TAPAS - Translational Algorithms for Psychiatry-Advancing Science
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.
Execution Options
Specifications
Associations
Recent Activity - Documents
Technical Publications documentation
A generative model of whole-brain effective connectivity. posted by Lars Kasper on Sep 19, 2018
Technical Publications documentation
Regression DCM for fMRI. posted by Lars Kasper on Sep 19, 2018
TAPAS README posted by Lars Kasper on Mar 12, 2018
TAPAS Wiki posted by Lars Kasper on Mar 12, 2018
Recent Activity - News
TAPAS v4.0.0 released posted by TAPAS Admin on Dec 16, 2020
TAPAS v3.1.0 released posted by TAPAS Admin on Apr 16, 2019
TAPAS v3.0.0 released posted by Lars Kasper on Sep 27, 2018
Recent Activity - Files
GitHub TAPAS Release Download posted by TAPAS Admin on Dec 3, 2020
GitHub TAPAS Release Download posted by TAPAS Admin on Mar 31, 2019
GitHub TAPAS Release Download posted by Lars Kasper on Sep 19, 2018
GitHub TAPAS Release Download posted by Lars Kasper on Mar 12, 2018