Rafal Bogacz obtained an interdisciplinary training during his doctoral and postdoctoral studies. He conducted his PhD at the University of Bristol jointly in the Departments of Computer Science and Anatomy, and next he worked as a postdoctoral researcher at Princeton University jointly in Departments of Applied Mathematics and Psychology. In 2004 he came back to Bristol where he worked as a lecturer and then a reader. He moved to University of Oxford in 2013.
Awards Training and Qualifications
1998 – MEng, Wroclaw University of Technology, Poland
2001 – PhD, University of Bristol
- Action Selection Modelling Group Research Group
- Senior Research Fellow in Computational Neuroscience at the Nuffield Department of Clinical Neurosciences
- Lecturer in Quantitative Methods at St John's College
My research is in the area of computational neuroscience, which uses mathematical models to understand how computations in neural circuits give rise to human and animal behaviour. My work focuses on the computational models of brain circuits underlying action selection and decision making. These circuits include a set of subcortical nuclei known as the basal ganglia, which has been intensively studied because it is affected by Parkinson’s disease. Although many questions remain open, the anatomy and the neural activity in the basal ganglia has been characterized to the extent that allows formulating a formal mathematical theory describing how it selects actions in the healthy brain, and how the pathological patterns of activity observed in Parkinson’s disease are generated.
My research concerns models of basal ganglia in both health and disease. I investigate how the cortico-basal-ganglia-thalamic network selects actions on the basis of noisy sensory inputs, and whether this network can perform statistically optimal action selection. I also study in which part of this network and under what conditions, the excessive oscillations in activity are generated in Parkinson’s disease.
Sources of funding
Wellcome Trust 2011-2015
Key Publications5 False False
Integration of reinforcement learning and optimal decision-making theories of the basal ganglia.
Bogacz R. and Larsen T., (2011), Neural Comput, 23, 817 - 851
Conditions for the generation of beta oscillations in the subthalamic nucleus-globus pallidus network.
Holgado AJ. et al, (2010), J Neurosci, 30, 12340 - 12352
The neural basis of the speed-accuracy tradeoff.
Bogacz R. et al, (2010), Trends Neurosci, 33, 10 - 16
Neural Correlates of Decision Thresholds in the Human Subthalamic Nucleus.
Herz DM. et al, (2016), Curr Biol, 26, 916 - 920
Action initiation shapes mesolimbic dopamine encoding of future rewards.
Syed EC. et al, (2016), Nat Neurosci, 19, 34 - 36
Computational Models Describing Possible Mechanisms for Generation of Excessive Beta Oscillations in Parkinson's Disease.
Pavlides A. et al, (2015), PLoS Comput Biol, 11
The subthalamic nucleus during decision-making with multiple alternatives.
Keuken MC. et al, (2015), Hum Brain Mapp, 36, 4041 - 4052
Dopamine and Consolidation of Episodic Memory: Timing is Everything.
Grogan J. et al, (2015), J Cogn Neurosci, 27, 2035 - 2050