1. MODELING THE PARKINSONIAN TREMOR AND ITS TREATMENT Supervisor : Dr Towhidkhah Designed by Yashar Sarbaz Amirkabir University of Technology

2. TITLES 1. INTRODUCTION OF PARKINSON’S DISEASE (PD) 2. SIMPLE MODELING 3. COMPLETING THE MODEL 4. MODELING THE TREATMENTS

3. 1.Intoduction of PD 1-1. Origin of PD (Basal ganglia) 1-2. Parts of Basal ganglia (BG) 1-3. PD & it’s symptoms

4. 1-1.Origion of PD (BG)

5. 1-2.Parts of BG

6. 1-3.PD & it’s symptoms Reason of PD: Loss of nerve cells in substantia nigra pars compacta Low level of Dopamine in patient’s brain Changing activity of other blocks

7. 1-3.PD and it’s symptoms Symptoms of PD: Hypokinesia Akinesia: lack of slowness of spontaneous and associative movement Rigidity: increased tone on passive manipulation of joints Tremor:rhythmic,involuntary,oscillatory movement around 4-6 Hz

8. Clinical Data Recording Velocity laser recording of rest tremor

9. 2.Simple modeling 2-1.Information about connections of Basal ganglia 2-2.Information about each block of Basal ganglia 2-3.Presenting mathematical model

10. 2-1.Connection of BG The number of input and output of each block The type of each input to block (Inhibitory and excitatory effect ) The strength changes of connections in patient and healthy cases A gain corresponding to Dopamine changes

11. 2-2.Each block of BG There are not detailed information about function of each block The major criteria for separating the different parts of BG are their anatomical and structural appearance and the kind of neurotransmitters Each block contain large value of neurons

12. Behavior of single neuron Membrane resistance Membrane capacitance longitudinal resistance

13. 2-3.Mathematical model

14. Changing activity of blocks HealthyPatient

15. Changes of strengths of connections

16. Block diagram of model

17. Relations of each blocks

19. Model response for illness case ( g=10 )

20. Model response for treated case ( g=1 )

21. Sample of clinical Data

22. Comparing power spectra of clinical Data and model response Clinical DataModel Response

23. 3.Completing the model 3-1.Synaptic transmission 3-2.Noise sources in synaptic transmission of healthy persons 3-3.Noise sources in synaptic transmission of patients 3-4.Completing the model

24. 3-1.Synaptic transmission Step1 Step2

25. 3-1.Synaptic transmission Step3&4

26. 3-1.Synaptic transmission step5

27. 3-1.Synaptic transmission step6

28. 3-2.Noise sources in synaptic transmission of healthy persons Calsium amount in cell Voltage gated channels Diffusion of neurotransmitters Ligand gated channels

29. 3-3.Noise sources in synaptic transmission of patients Lower of uptake Up regulation Diffusion of neurotransmitters

30. 3-4.Completing the model Replacing with Considering normal physiological Tremor:

31. Comparing results with clinical data g2rof record Model response with a=0.2

32. Comparing results with clinical data S15rof record Model response with a=0.2&b=0.2

33. Changing activity of blocks

34. 4.MODELING THE TREATMENTS 4-1.Kinds of PD treatments 4-2.Modeling drug effect 4-3.Modeling DBS effect 4-4.Prediction based on the model

35. 4-1.Kinds of Treatments 1-1. Medical treatment 1-2. Deep Brain Stimulation

36. Medical Treatment Levodopa Drug L-depernil Drug

37. DBS Target of Stimulation GPi: The Globus Pallidus Internal STN:The Subthalamic Nucleus Vim: The Ventro-Intermediate nucleus Thlamus

38. 4-2.Modeling drug effect Pharmacodynamics Pharmacokinetics

39. Pharmacodynamics Input is Levodopa drug Output is plasma level of drug

40. Model and clinical data

41. Relation of Pharmacodynamics

42. Pharmacokinetics input is plasma level of drug Output is g parameter of main model

43. Pharmacokinetics parts A nonlinear system (Saturation element) A first order system Scaling part

44. Response signal of Parmacodynamics part

45. Response signal of Pharmacokinetics part

46. Simple model response to drug prescription

47. Complete model response to drug prescription

48. 4-3.Modeling DBS effect Characteristics of the common DBS signal: 1. Frequency greater than 100 2. Pulse width about 90 3. Amplitude of stimulation voltage nearly 3 v

49. DBS characteristic for different subjects

50. Clinical data of subjects when DBS switch to on

51. Clinical data of subjects when DBS switch to off

52. Relation of DBS

53. ,

54. Variation of Parameter of g in DBS sec

55. Response of the simple model sec

56. Response of the complete model sec

57. 4-4.Prediction based on the model 4-4-1.Offering a new medical treatment 4-4-2.Optimization of the levodopa usage

58. Problems of Levodopa usage

59. 4-4-1.Offering a new medical treatment

60. Including GABA effect

61. Model response with different g & k=1 g=10 g=1

62. Model response with g=10 & k=0.1

63. Model response with g=5 & k=0.1

64. 4-4-2.Optimization of the levodopa usage

65. Optimization problem

66. Answer of optimization