Description: This model uses a compartmental approach to represent the progression of Alzheimer’s disease. It divides the brain into compartments for healthy neurons, neurons with amyloid-β plaques, and neurons with tau tangles. Transition rates between these compartments are influenced by factors such as amyloid-β production, tau phosphorylation, and neuronal death.
Results:
As amyloid-β and tau tangles increase, they disrupt communication between healthy neurons, leading to dementia and memory loss. Potential treatments could target amyloid-β and tau proteins to slow their growth.
Description: This model uses the FitzHugh-Nagumo equations to describe the electrical activity of a single neuron. The system is represented by two variables:
- V(t): Membrane voltage of the neuron at time t.
- W(t): Recovery variable related to the neuron’s firing ability.
Results:
The graph shows membrane voltage ( V ) (purple line) spiking over time, with the recovery variable ( W ) (green line) depicting the neuron's return to its initial state. This helps identify seizure thresholds and understand the refractory period preventing immediate neuron firing.
Description: This two-compartmental model represents Parkinson’s disease progression. It includes:
- Compartment 1: Dopamine stores in the brain.
- Compartment 2: Severity of motor symptoms (measured by MDS-UPDRS parts II and III).
The model simulates dopamine loss and the impact of levodopa treatment on motor symptoms.
Results:
- Dopamine Levels: Represented by the red line, showing a decrease over time.
- Motor Symptoms Severity: Represented by the blue line, increasing as dopamine levels fall.
As dopamine levels drop below a threshold, motor symptoms become more pronounced. Treatment aims to replenish dopamine levels to alleviate symptoms.