Sezione di Biostatistica, Neurofisiologia, Psichiatria

Neurophysiology Unit

The NEUROPHYSIOLOGY UNIT coordinated by Egidio D’Angelo is generating state of the art concepts, models and theories about brain functioning with special focus on the cerebellum. The unit operates on various projects on the front of experimental research in cellular/molecular neuroscience, computational modelling and integrative brain functions in health and disease.

The work is supported by the Human Brain Project, the EU flagship for brain research that operates EBRAINS, the international neuroinformatic platform for brain modelling. Other projects involve the EU (ETN: Cerebellar Emotional Networks), the Brain Connectivity Center of IRCCS Mondino and the Centro Fermi (Multiscale modelling of brain pathologies).

The Laboratory is composed by three laboratories:

  • The Neurophysiology Lab investigates plasticity and computation in cerebellar neurons and microcircuits. The laboratory provides the ideal environment to investigate physiology from subcellular mechanisms to network dynamics and behavior. The laboratory is equipped with electrophysiology setups for single-cell patch-clamp, intracellular calcium imaging, two-photon calcium imaging, voltage-sensitive dye imaging, optogenetics in vitro and in vivo, multielectrode arrays in vitro (high-density MEA) and in vivo. There are facilities for cellular and molecular biology.
  • The Neurocomputation Lab elaborates advanced computational models of neurons and microcircuits. The models are generated from and validated against experimental data at various levels, are passed through various steps of validation and simplification, and are then used to generate closed-loop robotic controllers and virtual brains. A dedicated cluster computing facility is used for data elaboration and modelling.
  • The Neuroimaging and Brain Modelling Lab investigates the relationship between brain structure, function and dynamics based on MRI techniques and Virtual Brain Modelling. Research is addressing issues related to motor control and cognition along with their pathological counterparts (including ataxia, autism, AD etc.).

Research is focused on the multiscale analysis and modelling of the brain and aims to:

  • understand the molecular/cellular mechanisms of neurons, synapses and microcircuits
  • clarify the meso-scale and large-scale processes in which local microcircuits are involved
  • simulate dynamic control of plasticity in trial-and-error learning
  • integrate the models into large-scale circuits of robots and virtual brains.

This research is coordinated with the development and refinement of experimental and neuroinformatic tools and occurs in collaboration with several national and international research centers and companies. The models are exploited for simulations of pathological alterations of plasticity and circuit dynamics generating multiple fall-out on brain modelling, theoretical understanding of brain functions and diseases, and infrastructure implementation.

 

Medical and Genomic Statistics Unit

The Unit of Medical and Genomic Statistics headed by Prof. Luisa Bernardinelli, is involved in the development of innovative statistical methodology prompted by challenging scientific problems spanning a wide range of applications. A relevant activity also concerns data analysis of observational, experimental and quasi experimental studies in collaboration with clinicians.

The Unit is equipped with a server HP Proliant DL580 gen9 384 GB RAM 120 cores to perform large scale genetic and epigenetic analysis using innovative bioinformatics tools.

The Unit is organized in four Laboratories whose activity is described below.

Statistical Genetics and Genomics Lab (( Prof.ssa L. Bernardinelli)-Dr D. Gentilini) The main research activity of the Lab is to investigate causal mechanisms in chronic disorders via the integration of genetics, epigenomics and gene expression data. The study of rare genetic and epigenetic variants and their role in the development of chronic-degenerative diseases represents a further field of interest. The Lab has developed a web platform with over 30 free applications for statistical data analysis used by over 30,000 people in over 180 countries around the world.

RECENT STATISTICAL METHODOLOGY

Bayesian approach to Causal inference via Mendelian Randomization, joint analysis of genetic and gene expression data to identify genes causally related to Multiple Sclerosis. Analysis of microarray, methylation and proteomic data. Analysis of pedigree data. Analysis of next generation sequencing data. Statistical approaches to study the effect of rare genetic and epigenetic variants on phenotypic traits.

RECENT EPIDEMIOLOGICAL INVESTIGATIONS. Identification of susceptibility genes of multiple sclerosis in the Nuoro province. Investigation of the biological function of ACCN1 and multiple sclerosis in  an animal experiment. Identification of causal blood biomarkers in multiple sclerosis  and of  causal brain gene expression via a Mendelian Randomization approach. Evaluation of  the effect of nutraceutic products in obesity. As to Covid-19 : investigation of the beneficial role of renin-aldosterone system inhibitor antihypertensives (with impactful implications on therapeutic practice) and of the value of dynamic clinical and biomarker data for mortality risk prediction. Development and validation for an individualized clinical prediction model to forecast psychotic recurrence in acute and transient psychotic disorders. NGS analysis in Marfan syndrome spectrum. Epigenome Wide Association and Stochastic Epigenetic Mutation Analysis on Cord Blood of Preterm Birth.

