Fu-logo-text-2x
Drucken

M.Sc. Cognitive Neuroscience

These pages are not displaying properly because the Compatibility View in your Internet Explorer is enabled. We suggest that you remove 'fu-berlin.de' from your list of sites that have Compatibility View enabled.

  1. In Internet Explorer, press the 'Alt' key to display the Menu bar, or press and hold the address bar and select 'Menu bar'.
  2. Click 'Tools' and select 'Compatibility View settings'.
  3. Select 'fu-berlin.de' under 'Websites you've added to Compatibility View'.
  4. Click 'Remove'.

Introduction to Programming

Learning objectives: 

Students acquire essential theoretical background knowledge for the practical implementation and evaluation of experimental studies in cognitive neuroscience. Specifically, they have gained practical knowledge and experience in imperative and object-oriented programming using a programming language and are aware of the importance of programming skills in neurocognitive research.

Content:

In accordance with current developments in cognitive neuroscience, students hone their practical skills in programming with RStudio, MATLAB, Python, or similar programming languages – skills that are currently highly sought after. They gain practical experience in managing empirical data and analysis methods, building on the theoretical introduction to this they have gained in the modules “Neurocognitive Methods and Data Analysis” and “Probabilistic and Statistical Modeling.” The focus is on the application of imperative programming in neurocognitive research. In particular, students practice the implementation of scripts for stimulus presentation (e.g., precise presentation of visual stimuli), data acquisition (e.g., response behavior, reaction times), data visualization, and statistical evaluation (e.g., output of charts, calculation of inferential statistics). Additionally, principles of data management (e.g., management of research data) in accordance with good scientific practice, as well as the cooperative use of development platforms (e.g., Github) and principles of publication and the availability of programming code in the sense of open science, are also practiced.