NX-450 / 5 credits

Teacher(s): Schürmann Felix, Romani Armando

Language: English


Summary

The course introduces students to a synthesis of modern neuroscience and state-of-the-art data management, modelling and computing technologies with a focus on the biophysical level.

Content

Keywords

data management, biophysically detailed modeling, scientific computing, simulation

Learning Prerequisites

Important concepts to start the course

  • general knowledge on cellular neuroscience
  • experience in elementary programming (preferentially python)

 

Learning Outcomes

By the end of the course, the student must be able to:

  • Interpret discrepancies between experimental findings
  • Assess / Evaluate different level of detail formulations of models
  • Integrate biological facts into detailed neuron and tissue models
  • Apply model concepts in simulations
  • Exploit standard modelling and simulation software
  • Analyze model predictions
  • Explain formalisms and approaches in simulation software

Teaching methods

The course will take place in presence on the EPFL campus.

Structure: each week there will be

  • 2x45min lecture
  • 45min interactive discussion with the teachers & TAs
  • 45min introduction of homework exercises, Q&A, group work (TAs present)

Exercises

  • practical programming/problem solving on topics from the lectures
  • done in groups, which remain for the entire semester
  • are graded on a weekly basis

 

Expected student activities

  • Students attend lectures
  • Students actively participate in the discussion on the topics of the lecture in the discussion session
  • Students complete weekly practical programming assignments relevant to the week's lecture in groups
  • Students write final exam in exam period

 

Assessment methods

  • Written exam: 70%
  • Continuous control (homework): 30%

In the programs

  • Semester: Fall
  • Exam form: Written (winter session)
  • Subject examined: Computational neurosciences: biophysics
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Fall
  • Exam form: Written (winter session)
  • Subject examined: Computational neurosciences: biophysics
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Fall
  • Exam form: Written (winter session)
  • Subject examined: Computational neurosciences: biophysics
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Fall
  • Exam form: Written (winter session)
  • Subject examined: Computational neurosciences: biophysics
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Fall
  • Exam form: Written (winter session)
  • Subject examined: Computational neurosciences: biophysics
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Fall
  • Exam form: Written (winter session)
  • Subject examined: Computational neurosciences: biophysics
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks

Reference week

 MoTuWeThFr
8-9     
9-10     
10-11 DIA003   
11-12    
12-13     
13-14 DIA003   
14-15    
15-16     
16-17     
17-18     
18-19     
19-20     
20-21     
21-22     

Tuesday, 10h - 12h: Lecture DIA003

Tuesday, 13h - 15h: Exercise, TP DIA003