TAPAS - Translational Algorithms for Psychiatry-Advancing Science

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.

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Specifications

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

Associations

has subpart:
can be extended by:
SPM
works well with:
SPM