High-level cognition in action under naturalistic settings
In real-world contexts, we do not only passively receive information but also actively explore the environment by interacting with biological entities and social agents and make hierarchical strategic planning to achieve behavioral goals and adaptively update them online. To examine such high-level cognitive processes linked to ecological brain functions, we are currently developing a range of interactive Minecraft-based 3D video game tasks in which subjects engage in active social interactions, strategic planning through hierarchically organized subgoals, and adaptive online strategy updates while navigating the virtual world. By creating interactive tasks in naturalistic environment, we aim to examine cognition and behaviors that occur beyond the laboratory settings and deepen our understanding of complex high-level cognitive functions and adaptive behaviors in a complex, multidimensional world.
Spatial foraging
Foraging, a successive action of seeking reward that yields the greatest long-term benefit, involves a complex cognitive process that can be found in creatures as diverse as insects and primates. Building an efficient foraging strategy inside a naturalistic environment requires navigation, memory and successive economic decision making. Yet, it is not well known how humans explore and exploit spatial regularity of rewards distributed inside a naturalistic 3D world for their optimal foraging. Using fMRI and Minecraft-based interactive games, we aim to seek how human transform external value into a foraging action under given environmental states and behavioral goals.
Hierarchical action planning
How do humans plan and perform hierarchically organized strategic actions to solve complex tasks? In a multi-dimensional environment, a single action may not directly lead to the final goal and reward. To achieve the final goal, it often needs to be decomposed into sub-goals and further into primitive actions. It is not well known how humans can substitute complex goals and actions with a less-complex structure and link them to an intrinsic reward system. Using fMRI and Minecraft-based interactive games, we aim to study high-level cognitive processes that are required to plan and perform multi-stage, hierarchical actions to achieve intended goals in a complex environment.
Social cognition
In everyday life, humans continuously learn complex relationships between objects (e.g., object network) or agents (e.g., social network). People can represent such relational knowledge as a form of “cognitive map” and infer the meaning of novel items using this map structure. Cognitive maps have been studied in many knowledge domains, such as spatial location, object identity, abstract knowledge, and social relationship. Using fMRI and Minecraft-based interactive games, we focus on how people learn and construct complex relational knowledge structures and what commonalities and differences exist in neural representations of social and non-social information.