Math and Matlab for Neuroscientists Training, 14 -18 August 2017, Radboud University, Netherlands

Publish Date: Feb 11, 2017

Deadline: Jun 01, 2017

Event Dates: from Aug 14, 2017 12:00 to Aug 18, 2017 12:00

About the training course

The purpose of this course is to learn some of the fundamental mathematical and signal-processing theorems that underlie most of the advanced data analysis techniques used in the field of neuroscience and cognitive neuroscience. The focus of this course is on the theory, mathematics, and programming implementations (not on how to use particular toolboxes). The course is designed for people who have a background in biology or psychology and would like to learn some about the mathematics.

Each day will be a mix of lectures and hands-on labwork. In the labwork you will have the opportunity to implement in Matlab the concepts discussed in lecture. Most labwork is done in small groups of 2-3 students. There will be several short quizzes each day to make sure you are learning the material. There will also be occasional homework assignments to help you consolidate and develop your newly learned skills. Quizzes and homework assignments are not graded and solutions will be provided the following day.

The major topics include:

  • Fourier transform,
  • convolution,
  • wavelets and time-frequency analyses,
  • matrix algebra including least-squares estimation and eigenvalue decomposition (principle components analysis).

This will be an intensive course designed for learning but there will be plenty of coffee and chocolates to keep you motivated. This material has been taught by Dr Cohen for seven years in several different countries and is the basis of the book Analyzing Neural Time Series Data (MIT Press, 2014).

You must bring a laptop with Matlab or Octave (a free Matlab-like software) installed. Desktop computers will not be available.

Learning outcome

After this course you are able to:

  • Understand the mechanics of the Fourier transform and how to implement it in Matlab.
  • Understand convolution and how to use it to perform time-frequency analyses in Matlab.
  • Understand the basics of matrix algebra and how to perform least-squares and eigenvalue decomposition in Matlab.

Entry level:

  • Master
  • PhD
  • Postdoc
  • Professional

For whom is this course designed
This course is designed for PhD students and postdocs who have experience with data analysis but who feel that they need more training in the fundamentals. Beginner-level experience with Matlab programming is necessary. The course focuses heavily on analog signals (LFP/EEG/MEG).

Admission requirements

Previous experience (beginner to moderate level) with Matlab programming is required. You will/earn a lot of Matlab in the course, but we cannot start from the most elementary introduction. A strong background in mathematics is not required. During the week-long course, you will have assignments and quizzes, and you may want to work after the lectures (this will not interfere with the social program).

Admission documents

  • Motivation letter
  • CV

Dates
Monday 14 August - Friday 18 August 2017 (one week)

Course leader
Dr. Michael X Cohen
Assistant professor
Donders Center for Neuroscience
Radboud University

Course fee
€ 500
The course fee includes the registration fee, course materials, access to library and IT facilities, coffee/tea, lunch, and a number of social activities.

Discounts
€ 450   early bird - deadline 1 April 2017 (10%)
€ 425   partner + RU discount (15%)
€ 375   early bird + partner discount (25%)

Number of EC
2 ECTS

More information: radboudsummerschool@ru.nl

For more information click "Further official information" below.


This opportunity has expired. It was originally published here:

http://www.ru.nl/radboudsummerschool/courses/2017/math-matlab-neuroscientists/

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Disciplines

Biology

Mathematics

Neuroscience

Psychology

Opportunity Types

Scholarships

Eligible Countries

International

Host Countries

Netherlands

Event Types

Trainings