Abstract
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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Jensen, A.: A Ia Cour-Harbo. Ripples in Mathematics. Springer (2001)
Nolte, J.: The Human Brain, Introduction to Functional Anatomy. Elsevier (2009)
Israel, Z., et al.: Microelectrode Recording in Movement Disorder Surgery. Thieme Medical Publishers (2004)
Alexander, B., et al.: Wavelet Filtering before Spike Detection Preserves Waveform Shape and Enhances Single-Unit Discr. J. Neuroscience Methods, 34–40 (2008)
Moran, A., et al.: Real-Time Refinement of STN Targeting Using Bayesian Decision-Making on the RMS Measure. J. Mvmt. Disorders 21(9), 1425–1431 (2006)
Quian Quiroga, R., Nadasdy, Z., Ben-Shaul, Y.: Unsupervised Spike Detection and Sorting with Wavelets and Superparamagnetic Clustering. MIT Press (2004)
Gemmar, P., et al.: MER Classification for DBS, 6th Heidelberg Innov. Forum (2008)
Ciecierski, K., Raś, Z.W., Przybyszewski, A.W.: Selection of the Optimal Microelectrode during DBS Surgery in Parkinson’s Patients. In: Kryszkiewicz, M., Rybinski, H., Skowron, A., Raś, Z.W. (eds.) ISMIS 2011. LNCS, vol. 6804, pp. 554–564. Springer, Heidelberg (2011)
Ciecierski, K., Raś, Z.W., Przybyszewski, A.W.: Foundations of Recommender System for STN Localization during DBS Surgery in Parkinson’s Patients. In: Chen, L., Felfernig, A., Liu, J., Raś, Z.W. (eds.) ISMIS 2012. LNCS, vol. 7661, pp. 234–243. Springer, Heidelberg (2012)
Novak, P., Przybyszewski, A.W., et al.: Localization of the subthalamic nucleus in Parkinson disease using multiunit activity. J. Neur. Sciences 310, 44–49 (2011)
Novak, P., et al.: Detection of the subthalamic nucleus in microelectrographic recordings in Parkinson disease using the high-frequency (> 500 Hz) neuronal background. J. Neurosurgery 106, 175–179 (2007)
Walker, H.K., Hall, W.D., Hurst, J.W. (eds.): Clinical Methods: The History, Physical, and Laboratory Examinations, 3rd edn. Butterworths, Boston (1990)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ciecierski, K., Raś, Z.W., Przybyszewski, A.W. (2013). Discrimination of the Micro Electrode Recordings for STN Localization during DBS Surgery in Parkinson’s Patients. In: Larsen, H.L., Martin-Bautista, M.J., Vila, M.A., Andreasen, T., Christiansen, H. (eds) Flexible Query Answering Systems. FQAS 2013. Lecture Notes in Computer Science(), vol 8132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40769-7_29
Download citation
DOI: https://doi.org/10.1007/978-3-642-40769-7_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40768-0
Online ISBN: 978-3-642-40769-7
eBook Packages: Computer ScienceComputer Science (R0)