Peirce, Jonathan.
Building experiments in PsychoPy / Jonathan Peirce & Michael MacAskill. - Los Angeles, California : Sage, 2018. - xi, 297 pages : color illustrations ; 25 cm.
Includes bibliographical references and index.
Machine generated contents note: 1.1.Creating experiments -- 1.2.Building versus coding -- 1.3.Pros and cons of open-source software -- 1.4.Understanding your computer -- 1.5.What is PsychoPy? -- 1.0.Getting started -- 1.7.Going further -- 1.8.Conventions of this book -- I.For the beginner -- 2.Building your first experiment -- 24.The Builder interface -- 2.2.Building the Stroop task -- 2.3.Define your conditions -- 2.4.Defining the trial structure -- 2.5.Adding a loop to repeat trials -- 2.6.Varying your stimuli on each trial -- 2.7.Add some instructions -- 2.8.Add a thank-you slide -- 2.9.Changing your info dialog -- 2.10.Analyze your data -- 3.Using images: a study Into face perception -- 3.1.Accuracy versus reaction time -- 3.2.Testing face recognition -- 3.3.Image sizes in different units -- 3.4.Comparing inverted and correctly oriented faces -- 3.3.Additional options for images -- 3.6.Using Opacity -- 3.7.Using Masks -- 3.8.Present a movie instead of an image Note continued: 4.Timing and brief stimuli: Posner cueing -- 4.1.Presenting brief stimuli precisely -- 4.2.Posner cueing -- 5.Creating dynamic stimuli (revealing text and moving stimuli) -- 5.1.What does dynamic mean and why is it useful? -- 5.2.Inserting code into parameters -- 5.3.Example 1: Revealing text gradually -- 5.4.Example 2: Spinning, expanding images -- 5.5.Example 3: Change colors through the rainbow -- 5.6.Example 4: Make a heart that has a pulse -- 5.7.Going further -- 6.Providing feedback: simple Code Components -- 6.1.Providing feedback -- 6.2.Updating the feedback color -- 6.3.Reporting the reaction time -- 6.4.Ideas for useful code snippets -- 6.5.Reporting performance over the last five trials -- 7.Ratings: measure the ��Big 5' personality constructs -- 7.1.Instruments for the measurement of personality -- 7.2.Categories, Likert or continuous ratings -- 7.3.Controlling when the Rating is finalized -- 7.4.What to store Note continued: 7.5.Finishing your task and scoring the data -- 8.Randomization, blocks and counterbalancing: a bilingual Stroop task -- 8.1.Blocking trials -- 8.2.The bilingual Stroop task -- 8.3.Build a blocked version of the Stroop task -- 9.Using the mouse for input: creating a visual search task -- 9.1.Getting spatial responses -- 9.2.Visual search -- 9.3.Implementing the task -- 9.4.Introducing the Mouse Component -- 9.5.Control stimulus visibility from a conditions file -- 9.6.Control stimulus positions using code -- 9.7.Responding to mouse clicks spatially -- 9.8.Selectively skipping a routine -- 9.9.Making smooth trial transitions -- 9.10.Pointing rather than clicking -- II.For the professional -- 10.Implementing research designs with randomization -- 10.1.How can we assign subjects to conditions or groups? -- 10.2.Understanding loop ordering options -- 10.3.Summary -- 11.Coordinates and color spaces -- 11.1.Coordinate systems -- 11.2.Color spaces Note continued: 11.3.Phase of textures -- 12.Understanding your computer timing issues -- 12.1.Understanding screen refresh rates -- 12.2.Testing your stimulus timing -- 12.3.Timing by screen refresh -- 12.4.Images and timing -- 12.5.Response-time precision -- 13.Monitors and Monitor Center -- 13.1.Computer display technology -- 13.2.Monitor Center -- 13.3.Monitor calibration -- 13.4.Spatial calibration -- 13.5.Gamma correction -- 13.6.Color calibration -- 13.7.Procedure -- 14.Debugging your experiment -- 14.1.Common mistakes -- 14.2.Common error and warning messages and what they mean -- 14.3.How to debug an experiment -- 14.4.Writing a better query to the forum -- 15.Pro tips, tricks and lesser-known features -- 15.1.Adding a README file to your experiment -- 15.2.Expand or shrink the Flow and Routine -- 15.3.Copying and pasting Routines and Components -- 13.1.Online repositories for sharing your experiments Note continued: 15.5.Using variables from the dialog box in your experiment -- 15.6.Controlling names of your data files and folders -- 15.7.Running in windowed mode -- 15.8.Recreating your data files -- 15.9.Skipping a part of your experiment -- 15.10.Turn tips back on -- III.For the specialist -- 16.Psychophysics, stimuli and staircases -- 16.1.Gratings and Gabors -- 16.2.Smooth-edged masks (Gaussian and raised cosine) -- 16.3.Using images as masks -- 16.4.Element arrays -- 16.5.Random Dot Kinematograms -- 16.6.Staircase and QUEST procedures -- 17.Building an fMRI study -- 17.1.Detecting trigger pulses -- 17.2.Non-slip timing -- 17.3.How to calibrate a monitor for fMRI -- 18.Building an EEG study -- 18.1.What is special about EEG studies? -- 18.2.Sending EEG triggers -- 18.3.Communicating by parallel port or LabJack -- 18.4.Sending EEG triggers by network connections -- 18.5.Using custom libraries -- 19.Add eye tracking to your experiment Note continued: 19.1.Eye tracking in Builder -- 19.2.Configuring ioHub -- 19.3.Programming ioHub -- 19.4.Add eye tracking to the visual search task -- 19.5.Data storage via ioHub -- 19.6.Saving image stimuli to disk -- 19.7.Conclusion -- Appendix A Mathematics refresher -- A.1.Sine and cosine -- A.2.Rescaling and changing start points -- A.3.Pythagoras' Theorem -- Appendix B Exercise Solutions.
