Oswal Group
Our aim is to provide a detailed understanding of how brain network activity at various timescales contributes to movement and cognitive function, both in health and in neurological diseases. Neurological symptoms are not static, but change over minutes, hours, or days, meaning that an understanding of the origins of their dynamics is necessary for the development of improved therapies. We aim to: (1) relate nerve cell activity within particular brain networks to specific symptoms and (2) modulate this activity in order to improve clinical outcomes.
We adopt a multidisciplinary approach to understand how communication within brain networks contributes to both normal and pathological brain health. To this end, we study healthy individuals and patients with neurological conditions that affect movement and cognition e.g., Parkinson’s disease, and other neurological conditions such as dementia.
Some of the patients we study have undergone a surgical procedure known as Deep Brain Simulation (DBS), during which electrodes are inserted deep into the brain to allow for therapeutic electrical stimulation. By recording from DBS electrodes and from cortical brain areas non-invasively (using EEG or MEG) it is possible to study cortico-basal ganglia interactions and reveal their modulation by DBS. A key goal of our research is to carefully characterise the network modulatory effects of DBS, in the hope that these can be reproduced using novel minimally-invasive techniques.
A parallel strand of our research leverages imaging modalities with high spatial and temporal resolution to reveal network disturbances that underly impairments of memory and motivation in patients. The neuronal mechanisms underlying these symptoms are presently poorly understood, and there are significant opportunities for improving treatments.
- Oscillatory dynamics underlying motor, memory, and motivational impairments in neurological disease
- Predicting pathological signals for Deep Brain Stimulation
- Refining Deep Brain Stimulation for symptom control
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Neuroimaging & neurophysiological techniques (MEG, EEG, MRI)
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Invasive recordings (local field potentials & ECOG)
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Deep Brain Stimulation
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Computational modelling, Machine Learning & signal processing

Mary Muers (far right) moderates an interactive session about training and career development opportunities.
Studentships
Project
Enhancing memory using Transcranial Ultrasound Stimulation and Targeted Memory Reactivation
Enhancing memory processing with brain stimulation has wide therapeutic potential in neurological and neuropsychiatric conditions. Non-invasive brain stimulation using devices has not yet been effectively leveraged to modulate memory in the human brain. A key limitation of non-invasive brain stimulation is that devices have, until recently, been limited to targeting superficial brain regions. However, Transcranial Ultrasound Stimulation (TUS) can now be used to precisely and non-invasively manipulate deep-lying neural circuits, including those in the hippocampus that are important for memory. State-of-the-art TUS provides a unique opportunity to establish a cost effective, non-invasive protocol to enhance memory in humans.
The overall goal of this PhD studentship is to design and implement a new TUS protocol to enhance memory. To achieve this, we will draw inspiration from well characterised endogenous neural activity dynamics in the hippocampus that support memory processing. We will combine TUS delivery with Targeted Memory Reactivation (TMR), which involves pairing new learning with specific auditory cues that are then played again during periods of rest or sleep. Together, the new TUS protocol will facilitate endogenous dynamics in the hippocampus, while the TMR will constrain the content of memory reactivation within these endogenous dynamics, to bias the brain to strengthen specific memories relevant for learning. After validating the new TUS/TMR protocol using behavioural measures, we will use ultra-high field Magnetic Resonance Imaging (MRI) to establish the neural consequences of this protocol. We will use machine learning to quantify the effect of hippocampal TUS/TMR on hippocampal memory reactivation (an index for memory ‘replay’). We will further use a next-generation TUS device to directly combine TUS/TMR with MRI.
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.
The studentship holder will be trained and develop expertise in cutting-edge methods in humans, including application of TUS, TMR, and ultra-high field MRI, including functional MRI and Magnetic Resonance Spectroscopy. You will use Python/Matlab for data analysis with advanced statistical methods, including application of machine learning.
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 updated 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.
Interested candidates should possess, or expect to receive, a 1st class or upper 2nd class degree (or equivalent) in a related scientific discipline, e.g. biological or physical sciences, medicine, computer science, engineering, mathematics. 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 Associate Professor Helen Barron by email on helen.barron@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 “26NDCN01MRC” into the funding tab.
The closing date for applications is 12.00 midday UK time on Tuesday 2nd December 2025.
