Bogacz Group
Our group uses computer simulations and mathematical analyses to understand learning, information processing and activity dynamics of brain networks. We use these models to investigate how neural circuits work in the healthy state, how their dynamics deteriorate in neurological disorders, and how their dynamics and information processing may be best restored by treatments. The research in our group is performed in close collaboration with experimental neuroscientists within the Unit, at the University of Oxford, and beyond.
Our work focuses on three central themes.
First, we investigate models of learning and information processing in the cerebral cortex. We seek a fundamental common principle describing computations in different areas of the cortex performing diverse functions. We are particularly interested in the predictive coding framework, which assumes that cortical areas build probabilistic models of the world and use this model to infer the most appropriate behaviour.
Second, we develop computational models of the neural circuits in basal ganglia that underlie action selection and decision making. Understanding these brain circuits is important, because they are affected by Parkinson’s disease. At the same time, developing a formal mathematical theory of basal ganglia function is feasible, as the anatomy and the neural activity in the basal ganglia has been characterized to a large extent.
Third, we use computational models to understand the effects of electrical deep-brain stimulation (DBS) on ongoing neural activity. The models we develop will be used to rapidly test candidate versions of closed-loop DBS in silico, and to identify how and when with respect to ongoing activity the stimulation should be provided to optimally restore neural activity normally present in healthy basal ganglia.
- predictive coding models of the cortex
- models of action selection in the basal ganglia
- models of deep-brain-stimulation
In the future, as the models describing action selection in healthy brain are further refined, we hope that the methodology developed through our research can pave the way towards closed-loop deep-brain-stimulation that will act as “computational prostheses”. Namely, they would use the recorded neural activity to calculate the function computed by the healthy basal ganglia, and force the activity in the circuit to the desired normal level. It will minimize the cognitive side-effects produced by the traditional stimulation. Such technology could be generalized to other brain regions, and other intervention types, and help to restore functions impaired by conditions and diseases affecting them.
We are committed to fostering an inclusive work environment that celebrates diversity and promotes equal opportunity within our group and the wider BNDU.
Mary Muers (far right) moderates an interactive session about training and career development opportunities.
Studentships
Project
Developing and testing brain stimulation patterns to promote half-harmonic entrainment for therapeutic benefit in Parkinson’s disease
Deep brain stimulation can markedly improve movement in people with Parkinson’s disease, yet we still do not fully understand how it works. Recent studies suggest that it may be particularly effective when gamma-frequency brain activity becomes synchronised to stimulation at half the stimulation frequency, a phenomenon known as half-harmonic entrainment. Understanding and improving deep brain stimulation therefore likely requires the ability to selectively control this synchronisation.
The overall goal of this PhD studentship is to develop new patterns of brain stimulation that promote gamma activity through half-harmonic entrainment, and to investigate whether doing so can improve movement in Parkinson’s disease. To achieve this, the project will combine mathematical modelling, experiments in healthy participants using non-invasive brain stimulation and electroencephalography, and a proof-of-concept study in people with Parkinson’s disease.
The project will take place in the Brain Network Dynamics Unit of the Nuffield Department of Clinical Neurosciences and in the Medical Research Council Centre of Research Excellence in Restorative Neural Dynamics (MRC CoRE RND). Students will benefit from the extensive interdisciplinary skills training and personalised career development opportunities available within the Unit and the MRC CoRE RND. Students will receive specialised training in their areas of project research (see below) as well as, for example, in the translation and commercialisation of research, best practice in Open Science, and how to effectively involve and engage patients and the public with research.
Spanning computational, experimental and clinical neuroscience, the studentship will provide advanced training in mathematical modelling of brain dynamics, the design and optimisation of brain stimulation, human electrophysiology and rigorous data analysis. You will gain hands-on experience with EEG and non-invasive brain stimulation in healthy participants. You will also have the opportunity to work with brain activity recordings and behavioural measurements from people with Parkinson’s disease undergoing deep brain stimulation. The project will additionally provide training in translating theoretical predictions into experiments in healthy participants and people with Parkinson’s disease.
This four-year Ph.D. (D.Phil.) studentship offers three years of full-time tuition fees at the Home rate, and four years of non-taxable stipend at the full-time UKRI rate (including any uplifts announced). Both Home students and International students are eligible to receive this funding package. Please see further details about MRC/UKRI studentships and UKRI guidance regarding Home and International eligibility. Successful offer-holders who have applied by the December deadline may also be considered for other University of Oxford scholarships.
Applications are invited from candidates who possess, or expect to receive a 1st class or upper 2nd class degree (or equivalent) in a related quantitative discipline, e.g. mathematics, physics, computer science, engineering. We also encourage applications from candidates with a degree in biological sciences or medicine who have experience with computational methods.
Previous experience in neuroscience research is highly desirable.
Candidates must contact the lead project supervisor before submitting an application. To find out more about this studentship, the research project, and the application process, please contact Dr Benoit Duchet by email on benoit.duchet@ndcn.ox.ac.uk.
To be considered for this studentship, please submit an application for admission to the D.Phil. in Clinical Neurosciences at the Nuffield Department of Clinical Neurosciences (course code RD_CU1), following the guidance for applications to this course. On the application form, in the section headed ‘Departmental Studentship Applications’, please indicate that you are applying for a studentship and enter the reference code “27NDCN01MRC” into the funding tab.
The closing date for applications is 12.00 midday UK time on Tuesday 1st December 2026.
Supervisors
Applications are invited from both Home students and International students to join a multidisciplinary team of researchers studying the synchronisation of brain activity to deep brain stimulation in Parkinson’s disease. This studentship is available from the start of academic year 2027/28, is for 4 years, and will be co-supervised by Dr Benoit Duchet and Professor Huiling Tan at the MRC Centre of Research Excellence in Restorative Neural Dynamics.
Like other Groups at the BNDU, we are committed to best practice in open research. We have created and curated a range of primary data, metadata and related resources that can be readily downloaded by external users from the BNDU's data sharing platform, Cambium.
