|
Teaching GuideTerm Faculty of Science |
| Mestrado Universitario en Neurociencia (Plan 2011) |
 Subjects |
| Computational neuroscience |
| Contents |
| Identifying Data | 2019/20 | |||||||||||||
| Subject | Computational neuroscience | Code | 610490016 | |||||||||||
| Study programme |
|
|||||||||||||
| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Official Master's Degree | 2nd four-month period |
First | Optional | 3 | ||||||||||
|
||||||||||||||
| Topic | Sub-topic |
| 1. Introduction to Computational Neuroscience 2. Models at the molecular level 3. Membrane-level models: from Boltzmann to Hodgkin-Huxley 4. Models at the neuron level: cable theory and model Compartmental of Rall 5. Synapse level models 6. Microcircuit models 7. Macrocircuit models 8. Coding in sensory receptors 9. Types of neural activity 10. Transmission of information in the brain 11. Spatial and temporal coding 12. Encoding by populations of neurons |
Espoñerase e comentaranse cos alumnos as diapositivas relacionadas con cada tema. |
| PRACTICUM |
Understand how modeling is done. Practices with neurosimulators. Report on the Application of the modeling process Exposure after analysis and criticism. |
|