PsychoPy is an open-source (free) software package for creating rich, dynamic experiments in psychology, neuroscience and linguistics. It provides an intuitive graphical interface (the "Builder") as well as the option to insert Python code. This combination makes it easy enough for teaching, but also flexible enough for all manner of behavioural experiments. As a result, PsychoPy has become the software package of choice in psychology departments at universities all over the world. Divided into three parts and with unique learning features to guide readers at whatever level they are at, this textbook is suitable for teaching practical undergraduate classes on research methods, or as a reference text for the professional scientist. The book is written by Jonathan Peirce, the original creator of PsychoPy and Michael MacAskill who have utilised their breadth of experience in Python development to educate students and researchers in this intuitive, yet powerful, experiment generation package.
1473991390 (paperback) 9781473991392 (paperback)
Psychology, Experimental--Computer programs.
Psychology, Experimental--Data processing.
Python (Computer program language)
BF198.7 / .P45 2018
Building experiments in PsychoPy / Jonathan Peirce & Michael MacAskill. - Los Angeles, California : Sage, 2018. - xi, 297 pages : color illustrations ; 25 cm.
Includes bibliographical references and index.
Machine generated contents note: 1.1.Creating experiments -- 1.2.Building versus coding -- 1.3.Pros and cons of open-source software -- 1.4.Understanding your computer -- 1.5.What is PsychoPy? -- 1.0.Getting started -- 1.7.Going further -- 1.8.Conventions of this book -- I.For the beginner -- 2.Building your first experiment -- 24.The Builder interface -- 2.2.Building the Stroop task -- 2.3.Define your conditions -- 2.4.Defining the trial structure -- 2.5.Adding a loop to repeat trials -- 2.6.Varying your stimuli on each trial -- 2.7.Add some instructions -- 2.8.Add a thank-you slide -- 2.9.Changing your info dialog -- 2.10.Analyze your data -- 3.Using images: a study Into face perception -- 3.1.Accuracy versus reaction time -- 3.2.Testing face recognition -- 3.3.Image sizes in different units -- 3.4.Comparing inverted and correctly oriented faces -- 3.3.Additional options for images -- 3.6.Using Opacity -- 3.7.Using Masks -- 3.8.Present a movie instead of an image Note continued: 4.Timing and brief stimuli: Posner cueing -- 4.1.Presenting brief stimuli precisely -- 4.2.Posner cueing -- 5.Creating dynamic stimuli (revealing text and moving stimuli) -- 5.1.What does dynamic mean and why is it useful? -- 5.2.Inserting code into parameters -- 5.3.Example 1: Revealing text gradually -- 5.4.Example 2: Spinning, expanding images -- 5.5.Example 3: Change colors through the rainbow -- 5.6.Example 4: Make a heart that has a pulse -- 5.7.Going further -- 6.Providing feedback: simple Code Components -- 6.1.Providing feedback -- 6.2.Updating the feedback color -- 6.3.Reporting the reaction time -- 6.4.Ideas for useful code snippets -- 6.5.Reporting performance over the last five trials -- 7.Ratings: measure the ��Big 5' personality constructs -- 7.1.Instruments for the measurement of personality -- 7.2.Categories, Likert or continuous ratings -- 7.3.Controlling when the Rating is finalized -- 7.4.What to store Note continued: 7.5.Finishing your task and scoring the data -- 8.Randomization, blocks and counterbalancing: a bilingual Stroop task -- 8.1.Blocking trials -- 8.2.The bilingual Stroop task -- 8.3.Build a blocked version of the Stroop task -- 9.Using the mouse for input: creating a visual search task -- 9.1.Getting spatial responses -- 9.2.Visual search -- 9.3.Implementing the task -- 9.4.Introducing the Mouse Component -- 9.5.Control stimulus visibility from a conditions file -- 9.6.Control stimulus positions using code -- 9.7.Responding to mouse