Cognition is a summary term for all processes that serve our knowledge about the world. Learning theories and perception theories describe how knowledge is gathered, built up, and integrated with existing knowledge. Memory theories describe how this information is stored and retrieved, and theories of motor behavior, action, and language describe how this knowledge is utilized for guiding our behavior.
Since cognitive processes are not observable by themselves, statistical modeling is particularly useful for disentangling components of cognition that contribute to behavior. The stochastic modeling of behavioral outcomes as well as response time distributions has helped to make tremendous progress in understanding cognitive functioning in recent decades. Examples are models for disentangling storage, maintenance, and retrieval in memory or evidence accumulation models for explaining response times and accuracy in decision making.
In line with the research foci of many members of the SMiP group we outline several proposals for developing new models of cognitive processes involved in recognition memory, recall from episodic memory, decision strategy choice, advice seeking for decisions, attention, and implicit association tasks. Each of these proposals provides a framework for several theses in principle. In addition, we propose possible applications of existing MPT models, diffusion models, and (generalized) hierarchical models to research questions in the fields of cognitive aging, sleep effects on episodic memory, decision making, subliminal priming, task switching, evaluative conditioning, and moral judgment.
These project proposals are exemplary, and further developments as well as own modeling ideas are welcome.