Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering
GNU General Public License v3
Yes
University of Zurich and ETH Zurich
NITRC
TAPAS - Translational Algorithms for Psychiatry-Advancing Science
OS Independent
Yes
MATLAB, Python
TAPAS Admin
TAPAS is a collection of algorithms & software tools developed by the Translational Neuromodeling Unit, Zurich, & collaborators. The goal of these tools is to support clinical neuromodeling, particularly computational psychiatry, neurology, & psychosomatics.
Contents:
ceode: Robust estimation of convolution based DCMs for evoked responses
HGF: The Hierarchical Gaussian Filter; Bayesian inference on computational processes from observed behaviour
HUGE: Variational Bayesian inversion for hierarchical unsupervised generative embedding
MICP: Bayesian Mixed-effects Inference for Classification Studies
MPDCM: Efficient integration of DCMs using massive parallelization
PhysIO: Physiological Noise Correction for fMRI
rDCM: DCM based, efficient inference on effective brain connectivity for fMRI
SEM: SERIA Model for Eye Movements (saccades & anti-saccades) and Reaction Times
VBLM: Variational Bayesian Linear Regression
FDT: Filter Detection Task
TAPAS is written in MATLAB & distributed under GNU GPL V3.
2020-9-09
5 - Production/Stable/Mature
v4.0.0
2019-3-26
5 - Production/Stable/Mature
v3.1.0
2018-9-19
5 - Production/Stable/Mature
v3.0.0
2018-3-12
5 - Production/Stable/Mature
v2.7.4.1
TAPAS - Translational Algorithms for Psychiatry-Advancing Science
Algorithm or Reusable Library, 5 - Production/Stable/Mature, Attention Deficit Disorder with Hyperactivity, EEG/MEG, Clinical Neuroinformatics, MR, Computational Neuroscience, Developers, End Users, GNU General Public License v3, English, OS Independent, MATLAB, Python, ANALYZE, NIfTI-1, Philips PAR/REC
http://www.nitrc.org/projects/tapas/, http://http://www.translationalneuromodeling.org/tapas
tapas@biomed.ee.ethz.ch