Synaptic plasticity is the activity-dependent modification of the strength of connections between neurons. Neural activity generates biochemical signals that activate a complex network of signalling proteins affecting synaptic change by modifying the number of receptors present at the synapse. Key to this process is the activation of feedback loops with sharp thresholds to sustain signalling. Also at the synapse are scaffold proteins that bind pathway members and shape their dynamics. Recent reports of the effects of scaffolds on threshold properties are in conflict. The aim of this
thesis is to determine the qualitative effects of combining feedback loops and scaffold proteins in computational models of synaptic plasticity. We found that the effect of scaffolds on threshold properties is highly dependent on biochemical context, but we did not find evidence of an interactive effect of feedback loops and scaffold proteins in this regard.