References
- Anderson, P.B. and Rogers, M.H. (2009). Deep Brain Stimulation: Applications, Complications and Side Effects, Nova Biomedical Books, New York, NY.
- Apostolidis-Afentoulis, V. and Lioufi, K.I. (2015). classification with linear and RBF kernels, http://www.academia.edu/13811676/SVM_Classification_with_Linear_and_RBF_kernels.
- Cagnan, H., Dolan, K., He, X., Contarino, M.F., Schuurman, R., Van Den Munckhof, P., Wadman, W.J., Bour, L. and Martens, H.C. (2011). Automatic subthalamic nucleus detection from microelectrode recordings based on noise level and neuronal activity, Journal of Neural Engineering8(4): 046006.
- Ciecierski, K.A., Raś, Z.W. and Przybyszewski, A.W. (2014a). Foundations of automatic system for intrasurgical localization of subthalamic nucleus in Parkinson patients, Web Intelligence and Agent Systems12(1): 63–82.
- Ciecierski, K., Mandat, T., Rola, R., Raś, Z.W. and Przybyszewski, A.W. (2014b). Computer aided subthalamic nucleus (STN) localization during deep brain stimulation (DBS) surgery in Parkinson’s patients, Annales Academiae Medicae Silesiensis5(68): 275–283.
- Dietterich, T.G. (2000). Ensemble methods in machine learning, in J. Kittler and F. Rodi (Eds), Multiple Classifier Systems, Springer, Berlin, pp. 1–15, DOI: 10.1007/3-540-45014-9_1.
- Duch, W., Adamczak, R. and Diercksen, G.H.F. (2000). Classification, association and pattern completion using neural similarity based methods, International Journal of Applied Mathematics and Computer Science10(4): 747–766.
- Freeman, E.A. and Moisen, G.G. (2008). A comparison of the performance of threshold criteria for binary classification in terms of predicted prevalence and kappa, Ecological Modelling217(1–2): 48–58.
- Ho, A.L., Ali, R., Connolly, I.D., Henderson, J.M., Dhall, R., Stein, S.C. and Halpern, C.H. (2018). Awake versus asleep deep brain stimulation for Parkinson’s disease: A critical comparison and meta-analysis, Journal of Neurology, Neurosurgery & Psychiatry89(7): 687–691.
- Hutchison, W.D., Allan, R.J., Opitz, H., Levy, R., Dostrovsky, J.O., Lang, A.E. and Lozano, A.M. (1998). Neurophysiological identification of the subthalamic nucleus in surgery for Parkinson’s disease, Annals of Neurology44(4): 622–628.
- Israel, Z. and Burchiel, K.J. (2011). Microelectrode Recording in Movement Disorder Surgery, Thieme, Stuttgart.
- Jeleń, Ł., Fevens, T. and Krzyżak, A. (2008). Classification of breast cancer malignancy using cytological images of fine needle aspiration biopsies, International Journal of Applied Mathematics and Computer Science18(1): 75–83, DOI: 10.2478/v10006-008-0007-x.
- Jensen, A. and la Cour-Harbo, A. (2001). Ripples in Mathematics: The Discrete Wavelet Transform, Berlin/Heidelberg.
- Kano, T., Katayama, Y., Kobayashi, K., Kasai, M., Oshima, H., Fukaya, C. and Yamamoto, T. (2006). Detection of boundaries of subthalamic nucleus by multiple-cell spike density analysis in deep brain stimulation for Parkinson’s disease, in J.W. Chang et al. (Eds), Advances in Functional and Reparative Neurosurgery, Springer, Vienna, pp. 33–35.
- Koch, C. (2004). Biophysics of Computation: Information Processing in Single Neurons, Oxford University Press, Oxford.
- Levy, R., Hutchison, W.D., Lozano, A.M. and Dostrovsky, J.O. (2000). High-frequency synchronization of neuronal activity in the subthalamic nucleus of parkinsonian patients with limb tremor, Journal of Neuroscience20(20): 7766–7775.
- Lewicki, M.S. (1998). A review of methods for spike sorting: The detection and classification of neural action potentials, Network: Computation in Neural Systems9(4): R53–R78.
