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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:	https://www.fuw.edu.pl/~suffa/Modelowanie/
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.
Mode:	Classroom
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
Bibliography:	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: weekly course term Navigate to timetable MO TU WYK W TH CW FR
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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