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Juha Gogulski develops personalized brain stimulation therapy for depression

With the support of a Fellow grant from Instrufoundation, Juha Gogulski aims to identify a biomarker - essentially a 鈥渇ingerprint鈥 of brain activity - that could predict which type of treatment would work best for each patient.
Juha Gogulski, kuva: Matti Ahlgren, Aalto-yliopisto
Juha Gogulski on Otaniemi campus. Photo: Matti Ahlgren.

Aalto University postdoctoral researcher and Instrufoundation Fellow grant recipient Juha Gogulski is developing individualized brain stimulation treatments for patients with depression.

Juha Gogulski鈥檚 research focuses on repetitive transcranial magnetic stimulation (rTMS). In this treatment, a rapidly changing magnetic field induces electrical currents in the brain, activating neurons and helping them to re-wire. The idea is that in depression, the activity of certain brain circuits is reduced, and stimulation may help normalize this activity.

鈥楻epetitive stimulation is typically applied in a one-size-fits-all manner. In theory, there is almost an unlimited number of parameter combinations, but we are not yet able to determine which ones work the best for each individual,鈥 Gogulski says.

His research aims to address this challenge. The project combines TMS with electroencephalography (EEG). Together, these methods are used to identify a biomarker - essentially a 鈥渇ingerprint鈥 of brain activity - that could predict which type of treatment would work best for a specific patient.

If such a biomarker can be developed, depression treatment could in the future be tailored based on measured brain activity, rather than relying on trial-and-error between different treatment options.

Exceptional research setup

The research is conducted at the Department of Neuroscience and Biomedical Engineering at Aalto University, where an exceptional research setup is available: a system of five overlapping TMS coils. Only four such systems exist worldwide. This setup allows stimulation to be precisely targeted to different brain regions without physically moving the coils. The stimulation target and other parameters can be adjusted electronically while simultaneously measuring the brain鈥檚 electrical responses.

The study also utilizes Aalto鈥檚 MRI resources, advanced analysis methods, and a high-performance computing cluster.

鈥榃e are analyzing a clinical dataset of depression patients who have undergone TMS鈥揈EG measurements across multiple brain regions. The dataset is unique, partly because highly precise methods have been used to ensure signal quality. Based on this data, we are building and validating a biomarker that could help select the optimal treatment pathway for each patient in the future,鈥 says Gogulski.

If successful, the impact could be significant for both patients and the healthcare system. But first, the researchers need to understand deeply how the brain responds to stimulation and which signals predict treatment response.

鈥業n that case, depression treatment would no longer rely on a 鈥榯ry and see鈥 approach. Treatment could be adjusted based on measured brain activity already during the treatment course, potentially improving outcomes and shortening treatment courses,鈥 Gogulski adds.

Gogulski began his studies in physics at University of Helsinki, but later sought work more closely connected to people and medicine. Medical studies quickly led him into neuroscience.

Now, the Instrufoundation Fellow grant is significant for Gogulski both personally and scientifically. The fellowship allows him to build his own line of research.

鈥楻eal breakthroughs often arise from long-term basic research. That is why grants play a crucial role in research. They enable the groundwork upon which new treatment methods can later be built.鈥

: Tia H盲rk枚nen, Instrufoundation

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