MRes students work on their research project throughout the year. Projects available for 2020-21 are shown below. You can apply for one of the listed projects, OR contact a supervisor to develop a different project. To do this, check our list of Neurotechnology supervisors and also our Department of Bioengineering research and academic staff pages to see which supervisors you may like to work with, then contact them informally to discuss opportunities and projects. If your first choice supervisor does not have space in their group (or is not taking on MRes students this year) then you are welcome to contact other supervisors.
Once you have decided on a project (either from the list, or one that you have discussed with a supervisor) you should apply via the College online system and state your chosen project(s)/supervisor(s) in the personal statement of your application. If you have already made your application but have not specified a supervisor or project, please contact the Centre for Neurotechnology Manager who can help you link your application to the correct supervisor.
MRes Neurotechnology projects available for 2020-21
Classification of EEG responses to multi-dimensional transcranial electrical stimulation
Supervisors: Gregory Scott (Brain Sciences), Ines Violante (second supervisor tbc)
A major shortcoming of medical practice is the lack of an objective measure of conscious level. Impairment of consciousness is common, e.g. following brain injury and seizures. Brain injury can also interfere with sensory processing and volitional responses, which confounds the behavioural assessment of conscious level. Any objective measure of consciousness would therefore ideally bypass sensory processing. One such example is the perturbational complexity index (PCI) , which quantifies the average complexity of brain activity to multiple pulses of transcranial magnetic stimulation to provide a uni-dimensional measure of conscious level.
We are interested in developing a novel measure of brain state derived from the set of brain responses evoked by a multi-dimensional (i.e. potentially varying in electrode space and time) ‘program’ of transcranial electrical stimulation (TES).
We have recently acquired the GTEN neuromodulation system, state-of-the-art hardware which allows TES and EEG to be recorded through the same high-density (256 electrode) cap (Figure A, simplified). This system allows stimulation through “any” combination of electrodes whilst simultaneously recording EEG through non-stimulation electrodes, or with all electrodes used for recording immediately after stimulation (Figure B).
We will use the GTEN system to execute a “program” of brain stimulations (or “pings”), covering a spatially-distributed set of electrode configurations, and record the EEG responses following each stimulation (Figure C). We propose that clinically relevant information about brain state can be inferred from the properties of the set of responses evoked by the multi-dimensional program of stimulation. This approach would allow conscious states to be placed on a multi-dimensional landscape , rather than reduced to a uni-dimensional measure of conscious level .
A simple analogy is active sonar technology which, in its basic form, emits a well-defined pulse of sound, often called a "ping", listens for reflections (echoes) of the pulse, and draws inferences about nearby objects based on the properties of the reflected pulses. Our approach extends this analogy by systematically varying the spatiotemporal form of the stimulations (“pings”) in order to derive more information than would be possible from repetitions of a single form of stimulation. That is, a diverse program of stimulation reveals more facets of a system than that afforded by analysing responses to a single stimulation.
This pilot project will investigate the question of whether EEG responses to diverse TES montages can even be distinguished in healthy resting awake participants, i.e. whether a machine learning classification algorithm can reliably classify EEG responses according to the stimulation applied. For example, given a set of 40 EEG recordings obtained from 10 repeats of 4 stimulation montages a-d, can the 10 EEG recordings corresponding to each of the montages a-d be correctly labelled a,b, etc. (Figure D)?
We expect the student will carry out data collection in a small group of healthy participants using the GTEN system and analyse data using e.g. Matlab, signal processing, statistics and machine learning to answer the research question. The scope of the data acquisition and analyses experiments will depend on time, progress made and other experimental constraints.
- Existing source code will be available for some of the required tasks.
- We expect students to take an active role in data curation and organisation.
- We ask all students interested in the project to come and discuss the project in advance, having read any appropriate references.
Casali AG et al. A theoretically based index of consciousness independent of sensory processing and behavior. Science translational medicine. 2013;5(198):198ra
Bayne T, Hohwy J, Owen AM. Are there levels of consciousness? Trends Cogn Sci 2016;20:405–13
Drug delivery across the blood-brain barrier using therapeutic acoustic wavelets
Supervisors: James Choi(Bioengineering), Magdalena Sastre (Brain Sciences)
Neurological diseases are among the most difficult diseases to treat, because drugs cannot enter the brain, because cerebral capillaries are lined by a blood-brain barrier (BBB).
We are developing a non-invasive and localised method of delivering drugs across the BBB. Using ultrasound and bubbles, we have been able to non-invasively and locally open the BBB for a short duration (less than 10 minutes) (Morse SM, et al., Radiology 2019), which allows drugs into the brain tissue.
The purpose of this project is to evaluate the effectiveness and safety of our acoustic wavelet drug delivery technology. For example, the student may explore the delivery of new and exciting drugs, such as nanobodies, antibodies, nanoparticles, etc; or may study the safety of the procedure, such as whether microglial cells and astrocytes have been activated.
