Computational Decision Making and Learning Group

Whether playing chess or deciding between ice cream flavors, a main component of decision making is to try to foresee the consequences of our choices. This requires us to learn from the past, and to extrapolate our experiences into the future. How does the brain solve this enormous task? Our group investigates the way the 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 memory and learning. Using computational modelling, behavioural analysis and magnetic resonance imaging, we have begun to unravel this interplay of learning and decision processes in the brain. We have shown, for instance, that when humans make choices, the activity patterns in orbitofrontal cortex are tailored to efficiently learn decision relevant aspects of the environment. We have also found that during periods of resting after a task, the hippocampus sequentially ‘replays’ those same relevant aspects of the environment – presumably in order to strengthen the learning of the structure of the decision environment. Using similar techniques, we have also investigated how ageing or anxiety affects such task relevant neural representations during navigation.

Research Foci

  • Representation learning
  • Replay
  • Computational Modelling
  • Ageing
    Detailed information about the lab can be found here.


The Computational Decision Making and Learning Group is funded by:

Key References

Schuck, N. W., & Niv, Y. (2019). Sequential replay of nonspatial task states in the human hippocampus. Science, 364(6447):eaaw5181. doi:10.1126/science.aaw5181

Kaplan*, R., Schuck*, N. W., Doeller, C. F. (2017).The role of mental maps in decision-making. Trends in Neurosciences, 40 (5), 256-259.
(*shared first authorship)

Schuck, N.W., Cai, M.B., Wilson, R.C. & Niv, Y. (2016). Human orbitofrontal cortex represents a cognitive map of state space. Neuron, 91 (6), 1402-1412.

Schuck, N.W., Gaschler, R., Wenke, D., Heinzle, J., Haynes, J.-D. & Reverberi, C. (2015). Medial Prefrontal Cortex Predicts Internally Driven Strategy Shifts. Neuron, 86(1), 331-340.

Eppinger, B., Schuck, N.W., Nystrom, L.E., Cohen, J.D. (2013). Reduced striatal responses to reward prediction errors in older compared with younger adults. Journal of Neuroscience, 33 (24), 9905-9912.

Schuck, N.W., Doeller, C.F., Frensch, P.A., Polk, T.A., Lindenberger, U. & Li, S.-C. (2015). Human Aging Alters Neural Computation and Representations During Spatial Navigation. NeuroImage, 117, 141-150.

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