Project Lines

11.2022 - 02.2026

Advanced brain imaging for mood and psychotic disorders

Funding: PNRR

Work Package 4 focuses on employing advanced neuroimaging techniques (fMRI and MEG) for the study of mood and psychotic disorders. The goal is to develop machine learning algorithms that can predict the clinical evolution of high-risk individuals, identify common and distinct neurobiological features of schizophrenia and bipolar disorder, and improve differential diagnosis through multimodal approaches. The integration between genetics, clinical data and neuroimaging will allow the identification of biological markers and functional patterns useful for understanding the pathophysiological mechanisms underlying disorders, facilitating prevention strategies, early diagnosis and therapeutic personalization. The project involves five universities (UNIBA, UNIGE, UNIPV, UNIBO, UNICAMPANIA) in an interdisciplinary approach, aimed at the definition of standardized pipelines and multi-site validations to improve diagnostic accuracy, with a view to personalizing the treatments of major psychiatric disorders.

The planned deliverables open up important clinical and translational applications. Predictive algorithms based on fMRI and MEG could support the early estimation of the severity of symptoms and the cognitive profile of people at risk, guiding personalized preventive interventions. The identification of common and differentiated neurobiological signatures in schizophrenia and bipolar disorder may contribute to identifying new diagnostic markers and potential therapeutic targets, favoring the development of targeted treatments. Finally, multimodal machine learning solutions could support the differential diagnosis between mood disorders and psychosis in pilot studies and after external validation, from a precision medicine perspective. Such tools can be validated in independent samples and integrated into health systems, with the aim of reducing misdiagnoses, optimizing therapeutic pathways and improving the prognosis and quality of life of patients.

TRL: 5

Cluster applicativi:
A.I., Health, Healthcare, Life Sciences, Lifescience