Decoding Epileptogenesis in a Reduced State Space

@article{Meyer2016DecodingEI,
  title={Decoding Epileptogenesis in a Reduced State Space},
  author={François G. Meyer and Alexander M. Benison and Zachariah Smith and Daniel S. Barth},
  journal={2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA)},
  year={2016},
  pages={152-157}
}
We describe here the recent results of a multidisciplinary effort to design a biomarker that can actively and continuously decode the progressive changes in neuronal organization leading to epilepsy, a process known as epileptogenesis. Using an animal model of acquired epilepsy, we chronically record hippocampal evoked potentials elicited by an auditory stimulus. Using a set of reduced coordinates, our algorithm can identify universal smooth low-dimensional configurations of the auditory evoked… 

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