integrated fmri preprocessing framework using extended kalman filter for estimation of slice-wise motion

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ID: 199936
2018
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Abstract
Functional MRI acquisition is sensitive to subjects' motion that cannot be fully constrained. Therefore, signal corrections have to be applied a posteriori in order to mitigate the complex interactions between changing tissue localization and magnetic fields, gradients and readouts. To circumvent current preprocessing strategies limitations, we developed an integrated method that correct motion and spatial low-frequency intensity fluctuations at the level of each slice in order to better fit the acquisition processes. The registration of single or multiple simultaneously acquired slices is achieved online by an Iterated Extended Kalman Filter, favoring the robust estimation of continuous motion, while an intensity bias field is non-parametrically fitted. The proposed extraction of gray-matter BOLD activity from the acquisition space to an anatomical group template space, taking into account distortions, better preserves fine-scale patterns of activity. Importantly, the proposed unified framework generalizes to high-resolution multi-slice techniques. When tested on simulated and real data the latter shows a reduction of motion explained variance and signal variability when compared to the conventional preprocessing approach. These improvements provide more stable patterns of activity, facilitating investigation of cerebral information representation in healthy and/or clinical populations where motion is known to impact fine-scale data.
Reference Key
pinsard2018frontiersintegrated Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Basile Pinsard;Basile Pinsard;Basile Pinsard;Arnaud Boutin;Arnaud Boutin;Julien Doyon;Julien Doyon;Habib Benali;Habib Benali;Habib Benali
Journal Journal of enzyme inhibition and medicinal chemistry
Year 2018
DOI
10.3389/fnins.2018.00268
URL
http://journal.frontiersin.org/article/10.3389/fnins.2018.00268/full
Keywords
fmri denoising neuropsychiatry biological psychiatry

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