Stochastic Models of Behaviour

The ultimate performance measure of an animals brain, is whether it can produce adequate behaviour to increase its species fitness. A basic characteristic of biological systems is the variability of behaviour. Variability can be observed across many levels of biological organisation: from movement in humans, the responses of cellular networks to repeated identical stimulations, to the interaction of bio molecules. Variability has, therefore, emerged as a key ingredient in understanding computational and biological mechanisms in the brain (Faisal et al, 2008, Nature Rev Neurosci). Advances in experimental methods have increased the availability, amount and quality of behavioural data for both humans and animals. Yet most behavioural studies lack adequate quantitative methods to model behaviour and its variability in a natural manner. These approaches make use of simple experiments with straightforward interpretation and subjectively defined behavioural performance indicators often averaging out meaningful variability. Thus, a major challenge in analyzing behavior is to discover some underlying simplicity in a complex stream of behavioral actions. The gain of such an analysis is that the underlying simplicity is often a reflection of the mechanism driving behavior.