Description Of Plugins | |
|---|---|
| BOLD Latency Mapping | BOLD Latency Mapping using piece-wise linear (pseudo-trapezoidal) fitting. Access to linked VTC in three approaches: 1. Use VOI file and perform VOI-based mapping. 2. Use VOI file and perform voxel-based mapping. 3. Use MSK files and perform voxel-based mapping. For more details, check the BLM Plugin Online Help Author: Fabrizio Esposito, Brain Innovation |
| Fuzzy Clustering of fMRI time series | This plugin performs a volume-based or cortex-based clustering of the voxels based on their time course, averaged or not. Please check the for a detailed guide. Author: Federico de Martino, Alain Smolders, Rainer Goebel. |
| Cluster-Level Statistical Thresholding GUI Plugin | ClusterThreshGUIPlugin implements a randomization technique to estimate a cluster-level confidence on the current overlaid volume map (VMP) given the current voxel-level confidence level. The intrinsic smoothness of the map is estimated (Forman et al., MRM 1995) and a user-specified number of simulations is performed to assign an alpha-value to each active cluster. Based on the simulations, a minimum cluster size threshold is set for the current VMP to achieve a corrected p of 0.05. For more details, check the ClusterThresh Plugin Online Help Author: Fabrizio Esposito and Rainer Goebel, Brain Innovation B.V. |
| Cluster-Level Statistical Threshold Estimator | ClusterThresh implements a randomization technique to estimate a cluster-level confidence on the current overlaid VMP given the current voxel-level confidence level. The intrinsic smoothness of the map is estimated (Forman et al., MRM 1995) and a user-specified number of simulations is performed to assign an alpha-value to each active cluster. Based on the simulations, a minimum cluster size threshold is set for the current VMP to achieve a corrected p of 0.05. For more details, check the ClusterThresh Plugin Online Help Author: Fabrizio Esposito, Brain Innovation B. V. |
| COPE | ~~ Pipeline including Correction based on Opposite Phase Encoding (COPE) ~~ This plugin corrects EPI data from reverse phase-encoded data (anterior-posterior (AP/PA) and left-right (LR/RL) via image registration. For the manual, please consult the COPE plugin help. Author: Joost Mulders, Levin Fritz and Hester Breman,Brain Innovation B.V. |
| Example GUI Plugin | This simple GUI plugin shows how to exchange information with a GUI script and a simple dialog that allows to perform simple operations (invert intensities in range, count voxels in range, undo) on the current VMR. You may use this source code to get started with writing your own GUI plugins. Author: Rainer Goebel, Brain Innovation B.V. |
| Granger Causality Mapping (GCM) v1.7 | Computes Granger Causality Maps (GCMs) for selected reference regions (VOIs). Granger causality mapping is a technique which explores directed influences (effective connectivity) between distinct regions in fMRI data. See The GCM Help Pages for more... Author: Alard Roebroeck, Maastricht University (updated by Rainer Goebel) |
| Independent Component Analysis (ICA) | This plugin performs a volume-based or cortex-based spatial ICA using the FastICA approach (Hyvarinen, Oja, 2000). A cortex-based ICA is computed if a cortex mask file is provided. Start the ICA using the "Independent Component Analysis" dialog (menu "FuncConn -> Independen Component Analysis (ICA)..."). The resulting component maps are saved in a ICA file. Author: Federico de Martino, Fabrizio Esposito, Rainer Goebel, Brain Innovation B.V. |
| PPI Plugin (v2.0) | This plugin creates the regressors needed for PsychoPhysiological Interaction (PPI) analysis. Author: Joost Mulders, Rick van Hoof, Rainer Goebel |
| RFX Granger Causality Mapping (GCM) v2.7 | Computes Granger Causality Maps (GCMs) for a reference region (VOI) across data of multiple subjects. A generic VOI may be used for all subjects or subject-specific VOI definitions, e.g. from individual localizer experiments. For more information, consult the RFX GCM Help Page. Author: Alard Roebroeck, Maastricht University, Rainer Goebel (RFX plugin code) |
| Self-Organizing Group ICA | This plugin implements the self-organizing group-level ICA, a method described in Neuroimage 25(2005): 193-205. Once you have specified individual ICA files, the program estimates a user-specified number of group-level components, based on the mutual similarities. As parameters it returns for each cluster the min, the mean and the max similarity measure. Author: Fabrizio Esposito, Brain Innovation B. V. |