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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.

  1. Biophysics
  • ions_demo.RMD: Nernst equation and membrane potential
  • HH_demo.Rmd: excitability of the Hodgkin-Huxley model
  • IF_demo.Rmd: simplified neuron models
  1. Coding
  • Coding_demo.Rmd: Variability of neuronal responses
  • Decoding_demo.Rmd: Bayesian decoding
  • Networks.Rmd: dynamics of balanced networks
  1. Synapse - Learning
  • Relyability_demo.Rmd: estimating the effect of synaptic (un)reliability
  • Perceptron.Rmd: classification with the perceptron - overfitting and cross-validation
  1. Hippocampus
  • 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