Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/185607
Title: COMPUTATIONAL MODELING AND INFORMATION PROCESSING OF FIRING PATTERNS IN PARKINSON DISEASE
Researcher: Singh Jyotsna
Guide(s): Dr Phool Singh and Dr Vikas Malik
Keywords: Computational Neuroscience, Brain disorder modelling, Parkinson disease, Subthalamic nucleus, Globus pallidus external, Basal ganglia, Activity patterns, discharge patterns
University: The Northcap University (Formerly ITM University, Gurgaon)
Completed Date: 2017
Abstract: newlineParkinson disease alters the information (discharge) patterns in movement related path- newlineways in brain. Experimental results performed on rats show that the activity patterns newlinechanges from single spike activity to mixed burst mode in Parkinson disease. However the cause of this change in activity pattern is not yet completely understood. Subthalamic newlinenucleus is one of the main nuclei involved in the origin of motor dysfunction in Parkinson newlinedisease. This thesis focuses on the analysis of information patterns generated in the sub- newlinethalamic nucleus and globus pallidus (external) network, in basal ganglia, in Parkinson newlinedisease. Analysis of information patterns is performed using a conductance-based model, newlineto investigate pathological oscillations in Parkinson disease, and explore possible origins newlinefor tremor and beta band synchronization including two major pathways, indirect and newlinehyper-direct pathways. Problems on the basis of above mentioned objective have been newlinediscussed in five chapters. First two chapters of the thesis are dedicated for the introduc- newlinetion to the subject, and literature survey of previous research work. newlineChapter three focuses on the information patterns generated in movement related path- newlineways, and how these patterns are altered in case of Parkinson disease. A single compart- newlinement conductance based model is considered for the work, which focuses on subthalamic newlinenucleus and synaptic input from globus pallidus external. In this chapter the discharge newlinepatterns generated for rats in the experimental setup are reproduced using the conduc- newlinetance based computational model for Parkinson disease. In Chapter four, the sensitivity of newlineconductance based model of subthalamic nucleus and globus pallidus (external), towards newlinevarious ions and their concentration have been discussed. In order to perform the analysis newlinebetween healthy and Parkinson primate, time series analysis has been performed. The newlineeffect of feedback mechanism on the activity patterns in healthy and Parkinson primate newlinehas also been analyzed. Discharge patterns are simulated to provide insight into role of newlinedi_erent ions and their importance to improve the correlation coefficient between healthy newlineand Parkinson disease discharge patterns. newlineChapter five focuses on the characterization of spiking patterns in healthy primate and newlineParkinson condition, on the basis of their spike frequency, spike trend and spike rate. newlineCharacterization has been performed for synaptic conductance, calcium, potassium and newlinesodium ionic currents. Behavior of model has been also studied for long time under newlinethe optimized parametric concentration. Focus of this study is to target the parameters newlinewhich play a vital role in improving the correlation coefficient among healthy primate and newlineParkinson condition discharge patterns, and also to study the effect of one parameter in newlinecomparison to other parameter on correlation coefficient. This study insights the causes newlineof deviation of Parkinson discharge pattern from healthy primate and to identify the pa- newlinerameters which might play a crucial role in the treatment of the disease. Conclusion of newlinethe thesis is presented in Chapter six. newlineTo solve all the mathematical and computational problems, I have used MATLAB 7.14 newlineon a system of 4GB RAM. These mathematical problems evolved the coupled differential newlineequations which were used to generate the discharge patterns inside the target neuron for newlinehealthy and Parkinson disease primate. These coupled differential equations are solved us- newlineing ode45 (MATLAB function). In time series analysis, the discharge patterns of healthy newlineprimate and Parkinson primate by calculating their cross correlation coefficient function, newlinehas been analyzed. Cross correlation function is used to and the correlation coefficient i.e. newlinethe similarity between healthy primate and Parkinson condition. Results of the research newlineprovide insight into the cause of origin of the disease and also can further be utilized to newlinestudy the effect of ionic concentration in devising a better diagnostic system. newline
Pagination: 139p.
URI: http://hdl.handle.net/10603/185607
Appears in Departments:Department of CSE & IT

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abstract.pdfAttached File51.13 kBAdobe PDFView/Open
bibliography.pdf98.36 kBAdobe PDFView/Open
biographical sketch of the scholar.pdf67.08 kBAdobe PDFView/Open
chapter 1 (1).pdf1.58 MBAdobe PDFView/Open
chapter 2 (1).pdf127.73 kBAdobe PDFView/Open
chapter 3 (1).pdf879.72 kBAdobe PDFView/Open
chapter 4.pdf205.86 kBAdobe PDFView/Open
chapter 5.pdf184.25 kBAdobe PDFView/Open
chapter 6.pdf53.41 kBAdobe PDFView/Open
contents.pdf51.72 kBAdobe PDFView/Open
list of figures.pdf99.51 kBAdobe PDFView/Open
list of publicatons.pdf49.39 kBAdobe PDFView/Open
list of tables.pdf78.56 kBAdobe PDFView/Open


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