Moses - Models of Higher Brain Functions

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Diese Modulbeschreibung gilt nicht im aktuellen Semester.

Die Modulbeschreibung gilt nur für den Zeitraum SS 2017 - WiSe 2020/21. Die Version für das aktuelle Semester (SoSe 2024) finden Sie hier: Modulbeschreibung des SoSe 2024

Module / Version:
#40078 / #3

Validity:
SS 2017 - WiSe 2020/21

Default display language:
English

Module title:
Models of Higher Brain Functions

Credits:
12

Responsible person:
Sprekeler, Henning

Grading:
benotet

Type of exam:
Mündliche Prüfung

Zugehörigkeit

Faculty:
Fakultät IV

Institute:
Institut für Softwaretechnik und Theoretische Informatik

Area of expertise:
34352100 FG Modellierung kognitiver Prozesse

Prüfungsausschuss:
No information

Kontakt

Office:
MAR 5-3

Contact person:
Sprekeler, Henning

E-mail address:
graduateprograms@bccn-berlin.de

Website:

https://www.bccn-berlin.de/courses-and-modules.html#ui-id-11

Learning Outcomes

Having completed this module, participants will know: - the basic concepts and most important topics in the Cognitive Neurosciences - the state-of-the-art models in these domains and their theoretical foundations. They will understand: - strengths and limitations of the different modeling approaches (e.g. bottom-up versus top-down) - the rationale behind models and their implementation - performance criteria and critical statistical tests. They will be able to: - modify models of cognitive processes - apply existing models to novel experimental paradigms, situations or data.

Content

Cognitive Neuroscience Lecture: - auditory and visual system - natural image statistics and sensory processing - motor system - psychology and neuroscience of attention - memory systems - executive control - decision making - science of free will and consciousness Theoretical Lecture & Analytic Tutorial: Computational models of - visual processing - attention - multisensory integration - decision making - behavioral learning (conditioning, reward learning) - motor control Programming Tutorial: - hands-on experience of the models covered in the lecture, by means of computer simulations in Python.

Module Components

Pflichtgruppe:

All Courses are mandatory.

Course Name	Type	Cycle	Language	SWS
Analytical Tutorial	TUT	SoSe	No information	2
Cognitive Neuroscience	VL	WiSe	No information	2
Programming Tutorial	TUT	SoSe	No information	2
Theoretical Lecture	VL	SoSe	No information	2

Workload and Credit Points

Analytical Tutorial (TUT):

Workload description	Multiplier	Hours	Total
Präsenzzeit	15.0	2.0h	30.0h
Vor-/Nachbereitung	15.0	6.0h	90.0h
			120.0h(~4 LP)

Cognitive Neuroscience (VL):

Workload description	Multiplier	Hours	Total
Präsenzzeit	15.0	2.0h	30.0h
Vor-/Nachbereitung	15.0	2.0h	30.0h
			60.0h(~2 LP)

Programming Tutorial (TUT):

Workload description	Multiplier	Hours	Total
Präsenzzeit	15.0	2.0h	30.0h
Vor-/Nachbereitung	15.0	6.0h	90.0h
			120.0h(~4 LP)

Theoretical Lecture (VL):

Workload description	Multiplier	Hours	Total
Präsenzzeit	15.0	2.0h	30.0h
Vor-/Nachbereitung	15.0	2.0h	30.0h
			60.0h(~2 LP)

The Workload of the module sums up to 360.0 Hours. Therefore the module contains 12 Credits.

Description of Teaching and Learning Methods

The lecture part consists of teaching in front of the class. Participants are expected to rehearse topics after class using the recommended literature. In preparation for the exercises and tutorials they use, in addition, their class notes. Homework assignments are given on a regular basis, and must be usually solved within one week. These assignments cover analytical & mathematical exercises (Analytical Tutorial) as well as numerical simulations & programming exercises (Programming Tutorial). Working in small groups of two to three students is encouraged. Homework assignments and their solutions are discussed during the tutorials. In addition, selected topics presented during the lecture are rehearsed by the tutor as needed.

Requirements for participation and examination

Desirable prerequisites for participation in the courses:

- mathematical knowledge: Some acquaintance with analysis, linear algebra, probability calculus and statistics - basic knowledge about neurobiology and cognitive psychology - basic programming skills, preferably some knowledge of Python - good command of the English language

Mandatory requirements for the module test application:

1. Requirement

Programming Tutorial: complete a sufficient number of the programming assignments

2. Requirement

Analytical Tutorial: gain at least 50% of the points in the homework assignments

Module completion

Grading

graded

Type of exam

Oral exam

Language

English

Duration/Extent

30 Min.

Duration of the Module

The following number of semesters is estimated for taking and completing the module:
2 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

Students must enroll per e-mail (to: graduateprograms@bccn-berlin.de) before the fourth (4th) lecture took place. Registration must include the following information: name, email, study program and university, matriculation number, module components to be taken. Students of the Master program in Computational Neuroscience have to register for the final oral exam at least three working days prior to the examination date. Registration has to be done with the examination office (Prüfungsamt) of TU Berlin. For students from other programs, other regulations may apply. Please consult the examination regulations (Prüfungsordnung) of your program.

Recommended literature
01. "Cognitive Neuroscience - The Biology of the Mind", Gazzaniga, Ivry, Mangun
02. "The Student's Guide to Cognitive Neuroscience", Ward
03. "Essentials of Cognitive Neuroscience", Postle

Assigned Degree Programs

Semester:

Zeige auch ausgelaufene Studiengänge und StuPOs

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

	Studiengang / StuPO	StuPOs	Verwendungen	Erste Verwendung	Letzte Verwendung
This module is not used in any degree program.

Students of other degrees can participate in this module without capacity testing.

Miscellaneous

No information

Models of Higher Brain Functions