Computational Neuroscience: Basics (4 C, 2 SWS) [B.Phy.7601(Bio)]

Learning outcome: Introduction to the different fields of Computational Neuroscience:

Models of single neurons,
Small networks,
Implementation of all simple as well as more complex numerical computations with few neurons.
Aspects of sensory signal processing (neurons as ?filters?),
Development of topographic maps of sensory modalities (e.g. visual, auditory) in the brain,
First models of brain development,
Basics of adaptivity and learning,
Basic models of cognitive processing.

Core skills: On completion the students will have gained...

...overview over the different sub-fields of Computational Neuroscience;
...first insights and comprehension of the complexity of brain function ranging across all sub-fields;
...knowledge of the interrelations between mathematical/modelling methods and the to-be-modelled substrate (synapse, neuron, network, etc.);
...access to the different possible model level in Computational Neuroscience.

Lehrveranstaltungen und Prüfungen
Lecture: Computational Neuroscience: Basics (2 WLH)

Examination: written examination (45 minutes)
Examination requirements: Having gained overview across the different sub-fields of Computational Neuroscience;
having acquired first insights into the complexity of across the whole bandwidth of brain
function;
having learned the interrelations between mathematical/modelling methods and the tobe-
modelled substrate (synapse, neuron, network, etc.);
being able to realize different level of modelling in Computational Neuroscience.

Workload
28 h attendance time
92 h self-study time

Admission requirements
none

Recommended previous knowledge
none

Number of repeat examinations permitted
twice

Course frequency
each summer semester

Recommended semester
2 - 6

Duration
1 semester

Language
English

Maximum number of students

Person responsible for module
Prof. Dr. Florentin Andreas Wörgötter