inf963 - Foundations of STS Eng.: Cognitive Processes (Course overview)

inf963 - Foundations of STS Eng.: Cognitive Processes (Course overview)

Department of Computing Science 6 KP
Module components Semester courses Wintersemester 2022/2023 Examination
Lecture
Exercises
Hinweise zum Modul
Prerequisites

No participant requirement

Reference text

The module will be offered in winter terms and should be completed within one semester. Both parts will run in parallel

Prüfungszeiten

At the End of the lecture periods

Module examination

Written exam. A bonus system will be employed.

Skills to be acquired in this module

The module aims to provide an overview of theories of cognitives processes.
Part 1 will be a lecture on neurocognition. Students will first acquire a general understanding of the brain mechanisms of different cognitive functions and the methods used to study these functions:

  • brain and cognition, methods of cognitive neuroscience
  • attention, learning and memory
  • emotional and social behavior
  • language, executive functions

Part 2 will be a lecture on neurophysiology. Students will acquire specific knowledge about neurophysiology and neuroanatomy, learn the fundamental concepts of multi-channel EEG analysis, and acquire hands-on skills in using EEGLAB, an open-source software toolbox for advanced EEG analysis. Competencies:

  • understanding of basic concepts of biomedical signal processing;
  • using EEG analysis tools interactively and independently;
  • understanding the complete chain of EEG analysis steps, from data import to the illustration of results;
  • ability to use open source tools for EEG analysis;
  • application of theoretical knowledge to practical problems of physiology.


Part 3 will be a seminar on cognitive engineering. Students will be introduced to methods, tools, and techniques (MTTs) to evaluate and predict human performance in small use cases in different domains (Aviation, Air Traffic Control, Automotive, Maritime, or Healthcare). Each student is expected to study and apply the MTT based on material and software provided and present and discuss the modeling approach and the results achieved with the other participants and experts in the seminar.
Professional competences
The students:

  • neuropsychological / neurophysiological knowledge

Methodological competences
The students:

  • interdisciplinary knowledge & thinking

Social competences
The students:

  • written and oral presentation and discussion of scientific and technical results with others.

Self-competences
The students:

  • reading, understanding, summarizing and critically evaluating scientific texts/literature