Depression affects approximately 332 million adults worldwide, or 5.2% of the global population, according to the World Health Organization (WHO, 2025). In Finland, it is the leading cause of extended illness-related absences and disability pensions. Researchers at the University of Helsinki studied brain activity in 263 individuals diagnosed with major depressive disorder and 75 healthy control subjects.

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The analysis revealed five distinct groups characterized by varying levels of functional connectivity between brain regions. This connectivity measures how well different areas of the brain communicate and function together.

Satu Palva, Director of the Neuroscience Center at the University of Helsinki, noted the interesting diversity in brain activity patterns among individuals with the same depression diagnosis. Some exhibited stronger than normal functional connectivity, while others showed weaker connections.

One specific group displayed notably strong inter-region connectivity linked to more severe substance abuse, while another group with weak connectivity exhibited symptoms more closely related to post-traumatic stress disorder (PTSD).

These findings may help clarify the contradictory results seen in previous depression research, indicating that a single diagnosis can encompass divergent brain activity patterns, suggesting that depression is not a uniform biological condition.

Using magnetoencephalography (MEG), the scientists recorded brain activity in real-time, achieving millisecond precision. This advanced technique allowed for a more immediate understanding of brain function compared to older methods with slower response times, according to Palva.

While brain measurements present a path towards tailored treatments, they currently cannot determine the right therapy for individual patients. Palva emphasized that the aim is to eventually link patients' symptoms to their unique brain activity patterns, potentially streamlining the process of finding effective therapies and moving away from a trial-and-error approach.

This research was conducted in collaboration with Aalto University and the Helsinki and Uusimaa Hospital District (HUS). The findings were published in the article titled "Magnetoencephalography oscillation-based functional connectivity identifies clinically relevant depression phenotypes" in Nature Mental Health (2026). DOI: 10.1038/s44220-026-00723-4.