Human behavior is commonly understood as emerging from a struggle between will and habit, i.e., between “intentional” processes driven by the current goal and “automatic” processes driven by available stimuli. This scenario suggests that it is mainly the goal-related processes that render behavior adaptive. Based on a novel theoretical framework (the Metacontrol State Model, combined with the Theory of Event Coding) that is motivated by recent behavioral and neuroscientific observations, we suggest an alternative view and argue that people can control the relative contributions of goal-driven and stimulus-driven processes to decision-making and action selection. In particular, people regulate the interaction between these processes by determining the ratio between (goal) persistence and flexibility, depending on task, situation, and personal experience—a process that we refer to as “metacontrol”.

 The project aims to identify and trace individual “metacontrol policies” (biases towards persistence or flexibility) and task- and condition-specific changes therein by means of behavioral, computational, and neuroscientific techniques, and by using virtual-reality methods. We will study, account for, and try predicting individual differences in the choice and implementation of such policies, identify and explain the cognitive and social consequences of adopting a particular policy, and investigate whether and how people can adopt metacontrol policies from others—either intentionally or automatically. We will also study whether and to what degree people use situational cues to automatize the implementation of suitable policies, and whether often-used, highly practiced policies can become chronified and turn into a trait-like processing style, as suggested by cultural studies.

 Methods: Robotics, Functional MRI, Computational Models, EEG Analysis, Virtual Reality, Cognitive Training, Behavioral Experiment, 7t, high-field fMRI, model-based fMRI

 Date: 1 December 2016 – 1 December 2021