  Human brain contains about 10 billion neurons, each of which has about
10~10,000 nerve endings from which neurotransmitters are released in response
to incoming spikes, and the released neurotransmitters then bind to receptors
located in the postsynaptic neurons. However, individually, neurons are noisy
and synaptic release is in general unreliable. But groups of neurons that are
arranged in specialized modules can collectively perform complex information
processing tasks robustly and reliably. How functionally groups of neurons
perform behavioural related tasks crucial rely on a coherent organization of
dynamics from membrane ionic kinetics to synaptic coupling of the network and
dynamics of rhythmic oscillations that are tightly linked to behavioural state.
  To capture essential features of the biological system at multiple
spatial-temporal scales, it is important to construct a suitable computational
model that is closely or solely based on experimental data. Depending on what
one wants to understand, these models can either be very functional and
biologically realistic descriptions with thousands of coupled differential
equations (Hodgkin-Huxley type) or greatly simplified caricatures
(integrate-and-fire type) which are useful for studying large interconnected
networks.
