Silvia Francesca Storti

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Foto Storti Silvia Francesca, January 17, 2022
Position
Associate Professor
Academic sector
ING-INF/06 - ELECTRONIC AND INFORMATICS BIOENGINEERING
Office
Ca' Vignal 2,  Floor 1,  Room 80
Telephone
+39 045 802 7908
E-mail
silviafrancesca|storti*univr|it <== Replace | with . and * with @ to have the right email address.
Personal web page
http://vips.sci.univr.it

Office Hours

Thursday, Hours 9:30 AM - 11:30 AM,   Ca' Vignal 2, Floor 1, room 80

Per fissare un appuntamento scrivere a silviafrancesca.storti@univr.it

Curriculum

Research interests

- Brain Computer Interfaces
- 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.)

Proposte di Tirocinio e Tesi

- Analisi della rete cerebrale utilizzando metodi connettività funzionale ed effettiva e teoria dei grafi in applicazioni cliniche (epilessia, stroke, malattie neurodegenerative, ecc.) 
- Modellazione dinamica della connettività funzionale del cervello
- Integrazione di neuroimaging funzionale-strutturale 
- BCIConnect: connettività basata su EEG per brain-computer interface nel controllo di dispositivi robotici 
- Deep Brain Project: analisi delle alterazioni delle sorgenti elettriche e connettività cerebrale tramite EEG in condizione simulata di acque profonde
È richiesta una buona conoscenza dei metodi di elaborazione dei segnali biologici e di Matlab

 

 

Modules

Modules running in the period selected: 17.
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 Biomedical Data and Signal Processing (2021/2022)   6  eLearning 2  (Laboratorio)
4  (Teoria)
PhD in Computer Science Brain Computer Interfaces (2021/2022)   3    3 
Bachelor's degree in Computer Science Probability and Statistics (2021/2022)   6  eLearning 4  (Teoria)
2  (Laboratorio)
Bachelor's degree in Computer Science Biomedical Data and Signal Processing (2020/2021)   6  eLearning 2  (Laboratorio)
4  (Teoria)
PhD in Computer Science Brain Computer Interfaces (2020/2021)   2  eLearning 2 
Bachelor's degree in Computer Science Probability and Statistics (2020/2021)   6  eLearning 2  (Laboratorio)
4  (Teoria)
Bachelor's degree in Computer Science Biomedical Data and Signal Processing (2019/2020)   6  eLearning 4  (Teoria)
2  (Laboratorio)
Bachelor's degree in Computer Science Probability and Statistics (2019/2020)   6  eLearning 4  (Teoria)
2  (Laboratorio)
Bachelor's degree in Computer Science Probability and Statistics (2018/2019)   6  eLearning 4  (Teoria)
2  [Bioinformatica] (Laboratorio)
2  [Informatica] (Laboratorio)

 
 

Research groups

Neuroimaging Group
Vision, Images, Patterns and Signals (VIPS)
VIPS activities are devoted to the analysis, recognition, modeling and prediction of multivariate multidimensional signals and patterns by artificial intelligence and machine learning techniques. Specific expertise and application domains include image processing, computer vision, pattern recognition, machine learning, human-machine interaction, computer graphics, mixed reality and gaming, analysis and modeling of biomedical and neuroscience data for both basic and translational research.
Research interests
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
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
Machine learning
Projects
Title Starting date
EDIPO: A computational solution for bringing neuroimaging genetic into translational research 4/1/20
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



Organization

Department facilities