RANALDI SIMONE
(syllabus)
Part I: electrical models of the neurons
Introduction to neural engineering
Passive models of excitable cells
Active models: Hodgkin-Huxley
Part II: neural signal processing
Mathematical models of spiking neural activity
Algorithms for spike detection
Algorithms for spike sorting
Practical implementations using Python
Part III: motor control
Introduction to motor control theories
Modular motor control
Muscle synergy analysis
Practical implementation using Python
(reference books)
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.
Aurelien Geron (2019). Hands on Machine Learning. O’Reilly
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