Dynamical Analyses on Beta Oscillations in a STN-GPE-GPI Model of Parkinson’s Disease

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261 632 266 692 274V302Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,62.363,3.132)"><path d="M303 0V28C221 34 213 39 213 125V525C213 610 221 616 303 622V650H38V622C120 616 128 610 128 525V125C128 40 120 34 38 28V0H303Z"></path></g></svg> on the frequency of the GPi firing rate (a<sub>1</sub>)–(a<sub>3</sub>) and the amplitude of GPi (b<sub>1</sub>)–(b<sub>3</sub>). Other parameters are taken from Parkinson’s state in Table <a href="../tab2/">2</a>.</div>

Complexity

fig5

Figure 5

Figure 5: Dynamical Analyses on Beta Oscillations in a STN-GPE-GPI Model of Parkinson’s Disease 