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Seit SS 2018

English

Stochastic processes in Neuroscience II

5

Stannat, Wilhelm

benotet

Mündliche Prüfung

Zugehörigkeit


Fakultät II

Institut für Mathematik

No information

Mathe

Kontakt


MA 5-1

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wilhelm.stannat@tu-berlin.de

No information

Learning Outcomes

Participants will learn advanced concepts, their theoretical foundation, and the most common models of stochastic processes used in computational neuroscience to model complex noisy neural systems. Participants will learn simulation techniques and how to evaluate simulation output. Participants will learn to adapt models to new problems as well as to develop new models of neural systems.

Content

This module provides advanced knowledge about the mathematical modeling, analysis and numerical simulation of complex neural systems under the influence of noise using stochastic processes. Specific topics addressed are: coupling of neurons, cooperative phenomena in neural networks, in particular in stochastic reaction diffusion models (synchronization, waves), continuum limits of neural networks (strong and weak coupling, reaction diffusion systems and neural field equations)

Module Components

Pflichtgruppe:

All Courses are mandatory.

Course NameTypeNumberCycleLanguageSWSVZ
Stochastische Prozesse in den NeurowissenschaftenVL3236 L 209WiSe/SoSeNo information2

Workload and Credit Points

Stochastische Prozesse in den Neurowissenschaften (VL):

Workload descriptionMultiplierHoursTotal
Attendance15.02.0h30.0h
30.0h(~1 LP)

Course-independent workload:

Workload descriptionMultiplierHoursTotal
Preparation and follow-up15.06.0h90.0h
Exam preparation15.02.0h30.0h
120.0h(~4 LP)
The Workload of the module sums up to 150.0 Hours. Therefore the module contains 5 Credits.

Description of Teaching and Learning Methods

Lecture

Requirements for participation and examination

Desirable prerequisites for participation in the courses:

Wahrscheinlichkeitstheorie I und II, Stochastische Prozesse in den Neurowissenschaften I

Mandatory requirements for the module test application:

This module has no requirements.

Module completion

Grading

graded

Type of exam

Oral exam

Language

German/English

Duration/Extent

No information

Duration of the Module

The following number of semesters is estimated for taking and completing the module:
1 Semester.

This module may be commenced in the following semesters:
Winter- und Sommersemester.

Maximum Number of Participants

This module is not limited to a number of students.

Registration Procedures

Standard

Recommended reading, Lecture notes

Lecture notes

Availability:  unavailable

 

Electronical lecture notes

Availability:  available

 

Literature

Recommended literature
Ermentrout, Terman, Foundations of Mathematical Neuroscience, Springer 2010
Klenke, Probability Theory - a comprehensive course, Springer 2008
Lang, Lord, Stochastic Methods in Neuroscience, Oxford University Press 2009
Oksendal, Stochastic Differential Equations, Springer 2010

Assigned Degree Programs


This module is used in the following Degree Programs (new System):

Studiengang / StuPOStuPOsVerwendungenErste VerwendungLetzte Verwendung
Mathematik (B. Sc.)113SS 2018SoSe 2024
Mathematik (M. Sc.)113SS 2018SoSe 2024
Technomathematik (B. Sc.)113SS 2018SoSe 2024
Technomathematik (M. Sc.)113SS 2018SoSe 2024
Wirtschaftsmathematik (B. Sc.)113SS 2018SoSe 2024
Wirtschaftsmathematik (M. Sc.)113SS 2018SoSe 2024

Miscellaneous

No information