Modelling and data analysis exercices for the computational neuroscience course http://cneuro.rmki.kfki.hu/education/neuromodel
Exercices are organised in 4 folders, corresponding to the 4 blocks of the course. You need to complete 1 exercise per block.
Each exercise is an R Markdown file - with extension Rmd. You can also view the pdf, which contains the R code and the description of the problem.
To complete the exercise, read the problem, perform the simulation/analysis, interpret the results and submit a single pdf file.
- ions_demo.RMD: Nernst equation and membrane potential
- HH_demo.Rmd: excitability of the Hodgkin-Huxley model
- IF_demo.Rmd: simplified neuron models
- Coding_demo.Rmd: Variability of neuronal responses
- Decoding_demo.Rmd: Bayesian decoding
- Networks.Rmd: dynamics of balanced networks
- Synapse - Learning
- Relyability_demo.Rmd: estimating the effect of synaptic (un)reliability
- Perceptron.Rmd: classification with the perceptron - overfitting and cross-validation
- Hopfield.Rmd: energy function, capacity and biological realstic memory networks
- PlaceCells.Rmd: place cells recorded from a freely moving rat - information rate, reliability and decoding
- Replay.Rmd: same dataset, directionality of place fields and replay events