Modelling pathophysiology of unipolar depression


  1. 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
  2. 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

Parkinson’s disease as a system-level disorder

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.


  1. Modelling motor learning in Parkinson: Integrating motion capture system, virtual reality and bio-constrained system-level computational modelling to investigate motor learning in Parkinsonian patients. Partners: Università di Genova, Radboud University. Coordinator: Daniele Caligiore
  2. Increasing serotonin to reduce Parkinsonian tremor: Using bio-constrained system-level computational modelling with two aims: (i) to study the neural mechanisms underlying a possible type of PD tremor: the one mainly involving the serotoninergic system; (ii) to study the effect of one possible new drug therapy that builds on the serotonin compensatory role in order to recover dopamine levels in tremor patients. Coordinator: Daniele Caligiore

Modelling pathophysiology of Alzheimer’s disease

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 therapies based on the combined action on dopamine and norepinephrine systems.


  1. Computational modelling of catecholamines dysfunction in Alzheimer’s Disease at pre-plaque stage. Investigating the pathophysiology in early stages of Alzheimer’s Disease (AD) by computational modelling. Partners: Campus Biomedico (RM), Neuromed – Istituto Neurologico Mediterraneo Pozzilli (IS). Coordinators: Daniele Caligiore & Massimo Silvetti
  2. Computational modelling of the early implications of the cerebro-cerebellar network alterations in the cognitive deficits of neurodegenerative diseases. Coordinator: Pierandrea Mirino

Modelling pathophysiology of ADHD


  1. 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

Modelling pathophysiology of autism


  1. Investigating the pathophysiology of the Autism spectrum disorders by combining computational modeling and behavioural experiments. Coordinator: Ghent University (BE); ISTC-referent: Massimo Silvetti

Cerebellum, basal ganglia, cortex as a system

Despite increasing evidence suggesting that cerebellum, basal ganglia and cortex work in concert as a system, the nature of the reciprocal interactions between these three brain regions remains unclear. This research thread aims at investigating these aspects.


  1. How the cerebellum and prefrontal cortex cooperate during associative learning. Coordinator: Daniele Caligiore
  2. Interactions between different learning processes in a model of human motor system. Coordinator: Daniele Caligiore