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A biophysical model of the cortex-basal ganglia-thalamus network in the 6-OHDA lesioned rat model of Parkinson’s disease

Overview of attention for article published in Journal of Computational Neuroscience, February 2016
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Title
A biophysical model of the cortex-basal ganglia-thalamus network in the 6-OHDA lesioned rat model of Parkinson’s disease
Published in
Journal of Computational Neuroscience, February 2016
DOI 10.1007/s10827-016-0593-9
Pubmed ID
Authors

Karthik Kumaravelu, David T. Brocker, Warren M. Grill

Abstract

Electrical stimulation of sub-cortical brain regions (the basal ganglia), known as deep brain stimulation (DBS), is an effective treatment for Parkinson's disease (PD). Chronic high frequency (HF) DBS in the subthalamic nucleus (STN) or globus pallidus interna (GPi) reduces motor symptoms including bradykinesia and tremor in patients with PD, but the therapeutic mechanisms of DBS are not fully understood. We developed a biophysical network model comprising of the closed loop cortical-basal ganglia-thalamus circuit representing the healthy and parkinsonian rat brain. The network properties of the model were validated by comparing responses evoked in basal ganglia (BG) nuclei by cortical (CTX) stimulation to published experimental results. A key emergent property of the model was generation of low-frequency network oscillations. Consistent with their putative pathological role, low-frequency oscillations in model BG neurons were exaggerated in the parkinsonian state compared to the healthy condition. We used the model to quantify the effectiveness of STN DBS at different frequencies in suppressing low-frequency oscillatory activity in GPi. Frequencies less than 40 Hz were ineffective, low-frequency oscillatory power decreased gradually for frequencies between 50 Hz and 130 Hz, and saturated at frequencies higher than 150 Hz. HF STN DBS suppressed pathological oscillations in GPe/GPi both by exciting and inhibiting the firing in GPe/GPi neurons, and the number of GPe/GPi neurons influenced was greater for HF stimulation than low-frequency stimulation. Similar to the frequency dependent suppression of pathological oscillations, STN DBS also normalized the abnormal GPi spiking activity evoked by CTX stimulation in a frequency dependent fashion with HF being the most effective. Therefore, therapeutic HF STN DBS effectively suppresses pathological activity by influencing the activity of a greater proportion of neurons in the output nucleus of the BG.

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The data shown below were compiled from readership statistics for 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Germany 2 2%
Unknown 114 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 18%
Researcher 20 17%
Student > Master 19 16%
Student > Bachelor 10 8%
Student > Doctoral Student 5 4%
Other 21 18%
Unknown 22 19%
Readers by discipline Count As %
Neuroscience 34 29%
Engineering 24 20%
Agricultural and Biological Sciences 8 7%
Medicine and Dentistry 7 6%
Computer Science 7 6%
Other 13 11%
Unknown 25 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 February 2016.
All research outputs
#20,306,690
of 22,846,662 outputs
Outputs from Journal of Computational Neuroscience
#263
of 307 outputs
Outputs of similar age
#337,055
of 400,570 outputs
Outputs of similar age from Journal of Computational Neuroscience
#8
of 11 outputs
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