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Computational Neuroscience - Summer term 2020

A Lecture Series from Models to Applications

Interdisciplinary lecture series taught by neuroscience experts from TUM and LMU that provides an introduction to computational neuroscience. Topics range from a general overview on neurobiology and basic modeling to neuroengineering and -prothetics. In winter terms a focus is given to neuroengineering and -prothetics whereas summer terms cover topics more strongly related to biological mechanisms.

Some background on Julius Bernstein, who lent his name to the Bernstein Network: Julius Bernstein (1839–1917): pioneer neurobiologist and biophysicist.

For general inquiries on the lecture please get in touch with Dr. Kay Thurley.

Day and Time

Tuesday 18:00-19:30 s.t., summer term 2020


The course will be held as a virtual lecture. More information and lecture notes will be posted on our Moodle site Moodle@elearningTUM about one week before the date of each lecture listed below.
At the regular time of the lecture, lecturers will be available for questions either via Zoom, chat or forum depending on the specific lecture. Details will be announced on our Moodle site too.


1 04/21


2 04/28 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

3 05/05 Luksch Biology

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

4 05/12 Herz Modelling

Single neuron models

5 05/19 Seeber Engineering


6 05/26 Flanagin Integration

 Human neuroimaging (fMRI), Modeling connections between brain regions

06/02 holiday

no lecture -- Pentecost

7 06/09 Busse Integration

Visual system I: neurobiology

8 06/16 Wachtler Integration

 Visual system II: computation

9 06/23 Thurley Integration

Temporal cognition

10 06/30 Flanagin Integration

 Spatial perception and navigation

11 07/07 Sirota Integration

 Methods of systems neuroscience: measurement and perturbation of neural activity

12 07/14 Sirota Integration

 Systems mechanisms of learning and memory from theory to experimental data



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.