neuroelf_methods

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neuroelf_methods [2013/02/01 22:30] jochen |
neuroelf_methods [2013/02/02 01:38] (current) jochen added cluster table function |
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===== List of methods (overview) ===== | ===== List of methods (overview) ===== | ||

- | The following list gives an overview on what methods of analysis and parameter estimation are implemented in NeuroElf (as far as they exceed basic operations, such as for example plain averaging across a dimension): | + | The following list gives an overview on what methods of analysis and parameter estimation are implemented in NeuroElf (as far as they exceed basic operations, such as for example plain averaging across a dimension, or auxiliary functions that are used for string manipulation, file in-/output, or extended array operations, etc.): |

==== Cluster size threshold estimation (alphasim) ==== | ==== Cluster size threshold estimation (alphasim) ==== | ||

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* allows to estimate the cluster size threshold for fully independent components of a conjunction analysis | * allows to estimate the cluster size threshold for fully independent components of a conjunction analysis | ||

* as a still experimental feature allows to apply a shift in the Z-distribution to account for shifts in the observed distribution of a statistical map (e.g. by-chance global "signal" in a covariate regression) | * as a still experimental feature allows to apply a shift in the Z-distribution to account for shifts in the observed distribution of a statistical map (e.g. by-chance global "signal" in a covariate regression) | ||

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+ | ==== Cluster table generation ==== | ||

+ | [[Cluster table|Cluster tables]] are often presented in publications describing analyses where whole-brain mapping was performed, i.e. the attempt in localizing the spatial nodes within cortex that subserve a specific function. This function is | ||

+ | |||

+ | * implemented in a combination of an M-file, **''[[clustervol|clustervol.m]]''** and a compiled MEX-file, coded in **''[[clustercoordsc|clustercoordsc.c]]''** | ||

+ | * whereas the M-file provides a command-line interface with rich options for output formatting, converting coordinates, thresholding volumes, etc. | ||

+ | * and the C/MEX-file provides the actual clustering of the binary (thresholded and masked) volume into separate spatial nodes | ||

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+ | Once a (thresholded) map has been segregated into separate volumes (such that voxels of different clusters do not "touch" voxels of another cluster), clusters of considerable size (e.g. more than 100 voxels) sometimes exhibit "local maxima", i.e. the spatial gradient becomes positive again from the overall maximum outwards after being negative in the beginning. To detect this, a 3D watershed algorithm has been implemented in the function **''[[splitclustercoords|splitclustercoords.m]]''**. | ||

==== Conjunction analysis (minimum t-statistic) ==== | ==== Conjunction analysis (minimum t-statistic) ==== |

neuroelf_methods.txt ยท Last modified: 2013/02/02 01:38 by jochen