Reward & Homeostasis

The reward and homeostasis group aims to address some simple, but surprisingly difficult problems. What are the evolutionary origins of reward value? What role does reward valuation play in our homeostasis? How are homeostatic states, motivations and reward values computed by the brain? How does this shape our decision-making? And what function does this all ultimately serve? 

The framework we work from makes one key assumption from which several other theoretical predictions can be made. The principal role of reward valuation is to shape behavior toward optimizing homeostatic states of the body, which in turn optimizes long-run survival. The work we do is thus partly theoretical and partly empirical.

We seek to derive theories of reward that are grounded on fundamental principles of homeostatic dynamics and their evolution. We draw on concepts, tools, and results, from a diversity of fields, including economics, ecology, physiology, and computational biology. And we use these to build computational models of reward and homeostasis. One major result of this approach is the discovery that economic phenomena can be derived from known statistical features of homeostasis, thus providing a unifying and evolutionarily grounded theory of simple homeostatic decision making.

From these models we can derive falsifiable predictions for behavioral, physiological, and neural responses. In human subjects, we triangulate between computational modelling, fMRI, physiological monitoring, economic & ethological behavior. 


We have received DKK 5.36 million from ARLA for “The Omnibus Satiety Metric” as part of a larger consortium between Arhus University, Hvidovre Hospital, and University of Copenhagen. The project is to study the neural mechanisms of satiety, focusing on how interoceptive and oro-sensory prediction errors encoded within hypothalamus are predictive of next-meal energy consumption. The technique is to be finessed for use as an industrial scale metric for satiety optimisation in food design. 

Online Lectures & Resources

Here are some online resources that are either useful, relevant, or somehow cool:

Learning math & statistics - for basics I would recommend Kahn academy; BetterExplained is very good for intuition as is SeeingTheory for statistics; Wolfram Alpha is excellent for visualisation, derivations (pro only) and its databases.

Online academic lectures – There are many excellent online lectures sites, here a just a few; TheEdge is good for conversation-based talks and interviews; generally Coursera is excellent for online courses, as are some of the university specific sites Stanford, Yale, MIT, Harvard, Sante Fe Institute; and other sites such as TalksAtGoogle.

Neuroimaging lectures - An obvious starting point for neuroimaging lectures are these on SPM from UCL. Until certain copyright issues are fixed, our own internal lecture videos are available only on the internal DRCMR wiki. Also look on Coursera.

Book recommendations

Here are some of the labs members favorite books and why:

Foundations of Neuroeconomic Analysis – the first, hopefully not the last, great book of neuroeconomics. A brave polemic on the consilience between psychology, economics and neuroscience in providing a compact explanatory account of decision making.

The Master and His Emissary – a heroic, mind-blowingly erudite synthesis of a brain-lateralisation theory, and its projection onto the history of western civilisation. The best case yet for the fundamental powers of bridging art, science, philosophy and humanities to answer the deepest of human questions.

Principles of Neural Design – In a discipline bogged down by ever more precise descriptions, this book takes the approach of how the brain should work, and by which principles and constraints. It offers a powerful explanatory account of what problems the brain faces, and how the constraints of these problems provide important insights into the biological design and function of neural systems.

Darwin’s Dangerous Idea – Daniel Dennett at his very best. The most brilliantly argued case for the reach and scope of evolutionary theory.

Understanding Psychology as a Science – Better than any statistics or psychology textbook. In fact it is a treatise on philosophy of science, providing a very accessible introduction to Popper, and his relevance to modern statistics, and experimental design, both in psychology but also far beyond.

Logic of Scientific Discovery – Outstanding philosophy of science, still as relevant today as its ever been. Not an easy read but worth the effort.

The Mating Mind – What Dennett does for survivalist perspectives on evolutionary theory, Miller does for sexual selection. Engaging, scholarly, challenging. Will profoundly change your perspective on evolution.

The Vital Question – A brilliant theory of life, the first I have read that gives me confidence we might one day crack the problem. It places energy as the central organising principle of the diversity and complexity of life.

Clear and Simple, As the Truth – The best book I have read about writing style. It eschews the mundanity of style as being a set of rules, and places it as a philosophical stance. They champion the style of classic style, and argue convincingly for its merits in many domains, and how to write it. The best way to improve your scientific writing.

Selected Publications

Hulme, O.J., Webb, E.J., Webb, Sebald, A. (In press). An Introduction to Physiological Economics. Handbook of Research Methods and Applications in Experimental Economics, Edward Elgar Publishing.

Hulme, O.J., Kvitsiani, D. (In press). Extending Models of How Foraging Works: Uncertainty, Controllability, and Survivability. Behavioral and Brain Sciences. Commentary on Anselme & Gunturkun

Hallsson, B.G., Siebner H.R., Hulme O.J. (2018). Fairness, fast and slow: A review of dual process models of fairness. Neuroscience and Biobehavioral Reviews. Jun;89:49-60. doi: 10.1016/j.neubiorev.2018.02.016.

Christensen, B.J., Schmidt J.B., Nielsen, M.S, Tækkerd, L., Holm, L., Lunn, S., Brediee, W.L.P., Ritz, C., Holst J.J., Hansenf, T., Hilbert A., le Roux, C.W., Hulme, O.J., Siebner, H.R., Morville, T., Naver, L., Floyd, A.K., Sjödin, A. (2018)..Patient profiling for success after weight loss surgery: An interdisciplinary study protocol. Contemporary Clinical Trials Communications. Feb 17;10:121-130. doi: 10.1016/j.conctc.2018.02.002.

