|SCIENTIFIC DISCIPLINARY SECTOR||ING-INF/06|
The aim of the course is to introduce the state-of.the art in the field of neural-interfaces. Hardware interfaces (neuro-electronic systems); techniques for measuring the electrophysiological activity of excitable cells and tissues; analysis techniques for neuronal signal analysis (from micro-to-macro; from patch-clamp to EEG). Introduction to functional connectivity (connectome) and interplay between connectivity and dynamics (dynome). Introduction to code of information in neuronal systems and brain-machine-interface (BMI).
Neuro-electronic interface modeling, transducers and measurement techniques for electrophysiology: in-vivo and in-vitro. Specific analysis techniques for neuronal electrophysiological signals. Problem of coding and transmission of information in neural systems.
Modeling of the neuro-electronic interface: capability to model wet-wardware interface (circuital models)
Techniques for electrophysiology and applications: ability to develop and use an experimental set-up from micro-to-macro (Micro Electrode Arrays; EEG)
Analysis techniques for neuronal signals: understanding algorithms for signal analysis; ability to implement algorithm for point-process and (introduction) time series.
Code of information and information transmission: ability to focus on the main issue about neural code and information transmission (connectivity and dynamics)
Fundamental of chemistry, biophysics, mathematics, electronics and computer science provided during the first three years of the Laurea in Biomedical Engineering.
Combination of traditional lectures (40 hours) and classroom discussion of the scientific paper presentations selected by each student (10-15 hours). Lab activities - optional (8 hours)
Modeling of the neuro-electronic interface: theoretical models of the solid-liquid interface; polarizable and not polarizable interface; Microtransducers and electrophysiological techniques; Micro Electrode, Silicon Transistors, Organic Transistors.
Techniques for electrophysiology and applications: in-vitro and in-vivo electrophysiology, intra-cellular and extracellular measurements, patch clamp; single cell recordings, network electrophysiology.
Analysis techniques for neuronal signals: spike and burst detection algorithms; statistical analysis and multiple spike train analysis (ISI, J-ISI, C-ISI, IBI); cross-correlation analysis; functional connectivity
Code of information and information transmission: neuronal input-output response; information theory applied to neuronal signals; entropy and mutual information; neuronal avalanches and self-organized criticalities.
SERGIO MARTINOIA (President)
GABRIELE ARNULFO (President Substitute)
MICHELA CHIAPPALONE (President Substitute)
All class schedules are posted on the EasyAcademy portal.
Public presentation of a selected Journal Paper on arguments related to the course. Presentation by two students are encouraged. Written exam oreinted to the solution of specific problem-exercise and theoretical questions.
The exam is constituted by the study and presentation of a scientific paper and by an additional written and oral examination.
|18/02/2021||09:00||GENOVA||Esame su appuntamento|
|17/09/2021||09:00||GENOVA||Esame su appuntamento|
Office: Via All’Opera Pia 11 A
Lab: Neuroengineering and Neurotechnologies, Via All’Opera Pia 13 (level -1)