A Multimodal Approach to Investigate the Cognitive Neuroscience of Decision Making

Decision making can be defined as the process of choosing a preferred option or course of action from a set of alternatives. In order to understand how humans make decisions and even predict decision-making behavior, academics in various fields such as psychology and economics, have developed formal models of decision-making behavior. These models have been inspired by behavioral data and the computational demands required of a decision making task. For example, sequential sampling models have been developed to account for behavioral data, and reinforcement learning models for repeated choice tasks have been developed to account for the computational demands of a task.

Importantly, cognitive functions such as decision making, cannot be completely understood on the basis of mathematical models and behavioral data alone; consideration of the neuronal processes underlying decision making is crucial. Thus, we are currently investigating how mental (cognitive) and neuronal processes map onto each other. A central goal of our group is to explicitly link brain function and behavior using formal models of decision-making behavior.

In pursuit of this goal, we’re investigating decision making in three different domains:

  1. Perceptual Decision Making - At the base of a number of different decisions we face in everyday life stands perceptual decision making. This is the process of translating sensory input into a chosen motor output.
  2. Reward-Based Decision Making and Decision Making Under Risk - Many of our everyday decisions are influenced by the potential outcomes associated with our options. In other words, the costs and benefits of our options and the probability of the outcomes are considered when we perform reward-based decision making and decision making under risk, respectively.
  3. Decision Making in Social Contexts - We make decisions in the context of our surroundings, influenced by a multitude of factors such as the social information available to us. Decision making in social contexts relies not only on social information obtained and computed by perceptual and reward-related processes but also requires more complex cognitive and emotional processing.


In order to conduct the above research we employ an integrative, multimodal and methodological approach consisting of techniques ranging from cognitive modeling based on behavioral data to functional magnetic resonance imaging (fMRI) and magnetencephalographic (MEG) experiments.