The goal of the FIPPA project was to extend the neural network simulator Arbor by key plasticity processes that allow to simulate and analyze the long-term adaptive dynamics of large-scale, morphologically-detailed neuronal networks. The models were ported and augmented in correspondence to neuro-theoretical investigations by the Tetzlaff research group at University of Göttingen.

• Spike-timing-dependent plasticity (STDP)
• Spike-based homeostasis
• Adaptive exponential integrate-and-fire (AdEx) neuron
• Synaptic tagging and capture (STC) in recurrent networks of point neurons

• Calcium-based synaptic plasticity
• Heterosynaptic calcium-based plasticity in dendrites
• Synaptic tagging and capture (STC) in recurrent networks of morphological neurons