Principles of Computational Modelling in Neuroscience

Plasticity in the nervous system describes its ability to adapt to change, in response to exposure to new information, fluctuations in the internal environment or external injury. In each case, computational models at different levels of detail are required. Given that memory traces are stored in modifiable synapses, to model the storage and retrieval of information requires models of the modifiable synapse and of a network of neurons. We discuss the processing ability of the network as a whole, given a particular mechanism for synaptic modification, modelled in less detail. Neurons also exhibit homeostatic plasticity, the ability to maintain their firing activity in response to a fluctuating environment. This can involve modulation of intrinsic membrane currents, as well as synaptic plasticity. It must work in concert with synaptic plasticity for learning and memory to enable neural networks to retain and recall stored information whilst still being responsive to new information.