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Hi Nabin,
Yes, if you select partial Pearson correlation, the covariates are considered then. So, before measures are calculated.
Best regards,
AnnaHi Nabin,
If you are using a structural pipeline, you can adjust for covariates by selecting the partial Pearson correlation or partial Spearman correlation when creating the graph/network. If you do not select one of these options, covariates won’t be used in the analysis.
- You can export the results to XLS if you right-click on the top of the table that is visualized by pressing Data Selected Measures or Data Selected Comparison:
Check Figure 11 and Figure 14 in this tutorial to see what I mean by going to Data Selected Measures or Data Selected Comparison: http://braph.org/tutorials/pipelines/pipeline-functional-comparison-bud/
- You can add as many metrics as you want, just change the name of the Measure in the measure_class field. The example file is to show how to calculate them using a script and not the GUI. So you can modify it as you need.
- To save the individual subject correlation matrices it is better to do it as well via script. Still, it is possible in the GUI if you press the IndexedDictionary button in the GRAPHS section in analysis.
Dear Sai Prasanna,
The export to XLS file in the GUI is made on the group average results. Nevertheless, we keep the results for each subject. To obtain those, you will need to create your own script. Use ‘example_FUN_WU’ as a base, which is located in the Functional folder inside pipelines, and after calculating the analysis use the following line of code:
ms1 = cellfun(@(x) x.getMeasure(measure_class).memorize('M'), analysis.memorize('G_DICT').getItems, 'UniformOutput', false);measure_class is the type of measure you want, for example, ‘Degree’.
Best regards,
Emiliano and AnnaDear Sergio,
We provide example data for using functional analysis pipelines. And by functional, we understand data that have a time series per each region of analysis. In that case, the example data (generated data) provided under “example data FUN (fMRI)” is also valid for EEG.
In order to get started with the software and the analysis of EEG data you can follow this tutorial: http://braph.org/tutorials/pipelines/pipeline-functional-comparison-bud/
In order to prepare your EEG data for analysis in BRAPH 2, you can follow these instructions: http://braph.org/tutorials/general/functional-data-format/
Best,
AnnaDear Avalon,
In our newest release (https://github.com/softmatterlab/BRAPH-2-Matlab/releases/tag/2.0.0.a3) we added connectivity multiplex pipelines, where the input is an adjacency matrix for each layer per subject.
To understand the structure of the input data, you can check the following tutorial http://braph.org/tutorials/general/connectivity-multiplex-data-format/Dear Sai Prasanna,
Could you please let us know which release are you using?
We recommend using our latest one: http://braph.org/2022/11/15/braph-2-0-0-a2-released/Sometimes parallel computing has problems while using Graphical user interfaces. You could try de-activating it.
Or you could deactivate in the GUI the Memorize Intermediate Results checkbox in the interface of comparison before calculating it, it is down after the measures list.You can just create your own atlas in XLS, following the same structure 🙂
And then make sure you have the same brain regions included in the atlas and in your subject’s dataBest,
AnnaDear Sai Prasanna,
Since you have time series as input, you should use the Functional pipelines, such as Pipeline functional comparison WU/BUD/BUT. In that case, you should arrange the files of each subject in the format 196 (rows) x 111 (columns)
Here you can see how to organize your subjects’ files to use functional pipelines: http://braph.org/tutorials/general/functional-data-format/The connectivity pipelines are to be used with already connectivity matrices of each subject as input (111×111)
Best,
Anna
- You can export the results to XLS if you right-click on the top of the table that is visualized by pressing Data Selected Measures or Data Selected Comparison:
