Computational Neuroscience: Vision and Memory

Due to the corona crisis this course will be offered as an online course in SS 2020.

I offer a pre-meeting 17.4. 11:00 to get used to the virtual room I am going to use and discuss the format.

Mor information is available at the moodle course, where RUB students should be able to log in without password.

This lecture covers basic neurobiology and models of selforganization in neural systems, in particular addressing

  • Learning
    • Hebbian Learning
    • Neural learning dynamics and constrained optimization
    • Dynamic field theory
  • Vision 
    • Receptive fields
    • Neural maps
  • Hippocampus
    • Navigation
    • Episodic memory
    • Hopfield Network

Lecturers

Details

Course type
Lectures
Credits
6 CP
Term
Summer Term 2020
E-Learning
moodle course available

Dates

Lecture
Takes place every week on Tuesday from 12:15 to 13:45 in room virtual.
First appointment is on 21.04.2020
Last appointment is on 14.07.2020
Exercise
Takes place every week on Tuesday from 10:30 to 12:00 in room virtual.
First appointment is on 28.04.2020
Last appointment is on 14.07.2020

Requirements

Good mathematical skills, linear algebra and calculus

Documents

Link Moodle course page: https://moodle.ruhr-uni-bochum.de/m/course/view.php?id=26613

The Institut für Neuroinformatik (INI) is a research unit of the Faculty of Computer Science at the Ruhr-Universität Bochum. Its scientific goal is to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory and 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 psychology and neurophysiology as well as machine learning, neural artificial intelligence, computer vision, and robotics.

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

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