clicks spatially -- 9.8.Selectively skipping a routine -- 9.9.Making smooth trial transitions -- 9.10.Pointing rather than clicking -- II.For the professional -- 10.Implementing research designs with randomization -- 10.1.How can we assign subjects to conditions or groups? -- 10.2.Understanding loop ordering options -- 10.3.Summary -- 11.Coordinates and color spaces -- 11.1.Coordinate systems -- 11.2.Color spaces Note continued: 11.3.Phase of textures -- 12.Understanding your computer timing issues -- 12.1.Understanding screen refresh rates -- 12.2.Testing your stimulus timing -- 12.3.Timing by screen refresh -- 12.4.Images and timing -- 12.5.Response-time precision -- 13.Monitors and Monitor Center -- 13.1.Computer display technology -- 13.2.Monitor Center -- 13.3.Monitor calibration -- 13.4.Spatial calibration -- 13.5.Gamma correction -- 13.6.Color calibration -- 13.7.Procedure -- 14.Debugging your experiment -- 14.1.Common mistakes -- 14.2.Common error and warning messages and what they mean -- 14.3.How to debug an experiment -- 14.4.Writing a better query to the forum -- 15.Pro tips, tricks and lesser-known features -- 15.1.Adding a README file to your experiment -- 15.2.Expand or shrink the Flow and Routine -- 15.3.Copying and pasting Routines and Components -- 13.1.Online repositories for sharing your experiments Note continued: 15.5.Using variables from the dialog box in your experiment -- 15.6.Controlling names of your data files and folders -- 15.7.Running in windowed mode -- 15.8.Recreating your data files -- 15.9.Skipping a part of your experiment -- 15.10.Turn tips back on -- III.For the specialist -- 16.Psychophysics, stimuli and staircases -- 16.1.Gratings and Gabors -- 16.2.Smooth-edged masks (Gaussian and raised cosine) -- 16.3.Using images as masks -- 16.4.Element arrays -- 16.5.Random Dot Kinematograms -- 16.6.Staircase and QUEST procedures -- 17.Building an fMRI study -- 17.1.Detecting trigger pulses -- 17.2.Non-slip timing -- 17.3.How to calibrate a monitor for fMRI -- 18.Building an EEG study -- 18.1.What is special about EEG studies? -- 18.2.Sending EEG triggers -- 18.3.Communicating by parallel port or LabJack -- 18.4.Sending EEG triggers by network connections -- 18.5.Using custom libraries -- 19.Add eye tracking to your experiment Note continued: 19.1.Eye tracking in Builder -- 19.2.Configuring ioHub -- 19.3.Programming ioHub -- 19.4.Add eye tracking to the visual search task -- 19.5.Data storage via ioHub -- 19.6.Saving image stimuli to disk -- 19.7.Conclusion -- Appendix A Mathematics refresher -- A.1.Sine and cosine -- A.2.Rescaling and changing start points -- A.3.Pythagoras' Theorem -- Appendix B Exercise Solutions.
PsychoPy is an open-source (free) software package for creating rich, dynamic experiments in psychology, neuroscience and linguistics. It provides an intuitive graphical interface (the "Builder") as well as the option to insert Python code. This combination makes it easy enough for teaching, but also flexible enough for all manner of behavioural experiments. As a result, PsychoPy has become the software package of choice in psychology departments at universities all over the world. Divided into three parts and with unique learning features to guide readers at whatever level they are at, this textbook is suitable for teaching practical undergraduate classes on research methods, or as a reference text for the professional scientist. The book is written by Jonathan Peirce, the original creator of PsychoPy and Michael MacAskill who have utilised their breadth of experience in Python development to educate students and researchers in this intuitive, yet powerful, experiment generation package.
1473991390 (paperback) 9781473991392 (paperback)
Psychology, Experimental--Computer programs.
Psychology, Experimental--Data processing.
Python (Computer program language)
BF198.7 / .P45 2018