Dear SPM-users,
we are happy to announce a new release 3.0.0 of our TAPAS software suite on GitHub: https://translationalneuromodeling.github.io/tapas/
Besides updates to most of our toolboxes (HGF, MPDCM, PhysIO, SERIA), we have two new 'tapas' for DCM:
• HUGE: Variational Bayesian inversion for hierarchical unsupervised generative embedding (https://doi.org/10.1016/j.neuroimage.2018.06.073).
• rDCM: DCM-based, efficient inference on effective brain connectivity for fMRI (https://doi.org/10.1016/j.neuroimage.2018.05.058).
For more information, see below** or checkout the documentation on GitHub: https://github.com/translationalneuromodeling/tapas/blob/master/README.md
We are excited about your feedback (https://github.com/translationalneuromodeling/tapas/issues)!
Kind regards,
Lars Kasper (PhysIO Developer)
TNU
**What is TAPAS?
TAPAS is a collection of software tools developed by the Translational Neuromodeling Unit (TNU, at University of Zurich and ETH Zurich, Switzerland) 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 (mostly in Matlab):
HGF: Hierarchical Gaussian Filter; Bayesian inference on computational processes from observed behaviour
HUGE: Variational Bayesian inversion for hierarchical unsupervised generative embedding
MICP: Mixed-effects Inference for Classification Studies
MPDCM: Massively Parallel DCM
PhysIO: Physiological Noise Correction for fMRI, integrated with SPM Batch Editor
rDCM: Regression Dynamic Causal Modeling, efficient inference on effective brain connectivity for fMRI
SEM: SERIA Model for Eye Movements (saccades and anti-saccades) and Reaction Times
VBLM: Variational Bayesian Linear Regression
--
Lars Kasper, PhD
Translational Neuromodeling Unit /
MR Technology and Methods Group
Institute for Biomedical Engineering
University of Zurich & ETH Zurich
Wilfriedstrasse 6 / Gloriastrasse 35
8032 Zurich / 8092 Zurich
phone: + 41 44 634 91 09 / +41 44 632 09 68
e-mail: [log in to unmask]
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