Question

Asked 7th Apr, 2020

University of South Carolina

How can I plot time series of each component resulted from group ICA Melodic?

I have run Melodic ICA on 4D resting state data of a group of subjects (56). Now I want to view spatial maps, time series and power spectrum for each component (25 components totally). I am using fsleyes on Melodic mode however voxel intensity across all components is shown in time series instead of the component time series for the current component. It is the case for power spectrum plot too. In plot control panel I have marked two available options: pixdim and component time courses for melodic images. I attached an image showing spatial maps, time series and power spectrum plots. Does anyone know how I can plot time series and power spectrum for each component not each voxel?

Any suggestion and comment is appreciated.

Screenshot from 2020-04-07 12-44-
51.png
1.34 MB

Time Series

Power Spectrum

ICA

Faraed Salman

Erbil polytechnic university

Pedro L. Contreras E.

University of the Andes (Venezuela)

Arif Armağan Gözütok

Istanbul Technical University

Tohid Rahimi

Bernard Garnier

bluesolutions consulting

How to extract BOLD signals of all the voxels within a mask in FSL?

Question

12 answers

Asked 2nd Dec, 2019

Sumit Swargiary

I am stuck at extracting the BOLD signals of all the voxels within a mask from 4D NIfTI images in FSL. In FSL if we hover over a 4D fMRI image to any particular voxel and click it, then we can see the time-series data of that particular voxel which is our required BOLD signal of that voxel. But I want the time-series or BOLD signal data of all the voxels within the mask extracted at once. How do I do it in FSL or if there is any script that can help me solve this problem.

It would be very much helpful for any kind of help provided.

For using the fslcc command how do I get the reference network and the melodic_IC file in the same space?

Question

Be the first to answer

Asked 4th Jan, 2023

Nair Ul Islam

I have done MELODIC analysis in the FSL, and performed group analysis. The fMRI data has been reduced to 30 ICs, which are present in the Melodic_IC file. Now, I want to individually identify these components, and for that I am using the Smith's atlas which contains 20 networks.

However, these two files are not in the same space. How can I get them into the same space so that I can use fslcc to identify the networks that my ICs refer to?

I have tried registering Melodic_IC and the reference fire to the MNI space, but it then it is not able to identify the networks correctly as both these files contained multiple concatenated maps, and flirt by default registers only the first map to the MNI space, and ignores the others. I also tried registering my melodic_IC file with the reference network, but I faced the same issues as well. Is there anything that I am doing wrong or overlooking?

How can I extract independent components of my fMRI data?

Question

2 answers

Asked 11th May, 2016

Shiva Alipour

Dear all,

I have 2 groups of healthy and autistic people each containing 10 individuals. for each individual I have extracted 264 most important voxels using an atlas. each voxel has a time series consisting of 180 samples.

Now here is the question. how should I extract independent components using ICA method? could you please recommend me some papers about it? I am pretty confused.

should I extract the ICs for each slice separately and then unite them all? what does it mean when they say temporal concatenation in articles? do they concatenate all time series of all voxels of a single subject in one row?

any help would be highly appreciated.

Best Regards

Group ICA using FSL Melodic: How would you interpret an excessive number of components in a particular group?

Question

7 answers

Asked 21st Jan, 2015

András Jakab

We have performed group ICA in two groups of patients (BOLD fMRI data). One group is controls, one is with very severe developmental brain abnormalities (mixed group). In controls, ICA revealed 6 components (mostly bilateral), while in the diseased group, we get 30-40 components on the group level, and the components are small and focal. Data preprocessing is the same, data quality is also the same (although the brains themselves might show some anatomical heterogeneity as well).

I am very curious how this excessive number of IC can be interpreted. We may assume that the diseased group have impaired brain functioning, even no brain functioning (e.g. due to neural migration disorders) at the respective areas.

Thank you.

András

Can anyone suggest an online tool for entering coordinates to view brain location (e.g. MNI vs Talairach)?

Question

33 answers

Asked 5th Mar, 2014

Christine Girges

I am using the newest version of SPM which gives coordinates in MNI space. However, I cannot seem to find an online tool that will allow me to enter these coordinates to view the brain location.

