Discrimination of the Micro Electrode Recordings for STN Localization during DBS Surgery in Parkinson’s Patients
During deep brain stimulation (DBS) treatment of Parkinson disease, the target of the surgery is a small (9 x 7 x 4 mm) deep within brain placed structure called Subthalamic Nucleus (STN). It is similar morphologically to the surrounding tissue and as such poorly visible in CT or MRI. The goal of the surgery is the permanent precise placement of the stimulating electrode within target nucleus. Precision is extremely important as wrong placement of the stimulating electrode may lead to serious mood disturbances. To obtain exact location of the STN nucleus an intraoperative stereotactic supportive navigation is being used. A set of 3 to 5 parallel micro electrodes is inserted into brain and in measured steps advanced towards expected location of the nucleus. At each step electrodes record activity of the surrounding neural tissue. Because STN has a distinct physiology, the signals recorded within it also display specific features. It is therefore possible to provide analytical methods targeted for detection of those STN specific characteristics. Basing on such methods this paper presents clustering and classification approaches for discrimination of the micro electrode recordings coming from the STN nucleus. Application of those methods during the neurosurgical procedure might lessen the risks of medical complications and might also shorten the – out of necessity awake – part of the surgery.
KeywordsParkinson’s disease DBS STN DWT RMS LFB HFB K-Means EM Clustering C4.5 Random Forest
Unable to display preview. Download preview PDF.
- 1.Jensen, A.: A Ia Cour-Harbo. Ripples in Mathematics. Springer (2001)Google Scholar
- 2.Nolte, J.: The Human Brain, Introduction to Functional Anatomy. Elsevier (2009)Google Scholar
- 3.Israel, Z., et al.: Microelectrode Recording in Movement Disorder Surgery. Thieme Medical Publishers (2004)Google Scholar
- 4.Alexander, B., et al.: Wavelet Filtering before Spike Detection Preserves Waveform Shape and Enhances Single-Unit Discr. J. Neuroscience Methods, 34–40 (2008)Google Scholar
- 6.Quian Quiroga, R., Nadasdy, Z., Ben-Shaul, Y.: Unsupervised Spike Detection and Sorting with Wavelets and Superparamagnetic Clustering. MIT Press (2004)Google Scholar
- 7.Gemmar, P., et al.: MER Classification for DBS, 6th Heidelberg Innov. Forum (2008)Google Scholar
- 12.Walker, H.K., Hall, W.D., Hurst, J.W. (eds.): Clinical Methods: The History, Physical, and Laboratory Examinations, 3rd edn. Butterworths, Boston (1990)Google Scholar