Reece Foundation PhD Studentships

Background Epilepsy is the recurrence of spontaneous unprovoked seizures which often involve a loss of consciousness and abnormal neural activity. Epilepsy is often associated structural and functional brain abnormalities detectable by MRI and EEG/MEG. Surgical treatment for epilepsy aims to remove the part of the brain thought to be causing seizures.  However around 40% of patients will continue to experience seizures even after such an invasive operation.  It is currently not possible to know which patients will be rendered seizure-free by surgery, and which will not before the operation.

Aim The aim of this PhD is to develop predictive computational models which can be used for 1) refining suggested surgical resection strategies and 2) predicting patient outcomes for a given strategy.

Methods In this PhD we will use MRI data from patients with epilepsy to infer a personalised brain network. We will then use the network to constrain parameters in a computer model of neural dynamics. The model dynamics will be fit to the patient’s own neural dynamics, measured by MEG.  After meeting this initial objective of model fitting, we will modify the parameters to perform simulated brain surgery to investigate if the model ‘seizes’ for a given simulated surgery. Model outputs will be compared against patient outcomes for validation. We have data acquired from over 100 patients who already underwent surgery and where the outcome is known.

Timelines This work would be the first of its kind to combine MRI and MEG data using a dynamical model in epilepsy, with the aim to ultimately contribute to improved patient outcomes. The work is timely considering the use of AI and advanced modelling, alongside improved accessibility to high performance computing.

Potential impact Through our extensive collaborator network we have the opportunity to move towards clinical translation, influencing clinical decision making within the lifetime of the PhD. This opportunity has the potential to improve our mechanistic understanding of seizures, and the optimal way to treat them.

Supervisory team We have a wide range of expertise in computing, medical imaging, and statistics in the lead supervisory team. We already collaborate extensively with colleagues in the medical faculty, and will continue in this manner. Dr Ahmadi, has extensive expertise in signal processing and medical computing, with an interest in application to epilepsy.

Professor Peter N Taylor peter.taylor@newcastle.ac.uk

Dr Alaa Alahmadi alaa.alahmadi@newcastle.ac.uk

Background: The structure and shape of the brain changes through development, ageing, and in disease. Cross-sectionally, changes in cortical shape and structure correlate with age, cognitive function, and disease severity or progression. However, it is less clear if brain structure derived from neuroimaging can also reliably track disease progression in individuals and longitudinal research is required to establish causal relationships between brain structure and disease processes.

Question/hypothesis/aim: We aim to track brain structure of individual subjects longitudinally, alongside clinical and cognitive outcome variables to develop individualised neuroimaging markers of ageing and degenerative processes.

Methods: Using large-scale open-access structural neuroimaging datasets, structural changes across different processes will be established and related to clinical and cognitive outcome measures. We will establish a baseline with healthy ageing as an initial process, with age and neuropsychological data as primary outcome measures. We will then investigate dementia and epilepsy as application domains, given the significance of brain structural changes in these disorders, and supervisory expertise.

Timelines: This interdisciplinary project fills a crucial knowledge gap in medical neuroimaging and provides a unique opportunity to combine novel computational/AI methods with huge datasets to gain a mechanistic understanding of how and why brain structure and shape change in different processes, and how this relates to clinical and cognitive outcomes. We aim to address urgent societal needs to advance knowledge of neurodegenerative disorders.

Potential impact: Leveraging longitudinal data, the project will improve our understanding of how ageing and diseases progress and how reorganisation occurs. It will inform on potential neurobiological causes of neurodegenerative and neurological diseases. Predicting disease progression of individuals based on the interaction of outcome measures, morphological and connectivity measures offers a huge leap forward in research and, crucially, could be translated into clinical tools to aid prognosis and inform medical decisions.

Supervisory team: We offer a rich research environment in both clinical and computational labs. Dr Yujiang Wang is a UKRI Future Leaders Fellow and co-PI of the Computational Neuroscience, Neurology, and Psychiatry (CNNP) lab in the School of Computing. Key expertise: the development of computational biomarkers based on mechanistic understanding of the processes driving brain shape. Prof. John-Paul Taylor is Clinical Professor of Translational Dementia Research and PI of the Lewy Body Lab in the Faculty of Medical Sciences. Key expertise: application of neurophysiology and neuroimaging to dementia populations.

Dr Yujiang Wang yujiang.wang@ncl.ac.uk

Professor John-Paul Taylor john-paul.taylor@ncl.ac.uk

Approximately 15% of the population have tinnitus, with 2% of the population experiencing profound negative long-term impact. Yet, no widely applicable treatment to quieten the sound exists. The majority of the world’s tinnitus population struggle to access specialist healthcare, but have access to a smartphone, which offers exciting treatment opportunities.

