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 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://dev.nitrcce.org/projects/tapas/, http://http://www.translationalneuromodeling.org/tapas tapas@biomed.ee.ethz.ch.nospam