Neuroimaging
Section committee
BELLANI Marcella
, Chair
BRAMBILLA Paolo,
Co-Chair
ROSSETTI Maria Gloria,
Secretary 
SQUARCINA Letizia,
Councillor 
MAGGIONI Eleonora,
First Other Councillor Section mission
This Section's mission is to:
The EPA Section of Neuroimaging means at inspiring a better understanding of the neural mechanisms underlying psychiatric disorders employing multimodal neuroimaging techniques. Advances in MRI techniques in particular have made it possible to elucidate brain network dysfunction and neurostructural changes in psychiatric disorders. The neuroimaging investigation will contribute to improving risk assessment, diagnosis, treatment and outcome prediction in major psychiatric disorders.
Section objectives
- Our Section aims to promote the knowledge and diffusion of neuroimaging techniques to explore the location and amplitude of morpho-functional changes of the brain in psychiatric diseases.
- To improve the evaluation of validity and reliability of neuroimaging biomarkers.
- To boost learning on connections between neurobiology symptomatology, cognition and global functioning to mitigate the impact of the mental disease on the people’ quality of life.
- To promote testing of specific hypotheses regarding the functional integrity of neural systems implicated in cognition by using ad-hoc tasks designed for functional MRI.
- To promote longitudinal neuroimaging research on at-risk populations to study the timing and development of neurobiological changes associated with the onset of psychiatric disorders and, ultimately,
- To improve cooperation between practitioners and scientists for the application of neuroimaging techniques in psychiatry (e.g. enrich knowledge about the potential advantages of applying neuroimaging
- To collaborate with European consortia on data sharing for high-quality mega-analyses, and, thereby, to increase the quality and reliability of the research findings.
- To improve machine learning, artificial intelligence methods and statistical learning in psychiatric neuroimaging for diagnosis classification and prediction of treatment response and prognosis.