Whenever we play chess, plan a vacation, or cook a meal, we are using past experience to inform our decisions. Our research group seeks to understand how the brain can generate such flexible behavior by extracting and reusing information from memory to predict future outcomes. To do so, we conduct behavioral and neuroimaging studies and employ machine learning algorithms and computational models of reinforcement learning. Specifically, these are our key research areas:

Orbitofrontal cortex and the representation of task states

Predictions derived from reinforcement learning theory regarding prediction error and value signals have found much support in neuroscientific data. But what about the elusive state representations that are necessary for reinforcement learning algorithms? Is there a neural counterpart of these states? Our lab investigates the nature and potential neural basis of these task state representations, see for instance Schuck et al., 2016, Neuron or Schuck et al., 2017.

The role of hippocampal replay in decision making

Fast sequences of neural activation patterns in the hippocampus have been linked to the 'replay' of previous spatial experiences. We investigate how such fast neural events can be detected with fMRI in humans and what their role is in decision making and creating a cognitive map of the current task, see Schuck & Niv, 2019, Science and Wittkuhn & Schuck, 2020, bioRxiv.

Influence of task irrelevant information on decision making

When we make a decision, we really should only focus on the few aspects that seem relevant. But we often fail to do that, for better or worse (getting distracted vs. thinking outside the box). Our lab therefore investigates the effects of task irrelevant information in decision making, see Schuck et al., 2015, Neuron.

How aging, genes and disease affect (spatial) memory & learning

Age and DNA have widespread effects on our brain as well as our cognitive abilities. Our lab investigates specific links between changes in neural representations associated with age and genotype, and cognitive changes. For instance, in Schuck et al., 2015, NeuroImage, we have investigated how well spatial boundaries are represented in the brain and how spatial navigation is related to this neural function. In Koch et al., 2020, Neuropsychologia we compared older and younger adults to see how precise the aging brain can processes walking direction. In other papers we have investigated how genetic factors and disease influence our memory, see Schuck et al., 2018, Neurobiology of Aging and Thurm et al., 2016, Neurobiology of Aging.