[FieldTrip] Opposite DICS Beamforming results on source and sensor level on resting state data

Stolk, A. (Arjen) a.stolk at fcdonders.ru.nl
Mon Jan 5 15:39:25 CET 2015


Hey Haiteng,

Is your contrast based on absolute signal frequency power? If so, did you check for any systematic differences in headposition (and especially in terms of distance to the sensors - the z-dimension) across the groups? I presume such a systematic difference could yield different results at the sensor- and source-level, but there are probably also other possibilities out there.

Yours,
Arjen

--
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen

Email:  a.stolk at donders.ru.nl<mailto:a.stolk at donders.ru.nl>
Phone:  +31(0)243 68294
Web:    www.arjenstolk.nl<http://www.arjenstolk.nl>
________________________________
From: fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl] on behalf of Haiteng Jiang [haiteng.jiang at gmail.com]
Sent: Monday, January 05, 2015 3:23 PM
To: fieldtrip at science.ru.nl
Subject: [FieldTrip] Opposite DICS Beamforming results on source and sensor level on resting state data

Hi  all,

   I performed DICS beamforming on resting-state data ( eyes closed) of a clinical population and controls. According to the sensor data,  the control groups have more alpha-band (8-14
Hz) activity over occipital  areas  after cluster statistic (attached figure  upper plot) . Curiously, after beamforming ,  group comparisons showed the reversed patters in visual cortex (attached figure  bottom plot) .Hence, the source-level results are opposite to the sensor-level results. This is *not* a problem of the design matrix, or confusing the groups.  I check  the individual neural  activity index on the single subject level .   They  make sense in general .  I also tune the parameter a lot (tapper, central frequency smooth frequency , regularization  parameter , et al ), the  opposite pattern remains.  I  understand that Beamformer images DO NOT DIRECTLY CORRESPOND TO ANY sensor data.   However, the opposite pattern is really weird.  I noticed that  Tobias Navarro Schröder had the similar issue 4 years ago (http://mailman.science.ru.nl/pipermail/fieldtrip/2011-May/003875.html).  Thus,  I am not the only one who encountered this problem.

   Any tips and suggestions will be greatly appreciated.  Thanks in advance!
      [cid:ii_i4jxr2sz1_14aba77f4264462a]


                                                            Best,
                                                            Hatieng






--
Haiteng Jiang
PhD candidate
Donders Institute for Brain, Cognition and Behaviour
Neuronal Oscillations Group
Computational Cognitive Neuroscience Lab
https://sites.google.com/site/haitengjiang/
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