In this project, the student will work on a novel type of sound therapy (Acoustic Ripple Therapy: ART) developed by the supervisory team, which they have shown has a significant lasting quieting effect on tinnitus. Importantly, this was delivered entirely online, using only methods feasible to implement in a smartphone app. The benefit was significant compared to a placebo version of the sound therapy. However, the benefits were variable, with the average benefit being modest, some people not benefitting, but a few getting a dramatic quieting of tinnitus, which some described as ‘life-changing’.

Whilst there is a theoretical principle on which it works, which is to reduce correlations in the activity patterns over time of neuronal populations representing different sound frequencies, the physiological mechanism behind ART remains to be established. In this PhD project, the student will work on better understanding basic mechanisms of quietening tinnitus through electroencephalography (EEG) recordings and analysis of neural oscillations.

The student will record the brain activity of people with and without tinnitus before, during and after ART. They will investigate how ART alters different types of brain activity, and which of these correlates best with symptomatic improvement. They will test different parameter variants of ART; those leading to the greatest changes in brain activity will then be tested in online clinical trials.

The supervisory team includes members of two internationally leading research groups in Newcastle University: one specialising in acoustic signal processing, and the other in auditory research and tinnitus neuroscience.

The ultimate aim, which will require further subsequent funding, is to package the technique as a smartphone app that will freely deliver the best available version of ART, run automated randomised trials to keep iteratively improving ART, and incorporate ART into audio content that users ordinarily listen to for pleasure, such as music. In other words, allow people to treat their tinnitus seamlessly through doing things they already do as part of their everyday life.

The project is feasible and realistic, and follows the work of a PhD student who completed both a programme of EEG studies and an online sound therapy trial.

Supervisors:

Dr Kai Alter kai.alter@newcastle.ac.uk

Dr Jeffrey Neasham jeff.neasham@newcastle.ac.uk

Dr William Sedley  william.sedley@newcastle.ac.uk

Dr Benjamin Sherlock benjamin.sherlock@newcastle.ac.uk

Dr Ekaterina A Yukhnovich ney14@newcastle.ac.uk

Background
Throughput, a measure of performance in bits/second combining speed and accuracy, is widely used in human-machine interaction studies but remains underexplored in the context of motor control and movement disorders. Understanding the underlying neural mechanisms could provide key insights into motor deficits. In disorders with processing deficits, such as Parkinson’s Disease or Alzheimer’s, throughput may be constrained by impaired decision-making or motor planning. By contrast, output deficits such as those seen in stroke or spinal cord injury produce weakness and the inability to control specific muscles (individuation), and hence impair motor execution. A systematic investigation of throughput could reveal distinct mechanisms underlying motor impairments and provide valuable diagnostic and therapeutic insights.

Research Question and Hypothesis

This project aims to understand the basis of throughput in healthy individuals and identify specific deficits in clinical populations with motor impairments. We hypothesize that throughput deficits will reflect interactions between muscle individuation and strength. By dissecting these contributions, we aim to identify condition-specific mechanisms underlying motor deficits.

Methods

The project will combine behavioural and neurophysiological approaches. We will use behavioural tasks designed to measure overall throughput, and sub-components such as precision, speed, and accuracy. Using these tasks combined with neurophysiological techniques (such as motor unit recordings and non-invasive brain stimulation), we can compare throughput (and its constraints) between different muscle groups (e.g. proximal vs. distal, extensor vs. flexor), as well as the contribution of motor command pathways such as the reticulospinal and corticospinal tracts. Initial quantification will be in healthy controls and then clinical studies will compare throughput in processing-deficit conditions (such as Parkinson’s Disease) and output-deficit conditions (such as stroke or spinal cord injury).

Timelines and Impact

This project is timely, given the growing interest in precision diagnostics and individualized rehabilitation for movement disorders. By identifying distinct contributors to motor deficits, this research could transform how we diagnose, monitor, and treat these conditions. The findings will also advance fundamental understanding of motor control in health.

Supervisory Team

The project will be supervised by an interdisciplinary team with expertise in motor control, neurophysiology and movement disorders, as well as with the clinical expertise required in implementing novel diagnostics and electroceuticals in patients. You will work closely with researchers developing cutting-edge measures of motor performance. This supportive environment will provide training in neurophysiological techniques, in data analysis, and clinical research.

This is an exciting opportunity to contribute to ground-breaking research at the intersection of neuroscience, motor control, and clinical rehabilitation.

