[FieldTrip] Artifact in LCMV beamformer source localization

Sarang S. Dalal sarang at cfin.au.dk
Wed Oct 4 09:47:19 CEST 2017

Hi Bushra,

Are you using the common filter approach to use the same spatial filter for your contrasted conditions?

(Although that example is focused on DICS and PCC, a similar approach can also be used for LCMV.)

This should reduce the likelihood of the 'middle of the head' artifact. If the filters are computed independently, however, then the noise suppression characteristics of each filter can be different, so the contrast would pull out differences in each filter's noise performance.

If you are already using this approach, then you can try weight normalization, which is one strategy for removing the noise bias (and usually prevents the 'center of the head' artifact even when no contrast is done). You can run this by adding to your cfg structure:
cfg.lcmv.weightnorm = 'nai'
- or -
cfg.lcmv.weightnorm = 'unitnoisegain';

Each of those methods should give you the same result with a contrast. The NAI is simply scaled against the theoretical noise power (i.e., the noise level = 1), so is often preferred when no contrast is done.


On Wed, 2017-10-04 at 07:33 +0000, Bushra Riaz Syeda wrote:


I am using lcmv to source localize somatosensory response of Electric stimulation to the index finger of the left hand of subjects.

500 ms of post-stimulus interval is contrasted to 500 ms of pre-stimulus interval. The problem is I see strong activity in the middle of the head for couple of my subjects. It is very strong for one subject as shown ( link to figure 1: https://chalmersuniversity.box.com/s/jxmq5zp8k9m9tdfpogem7ee3r4z9q3ac )and week for other subjects ( link for figure 2: https://chalmersuniversity.box.com/s/o3yl57s6phr96f9rxh4wuthjcgllr2vv ) . I thought that noise bias towards the center of the head is usually taken care of when comparing conditions. Could somebody guide me how to solve this problem. Specially figure 1 where the noise bias is so strong that I don’t see any activity in somatosensory cortex.

Thank you

Kind regards

Bushra Riaz

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