Computational Neuroscience: Neural Dynamics

The exam and course results are now available in the downloads section!

This course provides an introduction into a neural process accounts for perception, motor control, and simple forms of cognition. The vantage point is the dynamical systems approach, which emphasizes the evolution in time of behavior and of neural activation patterns as the basis for understanding how neural networks together with sensory and motor systems generate behavior and cognition. Dynamic stability, a concept shared with the classical biological cybernetics framework, is one cornerstone of the approach. Instabilities (or bifurcations) extend this framework and provide a basis for understanding flexibility, task specific adjustment, adaptation, and learning.

The course will include tutorial modules that provide some of the mathematical foundations. Theoretical concepts will be exposed in reference to a number of experimental model systems such as the perception of motion, visual and spatial working memory, movement planning, and others. In the spirit of Braitenberg´s "synthetic psychology", autonomous robots will be used to illustrate some of the ideas.

Exercises are integrated into the lectures. They consist of elementary mathematical exercises, the design of (thought) experiments and their analysis, and analysis of theoretical models and their relationship to experiment, all on the basis of the theoretical framework exposed in the main lectures. Learning to produce scientific texts with appropriate illustrations and documenting mathematical ideas is one of the learning goals of the course.

Some of the exercises refer to readings, scientific papers that students will study to do the exercises. Learning to read and understand research papers is another learning goal of the course.

Lecturers

Details

Course type
Lectures
Credits
6 CP
Term
Winter Term 2015/2016

Dates

Lecture
Takes place every week on Thursday from 14:15 to 16:00 in room NB 3/57.
First appointment is on 22.10.2015
Exercise
Takes place every week on Thursday from 16:15 to 17:00 in room NB 3/57.
First appointment is on 05.11.2015
Examination
Takes place on 03.03.2016 from 14:15 to 16:15 in room NB 02/99.

Requirements

This course requires some basic math preparation, typically as covered in two semesters of higher mathematics (functions, differentiation, integration, differential equations, linear algebra). The course does not make extensive use of the underlying mathematical techniques, but uses the mathematical concepts to express scientific ideas. Students without prior training in the relevant mathematics may be able to follow the course, but will have to work harder to familiarize themselves with the concepts.

Exercises

Exercises are corrected and held by Oliver Lomp. Details on grading are available in the course rules below.

Exam

The exam will take place on the 3rd of March 2016 from 14:15 to 16:15. Please register for the exam with your degree program where appropriate or, if the program does not require that, with our secretaries. Please note the rules for how the exam is evaluated by reading the "rules for getting credit" sheet in the download list below. Note that these have changed from our last course.

Literature

The course will be based on selected chapters of a forthcoming textbook. The first two chapters are available for download in the course materials below. These and others will also serve as readings for some of the exercises. 

For the mathematical background in dynamical systems an excellent resource is a book that is available online as a free download (thanks to the author's generosity): Edward R. Scheinerman's Invitation to Dynamical Systems.  This book covers both discrete and continuous time dynamical systems, while in the course we will only make use of continuous time dynamical systems formalized as differential equations. 

Documents

Lecture slides Chapter 1 of the textbook
Lecture slides Rules for getting credit
Exercises Exercise 1: Braitenberg vehicles
Lecture slides Chapter 2 of the textbook
Lecture slides Slides of presentation about course organization
Lecture slides Slides of first part of Dynamical Systems Tutorial
Lecture slides Slides of the fourth part of the Dynamic Field Theory core lecture
Lecture slides Slides of final lecture that links DFT to neural dynamics
Exercises Exercise 9: Dynamic Field Theory reading
Lecture slides Exam and course results
Lecture slides Slides of the third part of the Dynamic Field Theory core lecture
Exercises Exercise 8: Dynamic activation fields
Lecture slides Slides of the second part of the Dynamic Field Theory core lecture
Exercises Paper to be read for Exercise 7
Exercises Exercise 7: Population code
Lecture slides Slides of the first part of the Dynamic Field Theory core lecture
Lecture slides Slides of the second part of the Neural Dynamics core lecture
Lecture slides Essay exercise
Lecture slides Slides of the first part of the Neural Dynamics core lecture
Lecture slides Slides of the tutorial on decoding and Bayes' Theorem
Exercises Exercise 6: Neural coding
Lecture slides Slides of the tutorial on coding, tuning curves, maps
Exercises Exercise 5: Neurophysics tutorial
Lecture slides Slides of the tutorial on basic neurophysics
Lecture slides Template MATLAB simulator for exercise 4
Exercises Exercise 4: Dynamical systems tutorial: simulator
Lecture slides Slides of third part of Dynamical Systems Tutorial
Exercises Exercise 3: Dynamical systems tutorial part 2
Lecture slides Slides of second part of Dynamical Systems Tutorial
Exercises Exercise 2: Dynamical systems tutorial part 1
Lecture slides Slides of Braitenberg lecture
Lecture slides Slides of introductory lecture

The Institut für Neuroinformatik (INI) is a central research unit of the Ruhr-Universität Bochum. We aim to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory systems and while acting in those environments through effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental approaches from psychology and neurophysiology as well as theoretical approaches from physics, mathematics, electrical engineering and applied computer science.

Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany

Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210