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Hello Jan-Mathijs,</div>
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Thank you very much for your reply, I really appreciate that time you took to read and answer to my email. If I may size the opportunity of having your attention, with the aim of not abusing of your time, I'd like to clarify some aspects related to my second
question.</div>
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Regarding the first, I happened to realize it the very same day with further search, as clearly the 'deep dive' I first did was not so deep or at least not enough aware (I let you imagine how embarrassed I felt!).</div>
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Regarding the second, more relevant question, I see your point and agree with that, although it's not exactly what I meant to do. </div>
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I am <b>pre-computing the filter</b> with data from activity + baseline together (let's call it 'freq'), and what I input is the output of ft_freqanalysis (fourier) so that I have
<b>freq.fourierspctrm</b> with <b>nTtrials x nChann</b> (only 1 frequency). The caveat here is that the fourier spectra that I input in DICS has apparently only 1 frequency, but the<b> fourier coeffrcients in each trial</b> is computed at a specific,<b> different</b>,
frequency (integers with range 120-220).</div>
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So, the result is that I compute the filter with (e.g.,) 200 trials with CSDs at
<b>120Hz</b>, 300 trials with <b>145Hz</b> and so on. I then apply this filter to compute the source power of activity and contrasting it with baseline.</div>
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My theoretical justification is the neurobiological assumption for which I expect the
<b>same dipoles</b> to be responsible for generating neural activity at these <b>
different frequencies</b> (and this is not the part I am questioning). What I am questioning is instead what would be the
<b>reliability and stability of the estimated spatial filter</b> since I am <b>averaging CSDs computed at different frequencies</b>.</div>
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To summarize, while I have strong basis to motivate the neurobiological assumption, I don't know if the computation of the filter in such way results as
<b>mathematically incorrect or hardly interpretable</b>. </div>
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Honestly, apart from you guys, I don't know who could provide me with valuable insights in such a highly specific and integrated field, this is why I asked and why I really value your help.</div>
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Thank you so so much again for your attention and help in this matter.</div>
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Kind regards</div>
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<p style="background-color: rgb(255, 255, 255); margin: 0cm; font-family: Calibri, sans-serif; font-size: 11pt;">
<span style="font-size: 10.5pt; color: black;"><b>Enrico Sozza</b></span><span style="font-size: 10pt; color: black;">,</span><span style="color: black;"> </span><span style="font-size: 10pt; color: black;"><i>PhD Student</i></span></p>
<p style="background-color: rgb(255, 255, 255); margin: 0cm; font-family: Calibri, sans-serif; font-size: 11pt;">
<span style="font-family: "Calibri Light", "Helvetica Light", sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">Brainlab – Cognitive Neuroscience Research Group</span></p>
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<span style="font-family: "Calibri Light", "Helvetica Light", sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">Department of Clinical Psychology and Psychobiology</span></p>
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<span style="font-family: "Calibri Light", "Helvetica Light", sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">Institute of Neurosciences</span></p>
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<span style="font-family: "Calibri Light", "Helvetica Light", sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">University of Barcelona</span></p>
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<div id="divRplyFwdMsg" dir="ltr"><font face="Calibri, sans-serif" style="font-size:11pt" color="#000000"><b>From:</b> fieldtrip <fieldtrip-bounces@science.ru.nl> on behalf of Schoffelen, J.M. (Jan Mathijs) via fieldtrip <fieldtrip@science.ru.nl><br>
<b>Sent:</b> 29 March 2025 13:11<br>
<b>To:</b> FieldTrip discussion list <fieldtrip@science.ru.nl><br>
<b>Cc:</b> Schoffelen, J.M. (Jan Mathijs) <janmathijs.schoffelen@donders.ru.nl><br>
<b>Subject:</b> Re: [FieldTrip] DICS in fieldtrip: Hermitian vs not Hermitian spectral matrix computations - Multiple frequencies</font>
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<div style="line-break:after-white-space">Hi Enrico,
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<div>Nice that you dove into the code so deeply. With respect to your worries about computing the CSD-matrix from a matrix with Fourier coefficients as per the matlab syntax tmp*tmp’ I hope I can take these away by saying that the “ ‘ “ operator (the apostrophe)
acutally DOES a complex conjugate transposition of the matrix. (as opposed to “ .’ “, i.e. a dot followed by an apostrophe, which is a ’normal’ transpose)<br id="x_lineBreakAtBeginningOfMessage">
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<div>Regarding your second question: I am not sure whether I fully understand, but I assume that you mean to ask about applying previously computed spatial filters optimized for frequency band X, to data that quantifies frequency band Y (where Y is not contained
by the frequency band X)? I follow your reasoning, but I would say that this is somewhat suboptimal, even indeed as you say that different frequency components might have the same (at least at the spatial resolution permitted by the measurement technique)
neurobiological origins. The reason for this is that the idea that underlies the mathematics of the beamformers is not only that it aims to not distort activity originating from the current location of interest (i.e. the dipole source that you considering
for a given iteration of the scanning loop across all potential dipole positions in your source model), but that it also aims at suppressing potentially distortive effects of uncorrelated sources outside the current location of interest. Thus, a spatial filter
