Cognitive & Computational Neuroscience

Investigating the Neural Networks Shaping Cognition in Health and Disease

What is Cognitive and Computational Neuroscience?

Cognition is broadly defined to include a wide spectrum of faculties that we all take for granted as part of our mental toolkit: learning, decision-making, attention, reasoning, memory, language, and motor control... to name a few. 

Appropriately, cognitive neuroscience is the subfield of neurobiology charged with elucidating the neurobiological underpinnings of these faculties. 

Computational Neuroscience, on the other hand, is a subfield of neurobiology in which mathematical tools are used to develop and test theories of brain function. This commonly incorporates diverse approaches from computer science, physics, psychology, engineering, and mathematics, in order to understand how the nervous system performs its computations, and why. 

Both cognitive and computational neurosciences constitute a major research theme here at DRCMR. Our long-term vision is to pioneer new methodologies for bridging between computational modelling of cognition and neuroimaging, and to use this to understand brain function in health and disease. The key among these methodological efforts is to develop advanced methods for fitting computational models in parallel to individual neural elements - an approach that will allow us to change the way we ask questions about how computational variables are encoded and enacted in the brain. 

Decision-making and Reward

We have several groups of researchers pursuing research along a diversity of frontiers. For example, there are decision neuroscientists, otherwise known as neuroeconomists, who are attempting to dissect the neural architectures underlying risk-sensitive choice, in dynamic sequential gambling environments, foraging games, and in games involving large and real financial losses. Such games are formally modelled with econometric and computational models, the predictions of which are incorporated into the regression models utilised for EEG and fMRI. With the encoding of computational variables mapped in healthy brains, these studies are being extended to clinical populations on and off neuromodulating medication, to infer the impact of pathologies on these processes. 

The Reward and Homeostasis group seeks to build fundamental theories of reward value that are grounded in our physiology and evolutionary history. They employ mathematical models of how rewards should be valued with respect to homeostatic states of the body, to predict how the brain’s motivational systems should interface with reward systems. Future work on this will be focusing on triangulating between fMRI, modelling, and optogenetic work across species. 


Sensory and Motor Neuroscience

We have a group of sensory neuroscientists engaged in research on the neural basis of audition (hearing), using detailed anatomical functional mapping procedures and multivariate computational methods. 

Additionally, the Control of Movement group is a large community of researchers, investigating how the brain engages in motoric control of its body, integrating sensory information, skill-learning and optimising motor action. Their emphasis is on mapping and computationally modelling motor control mechanisms with EEG and fMRI, on modulating these mechanisms with stimulation methods such as direct current stimulation and transcranial stimulation.

Selected Publications

Michel Lange, V., Messerschmidt, M., Harder, P., Siebner, H. R. & Boye, K. Planning and production of grammatical and lexical verbs in multi-word messages. P L o S One. 12, 11 2017.

*Meder, D., *Haagensen, B., Hulme, O.J., Morville, T.M., Gelskov, S., Herz, D., Diomsina, B., Christensen, M., Madsen, K.M., Siebner, H.R., Tuning the Brake While Raising the Stake: Network Dynamics During Sequential Decision-Making Journal of Neuroscience

Herz, D.M., Christensen, M.S., Bruggemann, N., Hulme, O. J., Ridderinkhof, R.K., Madsen, K.H., Siebner, H.R.,(2014) Motivational tuning of fronto-subthalamic connectivity facilitates control of action impulses. Journal of Neuroscience

Meder, D., Madsen, K.M., Hulme, O.J., Siebner, H.R., Chasing probabilities – Signalling negative and positive prediction errors across domains. Neuroimage

Hulme,O.J., Skov, M., Chadwick M., Siebner, H.R., Ramsøy, T.Z.(2014) Sparse encoding of Associative Density in the Hippocampus Neuroimage

Research Area Members

Oliver Hulme


David Meder

Kristoffer Hougaard Madsen

Show all group members (11)