Lecture 1: Neuromodeling

Manuel Beiran: manuel.beiran-at-ens.fr

Introduction

What is a model?:

a mathematical description/framework of a real system

  • usefulness: should be able to make prediction
    • Just because experiments don’t contradict the model doesn’t mean that the model is “right”
    • But if the experiments contradict the model, then it’s wrong

Strong overlap with the course CO6.


Reports

  • the report should be a scientific report written in English

  • Include introduction/conclusion for each exercise

  • Use questions as a guideline to write a coherent explanation of the model

  • Each sentence should be rigorous. No:

    • “looks like an exponential”
    • “the model is not very realistic” (realistic for what?)
    • “we try to…”
    • “As a conclusion, we can say that” (“as a conclusion”: useless)
  • Don’t start a sentence with a greek letter: instead of “$α$ changes…”, say “The growth rate $α$ changes…”

  • Don’t plot lines that you don’t see

  • Axis labels: “magnitude (units)”

  • Figures should support text (captions): don’t describe them in a main paragraph

  • For plotting exponentials: think about logscales!

      plt.yscale('log')
    

Warning to spelling:

  • Sensitivity to initial conditions
  • Resources
  • Computational
  • Literature

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