We are looking for a PhD student to come and work with us at the University of Manchester. Please get in touch via the link below if you are interested!
About the Project Neuroplasticity is the mechanism that underpins the brain’s ability to learn or recover from traumatic events, but also its deterioration underlies several Neurodegenerative diseases and mental illnesses. It is an umbrella term that encompasses multiple processes occurring at different spatial and temporal scales (1, 2). The most commonly discussed type of plasticity is long-term potentiation (LTP) which is defined as an increase in efficacy between synapses of two neurons. Experiments designed to measure LTP are often done in cell slices or cultures using patch-clamp techniques. However, we often want to promote (and measure) plasticity in humans in-vivo but it is not clear how changes in synaptic efficacy manifest in macroscopic non-invasive imaging measurements such as magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS), or electroencephalography (EEG) that are available for use in humans. This project aims to link our detailed cellular-level knowledge of plasticity processes with systems-level observations in humans and is focused on answering the following 2 questions: 1. How can we modulate plasticity non-invasively in the brain? 2. How can we measure plasticity in vivo? To answer these questions you will combine mathematical/computational modelling of biophysically realistic large-scale neural networks that exhibit plasticity with cutting-edge neuroimaging techniques to test the model predictions. The model will be adapted so that its output can be compared to the three major imaging techniques described above and you will determine how changes in connectivity between and within brain regions in the model predict changes in our imaging metrics. There will be a particular focus on developing an EEG marker of plasticity as this currently does not exist. Finally, you will test the model predictions in an imaging study combining brain stimulation, EEG, MRI and MRS in a proof-of-concept experiment in humans. This will provide us with a deeper understanding of how to modulate and measure plasticity that can be deployed in the future for medical applications of brain stimulation such as in Parkinson’s disease, depression and pain control. Link to project: https://www.findaphd.com/phds/project/epsrc-dtp-model-predictive-control-of-brain-plasticity-for-optimal-non-invasive-brain-stimulation/?p158473
