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Computational Neuroscience - Summer term 2017

A Lecture Series from Models to Applications


Day and Time

Tuesday 18:00-19:30 s.t., summer term 2017

Venue

LMU Main Building, Geschwister-Scholl-Platz 1 (A), Room: A014
floor plan

Course material

Lecture notes, slides and further material can be found at Moodle@elearningTUM. For general inquiries on the lecture please get in touch with Dr. Kay Thurley.
Some background on Julius Bernstein, who lent his name to the Bernstein Network: Julius Bernstein (1839–1917): pioneer neurobiologist and biophysicist.

Overview

No.DateLecturerTopic
1 04/25 Luksch Biology

Motivation for doing computational Neuroscience; Neuroanatomy primer: General layouts of nervous systems, overview of the human brain and forebrain, morphology of neurons, visual and auditory pathways

2 05/02 Luksch Biology

Neurophysiology primer: Basic biology of neurons, resting and acting potentials, synaptic transmission, plasticity of neuronal connections, dendritic processing

3 05/09 Sirota Biology

Systems mechanisms of learning and memory: theory, methods and their application

4 05/16 Herz Modelling Modeling dynamics and computations of single neurons
5 05/23 Herz Modelling Theory of neural networks and learning
6 05/30 Ahmadi Modelling Deep learning
06/06 holiday Pentecost
7 06/13 Busse Integration Visual system I: neurobiology
8 06/20 Wachtler Integration Visual system II: computation
9 06/27 Glasauer Integration Spatial perception and navigation
10 07/04 Seeber Engineering Neuroprosthetics I: Cochlea Implants: System overview and stimulation algorithms
11 07/11 Seeber Engineering Neuroprosthetics II: Cochlea Implants: Electric stimulation of the auditory nerve, phenomenological models
12 07/18 Conradt Engineering Engineering applications of brain models
13 07/25 Exam

Time: 6:00 p.m.
Venue: A021, LMU Main Building

Registration for LMU students until July 11 by email  (Dr. Kay Thurley)!

Exam/Credits

3 ECTS
In the written examination, an overview of the various aspects of computational neuroscience will be tested. Knowledge-based learning outcomes from the lecture as well as the understanding and ability to solve (practical) problems will be assessed in a 60 min written examination with questions set and corrected by the respective lecturers. For questions on the exam please get in touch with Dr. Kay Thurley.
Here you can find an example exam.

Previous editions