Amirkabir University of Technology MODELING THE PARKINSONIAN TREMOR

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

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

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

1 -1. Origion of PD (BG)

1 -2. Parts of BG

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

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

Clinical Data Recording Velocity laser recording of rest tremor

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

2 -1. Connection of BG n n 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

2 -2. Each block of BG n n n 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

Behavior of single neuron n Membrane resistance Membrane capacitance longitudinal resistance

2 -3. Mathematical model

Changing activity of blocks Healthy Patient

Changes of strengths of connections

Block diagram of model

Relations of each blocks

Relations of each blocks

Model response for illness case ( g=10 )

Model response for treated case ( g=1 )

Sample of clinical Data

Comparing power spectra of clinical Data and model response Clinical Data Model Response

3. Completing the model n n 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

3 -1. Synaptic transmission Step 1 Step 2

3 -1. Synaptic transmission Step 3&4

3 -1. Synaptic transmission step 5

3 -1. Synaptic transmission step 6

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

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

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

Comparing results with clinical data g 2 rof record Model response with a=0. 2

Comparing results with clinical data S 15 rof record Model response with a=0. 2&b=0. 2

Changing activity of blocks

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

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

Medical Treatment n Levodopa Drug n L-depernil Drug

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

4 -2. Modeling drug effect n Pharmacodynamics n Pharmacokinetics

Pharmacodynamics n n Input is Levodopa drug Output is plasma level of drug

Model and clinical data

Relation of Pharmacodynamics

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

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

Response signal of Parmacodynamics part

Response signal of Pharmacokinetics part

Simple model response to drug prescription

Complete model response to drug prescription

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

DBS characteristic for different subjects

Clinical data of subjects when DBS switch to on

Clinical data of subjects when DBS switch to off

Relation of DBS

Relation of DBS ,

Variation of Parameter of g in DBS sec

Response of the simple model sec

Response of the complete model sec

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

Problems of Levodopa usage

4 -4 -1. Offering a new medical treatment

Including GABA effect

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

Model response with g=10 & k=0. 1

Model response with g=5 & k=0. 1

4 -4 -2. Optimization of the levodopa usage

Optimization problem

Answer of optimization