Our purpose is to understand better human category representation via investigating category learning strategies, the development of early lexical-semantic networks, and event memory processing. Within this comprehensive framework, we plan smaller sub-projects according to the local research infrastructure and societal needs. Understanding categorization behavior helps us predict learning disabilities at an early stage of development, revealing systematic errors and strategies behind generalization and lets us develop better visual learning aids in the future.
Ambition: Human conceptual system is impossible to model completely. However, we can understand better categorization behavior, the acquisition of the early concepts, and systematic errors in event memory.