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Computational Neuroscience of Reward

Our primary research interest concerns the brain’s reward system. Put simply: how does it work, and why? We explore computational theories that constrain how it should work and then test the predictions of these theories against behavioural, physiological, and neuroimaging data.

Computational Neuroscience of Reward Figure 1 

The figure above gives an example of how we use behavioural experiments to test theories of decision-making, and how this is combined with neuroimaging data which can be used to test the same theories, generating anatomical maps of hidden computational variables. This example here is for a project entitled "The ergodicity experiment".

There are two strands to the group’s research agenda:

The first strand asks how do reward computations shape behaviour to regulate our physiology.  Specifically, how are the values of primary rewards such as food and water configured by homeostatic states, and how should they be configured according to the constraints of survival. We are particularly interested in how models of this sort could provide a unified explanatory account of basic behavioural phenomena such as risk preferences, loss aversion, and temporal discounting. This work involves collaboration with endocrinologists, metabolic scientists, food scientists, and computational neuroscientists.

The second strand draws on a concept in physics known as ergodicity, and is the basis of the group’s connection to the London Mathematical Laboratory. Ergodicity here refers to thinking carefully about the types of averages that are relevant to behaviour, with a particular emphasis onhow decisions unfold over time. We are interested in the constraints that ergodicity imposes on decision-making, and whether such considerations can also offer a unified account of a number of disparate behavioral phenomena. We recently received funding from the Novo Nordisk Fonden to work together on experiments that expose subjects to different dynamical settings, testing how these dynamics modulate reward computations, and risk-taking behavior.

The group is committed to open science, and all future experiments will pre-register and release all code, materials, and data wherever possible. We also teach courses on the methods most central to our research, namely Bayesian statistics, as well as Bayesian modelling of cognition and the brain.

STUDENTS

We are always interested to hear from students with a quantitative training – physics, mathematics, computational biology, computational neuroscience, and related fields. If you are interested to work in the group please email  with a brief explanation of your interests and situation. We recommend reading the work of the group and thinking carefully about what specifically you would like to do.

NEWS

2022: Ollie Hulme will be giving a talk at the Ergodicity Economics conference in January 2022, on “Ergodicity and the brain” :

2021: Former group member and close collaborator David Meder won a prestigous Saperre Aude fellowship to work on computational models of reward and Parkinson’s disease.

2021: Ollie Hulme will be giving a lecture at this year’s Nudgestock – summer 2021 https://www.nudgestock.co.uk/

2021: We recently received an Interdisciplinary Exploratory Synergy grant from the Novo Nordisk foundation, total 5million Kr. The project involves a collaboration between the reward group at DRCMR, and the London Mathematical Laboratory.

2020: Ollie Hulme and David Meder received honorary fellowships at the Max-Planck-UCL centre for Computational Psychiatry and Aging.

2020-2021: Ollie Hulme was made an external fellow at the London Mathematical Laboratory.

VIDEO TALKS & SOCIAL MEDIA

Recent talks by the group are available at this Youtube channel:

https://www.youtube.com/channel/UCEKr1X0owzn7zOjhPnt_OZQ

Here is an accessible and short introduction to our work on ergodicity:

https://www.youtube.com/embed/XoCogIcEhi0

Occasionally research updates and announcements will be posted on twitter: @hulme_oliver

RELATED WORKS

Recent papers, blogposts, media, replications, critiques, and other related links discussing our research:

Best of nudgestock 2021: https://youtu.be/zaSz6mZe9lA

Ole Peters in Nature Physics 2019 https://www.nature.com/articles/s41567-019-0732-0

Reply to Peters by Doctor, Wakker & Wang 2020 https://www.nature.com/articles/s41567-020-01108-9

Adam Goldstein 2020: https://researchers.one/articles/20.02.00002

Adam Goldstein 2020: //medium.com/@aa_goldstein/multi-period-expected-utility-theory-predicts-zero-risk-aversion-in-copenhagen-experiment-same-as-60637aa28761>">https://medium.com/@aa_goldstein/multi-period-expected-utility-theory-predicts-zero-risk-aversion-in-copenhagen-experiment-same-as-60637aa28761

Jason Collins: https://jasoncollins.blog/risk-and-loss-aversion-in-ergodicity-economics/

Brandon Kochkodin: https://www.bloomberg.com/news/articles/2020-12-11/everything-we-ve-learned-about-modern-economic-theory-is-wrong

Selected Publications

Recent publications & Pre-prints 

Lopez-Yepez JS, Martin J, Hulme OJ, Kvitsiani D. (2021)
A normative account of choice history effects in mice and humans
PLoS Computational Biology

Meder D, Rabe F, Morville T, Madsen KH, Koudahl MT, Dolan RJ, Siebner HR, Hulme OJ. (2021)
Ergodicity-breaking reveals time optimal economic behavior in humans
PLoS Computational Biology

Morville T, Friston KJ, Burdakov D, Siebner HR, Hulme OJ. (Pre-print)
The Homeostatic Logic of Reward
bioRxiv, doi.org/10.1101/242974.