Supervisors:

Dr Demetris Soteropoulos Demetris.soteropoulos@ncl.ac.uk

Professor Stuart N Baker stuart.baker@ncl.ac.uk

Professor Mark R Baker mark.baker@ncl.ac.uk

This interdisciplinary project involves applying the quantum formalism (QF) to model experimental observations of human emotional memory performance, and the neural systems that support it, to better understand the interaction between elements. The quantum formalism provides a natural mechanism for modelling combinations of difficult-to-reconcile memory effects, such as the question order effect (where changing question order may change the respondent’s answer) and the response replicability effect (where repeated presentations of a question produce the same response across contexts). Conversely, the paradoxical temporal effects often observed in human memory performance mean it may provide a useful theatre for observing analogies of quantum phenomena we cannot access directly.

Temporally ordering the complex set of overlapping emotional events that comprise our lives is a demanding task, yet one our brains constantly undertake, providing shape and story to our lives. This ordering can enhance the detail, context, and accuracy of our memories - or be susceptible to distortions.

Behavioural Analysis: Initially, this project will use the QF to explore and model the role of emotional content and context on the temporal ordering and asynchronous retention of memories. Experiments will vary the proportion of negative, neutral, and positive stimuli and their relative temporal position to test predictions derived from this model. Behavioural outcomes measures will include memory performance and reaction time.

Implicit measures of memory encoding: We will use eye tracking to measure dependent variables (e.g., eye movement, pupil dilation, point of gaze, and blinking) to explore factors occurring during encoding of events containing different emotional content and occurring in different emotional contexts. We will apply the QF to these measurements to create a model that predicts the impact of emotional content  on the order and duration of memory for events. Seeing how this model encodes and represents these dependent variables will allow us to identify them as analogues to experimentally-unobservable mathematical elements of the QF, allowing us to more directly intuit how they these elements of the formalism manifest.

By integrating these disciplines, we aim to develop a sophisticated model that explains how emotional events influence memory accuracy and perception of time. The quantum formalism, typically used in physics, provides a natural mechanism for modelling psychological phenomena such as the question order effect and response replicability effect, and critically, perceptual responses to these.

Supervisory Team: Dr Barbara-Anne Robertson (Lecturer, Psychology) a.robertson@newcastle.ac.uk. Dr Jonte R Hance (Lecturer, Applied Quantum Foundations) jonte.hance@newcastle.ac.uk, Dr Tom Smulders (Reader, Evolutionary Neuroscience tom.smulders@newcastle.ac.uk.

The human cerebral cortex is the most sophisticated biological machine we know; it is the seat of higher cognition, memory and thought.  The basic architecture and the component cell types of the human neocortex appear similar to other, more widely studied mammalian brains (rodents and primates). However, little is known about synaptic function in humans.  Given the critical role of synaptic function in cognition, questions about human synaptic function assume the highest importance.  Studying synaptic communication in human neuronal circuits is not possible in situ but can be done using a remarkable resource: tissue that has been resected from the brains of patients having neurosurgical treatment and kept alive in artificial cerebrospinal fluid.

The student will use resected human cortical tissue to examine the structure and function of neuronal synapses, using a range of state-of-the-art imaging, electrophysiology and electron microscopy techniques.  Experimental findings will be incorporated into anatomically accurate computational models, to explore how neuronal communication may flow through human cortical networks. The student will examine how neuromodulators such as acetylcholine, dopamine and serotonin, which mediate various cognitive, executive and emotional functions, may alter synaptic communication and dendritic excitability and the propensity towards epileptic discharges. The student will test the hypothesis that the peculiarly long dendrites in human pyramidal cells confer a special facility for compartmentalizing activity and achieving rapid state changes. These functional features may underlie short-term memory and attentional switching but also carry the risk of tipping into epileptic pathological discharging. 

The supervisorial team combines expertise in the anatomy and physiology of mammalian neocortical microcircuits, statistical and computational modelling (Ramaswamy), cellular electrophysiology and imaging techniques and epileptic pathophysiology (Trevelyan & Ramaswamy). Our recent work has revealed the cellular and synaptic organizational principles of cortical networks (Ramaswamy); the principles of seizure initiation and termination (Trevelyan); ionic redistribution that confer variable network functions during circadian cycles (Trevelyan), and the anatomy, physiology and pharmacology of monoaminergic neuromodulator systems and the impact of serotonin on cortical function (Ramaswamy & Trevelyan). 

This timely project, supervised by an internationally recognized team, is an excellent opportunity for a student to be trained in the principles and analytical techniques of experimental and computational neuroscience using resected human brain tissue.

Supervisors:

Dr Srikanth Ramaswamy rikanth.ramaswamy@newcastle.ac.uk

Professor Andrew Trevelyan andrew.trevelyan@ncl.ac.uk

You must have, or expect to achieve, at least a 2:1 Honours degree, or international equivalent, in a subject relevant to the project (please contact the supervisors if you are unsure). A further qualification such as an MRes, or other research experience, is advantageous.

Please read these instructions carefully before you begin your application, and ensure you complete all the steps required.

