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Computational model of action selection in Parkinson's disease and the effect of deep brain stimulation

Benet i Bertran, Joan (2019) Computational model of action selection in Parkinson's disease and the effect of deep brain stimulation.

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Full Text Status:Access to this publication is restricted
Embargo date:31 December 2021
Abstract:Parkinson’s disease is a neurodegenerative disease characterized by the loss of dopaminergic neurons in the brain which cause tremor, bradykinesia, rigidity, postural instability, and cognitive impairment, among others. This symptomology is present in several tasks, e.g., action selection tasks. These tasks consist in sending a cue to the subject which indicates him to perform a task or withhold its response and do not perform the task. With these tasks what is attempted is to understand the aspects of the disease and work for more efficient treatments, which is also done by means of computational model which try unravel the theoretical aspects of the disease. In the current thesis, a model of the cortico-basal ganglia-thalamocortical loop is developed to try to reproduce the effects of action selection tasks in Parkinson’s disease conditions. The model is based in the Hodgkin-Huxley description of ion channels dynamics of the different populations of neurons that conform this loop with exception of the cortex, which is modeled by means of input/output functions to the other populations. The representation of action selection tasks in the model is used to study if the increase of the β-band (13-30Hz) in the subthalamic nucleus that is seen when these tasks are performed in parkinsonian cases is reduced when proper deep brain stimulation (DBS) is applied and then, to see if this frequency band can be used as biomarker for DBS. The model shows a good approximation of the network, obtaining the expected behavior of the network in resting conditions and the increase of the β-band as the severity of the disease is increased. With respect to the application of DBS, high frequency and low frequency DBS are applied, showing a decay of the β-band for high frequency DBS and a large increase for low frequency DBS. The results are an indicator that high frequency is an optimal treatment that eliminates the erratic oscillations and it the gives possibility of using the β-band as biomarker for treatment as the decay is noticeable. On the other hand, the increase of the β-band for low frequency DBS might be an indicator of the bad outcome obtained when this treatment has been applied.Parkinson’s disease is a neurodegenerative disease characterized by the loss of dopaminergic neurons in the brain which cause tremor, bradykinesia, rigidity, postural instability, and cognitive impairment, among others. This symptomology is present in several tasks, e.g., action selection tasks. These tasks consist in sending a cue to the subject which indicates him to perform a task or withhold its response and do not perform the task. With these tasks what is attempted is to understand the aspects of the disease and work for more efficient treatments, which is also done by means of computational model which try unravel the theoretical aspects of the disease. In the current thesis, a model of the cortico-basal ganglia-thalamocortical loop is developed to try to reproduce the effects of action selection tasks in Parkinson’s disease conditions. The model is based in the Hodgkin-Huxley description of ion channels dynamics of the different populations of neurons that conform this loop with exception of the cortex, which is modeled by means of input/output functions to the other populations. The representation of action selection tasks in the model is used to study if the increase of the β-band (13-30Hz) in the subthalamic nucleus that is seen when these tasks are performed in parkinsonian cases is reduced when proper deep brain stimulation (DBS) is applied and then, to see if this frequency band can be used as biomarker for DBS. The model shows a good approximation of the network, obtaining the expected behavior of the network in resting conditions and the increase of the β-band as the severity of the disease is increased. With respect to the application of DBS, high frequency and low frequency DBS are applied, showing a decay of the β-band for high frequency DBS and a large increase for low frequency DBS. The results are an indicator that high frequency is an optimal treatment that eliminates the erratic oscillations and it the gives possibility of using the β-band as biomarker for treatment as the decay is noticeable. On the other hand, the increase of the β-band for low frequency DBS might be an indicator of the bad outcome obtained when this treatment has been applied.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:31 mathematics, 35 chemistry, 53 electrotechnology
Programme:Electrical Engineering MSc (60353)
Link to this item:http://purl.utwente.nl/essays/79819
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