MPRG NeuroCode | Neural and Computational Basis of Learning, Memory and Decision Making

Every day humans are confronted with a variety of decisions, from selecting the type of ice cream to selecting the place of residence. Whether these decisions are trivial or complex, we usually try to foresee the influence our choices could have on our lives. How does the brain solve this enormous task? The overarching goal of the Max Planck Research Group NeuroCode – Neural and Computational Basis of Learning, Memory and Decision Making – is to address this question.

The group investigates the way the human brain supports decision making on the basis of previous experience, focusing on the impact of our memories on our decisions, but also on the impact of our decisions on learning and memory. In experiments conducted by the research group, participants will therefore be asked to come to decisions on the basis of their previous experience.

These experiments involve recording participants’ behavior and using magnetic resonance imaging (MRI), which allows the researchers to measure brain activity while a participant is making a decision. The interplay of learning and decision processes in the brain is of particular interest to the researchers. To understand the meaning of the observed brain activation patterns, they use methods from statistics and artificial intelligence that model the data.

In his previous research Nicolas Schuck was able to show that the interactions between learning, memory, and decision processes involve specific signals in a part of the brain called the orbitofrontal cortex. Building up on this finding, his group will focus on the question of what these signals can tell us about the brain’s algorithms during decision making based on previous experience.

The group began its work in September 2017.

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