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Decoding the direction of imagined visual motion using 7 T ultra-high field fMRI

Authors :
Martin A. Frost
Jan Zimmermann
Thomas C. Emmerling
Bettina Sorger
Rainer Goebel
Cognitive Neuroscience
RS: FPN CN 1
Netherlands Institute for Neuroscience (NIN)
Source :
Neuroimage, Neuroimage, 125, 61-73. Elsevier Science, NeuroImage, 125, 61-73. Academic Press
Publication Year :
2016
Publisher :
Academic Press, 2016.

Abstract

There is a long-standing debate about the neurocognitive implementation of mental imagery. One form of mental imagery is the imagery of visual motion, which is of interest due to its naturalistic and dynamic character. However, so far only the mere occurrence rather than the specific content of motion imagery was shown to be detectable. In the current study, the application of multi-voxel pattern analysis to high-resolution functional data of 12 subjects acquired with ultra-high field 7 T functional magnetic resonance imaging allowed us to show that imagery of visual motion can indeed activate the earliest levels of the visual hierarchy, but the extent thereof varies highly between subjects. Our approach enabled classification not only of complex imagery, but also of its actual contents, in that the direction of imagined motion out of four options was successfully identified in two thirds of the subjects and with accuracies of up to 91.3% in individual subjects. A searchlight analysis confirmed the local origin of decodable information in striate and extra-striate cortex. These high-accuracy findings not only shed new light on a central question in vision science on the constituents of mental imagery, but also show for the first time that the specific sub-categorical content of visual motion imagery is reliably decodable from brain imaging data on a single-subject level.<br />Highlights • Four different directions of visual motion can be decoded during imagery at 7 T. • We found very high classification accuracies in single subjects. • High variability between activation patterns and accuracies of different subjects

Details

Language :
English
ISSN :
10959572 and 10538119
Volume :
125
Database :
OpenAIRE
Journal :
Neuroimage
Accession number :
edsair.doi.dedup.....656d670fbf9a2a8c222a6b6994420bfd