI has an increased sensitivity, which can be used to acquire functional images with greater spatial resolution, and greater specificity of the blood oxygen level dependent (BOLD) signal to the underlying neuronal responses. Together, increased resolution and specificity enable investigating brain functions at a submillimeter scale, which so far could only be done with invasive techniques. At this mesoscopic spatial scale, perception, cognition and behavior can be probed at the level of fundamental units of neural computations, such as cortical columns, cortical layers, and subcortical nuclei. This represents a unique and distinctive advantage that differentiates ultra high from lower field imaging and that can foster a tighter link between fMRI and computational modeling of neural networks. So far, functional brain mapping at submillimeter scale has focused on the processing of sensory information and on well-known systems for which extensive information is available from invasive recordings in animals. It remains an open challenge to extend this methodology to uniquely human functions and, more generally, to systems for which animal models may be problematic. To succeed, the possibility to acquire high-resolution functional data with large spatial coverage, the availability of computational models of neural processing as well as accurate biophysical modeling of neurovascular coupling at mesoscopic scale all appear necessary.

KEYWORDS:

Computational models; Cortical columns; Cortical laminae; High spatial resolution; Subcortical; Ultra high magnetic fields

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