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Altered physiological brain variation in drug‐resistant epilepsy

Overview of attention for article published in Brain and Behavior, August 2018
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Title
Altered physiological brain variation in drug‐resistant epilepsy
Published in
Brain and Behavior, August 2018
DOI 10.1002/brb3.1090
Pubmed ID
Authors

Janne Kananen, Timo Tuovinen, Hanna Ansakorpi, Seppo Rytky, Heta Helakari, Niko Huotari, Lauri Raitamaa, Ville Raatikainen, Aleksi Rasila, Viola Borchardt, Vesa Korhonen, Pierre LeVan, Maiken Nedergaard, Vesa Kiviniemi

Abstract

Functional magnetic resonance imaging (fMRI) combined with simultaneous electroencephalography (EEG-fMRI) has become a major tool in mapping epilepsy sources. In the absence of detectable epileptiform activity, the resting state fMRI may still detect changes in the blood oxygen level-dependent signal, suggesting intrinsic alterations in the underlying brain physiology. In this study, we used coefficient of variation (CV) of critically sampled 10 Hz ultra-fast fMRI (magnetoencephalography, MREG) signal to compare physiological variance between healthy controls (n = 10) and patients (n = 10) with drug-resistant epilepsy (DRE). We showed highly significant voxel-level (p < 0.01, TFCE-corrected) increase in the physiological variance in DRE patients. At individual level, the elevations range over three standard deviations (σ) above the control mean (μ) CVMREG values solely in DRE patients, enabling patient-specific mapping of elevated physiological variance. The most apparent differences in group-level analysis are found on white matter, brainstem, and cerebellum. Respiratory (0.12-0.4 Hz) and very-low-frequency (VLF = 0.009-0.1 Hz) signal variances were most affected. The CVMREG increase was not explained by head motion or physiological cardiorespiratory activity, that is, it seems to be linked to intrinsic physiological pulsations. We suggest that intrinsic brain pulsations play a role in DRE and that critically sampled fMRI may provide a powerful tool for their identification.

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Mendeley readers

The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 64 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 9 14%
Student > Ph. D. Student 8 13%
Researcher 6 9%
Student > Bachelor 5 8%
Student > Doctoral Student 3 5%
Other 8 13%
Unknown 25 39%
Readers by discipline Count As %
Medicine and Dentistry 11 17%
Neuroscience 10 16%
Engineering 5 8%
Psychology 2 3%
Computer Science 2 3%
Other 8 13%
Unknown 26 41%