Hands On Training

Neuronal Dynamics

Ecole Polytechnique Fédérale de Lausanne (EPFL)

via

edX

Course Features

Duration

7 weeks

Delivery Method

Online

Available on

Limited Access

Accessibility

Mobile, Desktop, Laptop

Language

English

Subtitles

English

Level

Advanced

Effort

7 hours per week

Teaching Type

Self Paced

Course Description

This course gives an introduction to the field of theoretical and computational neuroscience with a focus on models of single neurons. Neurons encode information about stimuli in a sequence of short electrical pulses (spikes). Students will learn how mathematical tools such as differential equations, phase plane analysis, separation of time scales, and stochastic processes can be used to understand the dynamics of neurons and the neural code.

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Course Overview

Virtual Labs

International Faculty

Post Course Interactions

Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Recommended textbook: "NEURONAL DYNAMICS - from single neurons to networks and cognition", Cambridge Univ. Press 2014

Calculus, differential equations, probabilities

What You Will Learn

How mathematical tools such as differential equations, phase plane analysis, separation of time scales, and stochastic processes can be used to understand the dynamics of neurons and the neural code

Course Content

Expand all sections

Module 1: A first simple neuron model

Module 2: Hodgkin-Huxley models and biophysical modeling

Module 3: Two-dimensional models and phase plane analysis

Module 4: Two-dimensional models (cont.)/ Dendrites

Course Instructors

Wulfram Gerstner

Professor, Computer Science at EPFL

After studies of Physics in Tübingen and at the Ludwig-Maximilians-University Munich (Master 1989), Wulfram Gerstner spent a year as a visiting researcher at UC Berkeley. He received his PhD in Theor...