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
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.)
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 running in the period selected: 13.
Click on the module to see the timetable and course details.
Course | Name | Total credits | Online | Teacher credits | Modules offered by this teacher |
---|---|---|---|---|---|
PhD in Computer Science | Brain Computer Interfaces (2021/2022) | 3 | 3 | ||
Bachelor's degree in Computer Science | Biomedical Data and Signal Processing (2020/2021) | 6 |
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4 | (Teoria) |
2 | (Laboratorio) | ||||
PhD in Computer Science | Brain Computer Interfaces (2020/2021) | 2 |
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2 | |
Bachelor's degree in Computer Science | Probability and Statistics (2020/2021) | 6 |
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4 | (Teoria) |
2 | (Laboratorio) | ||||
Bachelor's degree in Computer Science | Biomedical Data and Signal Processing (2019/2020) | 6 |
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4 | (Teoria) |
2 | (Laboratorio) | ||||
Bachelor's degree in Computer Science | Probability and Statistics (2019/2020) | 6 |
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4 | (Teoria) |
2 | (Laboratorio) | ||||
Bachelor's degree in Computer Science | Probability and Statistics (2018/2019) | 6 | 2 | [Bioinformatica] (Laboratorio) | |
2 | [Informatica] (Laboratorio) | ||||
4 | (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
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 |
Office | Collegial Body |
---|---|
member | Council of the PhD School in Computer Science A.Y. 2018/2019 - Department Computer Science |
member | Collegio Didattico di Informatica - Department Computer Science |
member | Commissione Paritetica Docenti-Studenti Scienze e Ingegneria - Science and Engineering |
member | Computer Science Department Council - Department Computer Science |