Psych Snapshot: Natalia Egorova

Through Psych Snapshots we take the time to get to know some of our staff and students and understand their work and what makes them tick.

Please join us in welcoming one of our latest community members, Dr Natalia Egorova!

Why is your research important? What are the possible real world applications?

Natalia EgorovaI have a varied research portfolio spanning the fields of language, pain, stroke and depression, interrogated with neuroimaging, including task and resting state, time and frequency-resolved approaches, as well as brain stimulation.

At the Melbourne School of Psychological Sciences, I have started the Pain and Cognition Neuroimaging Lab, and focus on using experimental pain stimulation to unveil specificities of brain functioning in healthy participants and in clinical populations (psychiatric and neurological). For example, I investigate the neurobiology of sensory word learning or pain sensitivity in depression. As an Honorary Fellow at the Florey Institute of Neuroscience and Mental Health, I also study patterns of post-stroke neurodegeneration and brain functional decline associated with language deficits or depression.

The findings from my studies create opportunities for future translation and have led to several novel interventions – a new aphasia therapy, neuromodulation of placebo/nocebo effect in chronic pain, and physical exercise intervention in stroke.

What excites you about your work?

Being a cognitive neuroscientist is a diverse and rewarding job. Leading interdisciplinary research, I need to be an expert in my fields of language, pain, depression, and stroke, and keep up with advances in psychology, psychiatry and neurology. I need to be a physicist to understand MRI or EEG acquisition protocols. To perform neuroimaging analysis, I take on the roles of a statistician and a computer programmer coding in several languages.

I am a lab manager purchasing equipment, an accountant managing financial reports for grants, an HR specialist hiring research assistants. Occasionally I become an engineer, working out how to design custom cables to ensure connection and synchronised communication between various devices. I am a writer preparing articles and a designer making figures for talks and publications. I am a teacher supervising students and a public speaker delivering presentations and communicating with the media.

The challenge of performing at my best in all of these roles is exciting.

What might people be surprised to know about you?

My PhD was my first Science degree. My background prior to that was in Humanities: languages, politics, literature. My career as a cognitive neuroscientist is therefore an example of the 'you can be anything' attitude, and a reminder that education (in arts or sciences) is about developing learning and analytical skills, not obtaining a specialised professional qualification.

By the way, my professional degree is in real-time interpreting and translation (English-Russian-French), but I only practice it doing synchronous translation of English children's books into Russian for my 2 year-old.

What is one of the ways you are dealing with COVID and the changes to your work and home life?

Workwise, I am currently unable to run any of my experiments that require face-to-face interaction. Luckily, I have access to a rich neuroimaging dataset and can continue my stroke imaging work. For student projects, I am becoming an expert in systematic reviews and meta-analyses. COVID also finally forced me to learn how to code up an online experiment, so next semester I will be running my first online study.

In my personal life, working from home with a toddler has been challenging but we get to spend more time together. My husband and I work in half-day shifts, with work spilling into evenings and weekends. To maintain the distinction between weekdays and weekends, we implemented a few weekend routines, like cycling to a local deli shop on a Saturday or preparing a weekly Sunday roast.

What do you find most challenging about your research?

Acquiring imaging data is expensive and can take a long time, so it is very important to design studies well and control data quality. Any mistake is very costly, as it is not as easy to simply repeat the experiment. In addition, brain imaging is a very dynamic field, with rapid changes in data analysis tools and approaches. It is important to constantly learn new methods and be prepared for the fact that an analysis pipeline you developed only 2 years earlier may need to be completely updated, if it is not entirely obsolete.