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Generating Stimuli for Neuroscience Using PsychoPy.

Peirce JW - Front Neuroinform (2009)

Bottom Line: As a result, new experiments can be written very quickly, and trying to understand a previously written script is easy, even with minimal code comments.PsychoPy can also generate movies and image sequences to be used in demos or simulated neuroscience experiments.This paper describes the range of tools and stimuli that it provides and the environment in which experiments are conducted.

View Article: PubMed Central - PubMed

Affiliation: Nottingham Visual Neuroscience, School of Psychology, University of Nottingham Nottingham, UK.

ABSTRACT
PsychoPy is a software library written in Python, using OpenGL to generate very precise visual stimuli on standard personal computers. It is designed to allow the construction of as wide a variety of neuroscience experiments as possible, with the least effort. By writing scripts in standard Python syntax users can generate an enormous variety of visual and auditory stimuli and can interact with a wide range of external hardware (enabling its use in fMRI, EEG, MEG etc.). The structure of scripts is simple and intuitive. As a result, new experiments can be written very quickly, and trying to understand a previously written script is easy, even with minimal code comments. PsychoPy can also generate movies and image sequences to be used in demos or simulated neuroscience experiments. This paper describes the range of tools and stimuli that it provides and the environment in which experiments are conducted.

No MeSH data available.


The structure of PsychoPy. PsychoPy comprises a number of sub-modules for controlling different aspects of an experimental setup, from stimulus presentation to analysis of data. In turn these use a number of dependent libraries, that typically have a very good degree of platform-independence.
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Figure 2: The structure of PsychoPy. PsychoPy comprises a number of sub-modules for controlling different aspects of an experimental setup, from stimulus presentation to analysis of data. In turn these use a number of dependent libraries, that typically have a very good degree of platform-independence.

Mentions: The main modules that can be imported from PsychoPy, and the main libraries that they depend upon are shown in Figure 2.


Generating Stimuli for Neuroscience Using PsychoPy.

Peirce JW - Front Neuroinform (2009)

The structure of PsychoPy. PsychoPy comprises a number of sub-modules for controlling different aspects of an experimental setup, from stimulus presentation to analysis of data. In turn these use a number of dependent libraries, that typically have a very good degree of platform-independence.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2636899&req=5

Figure 2: The structure of PsychoPy. PsychoPy comprises a number of sub-modules for controlling different aspects of an experimental setup, from stimulus presentation to analysis of data. In turn these use a number of dependent libraries, that typically have a very good degree of platform-independence.
Mentions: The main modules that can be imported from PsychoPy, and the main libraries that they depend upon are shown in Figure 2.

Bottom Line: As a result, new experiments can be written very quickly, and trying to understand a previously written script is easy, even with minimal code comments.PsychoPy can also generate movies and image sequences to be used in demos or simulated neuroscience experiments.This paper describes the range of tools and stimuli that it provides and the environment in which experiments are conducted.

View Article: PubMed Central - PubMed

Affiliation: Nottingham Visual Neuroscience, School of Psychology, University of Nottingham Nottingham, UK.

ABSTRACT
PsychoPy is a software library written in Python, using OpenGL to generate very precise visual stimuli on standard personal computers. It is designed to allow the construction of as wide a variety of neuroscience experiments as possible, with the least effort. By writing scripts in standard Python syntax users can generate an enormous variety of visual and auditory stimuli and can interact with a wide range of external hardware (enabling its use in fMRI, EEG, MEG etc.). The structure of scripts is simple and intuitive. As a result, new experiments can be written very quickly, and trying to understand a previously written script is easy, even with minimal code comments. PsychoPy can also generate movies and image sequences to be used in demos or simulated neuroscience experiments. This paper describes the range of tools and stimuli that it provides and the environment in which experiments are conducted.

No MeSH data available.