I was using the following website (http://www.talairach.org/applet/) - but I am unsure if I need to convert or correct anything. Also, I am wondering why many of these online tools do not label any sulci?

How can I convert nifti files to img/hdr?

Question

5 answers

Asked 20th Jun, 2019

Diana Trujillo-Rodríguez

I need the images loaded into MATLAB for the analysis. I have the .nii segmentation file and in the instructions for practice I was asked to

manipulate the files as .hdr and .img, which, it says, MATLAB can read.

My question is, Is there an easy way to convert a file saved as .nii to .hdr and .img files? I need to discard the first scans of an fMRI time series to avoid T1 effects. I am totally new in this topic. So I am, for now, just learning the basics to complete a data analysis and I am stucked here.

How to do r to z fisher transformation using matlab?

Question

5 answers

Asked 30th Apr, 2019

Wasana Ediri Arachchi

I have functional connectivity .mat matrices and need to convert to fishers z score.

Thank you

How can I extract volume values (voxels, mm3?) for each individual on a particular cluster in FSL-VBM analysis?

Question

11 answers

Asked 10th May, 2016

Jonatan Ottino González

Hi everyone,

I ran a VBM analysis between unpaired groups and got 4 significant clusters.

I used the Cluster command to get the significant clusters on a text file to visualize their p-values, coordinates, etc.

Cluster –i tfce_corrp_tstat1 –t 0.95 -o cluster_size osize=cluster_size > results.txt

Then I used fslmaths to extract a particular cluster (remove just 1 out of 4 from the tfce_corrp_tstat1) and binarized it as a mask.

fslmaths –dt int cluster_size -thr <min value> -uthr <max value> -bin <mask_name>

Where –thr and -uthr is the minimum-maximum (threshold) value from the index_cluster column at the results.txt where every significant cluster is displayed (1-4). In my case the -thr and -uthr values were the same (1), because only cluster 1 was of my interest.

I checked the mask and everything went ok at this point (1 cluster = 1 mask).

I finally used fslmeants to calculate volumes for that cluster on each individual. The problem, I think, is that I’ve calculated the mean values of voxels' intensity in that cluster, not the total volume of it.

fslmeants –i <GM_mod_merg_s3> –m <cluster_mask> > results_cluster.txt

I would like to calculate the total volume of that particular cluster (voxels, mm3) for every subject (n=56) to do correlations/regressions with other behavioral/cognitive variables in SPSS. I think my problem is in Step 3, do someone know a better way to calculate volumes on a particular cluster?

I also performed a manual extraction for the data using kernel spheres but I’m not happy with the results/method because even if I merge several spheres to create a mask to cover all the cluster I still got some voxels out of it (and viceversa).

Thanks!

How to determine FOV of MRI scans?

Question

7 answers

Asked 4th Apr, 2016

Ali M. Hasan

I want to know how can I find Field of View of each patient in dataset, because I need it to compute the voxel volume

Removal of intra-class associations in joint transform power spectrum

Article

May 1993

A technique to remove the spectral contents of the intra-class association (ICA) with a hybrid joint transform correlator (JTC) is presented. We have shown that the removal of ICA content from the joint transform power spectrum (JTPS) can significantly improve the performance of correlations, the space bandwidth product and efficiency for a joint t...

A Method to Accurately Generate Synthetic Self-affine Time Series for -1 < beta < 3

Article

Dec 2009

Previous studies have proposed various methods to generate synthetic self-affine time series data. Our study shows that these previous methods generate synthetic time series in which beta is not constant over all frequencies. The inaccuracies result from a lack of phase information in the calculations, the inclusion of only positive frequencies, th...

Clock prediction and cross-sigma

Conference Paper

Apr 1996

A. Lepek

The purpose of this paper is to describe relations between the prediction of clock time series Xm, the prediction error standard deviation σ and σ which is used to estimate σ in the presence of noise. We confine the discussion to linear predictors. These predictors are sufficient to optimally predict clocks whose stability is described by an extens...

Got a technical question?

Get high-quality answers from experts.

Ask a question

How can I plot time series of each component resulted from group ICA Melodic?

Top contributors to discussions in this field

Similar questions and discussions

Related Publications