![]() ![]() ![]() In most cases, you would want to motion-correct the data, remove these drifts first or perform other types of typical data pre-processing before running the analysis. Low-frequency drifts and motion in the data can adversely affect the decomposition. The High pass filter cutoff controls the longest temporal period that you will allow. Changes here will not affect the analysis and only change the x-axis units of the final time series plots. TR controls the time (in seconds) between scanning successive FMRI volumes. ica directories, the name of which is based on the input data's filename (unless you enter an Output directory name).ĭelete volumes controls the number of initial FMRI volumes to delete before any further processing. Results for each input file will be saved in separate. You can select multiple files if you want MELODIC to perform a group analysis or if you want to run separate ICAs with the same setup. users/sibelius/) by pressing Select 4D data. Dataįirst, set the filename of the 4D input image (e.g. If you are running lots of analyses you probably want to turn this off you can view the same logging information by looking at the report_log.html or log.txt files in any MELODIC directories instead. The Progress watcher button allows you to tell Melodic not to start a web browser to watch the analysis progress. Structural images for use as "highres" images in registration should normally be brain-extracted using BET.īalloon help (the popup help messages in the MELODIC GUI) can be turned off once you are familiar with the GUI. To call the MELODIC GUI, either type Melodic in a terminal (type Melodic_gui on Mac), or run fsl and press the MELODIC button.īefore calling the GUI, you need to prepare each session's data as a 4D NIFTI or Analyze format image there are utilities in fsl/bin called fslmerge and fslsplit to convert between multiple 3D images and a single 4D (3D+time) image. For detail, see a technical report PDF.įsl_regfilt - command-line tool for removing regressors from data (melodic denoising) For detail, see a technical report on TICA PDF.Ī paper investigating resting-state connectivity using independent component analysis has been published in Philosophical Transactions of the Royal Society. For detail, see a technical report on MELODIC PDF.Ī paper on Tensor ICA for multi-session and multi-subject analysis has been published in NeuroImage. MELODIC can pick out different activation and artefactual components without any explicit time series model being specified.Ī paper on MELODIC Probabilistic ICA (PICA) has been published in IEEE TMI. 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 ( Multivariate Exploratory Linear Optimized Decomposition into Independent Components ) 3.0 uses Independent Component Analysis to decompose a single or multiple 4D data sets into different spatial and temporal components. Using melodic for just doing mixture-modelling.
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