Virtual brain twins for epilepsy treatment via deep brain stimulation

The NeuroSchool PhD Program of Aix-Marseille University (France) has launched its annual calls for PhD contracts for students with a master's degree in a non-French university and for  international co-supervised PhDs.

This project is one of the proposed projects. Not all proposed projects will be funded, check our website for details.

State of the art:

Both invasive deep brain stimulation and non-invasive stimulation are becoming promising new techniques providing treatment for drug-resistant brain disorders. In epilepsy, hodologically matched thalamic deep brain stimulation (HMT-DBS) has shown considerable potential, and is a possible treatment option in patients with epileptic foci that overlap with eloquent cortices or involve widespread brain regions. However, we still lack comprehensive understanding regarding the mechanism of neuromodulation and practical guidance about patient specific optimal stimulation parameters. Virtual brain twins (VBT), i.e. personalized whole brain network models, based on patient specific anatomical and functional imaging data, implement a causal mechanistic model of a patient’s brain dynamics and can be used to provide personalized diagnosis and treatment. We have developed the VBT for diagnosis in epilepsy over the past 10 years, which is currently being evaluated in the clinical trial “Epinov”. This PhD thesis will develop the VBT for epilepsy treatment via stimulation.

Objectives:

To construct a VBT pipeline for HMT-DBS by capturing key interictal and ictal thalamo-cortical dynamics in posterior quadrant epilepsy and optimize the associated stimulation parameters.

Methods:

1. We will develop a solid biophysical network model incorporating neuromodulation under deep brain stimulation to study treatment effects.
2. We will construct a VBT for each patient by extracting geometric information and structural connectivity from individual MRI data.
3. We will infer personalized parameters for each patient using a machine learning algorithm and the patients’ functional data.
4. We will validate the VBT by simulating stimulation, comparing it to the patient specific empirical stimulation data.
5. We will optimize stimulation parameters using the predictive power of the VBT pipeline.

Expected results:

• A biophysical network model with neuromodulation to address how brain activity responds to electrical stimulation by considering both local and global network effects.  
• A VBT pipeline with treatment effects from personalized data, compared and evaluated using empirical recordings from a retrospective cohort study.
• Optimization of the stimulation parameters using the VBT pipeline and assist clinicians to make treatment decisions, in a cohort of 10 patients. 

Feasibility: The CPP number is not known yet.

Within Aix Marseille Université, NeuroMarseille brings together 8 research laboratories and NeuroSchool, a graduate school in neuroscience, to increase the attractiveness of the university, international collaborations, interdisciplinarity, links with the clinical and industrial worlds and the integration of students into professional life. 

Launched in July 2018, NeuroSchool unifies and harmonizes the training of the third year of the Bachelor of Life Sciences (Neuroscience track), the Master's and the PhD in Neuroscience. 

• Master's degree from a non-French university in neuroscience or related field
• Fluent in English
• Problem-Solving and Critical Thinking – Capacity to tackle complex problems, think logically, and develop innovative solutions.
• Research and Analytical Skills – Ability to conduct independent research, critically analyze data, and synthesize information to generate new insights.
• Technical and Domain-Specific Expertise – Already have or capability to learn the knowledge and technical skills, in the domains of mathematical modelling, dynamical systems theory, neuroimaging and electrophysiological data analysis, and programming for computer science).
• Academic Writing and Communication – Strong ability to write research papers, reports, and grant proposals, along with presenting findings at conferences.
• Collaboration: Skills in working with interdisciplinary teams, engaging in academic discussions, and building professional relationships within the research community.