Location of Repository

1 An Automated Method For Spike Source Identification

By Roberto A. Santiago

Abstract

extracellular neuronal activity has gained increasing interest due to potential improvements to surgical techniques involving ablation or placement of deep brain stimulators as is common in the treatment of Parkinson’s disease. Critical to these procedures is the identification of different brain structures such as the globus pallidus internus (GPI). Evidence suggests that the spike trains from individual neurons contain enough information to identify the brain structure in which they are located. For the work reported here, spike train data gathered during surgical procedure from multiple patients is used. Using a moving window sampling approach, a novel feature extraction method for spike trains was developed. This method is then used in combination with a support vector classification algorithm. Results strongly indicate that the sampling methods reported here are able to extract the necessary information for highly accurate spike source identification. Index Terms—spike source identification, deep brain stimulation, feature extraction, automated classification, support vector machines A I

Year: 2013
OAI identifier: oai:CiteSeerX.psu:10.1.1.307.4911
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://citeseerx.ist.psu.edu/v... (external link)
  • http://web.cecs.pdx.edu/~edam/... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.