Projects at Turku Mood and Memory Lab

We aim to investigate currently used psychotherapeutic protocols in Finland, focusing on their efficacy, cost-effectiveness, as well as moderating factors related to patient-related features, such as comorbidity and medication use, as well as therapist- and therapy modality -related factors.

The project uses separate datasets: 1) A long-term psychotherapeutic treatment protocol combining schema therapy and dialectical behavior therapy for borderline personality disorder, currently being conducted in Satasairaala. We will assess the feasibility, cost-effectiveness, and psychiatric outcomes of this treatment protocol for patients attending the psychotherapy program. We will use both qualitative and quantitative methods to assess outcomes. 2) We draw on national registries (Kela rehabilitative long-term psychotherapy) to investigate the real-world relative effectiveness of different psychotherapy frameworks for depression and anxiety for clients undergoing rehabilitative long-term psychotherapy. We aim to also investigate differences in effectiveness between individual psychotherapists, thus illuminating the significance of therapist-related factors in psychotherapy outcomes.

The project contributes to understanding the context-specific effectiveness of psychotherapeutic interventions, thus aiding in establishing more targeted and cost-effective treatments for common mental disorders.

The Turku IMAGEN project ultimately aims to identify modifiable risk factors for aberrant ageing of the brain and mind. As proof-of-concept, we are currently building an analysis and data management pipeline to a) reconcile differences between clinically-acquired brain MRIs, b) extract versatile structural parameters from the MRIs, c) constitute a large dataset that combines the brain MRI parameters with diverse Auria biobank data. 

The project builds a database of ca. 4,400 MRI scans taken of people with cognitive decline and controls, combining this data with extensive metabolic, clinical, and genetic information gathered by the Auria biobank. All regulatory procedures are completed, and as of February 2026, volumetric brain data calculated with state-of-the-art automated methods from 1600 subjects are being combined with the biobank data. 

Using this novel information-rich database, we will analyse neural correlates of mental health and examine how mood symptoms, metabolic, genetic, and other health variables relate to brain ageing, cognitive performance, memory disorders, and overall mental well-being. A ca. 50% longitudinal subcohort with repeated MRIs enables tracking trajectories over time and strengthens causal inference.

With a multidisciplinary approach bridging psychiatry, neurology, and data science, the project contributes to the understanding of mental health’s relation to brain ageing. We are enriching the collaborating Auria biobank with a world-class brain imaging dataset and increasing laboratory competencies on automated analyses of brain imaging data relevant to mental health, ultimately aiming to identify actionable targets for promoting healthy brain ageing.