Choose which project you wish to apply for. Individuals can submit applications for more than one project advertised within the scheme.

Complete and submit the Reece Foundation Scheme form to apply.

You must also submit the following documents by email in a single .zip file attachment:

1. Your CV (including contact details for at least two academic (or other relevant) referees)
2. A covering letter – this should explain your particular interest in your chosen project. It should also include any additional information you feel is pertinent to your application.
3. Copies of your undergraduate degree transcripts and certificates.
4. A copy of your passport (photo page).
5. Your English language certificate (IELTS or TOEFL certificate, where applicable).

Documents should be submitted as .PDF files.

Do not submit photos of certificates.

Do not combine all the documents into one .PDF.

Each document type listed should be included in the .zip file and names as follows:

[candidate surname candidate name document type].

For example Jones Anna CV

Please zip the separate documents into a .zip file. Name the zip file:

Surname_name_[project number]

Email your zip file to centreforneuroscience@newcastle.ac.uk

The subject line of your email must include:

• Reece Foundation PhD 2025 
• The number of your chosen project
• The surname of the lead supervisor
• E.g. Reece Foundation PhD 2025; Project 1 Anand

Applications not meeting these criteria may be rejected.

You will receive confirmation by email that your application has been received.  If we require any further information from you about your application, we will be in touch.

You will need two referees, one of which must be an academic reference.  This could be:

• An undergraduate or master’s project/dissertation supervisor
• Personal tutor
• A module director/organiser
• Someone you have worked for in an academic context from your university.

If you are applying for a position with your current (or past) supervisors, it is not advisable to use them as a referee.  Supervisors are also competing for funding, so there is a conflict of interest.  In such cases your chosen supervisor can provide guidance on the most suitable referee to include.

Applications should be submitted by 28th February 2025.

What happens to my application after the closing date?

All completed applications will be screened by the Centre for Transformative Neuroscience for eligibility.  Following this:

• Applications will be scored by the supervisors and selection panel to arrive at a short list.
• The highest-ranking candidates in the short list will be invited to meet the supervisor of their selected project and to a panel interview. Meetings and interviews may take place in person or via zoom depending on circumstances.
• If a candidate has been shortlisted for more than one project, they will be asked to state their preferred project of the two.

If I am invited to interview, what does the interview process involve?

The interview will last approximately 30-45 minutes.  The interview format will involve:

• A short presentation by you describing a previous research project you’ve worked on. This includes a succinct description of how you contributed to that research (you will use screen share mode on the online platform if used).
• Around 30 minutes of questions from a panel of academics.

What happens after the interview?

Following the interview, candidates are scored by each panel member based on their performance.  The scores are collated, and a final ranking is decided, taking all factors into account.  Offers are made to candidates according to the rankings.

You will not be judged for having been out of academia, whether it is for work, caring duties, illness or anything else. Like everyone else, you will need a degree – however, there is no time limit on when this was awarded. We appreciate that experiences outside of academia can be a rich source of key skills that you would need for a PhD so be sure to think carefully about skills this experience has given you and make sure you tell us about them. It is likely that the supervisor or interview panel might want to know what drew you back to academia, so use this time to show how passionate you are about research.

You will not be penalised for not having a master’s degree. PhD studentships are highly competitive, and most successful applicants will have a master’s qualification. This is because of the experience a master’s degree provides rather than the certificate. However, experience can equally come from many other sources, such as work, both academic and non-academic.

If you are offered an interview, a standard email will be sent from the Centre team to your referees requesting a reference prior to your interview. We would advise that you contact your referees to advise them that they may receive a reference request.

The cover letter should explain your interest in your chosen projects and should include any additional information you feel is important to your application. You may wish to add why you are choosing Newcastle University. There are no formal word limits for your CV or cover letter, but we recommend you keep them concise.

Each student has a different set of strengths and weaknesses. That said, a passion for the project is an essential part of being a successful PhD student. It is a basic requirement that any supervisor will look for in selecting a student. Do remember that there may be some (but not endless) flexibility in what you actually do within the PhD project.

This will be dependent on the project supervisor. Our funding does not dictate any work schedule. It does ask that any difference from standard working patterns be agreed with your supervisor. It would be sensible to discuss this with them before you apply. Most supervisors will support a student's requirements (for example, to accommodate caring responsibilities), but the project may have specific requirements. E.g., where a particular type of lab work is necessary to complete the project.

Students may take on teaching or demonstration work, where this is compatible with their training in addition to a full-time studentship. This needs to be approved by their supervisors.  Other paid work would need the consent of the supervisor and should not delay or interfere with your research training. You may ask primary supervisors about flexibility of the PhD; this varies depending on the PhD project. Part time study is usually available; we advise that you discuss this further with the project supervisor.

Applications should be submitted by 28th February 2025.