Impact of Parkinson's Disease's Severity on Neuron Firing Pattern in Subthalamic Nucleus
Filed under:
Computational neuroscience
Jiri Wild (Dept. of Cybernetics, Faculty of Electrical Engineering, Czech Technical University), Dan Novak (Dept. of Cybernetics, Faculty of Electrical Engineering, Czech Technical University), Eduard Bakstein (Dept. of Cybernetics, Faculty of Electrical Engineering, Czech Technical University), Robert Jech (Dept. of Neurology, 1st Faculty of Medicine and General Teaching Hospital, Charles University in Prague)
Introduction
The Unified Parkinson’s Disease Rating Scale (UPDRS) is a standardized measure of parkinsonian patients’ abilities to perform basic motor skills, as well as the effect of the disease on activities of daily living and mental abilities. Although is UPDRS standardized it is still only a subjective measure depending on the experience and skills of the examiner. In this study, an objective analysis of the motor part of UPDRS is presented, based on the statistical properties of single-unit recordings gathered from Subthalamic Nucleus (STN) of parkinsonian patients during Deep Brain Stimulation (DBS) surgery.
Methods
For the total of 54 patients that underwent DBS surgery UPDRS score was assed prior to the surgery without any medication. During the DBS surgery 10s long signals were recorded from STN using parylenecoated tungsten microelectrodes with an exposed tip size of 15 − 25 μm. These signals were then processed using WaveClus [1] spike sorting software with carefully tuned parameters [2]. From the resulting neurons firing patterns inter spike interval (ISI) histograms (annotated with appropriate UPDRS score) were calculated. The inter-histogram distance were then computed using Kolmogorov-Smirnov (KS) statistic. Finally, ISI histograms were grouped based on their KS distance into three groups and the UPDRS scores of these groups were analyzed using standard ANOVA test.
Results
Grouping ISI histograms based on their KS statistic, resulted in groups of histograms with not only similar shape, but also a similar UPDRS scores. The UPDRS scores were significantly different (at level 0.05) between each group, thus forming groups of patients with low, medium and high motor UPDRS scores.
Conclusion
In this study, motor UPDRS scores of 54 parkinsonian patients were objectively analyzed with single-unit recordings obtained during DBS surgery. The analysis proved that there is a close relation between neuron firing patterns in STN and Parkinson disease motor symptoms.
References:
[1] Quiroga RQ, Nadasdy Z, Ben-Shaul Y. Unsupervised spike detection and sorting with wavelets and superparamagnetic clustering. Neural Comput 2004;16(8):1661–87.
[2] Wild J, Prekopcsak Z, Sieger T, Novák D, Jech R. Performance Comparison of Extracellular Spike Sorting Algorithms for Single-Channel Recordings. Journal of Neuroscience Methods. 2012, vol. 203, no. 2, p. 369-376. ISSN 0165-0270. http://dx.doi.org/10.1016/j.jneumeth.2011.10.013.
The Unified Parkinson’s Disease Rating Scale (UPDRS) is a standardized measure of parkinsonian patients’ abilities to perform basic motor skills, as well as the effect of the disease on activities of daily living and mental abilities. Although is UPDRS standardized it is still only a subjective measure depending on the experience and skills of the examiner. In this study, an objective analysis of the motor part of UPDRS is presented, based on the statistical properties of single-unit recordings gathered from Subthalamic Nucleus (STN) of parkinsonian patients during Deep Brain Stimulation (DBS) surgery.
Methods
For the total of 54 patients that underwent DBS surgery UPDRS score was assed prior to the surgery without any medication. During the DBS surgery 10s long signals were recorded from STN using parylenecoated tungsten microelectrodes with an exposed tip size of 15 − 25 μm. These signals were then processed using WaveClus [1] spike sorting software with carefully tuned parameters [2]. From the resulting neurons firing patterns inter spike interval (ISI) histograms (annotated with appropriate UPDRS score) were calculated. The inter-histogram distance were then computed using Kolmogorov-Smirnov (KS) statistic. Finally, ISI histograms were grouped based on their KS distance into three groups and the UPDRS scores of these groups were analyzed using standard ANOVA test.
Results
Grouping ISI histograms based on their KS statistic, resulted in groups of histograms with not only similar shape, but also a similar UPDRS scores. The UPDRS scores were significantly different (at level 0.05) between each group, thus forming groups of patients with low, medium and high motor UPDRS scores.
Conclusion
In this study, motor UPDRS scores of 54 parkinsonian patients were objectively analyzed with single-unit recordings obtained during DBS surgery. The analysis proved that there is a close relation between neuron firing patterns in STN and Parkinson disease motor symptoms.
References:
[1] Quiroga RQ, Nadasdy Z, Ben-Shaul Y. Unsupervised spike detection and sorting with wavelets and superparamagnetic clustering. Neural Comput 2004;16(8):1661–87.
[2] Wild J, Prekopcsak Z, Sieger T, Novák D, Jech R. Performance Comparison of Extracellular Spike Sorting Algorithms for Single-Channel Recordings. Journal of Neuroscience Methods. 2012, vol. 203, no. 2, p. 369-376. ISSN 0165-0270. http://dx.doi.org/10.1016/j.jneumeth.2011.10.013.
Preferred presentation format:
Poster
Topic:
Computational neuroscience
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