Morville T, Madsen K, Siebner HR, Hulme OJ. (2021)
Reward signaling in brainstem nuclei under glycemic flux
PloS One

Hulme, OJ, Wagenmakers EJ, Damkier P, Madelung CF, Siebner HR, Helweg-Larsen J, Gronau Q, Benfield TL, Madsen KH. (2021) A Bayesian reanalysis of the effects of hydroxychloroquine and azithromycin on viral carriage in patients with COVID-19.
PloS One. doi.org/10.1371/journal.pone.0245048

Friston KJ, Parr T, Zeidman P, Razi A, Flandin G, Daunizau J, Hulme OJ, Billig AJ., Litvak V, Price CJ., Moran RJ., Costello A, Pillay D, Lambert C. (2020)
Effective immunity and second waves: a dynamic causal modelling study
Wellcome Open Res2020, 5:204 (doi.org/10.12688/wellcomeopenres.16253.2)

van der Vegt JPM, Hulme OJ, Madsen KH, Buhmann C, Bloem BR, Münchau A, Helmich RC, Siebner HR (2020)
Dopamine agonist treatment increases sensitivity to gamble outcomes in the hippocampus in de novo Parkinson’s disease
NeuroImage Clinical

Faranda D, Castillo IP, Hulme OJ, Jezequel A, Lamb J, Sato Y, Thompson E, (2020)                                                                         
Asymptotic estimates of SARS-CoV-2 infection counts and their sensitivity to stochastic perturbation
Chaos. 2020;30(5):051107. doi:10.1063/5.0008834

Friston KJ, Parr T, Zeidman P, Razi A, Flandin G, Daunizau J, Hulme OJ, Billig AJ, Litvak V, Price CJ, Moran RJ., Lambert C. (2020)
Second waves, social distancing, and the spread of COVID-19 across America.
Wellcome Open Res 2020, 5:103 (doi.org/10.12688/wellcomeopenres.15986.1)

Friston KJ, Parr T, Zeidman P, Razi A, Flandin G, Daunizau J, Hulme OJ, Billig AJ, Litvak V, Price CJ, Moran RJ, Lambert C. (2020)
Dynamic causal modelling of COVID-19.
Wellcome Open Res 2020, 5:89

Friston KJ, Parr T, Zeidman P, Razi A, Flandin G, Daunizau J, Hulme OJ, Billig AJ., Litvak V, Price CJ., Moran RJ., Costello A, Pillay D, Lambert C. (2020)
Testing and tracking in the UK: A dynamic causal modelling study
Wellcome Open Research 5 (144), 144  

Hulme OJ, Morville T, Gutkin B. (2019)
Neurocomputational Theories of Homeostatic Control
Physics of Life Reviews, Jul 19. pii: S1571-0645(19)30100-9. doi: 10.1016/j.plrev.2019.07.005  

Hulme OJ, Webb EJ, Sebald A. (2019)
An Introduction to Physiological Economics
Handbook of Research Methods and Applications in Experimental Economics, Edward Elgar Publishing. 

Hulme OJ, Kvitsiani D. (2019)
Extending Models of How Foraging Works: Uncertainty, Controllability, and Survivability
Behavioral and Brain Sciences 2019 Jan;42:e43. doi: 10.1017/S0140525X18002017

Hallsson BG, Siebner HR, Hulme OJ. (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 BJ, Schmidt JB, Nielsen MS, Tækkerd L, Holm L, Lunn S, Brediee WLP, Ritz C, Holst JJ, Hansen T, Hilbert A, le Roux CW, Hulme OJ, Siebner HR, Morville T, Naver L, Floyd, AK, 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 KM, Mørup M,  Birknow MR, Fischer E, Hulme OJ,  Vangkilde A, Schmock H, Baaré WF, Didriksen M, Olsen L, Werge T, Siebner HR, Garrido MI. (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 MK, Scholl J, Madsen KH, Hulme OJ, Behrens TEJ, Rushworth MFS. (2017)
Simultaneous representation of a spectrum of dynamically changing value estimates during decision making
Nature Communications. Dec 5;8(1):1942. doi: 10.1038/s41467-017-02169-w.

Friis-Olivarius M, Hulme OJ, Skov M, Ramsøy TZ, Siebner HR. (2017)
Imaging the Creative Unconscious: Reflexive Neural Responses to Objects in the Visual and Parahippocampal Region Predicts State and Trait Creativity
Scientific Reports. Oct 31;7(1):14420. doi: 10.1038/s41598-017-14729-7.

Group Members

Oliver Hulme

Group Leader

Barbara Vad Andersen

Benjamin Skjold Frederiksen

Simon Steinkamp

Show all group members (5)

External Collaborators

Prof. Derek Byrne


Dr. Ole Peters


Dr. Alex Adamou


Dr. Mark Kirstein


Dr. Yonatan Berman


Prof. Sten Madsbad


Assoc. Prof. Tobias Andersen


Assoc. Prof. Christoffer Clemmensen


Postdoc Claus Brandt


Prof. Duda Kvitsiani


Adam Goldstein