A new concept of a unified parameter management, experiment control, and data analysis in fMRI: Application to real-time fMRI at 3T and 7T

Hollmann, Maurice; Mönch, Tobias; Mulla-Osman, Samir; Tempelmann, Claus; Stadler, Jörg; Bernarding, Johannes

doi:10.1016/j.jneumeth.2008.08.013

Cited by 19 publications

(17 citation statements)

References 19 publications

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“…An eight-element phased array coil (Siemens Medical Systems, Erlangen, Germany) was used for imaging. The vendor's EPI BOLD sequence and the corresponding reconstruction programs were modified to export each volume dataset immediately after acquisition and internal motion correction in real time to the host computer of the MRI scanner (Posse et al, 1999;Weiskopf et al, 2004Weiskopf et al, , 2007Hollmann et al, 2008). This software function performs the image export to any accessible computer in the local area network.…”

Section: Experimental Infrastructurementioning

confidence: 99%

Building virtual reality fMRI paradigms: A framework for presenting immersive virtual environments

Mueller

Lührs

Baecke

et al. 2012

Journal of Neuroscience Methods

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Section: Experimental Infrastructurementioning

confidence: 99%

Building virtual reality fMRI paradigms: A framework for presenting immersive virtual environments

Mueller

Lührs

Baecke

et al. 2012

Journal of Neuroscience Methods

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“…We implemented a real-time fMRI-classification experiment based on the experimental description language EDL (Hollmann et al, 2008). Data acquisition was performed with the same parameters as in the offline experiment except for shorter TRs.…”

Section: Methodsmentioning

confidence: 99%

“…Data acquisition was performed with the same parameters as in the offline experiment except for shorter TRs. The MR scanners' EPI scanning protocol was modified to immediately export the acquired and motion corrected volumes (Hollmann et al, 2008). On the classification host, transformation matrices for spatial normalization were calculated from the first acquired EPI-volume and applied to all subsequently acquired volumes.…”

Section: Methodsmentioning

confidence: 99%

Online tracking of the contents of conscious perception using real-time fMRI

et al. 2014

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Perception is an active process that interprets and structures the stimulus input based on assumptions about its possible causes. We use real-time functional magnetic resonance imaging (rtfMRI) to investigate a particularly powerful demonstration of dynamic object integration in which the same physical stimulus intermittently elicits categorically different conscious object percepts. In this study, we simulated an outline object that is moving behind a narrow slit. With such displays, the physically identical stimulus can elicit categorically different percepts that either correspond closely to the physical stimulus (vertically moving line segments) or represent a hypothesis about the underlying cause of the physical stimulus (a horizontally moving object that is partly occluded). In the latter case, the brain must construct an object from the input sequence. Combining rtfMRI with machine learning techniques we show that it is possible to determine online the momentary state of a subject's conscious percept from time resolved BOLD-activity. In addition, we found that feedback about the currently decoded percept increased the decoding rates compared to prior fMRI recordings of the same stimulus without feedback presentation. The analysis of the trained classifier revealed a brain network that discriminates contents of conscious perception with antagonistic interactions between early sensory areas that represent physical stimulus properties and higher-tier brain areas. During integrated object percepts, brain activity decreases in early sensory areas and increases in higher-tier areas. We conclude that it is possible to use BOLD responses to reliably track the contents of conscious visual perception with a relatively high temporal resolution. We suggest that our approach can also be used to investigate the neural basis of auditory object formation and discuss the results in the context of predictive coding theory.

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“…Magnetfeldst ä rken von 3 -4 Tesla scheinen zurzeit der bestm ö gliche Kompromiss zwischen der Verbesserung der Signalst ä rke und der Vermeidung von Messartefakten zu sein [4,5] . Allerdings hat Ultra-Hoch-Feld fMRT ( ≥ 7 T) ü ber die letzten Jahre starke Fortschritte gemacht und k ö nnte somit Grundlage f ü r die n ä chste Generation von Echtzeit-fMRT werden [6] . Auch bez ü glich der Messparameter , wie zum Beispiel der Bildaufl ö sung, gilt es, einen Kompromiss zwischen einer m ö glichst schnellen Bildakquisition, einer m ö glichst hohen Bildaufl ö sung und der Vermeidung von dadurch auftretenden Bildverzerrungen zu fi nden [7] .…”

Section: Introductionunclassified