htw saar Piktogramm QR-encoded URL
Back to Main Page Choose Module Version:
XML-Code

flag

Nervous System Evolution, Simulation, Cognition, Consciousness

Module name (EN):
Name of module in study programme. It should be precise and clear.
Nervous System Evolution, Simulation, Cognition, Consciousness
Degree programme:
Study Programme with validity of corresponding study regulations containing this module.
Neural Engineering, Master, SO 01.10.2025
Module code: NE2221.NSE
Hours per semester week / Teaching method:
The count of hours per week is a combination of lecture (V for German Vorlesung), exercise (U for Übung), practice (P) oder project (PA). For example a course of the form 2V+2U has 2 hours of lecture and 2 hours of exercise per week.
-
ECTS credits:
European Credit Transfer System. Points for successful completion of a course. Each ECTS point represents a workload of 30 hours.
5
Semester: according to optional course list
Mandatory course: no
Language of instruction:
English
Assessment:


[still undocumented]
Applicability / Curricular relevance:
All study programs (with year of the version of study regulations) containing the course.

NE2221.NSE Neural Engineering, Master, ASPO 01.04.2020 , optional course
NE2221.NSE Neural Engineering, Master, SO 01.10.2025 , optional course
Workload:
Workload of student for successfully completing the course. Each ECTS credit represents 30 working hours. These are the combined effort of face-to-face time, post-processing the subject of the lecture, exercises and preparation for the exam.

The total workload is distributed on the semester (01.04.-30.09. during the summer term, 01.10.-31.03. during the winter term).
The total student study time for this course is 150 hours.
Recommended prerequisites (modules):
None.
Recommended as prerequisite for:
Module coordinator:
Dr. Sebastian Markert
Lecturer:
Dr. Sebastian Markert


[updated 03.12.2024]
Learning outcomes:
The students are able to describe how nervous systems emerged and changed through evolution. They can compare nervous systems of animals, including humans. They can discuss the roundworm Caenorhabditis elegans as a model for holistic nervous system research. They can define what a connectome is and discuss the efficacy of connectomics as a means of understanding nervous systems as a whole. They can discuss the possibilities and limits of nervous system simulation. They can describe the state of research on cognition and consciousness. They can discuss hypotheses on consciousness.

[updated 03.12.2024]
Module content:
 
 
 
Nervous System Evolution, Simulation, Cognition, Consciousness – the biggest questions explored in the smallest worm
 
 
1.  Evolution of the nervous system
        1.1  How and when nervous systems emerged
        1.2  Universal principles of nervous system function
        1.3  Protostome versus deuterostome nervous systems
        1.4  Bird versus Mammal brains
        1.5  Human versus animal intelligence
 
2.  The roundworm model Caenorhabditis elegans
        2.1  The biology of the worm
        2.2  The nervous system of the worm
        2.3  The connectome of the worm
        2.4  Why we should study worms
        2.5  Why we should not study worms
 
3.  Connectomics
        3.1  Why we obtain connectomes
        3.2  How we obtain connectomes
        3.3  Which connectomes we have obtained
        3.4  What we have learned from connectomes
        3.5  Why connectomes disappoint
 
4.  Simulation of nervous systems
        4.1  The worm that woke up in a robot
        4.2  Uploading a mind into a machine
        4.3  Artificial neuronal networks
        4.4  Large Language Models versus nervous systems
 
5.  Consciousness
        5.1  Why consciousness evolved
        5.2  The twofold substrate independence of consciousness
        5.3  Consciousness is nowhere and everywhere
        5.4  The universe understands itself
        5.5  Where is grandma’s apple pie in the brain


[updated 03.12.2024]
Recommended or required reading:


[still undocumented]
 
[Fri Dec 27 01:31:04 CET 2024, CKEY=nnsescc, BKEY=nem2, CID=NE2221.NSE, LANGUAGE=en, DATE=27.12.2024]