This work will explore the use of spiking neural network models based on observations of areas of the brain associated with cognitive capabilities. In particular reservoir computing models of the prefrontal cortex, and continuous attractor models of the hippocampus will be utilised. This contrasts with existing work which utilises a rule-based/symbolic model, or a non spiking artificial neural network. One key reason for not using the latter is to attempt to produce not only a functional model of cognitive capabilities, but a model which can potentially be used for studying the biological source. These models will be tested by being embodied in simulated and physical robotic agents (neurorobot) and evaluated on behavioural tasks.