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Computational Neuroscience - Summer term 2015

A Lecture Series from Models to Applications


Day and Time

Tuesday 18:00-20:00 s.t., summer term 2015
April 14, 2015 to July 14, 2015

Venue

LMU Main Building, Geschwister-Scholl-Platz 1 (A), Room: A 017
floor plan

Course material

Lecture notes, slides and further material can be found at Moodle@elearningTUM.
For general inquiries on the lecture or questions
regarding exam/credits 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 04/14 Herz/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 04/21 Luksch Biology

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

3 04/28 Herz Modelling

Modeling the dynamics and computations of single neurons I

4 05/05 Herz Modelling

Modeling the dynamics and computations of single neurons II

5 05/12 Leibold Modelling

Populations of neurons; Theory of neural networks and learning

6 05/19 Leibold Modelling

Neural coding, information theory and application to neuroscience

7 05/26 holiday


8 06/02 Sirota Integration

Methods of systems neuroscience: measurement and perturbation of neural activity

Systems mechanisms of learning and memory from theory to experimental data

9 06/09 Flanagin Integration

Human neuroimaging (fMRI), Modeling connections between brain regions

10 06/16 Glasauer Integration

Spatial perception and navigation

11 06/23 MacNeilage Integration

Measuring and modeling perception

12 06/30 Conradt Engineering

Engineering applications of brain models

13 07/07 Seeber Engineering

Neuroprosthetics, examples: hearing aids and implants

14 07/14 Kleinsteuber Engineering

Machine learning and information retrieval in high dimensional data

15 07/21 Exam

 The exam will take place in Room A 021 (LMU Main Building).

 

Exam/Credits

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.