From Computational Memory Lab
- PyEPL (the Python Experiment-Programming Library) is a library for coding psychology experiments in Python. It supports presentation of both visual and auditory stimuli, and supports both manual (keyboard/joystick) and sound (microphone) input as responses. Visit the PyEPL SourceForge page for more information and downloads. (Methods paper can be found here.)
- PandaEPL is a cross-platform Python library for programming 3D spatial navigation experiments. (Methods paper can be found here.)
PyEPL-based experiments used in the Kahana Lab.
- pyFGS: Face/Grating Sternberg task (tgz)
- pyFR: Free Recall task (tgz)
- YellowCab II: Virtual Driving task (tgz (58.3 MB))
- ycCross: YellowCab Variant (tgz (30.5 MB))
- ycMagellan: PandaEPL-based YellowCab variant, as used in Manning et al., submitted (experiment tgz (50.8 MB), buildings tgz (3.1 GB))
- Trackball: Blinking and eye-movement task (tgz)
- Testsync: Simple program to send sync pulses (tgz)
- Penn TotalRecall: score and annotate behavioral audio files (replaces PyParse)
- Behavioral Toolbox: a suite of MATLAB functions to aid in analyzing behavioral Free Recall data
- Our EEG Toolbox is a set of Matlab functions to help in analyzing EEG data. (zip)
- Current version is 1.3.2, last update June 25, 2008.
- For documentation, please see
eeg_toolbox/doc/doc.pdf. Additionally, use the
helpfunction in Matlab for assistance with individual functions.
- You can also find Dr Josh Jacob's "Introduction to the EEG toolbox" here.
- The Context Maintenance and Retrieval model (CMR).