Coursebooks

In silico neuroscience

BIOENG-450

Lecturer(s) :

Romani Armando
Schürmann Felix

Language:

English

Summary

"In silico Neuroscience" introduces students to a synthesis of modern neuroscience and state-of-the-art data management, modelling and computing technologies.

Content

"In silico Neuroscience" introduces masters students to a synthesis of modern neuroscience and state-of-the-art data management, modelling and computing technologies. Following fundamental structural and functional building blocks of the mammalian brain from cells to circuits, the course teaches applied biophysical modeling for each of these building blocks and showcases applications thereof in modern neuroscience. Accordingly, the course covers a number of key technologies, including 1) how neuroscience data is acquired, organized and integrated, 2) data-driven modeling and validation, 3) simulation and analysis technologies. The target audience are technically adept students in the EPFL Neuroscience program and students from other programs (e.g. I&C, SB, CSE) interested in applying their domain techniques to neuroscience.

The week-by-week breakdown of the course is as follows:
w1. Introduction
Single Cells
w2. Morphologies
w3. Ion channels
w4. Single cell modeling I – Hodgkin & Huxley & Cable Equation
w5. Single cell modeling II – Parameter Optimization
w6. Neuroinformatics & Resources
Networks
w7. Synapses
w8. Connections
w9. Networks I – Assembling the pieces
w10. Networks II – In silico experimentation
w11. Simulation & Scientific Computing I
w12. Simulation & Scientific Computing II
w13. Point neural networks & Simplification
w14. Perspectives

 

Learning Prerequisites

Recommended courses

Neuroscience II

Introduction to programming

Projects in informatics

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:

Teaching methods

Due to the general COVID-19 situation, the course will be given remotely and no physical presence on campus is required for this course (apart from final exam)

Structure: each week there will be

Exercises

Expected student activities

Assessment methods

Written exam (80%);

Continuous control (20%)

In the programs

Reference week

 MoTuWeThFr
8-9     
9-10     
10-11     
11-12     
12-13     
13-14     
14-15     
15-16     
16-17     
17-18     
18-19     
19-20     
20-21     
21-22     
Under construction
 
      Lecture
      Exercise, TP
      Project, other

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  • Autumn semester
  • Winter sessions
  • Spring semester
  • Summer sessions
  • Lecture in French
  • Lecture in English
  • Lecture in German