On the estimation of brain signal entropy from sparse neuroimaging data.

@article{Grandy2016OnTE,
  title={On the estimation of brain signal entropy from sparse neuroimaging data.},
  author={Thomas H. Grandy and Douglas D. Garrett and Florian Schmiedek and Markus Werkle-Bergner},
  journal={Scientific reports},
  year={2016},
  volume={6},
  pages={23073}
}
Multi-scale entropy (MSE) has been recently established as a promising tool for the analysis of the moment-to-moment variability of neural signals. Appealingly, MSE provides a measure of the predictability of neural operations across the multiple time scales on which the brain operates. An important limitation in the application of the MSE to some classes of neural signals is MSE's apparent reliance on long time series. However, this sparse-data limitation in MSE computation could potentially… CONTINUE READING
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