Ateneo - UPO

The Bioinformatics of Neural Networks course offers an in-depth study of the biophysical mechanisms underlying the genesis, transmission, coding and processing of electrical signals in neurons and nerve networks. For the exercise part, a number of numerical exercises with the R code will be proposed.

Neuroscienze di Dale Purves, George J Augustine, David Fitzpatrick, William C. Hall, Anthony-Samuel Lamantia, Leonard E. White. Zanichelli, Last edition. Additional learning materials provided by the teachers.

The course deals with the biological aspects of neuronal networks such as the anatomical and functional organization of the nervous system, the way information is encoded in individual neurons, its transmission in nervous circuits, the network plasticity and the processing of information in central circuits. Students will explore both basic theoretical aspects and mathematical models as well as some aspects of neuroscience investigation techniques, such as electrophysiology, imaging and optogenetics. Knowledge and understanding: students will acquire the knowledge and ability to understand the molecular mechanisms associated with membrane bioelectric phenomena, the transmission of action potentials in nerve circuits, the effects of electrical activity on network connectivity and how this activity forms the basis of nervous system function Applying knowledge and understanding: the acquired knowledge will allow the student to understand how the neural network encodes and processes information and to apply this knowledge to carry out simple models based on numerical codes. Making judgements: students will be able to critically analyze scientific articles and new information. Communication skills: students will be able to explain, with appropriate scientific language, the contents of the course in a logical and complete way, making connections between the various topics. Learning skills: students will develop the ability to find adequate scientific sources to update and deepen the knowledge and skills acquired. Ability to use analysis software.

Students must possess an adequate basic knowledge of mathematics and statistics, physics, biology and physiology

Theoretical lectures and exercises.

In-depth readings will be assigned in itinere Students with disabilities or Specific Learning Disorders (DSA) or Special Educational Needs (BES) may request specific services and tools dedicated to them by contacting the Career Development and Coordination Staff and Student Services and consulting the dedicated page of the University website: https://uniupo. en/en/servizi/servizi-studenti- disabili-e-dsa Students with disabilities, DSA, BES, once they have made contact with the University Staff, can contact the teacher in charge of the course in relation to the declination of the examination methods, with regard to teaching aspects.

Written exam
For the exercise part, a short report will be requested

Organization of the nervous system. The neuron. The action potential. The synapse. The peripheral nervous system. The central nervous system. The cerebral cortex: anatomical and functional organization and synaptic plasticity.
Biophysics of the neuron and theoretical models. The membrane potential: Nernst-Planck equation, Nernst equation, Goldman-Hodgkin-Katz equation. The equivalent electric circuit model of the cell membrane. Passive membrane properties and cable equations. The Hodgkin-Huxley model. Markovian models for ion channels. Integrate-and-Fire models.
Investigation techniques. Electrophysiological techniques: the patch-clamp technique. Multi-electrode arrays (MEA). Live-imaging microscopy. Optogenetics

Knowledge: mechanisms of coding and information processing in the nervous system, with reference to both single neurons and neuronal populations.
Competences and Skills: ability to analyze and model the activity of neuronal networks.