to decompose a single or multiple 4D data sets into different spatial and temporal components. For multiple input data sets, MELODIC uses either Tensorial Independent Component Analysis (TICA), where data is decomposed into
to decompose a single or multiple 4D data sets into different spatial and temporal components. For ICA group analysis, MELODIC uses either Tensorial Independent Component Analysis (TICA), where data is decomposed into
spatial maps, time courses and subject/session modes or a simpler temporal concatenation approach. MELODIC can pick out different
activation and artefactual components without any explicit time series model being specified.
...
...
@@ -27,6 +27,7 @@ quote the journal reference listed there.
<LI><ahref="#regfilt">fsl_regfilt</a> - command-line tool for removing regressors from data (melodic denoising)<br>
</UL>
<ANAME="MelodicGUI"></A><hr><H2>Melodic GUI</H2>
<IMGALIGN=RIGHThspace=20vspace=20SRC="gui.png"
...
...
@@ -46,15 +47,20 @@ and fslsplit</a> to convert between multiple 3D images and a single 4D
should normally be brain-extracted using <ahref="../bet2/index.html"
target="_top">BET</a>.
<H2>GUI details</H2>
Contents<br>
<ahref="#misc">Misc</a><br>
<ahref="#data">Data</a><br>
<ahref="#prestats">Pre-Stats</a><br>
<ahref="#reg">Registration</a><br>
<ahref="#stats">Stats</a><br>
<ahref="#poststats">Post-Stats</a><br>
<ahref="#buttons">Bottom Row of Buttons</a><br>
<H3>GUI details:</H3>
<UL>
<LI><ahref="#misc">Misc</a><br>
<LI><ahref="#data">Data</a><br>
<LI><ahref="#prestats">Pre-Stats</a><br>
<LI><ahref="#reg">Registration</a><br>
<LI><ahref="#stats">Stats</a><br>
<LI><ahref="#poststats">Post-Stats</a><br>
<LI><ahref="#buttons">Bottom Row of Buttons</a><br>
<p>The Stats section lets you control some of the options for the decomposition. The default setting will most probably already be set to what you would want most of the time.
<p> By default, MELODIC will variance-normalise
<p> By default, Melodic will automatically estimate the number of
components from the data - you can switch this option off and then can specify the number of components explicitly.<p>
<p> You can select the type of analysis. If only a single input name was specified MELODIC will perform a single session ICA analysis.
<p> You can now select the type of analysis. MELODIC currently offers three options
<UL>
<LI><b>Single-session ICA:</b> This will perform standard 2D ICA runs on each of the input files. Data will be represented as a time x space matrix and be de-composed into a pairs of time courses and spatial maps.
<LI><b>Multi-session temporal concatenation:</b> This will perform a 2D ICA run on the concatenated data matrix (obtained by stacking all 2D data matrices of every single data set on top of each other). For each component the final mixing matrix <code>melodic_mix</code> contains the temporal response of all different data concatenated into a single column vector. The final reported time course will be the best rank-1 approximation to these different responses.
<LI><b>Multi-session Tensor-ICA:</b> This will perform a 3D Tensor-ICA decomposition of the data. Data will be represented as a time x space x sessions block of data and be de-composed into triplets of time courses, spatial maps and session/subject modes. For more details on the decomposition see the technical report <ahref="http://www.fmrib.ox.ac.uk/analysis/techrep/"> TR04CB1 </a>.
</UL>
<aname="poststats"></a>
<hr><H3>Post-Stats</H3>
<p> Melodic will also by default carry out inference on the estimated maps
using the mixture model approach. A threshold level of 0.5
using a mixture model and an alternative hypothesis testing approach. A threshold level of 0.5
in the case of alternative hypothesis testing means that a
voxel 'survives' thresholding as soon as the probability
of being in the 'active' class (as modelled by the Gamma
your terminal window will tell you where to find the web report.
...
...
@@ -161,15 +174,15 @@ followed by the relevant time-course of the ICA decomposition and the power-spec
<p>In the case of TICA or simple time series concatenation the time course plotted is the rank-1 approximation to all the different time courses that correspond to the given spatial map within the population.
<p>If a temporal design was specified in the <ahref="#poststats"target="_top">Post-Stats</a> section then the time series plot will also contain a plot of the total model fit. In addition, a simple GLM table will describe the fit in detail, providing information of the regression parameter estimates (PEs). Furthermore, MELODIC will perform a simple F-test on the estimated time course and the total model fit. For task related components the model fit will explain large amounts of the variaiton contained in the estimated time couse. In addition, if a contrast matrix was specified, the table will also contain Z-statistics and p-values for all the contrasts.
<p>If a temporal design was specified in the <ahref="#poststats"target="_top">Post-Stats</a> section then the time series plot will also contain a plot of the total model fit. In addition, a simple GLM table will describe the fit in detail, providing information of the regression parameter estimates (PEs). Furthermore, MELODIC will perform a simple F-test on the estimated time course and the total model fit. For task related components the model fit will explain large amounts of the variation contained in the estimated time couse. In addition, if a contrast matrix was specified, the table will also contain Z-statistics and p-values for all the contrasts.
If a group analysis was carried out then the report page will also include information on the distribution of the effect size across the population. A simple plot and a boxplot show the relative effect size across the different sessions/subjects. If a designmatrix was specified in the GUI setup then MELODIC will also include a GLM regression fit table.
If a group analysis was carried out then the report page will also include information on the distribution of the effect size across the population. A simple plot and a boxplot show the relative effect size across the different sessions/subjects. If a designmatrix was specified in the GUI setup then MELODIC will also include a GLM regression fit table.
where you should replace the comma-separated list of component numbers with the list that you previously recorded when viewing the MELODIC report.<br>
</UL>
The output file <code> denoised_data.nii.gz</code> then contains the filtered and denoised data set which can be used e.g. within FEAT. When running FEAT on this data make sure that the analysis is set to <code>Stats + Post-stats </code> as you do not want to run the other filtering steps (smoothing etc.) again on this data.
