Expyriment
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Mne Python | 2,408 |  | 99 | 185 | 18 hours ago | 76 | November 20, 2023 | 479 | bsd-3-clause | Python |
| MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python | ||||||||||
| Awesome Neuroscience | 974 | a year ago | ||||||||
| A curated list of awesome neuroscience libraries, software and any content related to the domain. | ||||||||||
| Fieldtrip | 772 | 13 hours ago | 124 | gpl-3.0 | MATLAB | |||||
| The MATLAB toolbox for MEG, EEG and iEEG analysis | ||||||||||
| Dcm2niix | 723 |  | 2 | 4 days ago | 2 | July 15, 2022 | 4 | other | C++ | |
| dcm2nii DICOM to NIfTI converter: compiled versions available from NITRC | ||||||||||
| Braindecode | 611 |  | 1 | 3 | 17 days ago | 49 | October 17, 2022 | 59 | bsd-3-clause | Python |
| Deep learning software to decode EEG, ECG or MEG signals | ||||||||||
| Brainiak | 315 | 1 | 3 days ago | 15 | October 15, 2020 | 87 | apache-2.0 | Python | ||
| Brain Imaging Analysis Kit | ||||||||||
| Clinica | 195 |  | 1 | 12 hours ago | 36 | September 08, 2023 | 60 | other | Python | |
| Software platform for clinical neuroimaging studies | ||||||||||
| Neuromorphic Computing Guide | 178 | 10 days ago | Python | |||||||
| Learn about the Neumorphic engineering process of creating large-scale integration (VLSI) systems containing electronic analog circuits to mimic neuro-biological architectures. | ||||||||||
| Dcm2bids | 133 |  | 1 | 1 | a month ago | 25 | October 12, 2023 | 3 | gpl-3.0 | Python |
| Reorganising NIfTI files from dcm2niix into the Brain Imaging Data Structure | ||||||||||
| Canlabcore | 133 | 5 days ago | 28 | other | MATLAB | |||||
| Core tools required for running Canlab Matlab toolboxes. The heart of this toolbox is object-oriented tools that enable interactive analysis of neuroimaging data and simple scripts using high-level commands tailored to neuroimaging analysis. | ||||||||||
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Overview
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. Due to the availability of an Android runtime environment, Expyriment is also suitable for the development of experiments running on tablet PCs or smart-phones.
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.
- Project Homepage: http://www.expyriment.org
GNU General Public License v3 (see details)
Florian Krause ([email protected]) & Oliver Lindemann ([email protected])
Documentation
Documentation can be found in the directory "documentation". For online documentation see: http://docs.expyriment.org
Examples
For online examples see: http://stash.expyriment.org/examples
Installation
The latest stable release of Expyriment can be found at Github: https://github.com/expyriment/expyriment/releases/latest For detailed installation instructions, please see the online documentation: http://docs.expyriment.org/Installation.html
Reference
Krause, F., & Lindemann, O. (2014). Expyriment: A Python library for cognitive and neuroscientific experiments. Behavior Research Methods, 46(2), 416-428. http://dx.doi.org/10.3758/s13428-013-0390-6
Contributing
Join other contributors and help us out with Expyriment development! We are very happy to receive pull requests on GitHub.
