Principles of Computational Neuroscience (blended + hands-on with UniTs)

Dr. Michele Giugliano

Amount of frontal teaching:
28 hours


Computational Neurosciences is a multidisciplinary field that studies brain functions and dysfunctions and how information is processed by cells and circuits, by ultimately building mathematical models and numerically simulating them on computers, aiming at tackling scientific questions that are relevant for the understanding of the brain. These models are often, but not always, intimately grounded in first-principle biology, biochemistry, physics, and electromagnetism, so that the processes within individual nerve cells, synapses, and networks are described like a real pendulum can be studied by pen and paper, by a simple formula and a series of parameters.

Through this course, students will increasingly start making quantitative judgements of cell electrophysiology and biophysics, analysing how significant discoveries could be made in these domains and where the availability of solid theoretical and computational tools revealed to be extremely fruitful. Students will become fluent in this language and skills. Students will be presented by a quantitative style of analysis of neural systems, as an opportunity to expand their learning skills towards "synthesis", "quantitative analysis", and "in silico investigation" in Neurobiology. 

The course covers the following topics:

  1. Introduction
  2. Mathematical Refresher
  3. Neuroelectronics
  4. The Hodgkin-Huxley model
  5. Synaptic Transmission
  6. Short-term synaptic plasticity
  7. Simplified Spiking Neuronal Models
  8. Firing-Rate Population Models



The course website, containing teaching aids, resources, handouts, videos, links, references and prerequisite material is available to SISSA's personnel by clicking here.





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