Connecting Individual Differences to the Functional Complexity of Animal Groups
2 Ph.D./Postdoctoral Positions
This project will explore how inter-individual differences in behavior and physiology (such as differences in individual sensitivity, uncertainty, influence of and by others in the group, sensory capabilities, decision-making algorithms etc.) impact the sensing, decision-making and search dynamics of the groups. We will seek to understand how differences affect whether a decision is made, which alternative or sequence of alternatives is chosen, the speed and accuracy of the decision or search, and the responsiveness of the decision and search to changes in the environment. We are open to employing different experimental systems in this study, including (but not exclusively) fish and birds.
We aim to examine individual differences for the following kinds of dynamics, which are fundamental to collective animal behavior:
- Spreading dynamics describe how easily a response by an individual to a stimulus, such as a threat, target, or source of data, spreads through a networked group of individuals. Spreading dynamics underlie the dynamics of collective decision-making and search.
- Decision-making and search dynamics describe how individuals and the group as a whole make choices among alternatives: for example, choosing which alternative is true, which action to take, which direction or motion pattern to follow, or when something in the environment or in the state of the system has changed. Decision-making under limited information and uncertainty is fundamental to search tasks in which individuals must choose among options in order to find a target or peak in an uncertain distributed ﬁeld.
- Multiple task management describes how tasks such as search and threat avoidance are carried out simultaneously given costs, benefits, and limited resources that derive from complex, real-world environments. Spreading and decision-making dynamics are fundamental to multiple task management.
We know little about the relationship between social network structure and contagion, and have no information at all about multiple layers of communication (such as mediated by different sensory modalities) and how individuals integrate these layers of sensory input when making decisions. We will address these issues using methodologies in which we can quantify inter-individual differences in sensing and response to stimuli as well as by physically and pharmacologically manipulating sensory modalities allowing us to precisely test specific hypotheses regarding social contagion in natural animal groups. This will allow us to reveal how the structure of communication networks impacts collective sensing, search, foraging and avoidance of risk.
The successful candidates will, have access to world-class research facilities including considerable in-house expertise in machine learning, automated tracking, sensory reconstruction, virtual reality and and behavioural analysis technologies. (Advisor: Iain Couzin)