Measurement and Modeling of the Central Nervous System Function
Mätning och modellering av centrala nervsystemets funktion

EITN65F, 7.5 credits

Valid from: Spring 2017
Decided by: Professor Thomas Johansson
Date of establishment: 2017-02-09

General Information

Division: Electrical and Information Technology
Course type: Course given jointly for second and third cycle
The course is also given at second-cycle level with course code: EITN65
Teaching language: English

Aim

To provide knowledge of how the nervous system works and how it's modeled at various levels, from cellular to higher brain functions. Understanding the processes of nerve impulses at the cellular level, and how these are measured and simulated. Understanding how the cells are connected in simple networks, and how these can be simulated. Understanding how the higher functions can be described, modeled and simulated. To understand how nerve signals can be measured through both invasive and non invasive methods. Understanding the basic electronics impedance, gain, and filtering, which is necessary to measure the signals. Understanding the basic signal analysis of nerve signals that spike sorting and correlation.

Goals

Knowledge and Understanding

For a passing grade the doctoral student must

• Understand how neurons signals arise, connects and propagates
• Understand the modeling of neurons, both individually and in populations.
• Understand the requirements of measurement in order to register the nerve signals both invasive and with surface electrodes.

Competences and Skills

For a passing grade the doctoral student must

• Be able to reason about how the nervous system works at different levels and describe how these can be measured and simulated.
• Be able to describe the function of the nervous system at different levels and be able to set up a simulation of these.
• Be able to describe how nerve signals can be measured in different ways and which the demands are.

Judgement and Approach

For a passing grade the doctoral student must

• Understand the ethical issues in the analysis of signals from the CNS and in the measurement of these.
• Be able to see the limitations of the results of analysis and modeling.

Course Contents

The course consists of lectures and 5 written assignments where students apply the different simulation and modeling methods. Lectures will include operation and modeling of the nervous system at different levels, and review of the simulation tools that will be used. The course also covers methods for nerve signals in vitro and in vivo, and the electronics required for this. The course ends with a small project where the PhD candidate select a problem and simulate its behavior or analyze its signals.

Course Literature

Gerstner, W., Kistler, Werner M., Naud, R. & Paninsk, L.: Neuronal Dynamics. Cambridge University Press, 2014. ISBN 9781107635197.
Book is available at: http://neuronaldynamics.epfl.ch/index.html

Instruction Details

Types of instruction: Lectures, laboratory exercises, project

Examination Details

Examination formats: Written report, written assignments, miscellaneous. Short verbal project presentation.
Grading scale: Failed, pass
Examiner:

Admission Details

Assumed prior knowledge: Basic courses in programming, physiology and signal processing.
Selection criteria: PhD candidates research relevance.

Further Information

Course Coordinator: Anders J Johansson, anders_j.johansson@eit.lth.se

Course Occasion Information

Contact and Other Information

Course coordinators:
Web page: http://www.eit.lth.se/index.php?ciuid=1079&coursepage=6228&L=0