Identifying prototypical components in behaviour using clustering algorithms.

ABSTRACT: Quantitative analysis of animal behaviour is a requirement to understand the task solving strategies of animals and the underlying control mechanisms. The identification of repeatedly occurring behavioural components is thereby a key element of a structured quantitative description. However, the complexity of most behaviours makes the identification of such behavioural components a challenging problem. We propose an automatic and objective approach for determining and evaluating prototypical behavioural components. Behavioural prototypes are identified using clustering algorithms and finally evaluated with respect to their ability to represent the whole behavioural data set. The prototypes allow for a meaningful segmentation of behavioural sequences. We applied our clustering approach to i

SUBMITTER: Braun E 

PROVIDER: S-EPMC2825265 | biostudies-literature | 2010 Feb

REPOSITORIES: biostudies-literature