Project Title: Development of non-invasive deep brain stimulation technology
Supervisor: Dr Nir Grossman
Location: Level 5, Burlington Danes, Hammersmith Campus
I am a PhD student at the Centre for Doctoral Training in Neurotechnology, working on improving a non-invasive deep brain stimulation technique called temporal interference and developing new stimulation principles. Prior to joining Imperial, I undertook my MEng degree in biomedical engineering at UCL. During that time, I developed an interest in the interaction between technology and biological systems and subsequently worked in robotics and neuroscience laboratories on developing body- and brain-machine interfaces. Having experienced both clinical and basic research, I am happy to be now involved in a project that takes from and can bring benefits to both these worlds.
- 2018-present MRes in Neurotechnology and PhD in Medicine, Imperial College London
- 2014-2018 MEng Biomedical Engineering, University College London [First Class Hons]
Physical means of brain stimulation, such as the use of implanted electrodes for deep brain stimulation (DBS), are a non-pharmacological means to probe and treat dysfunctional neural networks through direct control of circuit activity. DBS is used around the world to treat patients with severe movement and affective disorders but the risk from inserting electrodes into the brain limits the therapeutic impact of DBS and makes the exploration of new brain targets difficult.
A new stimulation technique called temporal interference (TI), unlike most other non-invasive methods, shows the potential to reach deep brain areas without activating the overlying structures. The overall aim of my PhD project is to develop a technology based off TI for non-invasive and focal DBS to pave the way for new experimental frontiers and DBS therapies with reduced risk for patients. During the project I will be exploring methods to improve the focality and strength of the TI technique, including potentially revising the stimulation principle, and testing them in computational and biological models.
De Santis D, Dzialecka P, Mussa-Ivaldi FA. Unsupervised Coadaptation of an Assistive Interface to Facilitate Sensorimotor Learning of Redundant Control. 7th IEEE International Conference on Biomedical Robotics and Biomechatronics 2018
Affiliate member of Institute of Physics and Engineering in Medicine