Opening in November 2025, the MRC CoRE RND is an exciting team science enterprise that is focused on harnessing the moment-to-moment interactions between nerve cells (‘neural dynamics’) to transform medical device-based therapy for brain conditions. The MRC CoRE RND incorporates discovery research and translational research aligned to empirical neuroscience, computational neuroscience, experimental medicine, and biomedical engineering. The MRC CoRE RND is exceptionally collaborative, involving partners in academia, neurotechnology industry, research charities, and clinical services. It will champion values supporting a positive research culture.
Supervisors
Applications are invited from both Home students and International students to join a multidisciplinary team of researchers studying how cells and circuits in the brain work together to perform computations that support memory, and how perturbations to these computations may explain core symptoms reported in people with neuropsychiatric conditions. This studentship is available from the start of academic year 2026/27, is for 4 years, and will be co-supervised by Associate Professor Helen Barron, Professor Charlotte Stagg and Dr Ashwini Oswal at the MRC Centre of Research Excellence in Restorative Neural Dynamics.
Project
Neurophysiological biomarkers for optimising adaptive Deep Brain Stimulation for Parkinson’s
Although Deep Brain Stimulation (DBS) is an established therapy for Parkinson’s disease, its potential for personalised symptom control remains underexploited. Recent advances in DBS technology now enable simultaneous neural sensing and responsive, tailored stimulation. These developments create new opportunities to identify neurophysiological biomarkers that could be targeted to alleviate specific symptoms, including tremor, gait disturbance, and cognitive impairment.
The goal of this PhD studentship is to advance our understanding of how activity within cortico-basal ganglia circuits contributes to specific motor and non-motor symptoms of Parkinson’s. These insights will inform the development of novel DBS strategies designed to normalise circuit dysfunction underlying individual symptoms. To achieve this, we will collect clinical and neurophysiological data from patients implanted with sensing-enabled DBS devices. Cortical activity, sleep, movement, and gait will be monitored using electroencephalography (EEG), electromyography (EMG), and wearable sensors. Advanced signal processing and machine learning methods will then be applied to identify biomarkers and to design targeted stimulation paradigms, which will be tested with patients.
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.
Focusing on the cortico-basal ganglia circuit in Parkinson’s, this studentship offers the opportunity to work with cutting-edge techniques including wireless neural activity streaming from implanted DBS devices, high density EEG, EMG, and wearable sensor recordings. You will gain advanced training in patient facing research and in state-of-the-art analytical approaches spanning signal processing, computational modelling, and machine learning.
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 updated 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.
Interested candidates should possess, or expect to receive, a 1st class or upper 2nd class degree (or equivalent) in a related scientific discipline, e.g. biological or physical sciences, medicine, computer science, engineering, mathematics. 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 Ashwini Oswal by email on ashwini.oswal@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 “26NDCN01MRC” into the funding tab.
The closing date for applications is 12.00 midday UK time on Tuesday 2nd December 2025.
Opening in November 2025, the MRC CoRE RND is an exciting team science enterprise that is focused on harnessing the moment-to-moment interactions between nerve cells (‘neural dynamics’) to transform medical device-based therapy for brain conditions. The MRC CoRE RND incorporates discovery research and translational research aligned to empirical neuroscience, computational neuroscience, experimental medicine, and biomedical engineering. The MRC CoRE RND is exceptionally collaborative, involving partners in academia, neurotechnology industry, research charities, and clinical services. It will champion values supporting a positive research culture.
Supervisors
Applications are invited from both Home students and International students to join a multidisciplinary team of researchers studying neurophysiological biomarkers to improve adaptive Deep Brain Stimulation for Parkinson’s. This studentship is available from the start of academic year 2026/27, is for 4 years, and will be co-supervised by Dr Ashwini Oswal, Professor Huiling Tan, Professor Hayriye Cagnan and Professor Andrew Sharott at the MRC Centre of Research Excellence in Restorative Neural Dynamics. The studentship project will also benefit from the expertise of Professor Alex Green at the Nuffield Department of Clinical Neurosciences.
Recent Publications
Recent Preprints
Datasets are available through our dataset platform which is designed to enable the sharing of several classes of research data generated by the Medical Research Council Brain Network Dynamics Unit at the University of Oxford (MRC BNDU). The datasets could include:
- Electrophysiological recording from humans and rodents
- Digital micrographs of brain tissue
- Scripts and code used for analysis of data
- Printable 3D models and microcontroller code
- Code for modelling of neuronal networks
All downloads require making an account; the primary reason for this is to enable us to monitor downloads of datasets which allows us to report this to funding bodies.