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<p class="MsoNormal">Dear community,<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><span lang="EN-US">I am working on resting-state EEG data with around 40 trials per subject, each trial with a length of 10 seconds (sfrequency= 150Hz). This data is preprocessed using fieldtrip functions (Low-, Highpass filtering, ICA
etc.) and then source reconstructed with the LCMV beamformer to 2338 source points on the individual subjects cortex.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Now I want to estimate Granger Causality (GC) for all of the 2338 source points, which requires mvar models of each subjects data. Here I use the “BioSig” toolkit with the default Vieira-Morf algorithm to remodel my data.
While modelling most of my matrices are very badly conditioned with rcond’s of e<sup>-18</sup> and lower.
<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">After modelling it is necessary to choose the best fitting model order. So I calculate the Akaike and Bayesian Information criterion (AIC, BIC). But the AIC and BIC results are all “Inf” or “-Inf”, since the determinate
of the noisecovariance results in that.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">So does anyone else came across this issue? My presumption is, that the enormous amount of 2338 source/signals unavoidably results in badly conditioned matrices, since the number of comparisons/predictions that need to
be made is too high and the algorithm assumes that every source/signal takes a role in every prediction of every value, therefore resulting in very small values for each ar-coefficient.
<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">I appreciate any comment and/or contribution to that topic.
<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Greetings and all the best,<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Daniel van de Velden<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="color:#A6A6A6;mso-fareast-language:DE">------------------------------------------------</span><span style="color:#A6A6A6;mso-fareast-language:DE"><o:p></o:p></span></p>
<p class="MsoNormal" style="line-height:12.0pt;mso-line-height-rule:exactly"><span style="font-size:10.0pt;color:black;mso-fareast-language:DE"><o:p> </o:p></span></p>
<p class="MsoNormal" style="line-height:12.0pt;mso-line-height-rule:exactly"><i><span style="font-size:10.0pt;color:#365F91;mso-fareast-language:DE">Daniel van de Velden (M.Sc.) || PhD candidate<o:p></o:p></span></i></p>
<p class="MsoNormal" style="line-height:12.0pt;mso-line-height-rule:exactly"><i><span style="font-size:10.0pt;color:#365F91;mso-fareast-language:DE">Wissenschaftlicher Mitarbeiter<o:p></o:p></span></i></p>
<p class="MsoNormal" style="line-height:12.0pt;mso-line-height-rule:exactly"><i><span style="font-size:10.0pt;color:#365F91;mso-fareast-language:DE">Klinik für Klinische Neurophysiologie
<o:p></o:p></span></i></p>
<p class="MsoNormal" style="line-height:12.0pt;mso-line-height-rule:exactly"><i><span style="font-size:10.0pt;color:#365F91;mso-fareast-language:DE">Georg-August-Universität Göttingen<o:p></o:p></span></i></p>
<p class="MsoNormal" style="line-height:12.0pt;mso-line-height-rule:exactly"><i><span style="font-size:10.0pt;color:#365F91;mso-fareast-language:DE">Robert-Koch.Str. 40, 37075 Göttingen<o:p></o:p></span></i></p>
<p class="MsoNormal" style="line-height:12.0pt;mso-line-height-rule:exactly"><i><span lang="EN-US" style="font-size:10.0pt;color:#365F91;mso-fareast-language:DE">Tel. 0551- 39-65106<o:p></o:p></span></i></p>
<p class="MsoNormal"><o:p> </o:p></p>
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