- MetaDep project: Investigating the pathophysiology of unipolar depression by combining computational modeling, neuroimaging (fMRI) and behavioural experiments. Partners: Policlinico Umberto I (RM), Università Sapienza di Roma, Santa Lucia Foundation (IRCCS,RM), Donders Institute for Brain and Cognition (NE). Coordinator: Massimo Silvetti
- CATO: Computer Aided Therapy Optimization for unipolar depression. It uses computational modeling (from MetaDep) for generating personalized digital avatars of single patients and testing in silico the efficacy of different pharmacological therapies. Partners: same as MetaDep. Coordinator: Massimo Silvetti
Traditionally, Parkinson’s disease (PD) has been studied by focusing on primary dysfunctions occurring in the basal ganglia, such as the progressive loss of nigro-striatal dopamine transmission. Recently, changes in cerebellar circuits and their interactions with thalamo-cortical and the basal ganglia are also recognized to be significant in the pathophysiology of PD. Moreover, increasing evidence suggests that aside from dopamine other neuromodulatory systems are critically involved such as noradrenergic, serotonergic, cholinergic and other monoaminergic neuronal populations. However, notwithstanding the increasing recognition that PD affects a complex brain network, the most common treatments still target a few subcortical areas, and are designed to reinstate dopaminergic regulation or to inactivate, for example through DBS, abnormal activity mainly in the basal ganglia. While this single area approach is able to alleviate some of the motor impairments, it remains less effective against others (e.g., tremor is often resistant to levodopa, axial and non-motor symptoms can be resistant to DBS) and it is not suitable to address the increasingly recognised multifaceted of PD subtypes. The approach limits the finding of new early prevention strategies and therapeutic actions to the treatment of PD. By contrast, the full recognition that PD affects a complex brain network could explain the vast range of PD manifestations and the variable effects of treatments in different patients and PD subtypes. Moreover, this approach could support the identification of new parameters for personalised early risk prediction, and the search of tailored treatments that aim to address multiple impairments while taking into consideration their complex interdependencies.
- Unraveling gender differences in Parkinson’s disease through explainable machine learning. Partners: Università di Roma Tor Vergata, Università di Pavia. Coordinator: Daniele Caligiore
- Simulating noradrenaline and serotonin depletions in Parkinson’s disease through a bio-constrained differential equations system. Partners: Università di Firenze, IRCSS Fondazione Santa Lucia di Roma. Coordinator: Daniele Caligiore
Despite recent influential data support the role of dopamine and norepinephrine dysregulation in the early pathogenesis of Alzheimer’s disease (AD), the nature of these alterations and their pathophysiological role are not yet elucidated. Understanding these aspects could be important for early diagnosis at pre-plaque stage and to devise new system-level therapies.
- Explainable Machine Learning To Predict And Differentiate Alzheimer’s Progression By Gender. Partners: Università Sapienza di Roma, IRCSS Fondazione Santa Lucia di Roma, Policlinico Umberto I di Roma. Coordinator: Daniele Caligiore
- ExplAIn Medical Analysis (EMA), a project aiming at developing an artificial intelligence system aimed at providing clear and accessible guidance for early diagnosis and monitoring of Alzheimer’s disease progression. Partners: Università Sapienza di Roma, IRCSS Fondazione Santa Lucia di Roma, Policlinico Umberto I di Roma, CNR- Istituto di Tecnologie Biomediche. Coordinator: Daniele Caligiore
- Investigating the pathophysiology of the attention deficit hyperactivity disorder by combining computational modeling, neuroimaging (EEG) and behavioural experiments. Partners: Policlinico Umberto I (RM), Università Sapienza di Roma. Coordinator: Massimo Silvetti
- Investigating the pathophysiology of the Autism spectrum disorders by combining computational modeling and behavioural experiments. Coordinator: Ghent University (BE); ISTC-referent: Massimo Silvetti