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.

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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