Expyriment: A Python library for cognitive and neuroscientific experiments

An Erratum to this article was published on 24 January 2014

Abstract

Expyriment is an open-source and platform-independent lightweight Python library for designing and conducting timing-critical behavioral and neuroimaging experiments. The major goal is to provide a well-structured Python library for script-based experiment development, with a high priority being the readability of the resulting program code. Expyriment has been tested extensively under Linux and Windows and is an all-in-one solution, as it handles stimulus presentation, the recording of input/output events, communication with other devices, and the collection and preprocessing of data. Furthermore, it offers a hierarchical design structure, which allows for an intuitive transition from the experimental design to a running program. It is therefore also suited for students, as well as for experimental psychologists and neuroscientists with little programming experience.

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Notes

  1. 1.

    www.debian.org. For the use of GNU/Linux in the field of neuroscience, see Hanke and Halchenko (2011).

  2. 2.

    www.debian.org

  3. 3.

    www.ubuntu.org

  4. 4.

    Note that each Expyriment stimulus can be integrated into the design hierarchy as well, using the method.

  5. 5.

    www.raspberrypi.org

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Acknowledgments

We thank Pascal de Water for great technical support, Sebastiaan Mathôt for his code evaluation and for choosing Expyriment as the default back end of OpenSesame 0.27, as well as dozens of students and colleagues for using old preliminary versions of Expyriment for their studies. Without their feedback, Exypriment would not have reached the level of a stable and reliable experiment programming library.

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Correspondence to Florian Krause.

Appendix

Appendix

Listing 1
figure4

Programming code for a response time experiment to assess a spatial stimulus–response compatibility effect (the Simon effect; Hommel, 1993)

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Krause, F., Lindemann, O. Expyriment: A Python library for cognitive and neuroscientific experiments. Behav Res 46, 416–428 (2014). https://doi.org/10.3758/s13428-013-0390-6

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Keywords

  • Software
  • Programming library
  • Python
  • Experimental design
  • Stimulus presentation