Dear Vladimir

Thanks a lot for your help.

I will try your comments.

Best regatds.

Nasibeh

On Mon, Oct 30, 2017 at 6:01 PM, Vladimir Litvak

<[log in to unmask]> wrote:

Dear Nasibeh,

Connectivity analyses are challenging even with a large number of channels. Projecting your data to source space does not get rid of volume conduction. I would recommend you to use a minimum norm solution and perhaps carefully choose your connectivity measure to, for instance, only use the imaginary part of the cross-spectrum. 

Best,

Vladimir

On Mon, Oct 30, 2017 at 2:21 PM, nasibeh talebi <[log in to unmask]> wrote:

Dear Vladimir

Thanks a lot for your helpful advice. Actually, I am going to perform a connectivity study with this dataset, and as the connectivity measures are affected by the "volume conduction" effect, I want to extract the underlying sources of the scalp potentials.

I am wondering if I can have your comments.

Best,

Nasibeh

On Monday, October 30, 2017, 5:39:21 PM GMT+3:30, Vladimir Litvak <[log in to unmask]> wrote:

Dear Nasibeh,

19 electrodes is indeed a pretty low number. If the spatial solution cannot be well estimated then also the time courses will not be separated well. If you are just interested in the temporal dynamics it might be better to stay at the sensor level. 

I don't think using a coarse mesh can change anything in this case, but perhaps using IID or COH solution (the latter similar to LORETA) will be more robust with a small electrode number than MSP.

Best,

Vladimir

On Mon, Oct 30, 2017 at 1:53 PM, nasibeh talebi <00000a9d20e1b6de-dmarc- [log in to unmask]> wrote:

Dear Eugenio

Thanks a lot for your great help. Would you please help me with these two question:

1. The low accuracy problem of the source reconstruction (due to the small number of EEG electrodes ) is only related to the spatial specification of the sources, or their temporal activity is also poorly estimated?

2. for a small number of electrodes, is it preferable to use "coarse cortical mesh" instead of normal?

Best regards

Nasibeh

On Monday, October 30, 2017, 11:56:14 AM GMT+3:30, Eugenio Abela <[log in to unmask]> wrote:

Source recon from 19 electrode EEG is tricky because of low spatial sampling; be careful when interpreting the data. 

That being said, your time series looks ok to me - SPM applies a Hanning window per default, so the data will have highest amplitude in the middle of the trial and be damped towards beginning and end. This can be switched off; have a look at the EEG section of the SPM manual

Hope that helps

- Eu

Am 30.10.2017 um 08:17 schrieb nasibeh talebi <00000a9d20e1b6de-dmarc- [log in to unmask]>:

Dear SPM experts

 

Hi

 

I have a 19-channel resting state EEG dataset. The EEG is recorded for about 120s at the sampling rate of 128Hz.

I want to perform the 3D source reconstruction and extract the temporal activity of the sources. I used the MSP algorithm in SPM, but the results are strange (attached file).

Does SPM have an appropriate source reconstruction algorithm for resting state EEG? or should I choose an alternative toolbox?

 

Best regards

Nasibeh

<td5_sourceSample_MSP.tif>