Modeling Adaptation Effects in fMRI Analysis
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Golland_Modeling adaptation.pdf
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Author(s)
Ou, Wanmei
Raij, Tommi
Lin, Fa-Hsuan
Golland, Polina
Hamalainen, Matti S.
Date Issued
2009
Journal
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009
Publisher
Springer-Verlag Berlin Heidelberg
Citation
Ou, Wanmei, Tommi Raij, Fa-Hsuan Lin, Polina Golland, and Matti Hamalainen. “Modeling Adaptation Effects in fMRI Analysis.” in Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009, (Lecture Notes in Computer Science; Volume 5761) (2009): 1009–1017.
Version
Author's final manuscript
Abstract
The standard general linear model (GLM) for rapid event-related fMRI design protocols typically ignores reduction in hemodynamic responses in successive stimuli in a train due to incomplete recovery from the preceding stimuli. To capture this adaptation effect, we incorporate a region-specific adaptation model into GLM. The model quantifies the rate of adaptation across brain regions, which is of interest in neuroscience. Empirical evaluation of the proposed model demonstrates its potential to improve detection sensitivity. In the fMRI experiments using visual and auditory stimuli, we observed that the adaptation effect is significantly stronger in the visual area than in the auditory area, suggesting that we must account for this effect to avoid bias in fMRI detection.
Description
available in PMC 2013 June 30
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1007/978-3-642-04268-3_124
