Paper
6 March 2014 A stereoscopic system for viewing the temporal evolution of brain activity clusters in response to linguistic stimuli
Angus Forbes, Javier Villegas, Kyle R. Almryde, Elena Plante
Author Affiliations +
Proceedings Volume 9011, Stereoscopic Displays and Applications XXV; 90110I (2014) https://doi.org/10.1117/12.2042200
Event: IS&T/SPIE Electronic Imaging, 2014, San Francisco, California, United States
Abstract
In this paper, we present a novel application, 3D+Time Brain View, for the stereoscopic visualization of functional Magnetic Resonance Imaging (fMRI) data gathered from participants exposed to unfamiliar spoken languages. An analysis technique based on Independent Component Analysis (ICA) is used to identify statistically significant clusters of brain activity and their changes over time during different testing sessions. That is, our system illustrates the temporal evolution of participants' brain activity as they are introduced to a foreign language through displaying these clusters as they change over time. The raw fMRI data is presented as a stereoscopic pair in an immersive environment utilizing passive stereo rendering. The clusters are presented using a ray casting technique for volume rendering. Our system incorporates the temporal information and the results of the ICA into the stereoscopic 3D rendering, making it easier for domain experts to explore and analyze the data.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Angus Forbes, Javier Villegas, Kyle R. Almryde, and Elena Plante "A stereoscopic system for viewing the temporal evolution of brain activity clusters in response to linguistic stimuli", Proc. SPIE 9011, Stereoscopic Displays and Applications XXV, 90110I (6 March 2014); https://doi.org/10.1117/12.2042200
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CITATIONS
Cited by 8 scholarly publications.
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KEYWORDS
Brain

Visualization

Functional magnetic resonance imaging

Independent component analysis

Neuroimaging

Volume rendering

Statistical analysis

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