Open Source Psychology Software

IRAMUTEQ : Interface de R pour les Analyses Multidimensionnelles de Textes et de Questionnaires. Logiciel de traitement de données pour des corpus texte ou de type individus/caractères. Permet notamment de réaliser des analyses de type "ALCESTE"

On The Mark is a video and image scoring system that allows one to mark any number of events and durations through a simple, easy-to-use graphical interface.

Global Consciousness Project uses hardware "random" number generators and finds patterns between that and major world events. This Java applet will run on their webpage and translate that data to music-like audio. Or for general audio synthesizing.

ELIA(Eyegaze Language Integration Analysis) supports the analysis of eye-tracking data for studies in language processing. ELIA eases early analysis of data to enable iterative development of experiments in response to spoken language.

EyeMap is a visualization and analysis tool for text reading eye movement data. It can process Unicode, proportion/non-proportion and spaced/unspaced reading materials, which supports various languages and experiment methods.

FreeBrain will be an application for the analysis of 2D neurophysiological signals, like heart-rate, EEG or eyemovements. It is aimed at those who want intuitive or free software and those who want a customizeble tool that can handle mixed datasets.

HabraCharts is an open source project collecting information from habrahabr.ru

The aim of the JQuizAPI project is to define a simple API to construct test that may be used in diferent areas: - Surveys - Psychometric tests - Polls

For the purpose of policy simulation in coupled social-ecological systems (e.g. energy supply), a credible modelling of actors – especially citizens – and their decision processes is needed. This requires a framework capable of handling high numbers of heterogeneous agents (several hundreds of thousands). LARA (Lightweight Architecture for boundedly Rational Agents) meets these requirements and fills the gap between frameworks without built-in psychological foundations and full-fledged cognitive architectures which are both not viable options in this context. LARA provides prefabricated components of an agent’s decision process like perception, memory, and different modes of decision making. These components are psychologically plausible, i.e. based on appropriate psychological results and theories. Moreover, interfaces for basic learning and social influence are available.

This Matlab toolbox runs a GLM on graph theoretic network properties in brain networks. The GLM accepts continuous & categorical between-participant predictors and categorical within-participant predictors. Significance is determined via non-parametric permutation tests. The toolbox allows testing of both fully connected and thresholded networks (based on a range of thresholds). The toolbox also provides a data processing path for resting state fMRI data. Several options for partialing nuisance signals are available, including local and total white matter signal (Jo et al., 2013), calculation of Saad et al. (2013)'s GCOR, and the use of Chen et al. (2012) GNI method to determine whether global signal partialing is needed. In addition, Power et al. (2014)'s motion scrubbing method is available.

NeuroKiwi is the application of the Associative Model (AM, previously dubbed AMDroid), being a model storing relational change-detections. The application tries to emulate ground-up knowledge accumulation with limited or no prior knowledge of shapes or patterns.

An interactive tool for the simulation and visualization of the electromagnetic activity of the brain.

The term "question-answer paradigm" (QAP) is used in psycho-linguistics to refer to a familiar mode of human discourse. QAParadigm facilitates a common QAP experiment that involves a visual display, then a verbal question about the display.

This is a package for Structural Equation Modeling in development. It is written for extensibility, that is, you can easily define your own objective functions and other parts of the model. At the same time, it is (very) fast. We provide fast objective functions, gradients, and for some cases hessians as well as approximations thereof. As a user, you can easily define custom loss functions. For those, you can decide to provide analytical gradients or use finite difference approximation / automatic differentiation. You can choose to mix loss functions natively found in this package and those you provide. In such cases, you optimize over a sum of different objectives (e.g. ML + Ridge). This strategy also applies to gradients, where you may supply analytic gradients or opt for automatic differentiation or mixed analytical and automatic differentiation. You may consider using this package if you need extensibility and/or speed, and if you want to extend SEM.

The Wittgen programming language consists of just two instructions and one special variable name. Wittgen allows you to assign any text string to a variable of any name. It also allows you to retrieve the text assigned to that variable. Lastly, it has a special variable called “Doing Now”. Every execution step consists of retrieving the contents of Doing Now, removing the first assign found in that content and performing that assign. In the course of performing that assign any retrieve operations indicated in the text are performed before committing the assign. That is all there the system does. The driving motivation for this design is that as far as we know, the human mind supports these two instructions.It may have additional mechanisms that create new assigns, but using the results of these mechanisms requires a system built from these instructions.

This software aims in providing a Greek version CES-D test.

This project aims at developing R-based Software for the analysis of typical neuroscientific data. These will include time resolved bootstrap tests and fitting and testing of psychometric functions.