TAPAS - Translational Algorithms for Psychiatry-Advancing Science

TAPAS is a collection of algorithms and software tools developed by the Translational Neuromodeling Unit (TNU, Zurich) and collaborators. The goal of these tools is to support clinical neuromodeling, particularly computational psychiatry, computational neurology, and computational psychosomatics.

Currently, TAPAS includes the following packages:

HGF: The Hierarchical Gaussian Filter; Bayesian inference on computational processes from observed behaviour

MICP: Bayesian Mixed-effects Inference for Classification Studies

MPDCM: Massively Parallel DCM; Efficient integration of DCMs using massive parallelization

PhysIO: Physiological Noise Correction for fMRI

SEM: SERIA Model for Eye Movements (saccades and anti-saccades) and Reaction Times

VBLM: Variational Bayesian Linear Regression

TAPAS is written in MATLAB and distributed as open source code under the GNU General Public License (GPL, Version 3).

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Other Keywords:
Bayesian, DCM, fMRI, HGF, PhysIO, SPM


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