Whitney Tabor - US grants

Rules play a central role in human behavior. Social rules (e.g., do unto others as you would have them do unto you; don't judge a book by its cover) support the harmonious coexistence of people in a society. Rules of individual choice-making (e.g., exercise daily, beware of strangers bearing gifts) support the well-being of individuals. Although we are usually not consciously aware of using them, there are many rule-like behaviors associated with our use of language (e.g. add -s to form the plural of a noun). An important property of linguistic rules, like social rules and individual rules, is that they admit exceptions (e.g., not all nouns form a plural with -s). Knowing when to apply the rules and when to make exceptions is an important facet of being an effective member of a language community. This project investigates neural models of the formation of linguistic rules to understand how humans achieve an appropriate balance between rigid rule-following and flexibility. It explores human learning of simple invented languages in laboratory experiments and compares the results with mathematical models that approximate important features of neural systems. The goals are to identify two extremes---situations where people adopt rigid, universal rules and situations where they treat every instance as a special case---and then to examine how a balance between these can be achieved. By studying the neural underpinnings of such learning processes, we can gain insight into what kinds of human-environment relationships sustain appropriately systematic but flexible behavior.

This project has implications for the science of learning and for understanding the neural connectivity patterns that underlie complex thinking. Regarding learning, people sometimes fail to discover systematic principles, e.g. learning the spelling-sound correspondences that support reading. This project may shed light on why this happens. Regarding societal well-being, the tendency of people to form stereotypes appears to be a case of learning a rule "too well," that is failing to strike the right balance between generalization and exception making. By examining what brain/environment circumstances lead to such inaccurate learning, the research may help societies avoid the formation of rigid stereotypes.

This INSPIRE award is partially funded by the Perception, Action, and Cognition Program in the Division of Behavioral and Cognitive Sciences in the Directorate for Social, Behavioral and Economic Sciences, the Animal Behavior Program in the Division of Integrative Organismal Systems in the Directorate for Biology, and the Dynamical Systems Program in the Division of Civil, Mechanical & Manufacturing Innovation in the Directorate for Engineering.

The project explores the question of how the activities of individuals become integrated into a smoothly functioning society: What are the dominant mechanisms? How resilient are they? How do they depend on the properties of individual society members? To this end, investigators from engineering, biology, psychology and linguistics will work together to study bee colonies and groups of humans to understand how organization and coordination emerges from these multi-agent systems and the factors that influence their robustness and resilience to perturbations. The project relies on quantitative observations of the dynamic emergence of patterns of interaction and coordination using an unprecedented, 24/7 monitoring system of a beehive as well as in groups of humans under controlled conditions designed to distinguish between failed and successful coordination. The investigators will pursue a combined theoretical, experimental, and computational framework for characterizing the resultant parallel and asynchronous communication systems. The work depends crucially on the interdisciplinary framework and the direct involvement of content expertise from the disciplines represented by the investigators. For example, the human transportation network is designed to resemble the coordinated delivery of nectar through a beehive, but with options for varying the number of different materials transported, the size of arena, the flow rates of the materials, and so on.

The investigators are exploring whether a comprehensive computational framework can be discovered to understand, predict and prevent the collapse of very different types of communities (bees and human networks). The research results are expected to provide insight into how to manipulate the behavior of a complex system, for example to address societal challenges associated with the collapse of pollinating bee colonies or the destructive behavior that is often associated with phases of social transition in groups of humans.