Nonlinear Analysis Of Interspike Intervals Of Globus Pallidus In Parkinson's Disease

Parkinson' s disease (PD) is a progressive degenerative disease. Its cardinal symptoms are rigidity, tremor, dykinesia and akinesia. Although many surgical ways are used to treat PD, it remains uncurable because the etiology remains unknown. There will be more and more people who suffer from PD in the near future with the increasing number of the aged man in China. In another hand, many physiologists believe that the mode of the neural code is mean rate code which has been proved by many researches. However, this mode has many limitationssuch as too simple, low efficiency, less information et al. Now in this essay we will use a new way to analysis the electrophysiological character of neuron of globus pallidus in PD patients. OBJECTIVEAnalysis ISIs of different parts of globus pallidus in parkinson' s disease by methods derived from nonlinear dynamics and open out the relationship between PD and the electrophysiological character of neuron of globus pallidus in PD patients. METHODS(1) All the experiment group are inpatient in our department between March and August in 2004, who accept stereotatic surgery on internal pallidum.(2) Record the discharge of pallidum neurons for 60s, the data is stored in hard disk.(3) Identify and select the single-unit discharge based on the amplitude, frequency and pattern. Only the single-unit discharge neurons would be studied. Theneurons are located by identifying the typical neuron discharge of Gpe, Gpi and lamina between Gpe and Gpi and compared with the standard atlas.(4) Demarcate the spikes after operation and set uptrains of Interspike Intervals.(5) An improved GrassbergerHProcaccia (GP) algorithmwas proposed for computing the correlation dimensions (CDs) of Interspike Intervals (ISIs) in internal and external segment of globus pallidus (Gpi and Gpe). Analysis was also performed by calculating the largest Lyapunov exponents of Gpi and Gpe.RESULTS(1) Both ISIs of Gpi and Gpe are chaotic.(2) It was found that Gpe is a 5. 5 ~ 6.4 dimensional complex dynamic systems, while Gpi is some 3.7 ~4. 6 dimensional. Gpe has the largest Lyapunov exponents of about 0. 36 ~ 0. 45 and the largest Lyapunov exponents of Gpi is about 0. 25 ~ 0. 32, besides, both of them are positive numbers. The largest Lyapunov exponents and CDs of Gpi are significantly lower than those of Gpe. ( t_cd =2.47, p_CD<0.01; t_L=3.22, p_L<0.01)...