Computational Neuroscience: A Lecture Series from Models to Applications
Course 0000000093 in SS 2020
General Data
| Course Type | lecture |
|---|---|
| Semester Weekly Hours | 2 SWS |
| Organisational Unit | Associate Professorship of Audio Information Processing (Prof. Seeber) |
| Lecturers |
Harald Luksch |
| Dates |
Assignment to Modules
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EI7646: Computational Neuroscience: Eine Ringvorlesung von Modellen bis zu Anwendungen / Computational Neuroscience: A Lecture Series from Models to Applications
This module is included in the following catalogs:- Catalogue of non-physics elective courses
Further Information
Courses are together with exams the building blocks for modules. Please keep in mind that information on the contents, learning outcomes and, especially examination conditions are given on the module level only – see section "Assignment to Modules" above.
| additional remarks | A. General overview: Anatomical and physiological basis of neuroscience (2VL, Luksch): - 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 - Neurophysiology primer: Basic biology of neurons, resting and acting potentials, synaptic transmission, plasticity of neuronal connections, dendritic processing B. Modeling: Neural dynamics and coding (3 VL, Herz, Ahmadi) - Modeling dynamics and computations of single neurons - Theory of neural networks and learning - Deep Learning C. Towards integration in the nervous system (4VL, Sirota, Busse, Wachtler, Glasauer): - Systems mechanisms of learning and memory: theory, methods and their application - Visual system I: neurobiology - Visual system II: computation - Spatial perception D. Engineering for Neuroscience and Neuroprosthetics (3 VL, Seeber, Conradt): - Neuroprosthetics I: Cochlea Implants: System overview and stimulation algorithms - Neuroprosthetics II: Cochlea Implants: Electric stimulation of the auditory nerve, phenomenological models - Engineering applications of brain models An overview of current research at the Bernstein Center for Computational Neuroscience Munich. Updates of the teaching content and further material can be found on the BCCN page (http://www.bccn-munich.de/teaching/computational-neuroscience). |
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| Links |
E-Learning course (e. g. Moodle) TUMonline entry |