From Volvo to the vagus nerve: Oskar Allerbo is researching how to read the body’s electrical activity
Oskar is a post-doctoral researcher working with MedTechLab researchers Peder Olofsson, KI, and Henrik Hult, KTH, specialising in bioelectronic medicine. We asked him to tell us a little about himself and his research.
Describe your research – what is it about and what do you want to achieve?
“The vagus nerve is an important part of the parasympathetic nervous system and is connected to several different internal organs. Studies have already shown how stimulating the vagus nerve with an external voltage source can reduce inflammation in the body. Our goal is actually the opposite: Is it possible to detect inflammation by reading the electrical activity of the nerve? We are trying to achieve this in experiments on mice, where my job is to analyse the data from the experiments.”
How can what you do benefit patients and health services and when?
“Continuous measurements of the degree of inflammation in the body open up completely new possibilities for treating inflammation. This is partly because you can get information about what is happening at an early stage, but also because of the possibility of immediate feedback on the interventions you make. When this will be available in healthcare, I dare not guess. The first step is to succeed in the lab.”
What are the main challenges you have encountered so far in the project? How are you addressing them?
“A major challenge is that we don’t know if what we are trying to do is possible with current technology. The vagus nerve consists of about 100,000 nerve fibres and the data we are interested in is probably only represented in a fraction of these. Moreover, the data is very noisy. Because of all the processes going on simultaneously in a body, it is virtually impossible to perform the same experiment twice. We try to address this by using as robust, noise-free methods as possible, both in the experiments themselves and in the data analysis.”
What is a typical day like for you at work?
“I basically just stand in front of the computer and write, programme and think. Sometimes I take walks to clear my head. This may sound monotonous, but I am very happy. Because I only need my computer and a pen and paper, I can work almost anywhere and at any time, which makes my life as a parent of young children much easier.”
What do you like about working across disciplines? What have you learnt through this?
“It’s very stimulating to talk to people with different specialisations. I think it’s clear how our fields are difficult in very different ways and that it forces us to approach problems from very different angles. I also think that a prerequisite for successful interdisciplinary work is a high level of expertise in all the different disciplines that will be working together, which I feel we have in our project.”
What motivates you during tough periods in research or when you are stuck?
“I think I have one of the best jobs in the world: I have a lot of freedom to solve incredibly interesting problems with incredibly knowledgeable and interesting people. Being able to continue to be part of the academic world is a very strong motivator. When I get stuck on a question, I usually try to do something else for a while. Or rephrase the question to make it easier to solve. One thing I really appreciate about research is that you often solve different questions than you thought you would solve when you started, but that this is also considered good.”
Finally, tell us about your background, why you became a researcher and what you want to do in the future
“After studying at Chalmers, I worked for six years in industry, at Volvo and Ericsson. But I gradually realised that it wasn’t really my thing. I thought there was too much focus on processes and too little focus on the actual product. A year as a research engineer in computer science confirmed that academia was a better fit for me, so I applied for, and got, a PhD position in mathematical statistics. I really love the freedom and the opportunity to develop that is offered in the Academy, and hope that I will manage to stay here. My dream is to work on theory and method development in statistics and machine learning, and to use my knowledge in applied projects in all sorts of different topics – much like this position.”