About Me
Hi, my name is Borana and I’m currently a PostDoctoral researcher in Computational Neuroscience. I am well used to working within an interdisciplinary team, where theoreticians, programmers, biologists and clinicians come together to provide innovative approaches to health and diagnostics. My work has also taught me autonomy, adaptability and perserverance.
I recently obtained my PhD in “Modelling brain stimulation for drug-resistant epilepsy”, where I used individualized Virtual Brain Models to study brain stimulation in epilepsy. I have solid knowledge in computer science and applied mathematics, where I obtained an engineering degree in Grenoble INP - ENSIMAG.
I love applying mathematics to physical and biological phenomena, in particular for health and clinical applications ! I also am amazed by the brain and what it can do.
I am most skilled in: Programming, Brain imaging, Modelling and Simulations.
Projects
Building virtual brain twins and simulated brain activity of real patients with drug-resistant epilepsy
The goal of this project was to build a synthetic copy of an empirical dataset of 30 patients with drug-resistant epilepsy.
People with drug-resistant epilepsy suffer from intractable seizures and can be treated with brain surgery. Their chance of becoming seizure-free heavily relies on proper diagnosis of brain regions responsible for seizure generation, known as epileptogenic zones (EZ). In the clinic, empirical recordings of brain activity are used to estimate these brain regions. However, the underlying ground truth is not available. We built a virtual cohort of 30 patients with drug-resistant epilepsy, using individual patients’ data to simulate their epileptic brain activity. This brain modeling based on personalized data is referred to as a virtual brain twin. The key parameters of these virtual brain twins including the EZ settings serve as the ground-truth. Epileptic brain activity is simulated at the whole-brain level and mapped onto intracranial sensors to mimic real recordings. We quantified how well the synthetic signal captured features from the empirical data. For each virtual brain twin, we generated spontaneous seizures, stimulated seizures and interictal activity. This cohort is made available to the scientific community to benchmark methods such as estimation of EZ and source localization.
Experience
Theoretical Neuroscience Group - Institut de Neurosciences des Systemes
Postdoctoral Researcher
January 2025 - Present
ins-amu.fr
Using virtual brain twins to predict brain stimulation responses in-silico.
Following my PhD thesis work, I am continuing to use individualized virtual brain models to predict stimulation response in drug-resistant epilepsy. Here, I am using brain imaging data to parametrize the virtual brain twins and performing simulations to compare the outcome to the empirical data. Using a genetic algorithm approach, I am estimating the parameters of the virtual brain twin that can predict the empirical data.
Theoretical Neuroscience Group - Institut de Neurosciences des Systemes
PhD candidate
May 2021 - December 2024
https://ins-amu.fr/
Modeling brain stimulation for diagnosis of drug-resistant epilepsy
I completed a PhD in Computational Neuroscience, using virtual brain models to diagnose drug-resistant epilepsy. My project was focused on modelling the effects of brain stimulation in epilepsy, in particular when triggering seizures. To this end, I extended an existing model to account for brain stimulation effects in seizure generation in epilepsy, which I tested and validated in a synthetic cohort of 30 patients with drug-resistant epilepsy. In addition, the modelling framework was extented for high-resolution virtual brain models and non-invasive stimulation, demonstrating a potential methodology for purely non-invasive diagnosis of drug-resistant epilepsy.
Education
Aix-Marseille University
PhD in Neuroscience
2021 - 2024
During my PhD at Aix-Marseille University I learnt most of my key skills that have I have taken through my career such as teamwork and working to tight deadlines. I thouroughly enjoyed my time as university and learnt a lot about a healthy work life balance.
Grenoble INP - ENSIMAG
Engineering degree in Computer Science and Applied Mathematics
2017 - 2020
ENSIMAG is recognized as one of the best French engineering schools in computer science.
During my studies at ENSIMAG I learnt the basis of programming and applied mathematics. I was lucky to learn from very passionate individuals in good programming practices, to apply what we learned in many different programming projects throughout the year and to socialize during the many student association events.
Grenoble Alpes University
Bachelor's in Mathematics and Computer science
2015 - 2017
Grenoble Alpes University is a highly reputable French university.
During my studies I learnt programming for the first time and got to fall in love with the beauty of mathematics !
A Little More About Me
Alongside my interests in networks and software engineering some of my other interests and hobbies are:
- Rock climbing
- Gaming
- Knitting
- Becoming a ninja
Look at this cool image