Statistics for Contemplative Sciences Lab (Prof.ssa L. Bernardinelli)). The Lab investigates the beneficial causal effects of meditation training on physical and psychological wellbeing in the general population, in the work environment, in people affected by insomnia and in medical students. The Lab organizes meditation intervention classes and performs the study design and the statistical analysis of the data collected.
Multivariate Statistics Lab ( Prof. M. Grassi). Lab had experience in interdisciplinary collaborations (see below) and a track record of applying multivariate statistics based on structural causal modelling, graphical modelling and network analysis, and recently in machine learning (random forests and causal structure discovery) often with original solutions for the analysis of genomic and genetic data and for the modeling of MRI data in the studies of brain dysfunctions (see Figure below). Lab has a long expertise as R user and package developer, recently SEMgraph package for Causal Network Analysis of High-Throughput Data with Structural Equation Models is load in GitHub and CRAN archives.

RECENT INVESTIGATIONS. Lab collaborates with large multi-centric projects both italian (IPSYS: Italian Project on Stroke in Young Age, MUCH: The Multicenter Study on Cerebral Haemorrhage in Italy; STROKOVID-19 network) and international (IFGC: International Frontotemporal Dementia Genetics Consortium, GENFI: Genetic Frontotemporal dementia Initiative) applying on several articles published in indexed peer-reviewed and leader neurology journals (brain, jama neurology, Annals of Neurology, …) innovative statistical methodology (see above).

From: Frontiers in Neuroscience 2019: doi: 10.3389/fnins.2019.00211)

Clinical Epidemiology Lab (Prof. M. Comelli)

The present research work concerns the application of mixed general and survival models in clinical epidemiology. Attention focuses on the selection and validation of the appropriate probability and statistical models for epidemiological research. The substantive relevance of the models’ estimates and predictions, in the different fields where they are applied (Dentistry, Infectious Diseases, Nephrology, Neurology, Psychiatry, Physical Rehabilitation etc.) is given the utmost consideration.

 

Psychiatry Unit

The Psychiatry Unit directed by Prof. Pierluigi Politi conducts its research activity on several psychiatric conditions, focusing especially on schizophrenia spectrum and autism spectrum disorders.

In the recent years, the Psychiatry Unit coordinated several projects on PSYCHOSIS AND SCHIZOPHRENIA SPECTRUM. Specifical focuses concern:

  • Alterations in exteroceptive and interoceptive sensory channels and their relationship with psychotic symptoms;
  • The factors defining the self/other boundary in individuals with these conditions, such as world/self ambivalence and source monitoring;
  • The characterization of neurofunctional dynamics determining the core symptoms of psychosis and acute phases of schizophrenia.

The AUTISM LABORATORY is a research center developed since the ’80s and currently directed by Prof. Pierluigi Politi. The laboratory focuses on the evolution of autism in adult individuals, taking into consideration clinical and social aspects of this condition. The laboratory actively cooperates with other local facilities, including those of the Psychiatric Operating Unit, the residential adult center Cascina Rossago, and the daycare center “Il Tiglio”.

Current research activity in the Autism Laboratory includes the following projects:

  • Study of the potential associations between sensory, behavioral and biological indicators in adults with autism and intellectual disability, and investigation of possible clinical sub-phenotypes on the basis of such associations;
  • Reading comprehension in high-functioning autistic individuals, neurotypical individuals and “bad readers” (with reading comprehension disturbances). Participants will be asked to make both physical and mentalistic inferences concerning a written text. The study will be followed by a training of mental inferences employing stories and excerpts;
  • Assessment of performance of autistic individuals in source monitoring tasks, measuring the ability to correctly attribute stimuli, experiences, and memories to correct sources. Among the potential implications, the role of metacognition and the capacity to move perspective from self to other are considered;
  • Use of complementary and alternative therapies in autism spectrum disorders, with the aim of improving specific symptoms and comorbidities. Critical evaluation of the dissemination of certain practices, applications, efficacy, risk profile and demographical pattern of use;
  • Study and revision of outcome tools used for the evaluation of therapeutic interventions in autism spectrum disorders, with specific focus on the assessment of core symptoms;
  • Evaluation of the brain-gut axis in autism spectrum disorders;
  • Evaluation of wearable sensors for the definition of emotional states in autism spectrum disorders;
  • Evaluation of clinical phenotypes connected with acoustic sensitivities in autism spectrum disorders.