for a particular dipole location does not only reflect properties of the (possibly present) neural source at that location, but also implicitly reflects the other sources of the overall signal at frequency band X. </div>
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<div>Best wishes,</div>
<div>Jan-Mathijs</div>
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<blockquote type="cite">
<div>On 27 Mar 2025, at 16:17, Enrico Sozza via fieldtrip <fieldtrip@science.ru.nl> wrote:</div>
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Hello FieldTrip community allies,</div>
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I come to seek your help in a field that goes way deeper than what my background allows me to understand, so forgive me beforehand if my questions come as no-sense or missing solid theoretical bases.</div>
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I am trying to source localize oscillatory EEG data through DICS beamforming and I came across some theoretical/methodological doubts that I couldn't clarify through the available documentation. </div>
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The first is related to the 'equivalence' of the output of ft_sourceanalysis with method DICS depending on what type of data you input: for what I read, it seems you can feed it with frequency data as output of ft_freqanalysis<span class="x_Apple-converted-space"> </span><u>with
either output 'fourier' or 'powandcsd</u>' and expect the same computation. </div>
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Yet, after a deep dive into the functions, it seems that in ft_checkdata, with freq.fourierspctrm as input, computes<u> just a symmetrical matrix</u> (Cf, to be inverted later on) but n<u>ot the Hermitan transpose with the complex conjugates (Actual CSD matrix)</u>,
which seems to be critical for an adequate estimation of spectral properties and spatial relationship. So, I would say it is not actually the same, and I would say is mathematically 'invalid' (?). If so, why is it implemented in FieldTrip? Why does it compute</div>
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data.fourierspctrm = reshape(data.fourierspctrm, [nrpt nchn nfrq*ntim]);</div>
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crsspctrm = complex(zeros(nchn,nchn,nfrq*ntim));</div>
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for k = 1:nfrq*ntim</div>
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tmp = transpose(data.fourierspctrm(:,:,k));</div>
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tmp(~isfinite(tmp)) = 0;</div>
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n = sum(tmp~=0,2);</div>
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crsspctrm(:,:,k) = tmp*tmp'./n(1);</div>
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instead of: </div>
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<span style="">    <span class="x_Apple-converted-space"> </span></span><span style="color:rgb(147,69,17)">crsspctrm(:,:,k) = tmp*conj(tmp')./n(1); </span></div>
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I guess manually changing the function it is somehow not suggested, otherwise it would have been coded as such since the beginning, but I am still left with quite a bit of uncertainty in such regard.</div>
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My other question is: </div>
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I know DICS is implemented to computing spatial filters tailored to a<span class="x_Apple-converted-space"> </span><u>specific frequency</u>, due to the process of averaging CSDs across trials before computing the inverse. Yet, I also saw that at the end with
'cfg.realfilter = yes' it only works with the<span class="x_Apple-converted-space"> </span><u>real part</u> of the matrix, keeping only the information regarding near zero-lag correlated signal and ignoring any phase-related relationship. </div>
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Keeping this into consideration, and<span class="x_Apple-converted-space"> </span><u>assuming neurobiologically</u> that activity ad different frequencies<span class="x_Apple-converted-space"> </span><u>come from the same neural generators</u>, would it be
mathematically inappropriate or impossible to interpret to compute DICS feeding it with fft coefficients computed at<span class="x_Apple-converted-space"> </span><u>different frequencies across trials</u>? Again, bearing in mind that the goal is source localizing
oscillatory activity (i.e., power) at those different frequencies in different trials, assuming they come from the same sources.</div>
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I am learning so much about this in-depth physics of signal processing and it's quite exciting, but my resources are quite limited, and I therefore would really value and appreciate any insight from you guys, hoping that I am not already blindingly hitting
a wall.</div>
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Thank you very much in advance for the time you took to read this email and for your help.</div>
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Best of luck with your work</div>
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Regards</div>
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<div style="margin:0cm; background-color:rgb(255,255,255); font-family:Calibri,sans-serif; font-size:11pt">
<span style="font-size:10.5pt"><b>Enrico Sozza</b></span><span style="font-size:10pt">,</span><span style=""> </span><span style="font-size:10pt"><i>PhD Student</i></span></div>
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<span style="font-family:"Calibri Light","Helvetica Light",sans-serif; font-size:9pt">Brainlab – Cognitive Neuroscience Research Group</span></div>
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<span style="font-family:"Calibri Light","Helvetica Light",sans-serif; font-size:9pt">Department of Clinical Psychology and Psychobiology</span></div>
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<span style="font-family:"Calibri Light","Helvetica Light",sans-serif; font-size:9pt">Institute of Neurosciences</span></div>
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<span style="font-family:"Calibri Light","Helvetica Light",sans-serif; font-size:9pt">University of Barcelona</span></div>
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<span style="font-family:"Calibri Light","Helvetica Light",sans-serif; font-size:9pt">P. Vall d'Hebron 171, 08035 Barcelona, Catalonia-Spain</span><span style="font-family:"Calibri Light",sans-serif; font-size:9pt; color:rgb(102,102,102)"><br>
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