Larsen, K.M., Mørup, M.,  Birknow, M.R., Fischer, E., Hulme, O.J.,  Vangkilde, A., Schmock, H., Baaré, W.F., Didriksen M., Olsen, L., Werge, T., Siebner, H.R., Garrido M.I. (2018). Altered auditory processing and top-down connectivity in 22q11.2 Deletion Syndrome..Schizophrenia Research. Jan 30. pii: S0920-9964(18)30048-3. doi: 10.1016/j.schres.2018.01.026.

Meder, D., Kolling, N., Verhagen, L., Wittmann, M. K., Scholl, J., Madsen, K. H., Hulme, O. J., Behrens, T. E. J. & Rushworth, M. F. S.
Simultaneous Representation of a Spectrum of Dynamically Changing Value Estimates during Decision Making.

Meder, D., Kolling, N., Verhagen, L., Wittmann, M. K., Madsen, K. H., Hulme, O. J., Behrens, T. E. J., Siebner, H. R. & Rushworth, M. F.
Simultaneous Representation of a Spectrum of Dynamically Changing Value Estimates.

Meder, D., Kolling, N., Verhagen, L., Wittmann, M. K., Scholl, J., Madsen, K. H., Hulme, O. J., Behrens, T. E. J. & Rushworth, M. F. S.
Simultaneous representation of a spectrum of dynamically changing value estimates during decision making.
Nature Communications. 8, 1942 2017.

Hulme,O.J, & Madsen, K.M. (2016) Reward and the Predictive Brain, in “ The Predictive Brain”, Hjerne Forum

 *Meder, D., *Haagensen, B., Hulme, O.J., Morville, T.M., Gelskov, S., Herz, D., Diomsina, B., Christensen, M., Madsen, K.M., Siebner, H.R., (2016) Tuning the Brake While Raising the Stake: Network Dynamics During Sequential Decision-Making Journal of Neuroscience

Meder, D., Madsen, K.M., Hulme, O.J., Siebner, H.R., (2016) Chasing Probabilities - Signaling negative and positive prediction errors across domains– Neuroimage

Schmock H, Vangkilde A, Larsen KM, Fischer E, Birknow MR, Jepsen JR, Olesen C, Skovby F, Plessen KJ, Mørup M, Hulme O, Baaré WF, Didriksen M, Siebner HR, Werge T, Olsen L. (2015) The Danish 22q11 research initiative. BMC Psychiatry

Laursen, H.R., Siebner, H.R, Haren, T., Madsen, K., Grønlund, R., Hulme, O.J., Henningsson, S., (2014) Variation in the OXTR gene is associated with behavioral and neural correlates of empathic accuracy. Frontiers in Behavioural Neuroscience

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

Chumbley, Köchli, Hulme, Stan Van Uum, Evan Russel, Koren, Engelman, Pizzagalli & Fehr (2014) Stress and reward: long term cortisol exposure predicts the strength of sexual preference Physiology and Behavior

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

Herz, D.M., Hulme, O.J., Florin, E., Christensen, M.S., Timmermann, L., Siebner, H.R., (2013) Levodopa reinstates connectivity from prefrontal to premotor cortex during externally paced movement in Parkinson's disease. Neuroimage

Van der Vegt, J.P.M., Hulme, O.J., Zittel, S., Madsen, K.H., Weiss, M.M., Buhmann, C., Bloem, B.R., Münchau, A., Siebner, H.R., (2013) Attenuated neural response to gamble outcomes in drug-naive patients with Parkinson’s Disease. Brain

Bach, D., Hulme, O., Penny, W., and Dolan, R. (2011). The Known Unknowns: Neural Representation of Second-order Uncertainty and Ambiguity. Journal of Neuroscience.

Hulme, O.J., Whiteley, L.E., and Shipp, S. (2010). Spatially Distributed Encoding of Covert Attentional Shifts in Human Thalamus. Journal of Neurophysiology.

Fleming, S., Whiteley, L.E., Hulme, O., Sahani, S., and Dolan, R., (2010). Effects of Category-specific Costs on Neural Systems for Perceptual Decision-making. Journal of Neurophysiology.

Kirk, U., Hulme, O.J., Skov, M., and Christensen, M.S. (2009). Modulation of aesthetic value by semantic context: an fMRI study.. Neuroimage.

Hulme, O.J., Friston, K. and Zeki, S. (2009). Neural Correlates of Stimulus Reportability. Journal of Cognitive Neuroscience.

Zeki, S., Hulme, O.J., Roulston, B., and Atiyah, M. (2008). The encoding of temporally irregular and regular visual patterns in the human brain.. Plos One.

Friston, K., Chu, C., Mourão-Miranda, J., Hulme, O.J., Rees, G., Penny, W., and Ashburner, J. (2008). Bayesian Decoding of Brain Images. Neuroimage.

Hulme, O.J., and Whiteley, L. (2007). The “Mesh” as Evidence - Model Comparison and Alternative Interpretations of Feedback. Behavioural and Brain Sciences.

Hulme, O.J. and Zeki, S. (2006). The Sightless View: Neural Correlates of Occluded Objects. Cerebral Cortex.


Group Members

Oliver Hulme

Group Leader

David Meder

Barbara Vad Andersen

Benjamin Skjold Frederiksen

External Collaborators

 Boris Gutkin

ENS, Paris

Denis Burdakov

Crick Institute, UK

Karl Friston

University College London, UK

Edward Webb

University of Leeds, UK

Christoffer Clemmensen

Copenhagen University, DK

Alexander Sebald

Copenhagen University, DK

Sten Madsbad

Copenhagen University, DK

Anders Sjodin

Copenhagen University, DK

Derek Byrne

Aarhus University, DK

Duda Kvitsiani

Aarhus University, DK

Barbara Andersen

Aarhus University, DK