Content area

Abstract

Human MRI scanners at ultra-high magnetic field strengths of 7 T and higher are increasingly available to the neuroscience community. A key advantage brought by ultra-high field MRI is the possibility to increase the spatial resolution at which data is acquired, with little reduction in image quality. This opens a new set of opportunities for neuroscience, allowing investigators to map the human cortex at an unprecedented level of detail. In this review, we present recent work that capitalizes on the increased signal-to-noise ratio available at ultra-high field and discuss the theoretical advances with a focus on sensory and motor systems neuroscience. Further, we review research performed at sub-millimeter spatial resolution and discuss the limits and the potential of ultra-high field imaging for structural and functional imaging in human cortex. The increased spatial resolution achievable at ultra-high field has the potential to unveil the fundamental computations performed within a given cortical area, ultimately allowing the visualization of the mesoscopic organization of human cortex at the functional and structural level.

Details

Title
Ultra-high field MRI: Advancing systems neuroscience towards mesoscopic human brain function
Author
Dumoulin, Serge O 1 ; Fracasso, Alessio 2 ; Wietske van der Zwaag 3 ; Jeroen CW Siero 4 ; Petridou, Natalia 5 

 Spinoza Centre for Neuroimaging, Amsterdam, Netherlands; Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, Netherlands 
 Spinoza Centre for Neuroimaging, Amsterdam, Netherlands; Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, Netherlands; Radiology, University Medical Centre Utrecht, Utrecht, Netherlands 
 Spinoza Centre for Neuroimaging, Amsterdam, Netherlands 
 Spinoza Centre for Neuroimaging, Amsterdam, Netherlands; Radiology, University Medical Centre Utrecht, Utrecht, Netherlands 
 Radiology, University Medical Centre Utrecht, Utrecht, Netherlands 
Pages
345-357
Publication year
2018
Publication date
Mar 2018
Publisher
Elsevier Limited
ISSN
10538119
e-ISSN
10959572
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2017203788
Copyright
Copyright Elsevier Limited Mar 2018