To gain specific knowledge in theories, methods and technologies for understanding and analysing the functionality of the human nervous system. In particular, the course gives practical examples of applications in the field of assistive technologies in disability, like brain computer interfaces and neuroprosthetics.
teacher profile teaching materials
- introduction to neural engineering, definitions, fields of application, past and present technologies.
- focus of the course: recording from the nervous system, stimulating the nervous system, extracting features, defining models.
Part 1 - from anatomy to function: neuron models
- basics of anatomy of the nervous system, basics of activity of the nervous system, neural cell structure, neural cell functioning, resting potential, action potential generation and propagation
- passive neuron models
- active neuron models: if, h-h, fh-n.
Part 2 - interfacing and recording data from the nervous system
- obtaining information from the nervous system: bioelectrodes, technological solutions for transforming ion currents into electronic currents
- neural recording: microelectrodes
- biopotentials: models of the spiking activity.
Part 3 – extracting information from the nervous system
- spike detection
- spike sorting
- activity 1: spike detection and sorting from neural signals
- activity 2: neural system - model identification - muscle synergies
He, B. (Ed.). (2007). Neural engineering. Springer Science & Business Media.
Programme
Basics of neural engineering- introduction to neural engineering, definitions, fields of application, past and present technologies.
- focus of the course: recording from the nervous system, stimulating the nervous system, extracting features, defining models.
Part 1 - from anatomy to function: neuron models
- basics of anatomy of the nervous system, basics of activity of the nervous system, neural cell structure, neural cell functioning, resting potential, action potential generation and propagation
- passive neuron models
- active neuron models: if, h-h, fh-n.
Part 2 - interfacing and recording data from the nervous system
- obtaining information from the nervous system: bioelectrodes, technological solutions for transforming ion currents into electronic currents
- neural recording: microelectrodes
- biopotentials: models of the spiking activity.
Part 3 – extracting information from the nervous system
- spike detection
- spike sorting
- activity 1: spike detection and sorting from neural signals
- activity 2: neural system - model identification - muscle synergies
Core Documentation
Horch, K. W., & Dhillon, G. S. (Eds.). (2004). Neuroprosthetics: theory and practice (Vol. 2). World Scientific.He, B. (Ed.). (2007). Neural engineering. Springer Science & Business Media.
Type of evaluation
The final exam is composed of a written/practical part lasting 3.5 hours, and an oral colloquium. The written part contains a set of numerical exercises, while the practical part is based on neural signal processing in Matlab. The oral part will start from the discussion of the written/practical exam, followed by a colloquium on the topics of the course.