Silvia Francesca Storti

Foto Storti Silvia Francesca,  September 24, 2013
Temporary Assistant Professor
Academic sector
Ca' Vignal 2,  Floor 1,  Room 64B
+39 045 802 7803
silviafrancesca|storti*univr|it <== Replace | with . and * with @ to have the right email address.
Personal web page

Research interests

- Multimodal functional neuroimaging integration (EEG/high-density EEG, fMRI, ASL, EEG-TMS data)
- Brain functional connectivity inference
- Network analysis in health and clinical applications (epilepsy, stroke, neurodegenerative diseases, etc.)


Modules running in the period selected: 2.
Click on the module to see the timetable and course details.

Course Name Total credits Online Teacher credits Modules offered by this teacher
Bachelor's degree in Computer Science Probability and Statistics (2018/2019)   6  eLearning (Teoria)

Topic Description Research area
Neuroimaging The main activity is in the field of neuroimaging, including structural (diffusion MRI) and functional (EEG, fNIRS, functional MRI) imaging as well as perceptual analysis through cognitive science methods. The goal is to gain an holistic view of human brain when inspected in specific conditions by the integration of multi-modal multi-scale probing and modeling. In addition, advanced computer vision and pattern recognition methods are employed for designing numerical biomarkers for the characterization of healthy and pathological conditions. Bioinformatics and medical informatics
Applied computing - Life and medical sciences
Neuroimaging Data Analysis This domain regards the analysis of data coming from sensing devices measuring the brain strucural and functional information. The main utilised device is Magnetic Resonance Imaging (MRI) in its various modalities such as diffusion, structural, and functional MRI, as well as other sensors like EEG, fNIRS, MEG. The main goal is to better understanding brain functions by means of an integrated functional and structural analysis of the brain connectivity or of specific brain regions. This investigation is mainly performed with reference to neurological disorders - like autism and schizophrenia - and in comparison with control (healthy) subjects. Machine Intelligence
Computing methodologies - Machine learning
Title Starting date
Co-registrazione EEG-fMRI-sEMG nei soggetti normali studio normativo e metodologico 1/1/08
Co-registrazione EEG-fMRI in epilessia 1/1/08
Co-registrazione sEMG-fMRI in pazienti con stroke trattati con tossina botulinica 1/1/08
fMRI con protocollo di stimolazione del nervo mediano in soggetti sani 1/1/08
fMRI con protocollo di stimolazione del nervo mediano in pazienti con stroke in fase acuta 1/1/08
fMRI con protocollo di mobilizzazione passiva in pazienti con stroke in fase acuta 1/1/08
Monitoraggio dell’eccitabilità corticale dopo stroke mediante stimolazione magnetica transcranica 1/1/08
Farmaci e recupero motorio: studio mediante utilizzo di stimolazione magnetica transcranica 1/1/08
Coregistrazione EEG-TMS 1/1/08


Department facilities