This is a multidisciplinary project that spans physical acoustics, bubble physics, BBB structure and function, and neuroscience. Dr. James Choi will guide the use and development of the acoustic technology and the evaluation of drug delivery while Dr. Magdalena Sastre will guide the analysis of safety.
Ultrafast phenotyping of optically cleared human cortical tissue grafts with lightsheet microscopy and automated image analysis
Supervisors: Vincenzo De Paola (Institute of Clinical Sciences), Anil Bharath (Bioengineering)
Model organisms are commonly used for studies of brain physiology and pathogenesis, but the extent to which the principles uncovered can be translated to humans remains unclear. Recently, we established a new approach to study human cortical synaptic networks using transplanted donor-derived cells and intravital longitudinal imaging and discovered new cellular and synaptic phenotypes in Down syndrome (Real et al 2018).
This project aims at developing a new method to characterise the post-mortem cellular content of human cortical tissue grafts. Currently, this is a time-consuming and low-throughput step as it requires slicing the fixed brain. Only a small portion of the graft can be studied by immunohistochemistry with each marker, a process which often takes several weeks to months. Therefore, the specific aims of this project are to:
1) Apply ScaleS (Hama et al 2015), a reagent which renders brain tissue transparent within hours, to optically clear human cortical tissue grafts;
2) Test the feasibility of using multiple markers on the same tissue;
3) Develop an automated pipeline to analyse and quantify cell density and neurite extension from lightsheet microscopy images (with Anil Bharath).
These tools will likely accelerate our understanding of how the complexity of the human neocortex is perturbed in several neuropsychiatric conditions.
Use of electrophysiological and structural markers of inter-hemispheric connectivity to model the beneficial effect of noisy galvanic vestibular stimu
Supervisors: Barry Seemungal (Brain Sciences), Timothy Constandinou (Electrical and Electronic Engineering)
Introduction: Electrical stimulation of the vestibular system – obtained by applying a current to the mastoid processes, and is called Galvanic vestibular stimulation (GVS) - enhances postural control, and vestibular perception, in healthy subjects and patients with neuro-degeneration. Our recent data in traumatic brain injury show impaired postural control with disrupted white matter tracts linking the frontal cortices. We hypothesise that the GVS effect upon postural control is mediated by enhanced bi-frontal connectivity.
Objectives: 1) Use noisy GVS to modulate vestibular-mediated postural control. 2) Assess changes in bi-hemispheric connectivity with GVS using: (a) neuro-navigated motor cortex TMS (transcranial magnetic stimulation); and (b) interhemispheric coherence changes in EEG. 3) Model the link between intervention (GVS) and function (postural control) using neurophysiological (EEG, TMS) and structural parameters (diffusion tensor imaging) of inter-hemispheric connectivity.
This project requires a minimum of 2 students working together (but can accommodate a 3rd student). This project is health themed focusing on brain circuits in health and disease and how this relates to brain disease and diagnosis. You would be working with engineers, scientists and clinicians and both healthy and patient cohorts developing the stimulation devices and analysing the data through appropriate tools.
Previous MRes Neurotechnology Projects (for information only)
Some of the MRes projects from previous years are shown here.
|Claudia Clopath, Andrei Kozlov||Development of long-range connections in auditory cortex|
|Martyn Boutelle, Pantelis Georgiou, Mark Wilson||Neurochemical CMOS array – bedside assay of ionic and inflammatory marker from the human brain|
|Dario Farina, Etienne Burdet, Emmanuel Drakakis, Patrick Kaifosh (Cognescent)||Surface Electromyography for Brain-Machine Interface Applications|
|Ravi Vaidyanathan, Alison McGregor, Hildur Einarsdóttir (Ossur), Ásgeir Alexandersson (Ossur)||Sensory Motor Interface for Lower Extremity Robots (SMILER)|
|Dario Farina, Paul Bentley||A clinically-viable brain-computer interface for inducing neuroplasticity for stroke rehabilitation|
|Nir Grossman, Bill Wisden, Paul Matthews||Development of non-invasive deep brain stimulation technology|
|Adam Hampshire, Aldo Faisal, Rob Leech, Gregory Scott||Whole-brain dynamics and higher cognitive processing in disorders of consciousness|
|Tobias Reichenbach, Etienne Burdet||Engineering tactile signals to aid hearing in noisy background|
|Chris Rowlands, Paul Chadderton||3D-resolved optogenetic excitation using time-averaged speckle patterns|
|David Sharp, Nir Grossman, Adam Hampshire, Peter Hellyer||Closed-loop, personalized brain stimulation intervention for impairment of cognitive control|
|Mengxing Tang, Mike Warner, Matthew Williams||3D ultrasound computed tomography of the brain|
|Simon Schultz, Mauricio Barahona||Analysis of calcium signals recorded endoscopically from the rodent brain|
|Mengxing Tang, Mike Warner||Ultrasound technologies for brain imaging and therapy|
|Simon Schultz, Amanda Foust||Ensemble coding models in the LGN: an asymmetry between ON and OFF?|
|Emmanuel Drakakis, Dario Farina||Modular Reconfigurable Low-Power Stimulators|