Programming behavioral experiments with MATLAB and Psychtoolbox : 9 simple steps for students and researchers  
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Programming behavioral experiments with MATLAB and Psychtoolbox : 9 simple steps for students and researchers


Programming behavioral experiments with MATLAB and Psychtoolbox : 9 simple steps for students and researchers

Title: Programming behavioral experiments with MATLAB and Psychtoolbox : 9 simple steps for students and researchers | Author(s): Misirlisoy, Erman | Publisher: Routledge | Year: 2017 | Language: English | Pages: 81 | ISBN: 9781315616667, 1315616661, 9781317205630, 1317205634 | Size: 2 MB  | Extension: pdf

 

Human behavior is fascinating so it’s no surprise that psychologists and neuroscientists spend their lives designing rigorous experiments to understand it. MATLAB is one of the most widely used pieces of software for designing and running behavioral experiments, and it opens up a world of quick and flexible experiment programming.

This book offers a step-by-step guide to using MATLAB with Psychtoolbox to create customisable experiments. Its pocket size and simple language allow you to get straight to the point and help you to learn fast in order to complete your work in great time. In nine simple steps, it guides you all the way from setting parameters for your experiment to analysing the output. Gone are the daunting days of working through hundreds of irrelevant and complicated documents, as in this handy book, Erman Misirlisoy coaxes you in the right direction with his friendly and encouraging tricks and tips.

If you want to learn how to develop your own experiments to collect and analyse behavioral data, then this book is a must-read. Whether you are a student in experimental psychology, a researcher in cognitive neuroscience, or simply someone who wants to run behavioral tasks on your friends for fun, this book will offer you the skills to succeed.

 

 

Table of contents :

Step 0. Preliminary notes --

step 1. Initialisation --

step 2. Setting parameters and opening up variables to store experimental conditions and data --

step 3. Executing for loops to iterate through trials --

step 4. Using if statements to define trials and present stimuli --

step 5. Presenting stimuli and recording responses --

step 6. Saving data --

step 7. Debugging, optimisation and functions --

step 8. Testing and sanity checks on data --

step 9. The basics of data analysis.

 

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