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Computational Neuroscience

General data

Course ID: 1100-5NI11
Erasmus code / ISCED: (unknown) / (unknown)
Course title: Computational Neuroscience
Name in Polish: Modelowanie komputerowe układu nerwowego
Organizational unit: Faculty of Physics
Course groups: (in Polish) ZFBM, II stopień; Neuroinformatyka
Course homepage:
ECTS credit allocation (and other scores): 7.50 Basic information on ECTS credits allocation principles:
  • the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS;
  • the student’s weekly hourly workload is 45 h;
  • 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes;
  • weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS;
  • work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load.

view allocation of credits
Language: Polish
Prerequisites (description):

This course provides an introduction to the field of theoretical and computational neuroscience.



Short description:

We will explore the models and computational principles governing various aspects of neuronal dynamics, including passive membrane properties, active currents and action potentials, synaptic transmission, generation of rhythmic activity and synchronization. We will also develop computational models at the mesocopic scale.

We will make use of Simulink and Neuron simulation software

Full description:

1. Introduction to Matlab and Simulink

2. Population models - alpha rhythm model of Lopes da Silva

3. Introduction to Neuron, building simple models using graphical user interfaces.

4. Theory - resting membrane potential

5. Simulation of resting membrane potential

6. Theory - action potential

7. Simulations of action potential

8. Membrane currents and their influence on neuron's firing pattern

9. Theory - synaptic transmission

10. Simulations of synaptic transmission

11. Simple models in hoc language

12. NMDL language

13. Object oriented programming in hoc.

14. Integrate and fire (IF) neuron model

15. Networks of IF neurons

15. Realistic neuronal neurons

Student's workload:

75h - attending the lectures - 5 ECTS

30h - preparations for the lectures - 1 ECTS

45h - final project - 1.5 ECTS

Total: 7.5 ECTS


Nicholas T. Carnevale, Michael L. Hines The NEURON Book, Cambridge University Press, 2006 (free pdf)

Peter Dayan and Laurence F. Abbott Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems, MIT Press, 2001 (free pdf)

Wulfram Gerstner and Werner M. Kistler, Spiking Neuron Models: Single Neurons, Populations, Plasticity, Cambridge University Press, 2002 (free html)

D. Johnston and S. M. Wu Foundations of Cellular Neurophysiology, MIT Press 1995

Learning outcomes:

Students will learn how mathematical and computational tools can be used to understand the dynamics of neurons, neural networks and generation of some of the EEG rhythms.

Assessment methods and assessment criteria:

An individual project

Presence in the classroom has no influence on the final grade, yet it is encouraged.

Participation in the course allows to obtain 5 ECTS for the Student Group Project. Group projects should be performed in groups of 3-5 students and should be documented in the publicly available final report.

Practical placement:

Not applicable

Classes in period "Winter semester 2023/24" (in progress)

Time span: 2023-10-01 - 2024-01-28
Selected timetable range:
Navigate to timetable
Type of class:
Classes, 45 hours, 20 places more information
Lecture, 30 hours, 20 places more information
Coordinators: Piotr Suffczyński
Group instructors: Piotr Suffczyński
Students list: (inaccessible to you)
Examination: Course - Grading
Lecture - Grading
Course descriptions are protected by copyright.
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