- Mallet, L., Schüpbach, M., N’Diaye, K., Remy, P., Bardinet, E., Czernecki, V., Welter, M.-L., Pelissolo, A., Ruberg, M., Agid, Y. and Yelnik, J. (2007). Stimulation of subterritories of the subthalamic nucleus reveals its role in the integration of the emotional and motor aspects of behavior, Proceedings of the National Academy of Sciences104(25): 10661–10666.
- Mandat, T.S., Hurwitz, T. and Honey, C.R. (2006). Hypomania as an adverse effect of subthalamic nucleus stimulation: Report of two cases, Acta Neurochirurgica148(8): 895–898.
- Mandat, T., Tykocki, T., Koziara, H., Koziorowski, D., Brodacki, B., Rola, R., Bonicki, W. and Nauman, P. (2011). Subthalamic deep brain stimulation for the treatment of Parkinson disease, Neurologia i Neurochirurgia Polska45(1): 32–36.
- Moran, A., Bar-Gad, I., Bergman, H. and Israel, Z. (2006). Real-time refinement of subthalamic nucleus targeting using Bayesian decision-making on the root mean square measure, Movement Disorders21(9): 1425–1431.
- Nieuwenhuys, R., Voogd, J. and Van Huijzen, C. (2007). The Human Central Nervous System: A Synopsis and Atlas, Springer, Berlin.
- Novak, P., Daniluk, S., Ellias, S.A. and Nazzaro, J.M. (2007). Detection of the subthalamic nucleus in microelectrographic recordings in Parkinson disease using the high-frequency (> 500 Hz) neuronal background, Journal of Neurosurgery106(1): 175–179.
- Parent, A. and Hazrati, L.-N. (1995). Functional anatomy of the basal ganglia. II: The place of subthalamic nucleus and external pallidium in basal ganglia circuitry, Brain Research Reviews20(1): 128–154.
- Saleh, S., Swanson, K.I., Lake, W.B. and Sillay, K.A. (2015). Awake neurophysiologically guided versus asleep MRI-guided STN DBS for Parkinson disease: A comparison of outcomes using levodopa equivalents, Stereotactic and Functional Surgeny93(6): 419–426.
- Schaltenbrand, G. (1977). Atlas for Stereotaxy of the Human Brain, Georg Thieme, Stuttgart.
- Schiaffino, L., Muñoz, A.R., Martínez, J.G., Villora, J.F., Gutiérrez, A. and Torres, I.M. (2016). STN area detection using K-NN classifiers for MER recordings in Parkinson patients during neurostimulator implant surgery, Journal of Physics: Conference Series705(1): 012050.
- Shamir, R.R., Zaidel, A., Joskowicz, L., Bergman, H. and Israel, Z. (2012). Microelectrode recording duration and spatial density constraints for automatic targeting of the subthalamic nucleus, Stereotactic and Functional Neuro-surgery90(5): 325–334.
- Smith, S.W. (1997). The Scientist & Engineer’s Guide to California Technical, Digital Signal Processing, Publishing, San Diego, CA.
- Temel, Y., Blokland, A., Steinbusch, H.W.M. and Visser-Vandewalle, V. (2005). The functional role of the subthalamic nucleus in cognitive and limbic circuits, Progress in Neurobiology76(6): 393–413.
- Valsky, D., Marmor-Levin, O., Deffains, M., Eitan, R., Blackwell, K. T., Bergman, H. and Israel, Z. (2017). Stop! border ahead: Automatic detection of subthalamic exit during deep brain stimulation surgery, Movement Disorders32(1): 70–79.
- Williams, C.K.I. (2003). Learning with kernels: Support vector machines, regularization, optimization, and beyond, Journal of the American Statistical Association98(462): 489–489.
- Zaidel, A., Spivak, A., Shpigelman, L., Bergman, H. and Israel, Z. (2009). Delimiting subterritories of the human subthalamic nucleus by means of microelectrode recordings and a hidden Markov model, Movement Disorders24(12): 1785–1793.