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Computational Neuroscience - Winter term 2017/18

A Lecture Series from Models to Applications

Day and Time

Tuesday 18:00-20:00 s.t., winter term 2017/18


IMETUM, Technische Universität München, Boltzmannstr. 11, Hörsaal E.126 im IMETUM Erdgeschoss

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.


1 10/17 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 10/24 Luksch Biology

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

10/31 holiday no lecture -- Reformation day
3 11/07 Leibold Modeling Modeling dynamics and computations of single neurons
4 11/14 Leibold Modeling Populations of neurons; Theory of neural networks and learning
5 11/21 Leibold Modeling Neural coding, information theory and application to neuroscience
6 11/28 Ahmadi Modeling Deep learning
7 12/05 Wolfrum Engineering Cell-chip communication
8 12/12 Seeber Engineering Neuroprosthetics I: Cochlea Implants: System overview and stimulation algorithms
12/19 no lecture
9 01/09 Seeber Engineering Neuroprosthetics II: Cochlea Implants: Electric stimulation of the auditory nerve, phenomenological models
10 01/16 Hemmert Engineering Neuroprosthetics III: Key issues in neuro implants
11 01/23 Hemmert Engineering Neuroprosthetics IV: Retina Implants, Deep Brain stimulation, optical Neuro-Stimulation
12 01/30 Röhrbein Engineering Neurorobotics I
13 02/06 Röhrbein Engineering Neurorobotics II


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 and the sample solutions.

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