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<p>Dear Johannes, thank you for your answer. My bad--I was not using an up-to-date version of FieldTrip. Indeed, now that I have updated the code, the transfer matrix is not computed again by ft_prepare_leadfield. <span style="font-size: 12pt;">I think that
a similar check might be necessary for the call to ft_prepare_sourcemodel (line 178 of ft_prepare_leadfield), since the
<span style="font-family: Calibri, Helvetica, sans-serif, EmojiFont, "Apple Color Emoji", "Segoe UI Emoji", NotoColorEmoji, "Segoe UI Symbol", "Android Emoji", EmojiSymbols; font-size: 16px;">
FieldTrip-</span>SimBio pipeline also calls that function explicitly beforehand.</span></p>
<p><br>
</p>
<p>In order to parallelize the transfer matrix computation, in sb_transfer, I suggest that the code at line 41, which currently reads "clear vecb;", be replaced by "vecb=[];", because there is a transparency issue when using "clear" within a parfor loop (see <a href="https://ch.mathworks.com/help/distcomp/transparency.html" class="OWAAutoLink" id="LPlnk178379" previewremoved="true">https://ch.mathworks.com/help/distcomp/transparency.html</a>).</p>
<p><br>
</p>
<p>I have also been trying to parallelize ft_prepare_leadfield. Given that ft_compute_leadfield is called once per grid point, I replaced the for loop at line 301 of ft_prepare_leadfield with a parfor loop. The indexing of grid.leadfield{thisindx} poses a "sliced
variable" problem to MATLAB though. The workaround I used was to create a temporary variable, grid_leadfield, and to index it with {i} instead of {thisindx}. At the end of the loop, the "<span>grid.leadfield(insideindx)=grid_leadfield;" line reestablishes
that variable. I am currently testing this.</span></p>
<p><span><br>
</span></p>
<p><span>Pierre</span></p>
<p><br>
</p>
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<div id="x_divRplyFwdMsg" dir="ltr"><font face="Calibri, sans-serif" color="#000000" style="font-size:11pt"><b>De :</b> fieldtrip <fieldtrip-bounces@science.ru.nl> de la part de fieldtrip-request@science.ru.nl <fieldtrip-request@science.ru.nl><br>
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<b>Objet :</b> fieldtrip Digest, Vol 99, Issue 22</font>
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Today's Topics:<br>
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1. Postdoc opportunity (up to 4 years), Obleser lab, Lübeck<br>
(GER) (Jonas Obleser)<br>
2. Re: Error in source localisation statistics<br>
(Schoffelen, J.M. (Jan Mathijs))<br>
3. issue with FieldTrip-SimBio pipeline for EEG FEM forward<br>
solution (Pierre Bastien Megevand)<br>
4. Parcellate the reconstructed source time series (Neeraj kumar)<br>
5. Re: issue with FieldTrip-SimBio pipeline for EEG FEM forward<br>
solution (Johannes)<br>
<br>
<br>
----------------------------------------------------------------------<br>
<br>
Message: 1<br>
Date: Thu, 21 Feb 2019 14:46:54 +0100<br>
From: Jonas Obleser <jonas@obleser.de><br>
To: fieldtrip@science.ru.nl<br>
Subject: [FieldTrip] Postdoc opportunity (up to 4 years), Obleser lab,<br>
Lübeck (GER)<br>
Message-ID: <0866A3D2-FD30-421C-A138-B34E45CE7704@obleser.de><br>
Content-Type: text/plain; charset="utf-8"<br>
<br>
Dear colleagues, <br>
<br>
sorry for any crossposting:<br>
I am hiring a Postdoc to do some exciting Cogn Neuro with my lab and me near the baltic sea in the years to come.<br>
<br>
This post is not grant-based, so more-than-usual freedom, topicwise, but some modest teaching involvement. Application deadline March 15, starting date any time, full German contract up to 4 years.<br>
<br>
If interested/in doubt, please talk to me. Contact details below.<br>
Thanks for spreading the news, <br>
Jonas<br>
<br>
obleserlab.com <<a href="http://obleserlab.com/" id="LPlnk902076" previewremoved="true">http://obleserlab.com/</a>><br>
uni-luebeck.de <<a href="http://uni-luebeck.de/" id="LPlnk798457" previewremoved="true">http://uni-luebeck.de/</a>>
<br>
<br>
Job ad in English:<br>
<a href="https://auditorycognition.com/docs/Postdoc-Obleserlab-March2019.pdf" id="LPlnk874880" previewremoved="true">https://auditorycognition.com/docs/Postdoc-Obleserlab-March2019.pdf</a> <<a href="https://auditorycognition.com/docs/Postdoc-Obleserlab-March2019.pdf" id="LPlnk24908" previewremoved="true">https://auditorycognition.com/docs/Postdoc-Obleserlab-March2019.pdf</a>>
<br>
<br>
Job ad in German:<br>
<a href="https://www.academics.de/jobs/wissenschaftlicher-mitarbeiter-post-doc-m-w-d-am-institut-fuer-psychologie-universitaet-zu-luebeck-luebeck-1004361?user_token=SFMyNTY.g3QAAAACZAAEZGF0YWIAAG6AZAAGc2lnbmVkbgYAt8Q1EGkB.yJa3d_6Otl3R_0t0GvEOLq-etYWIp13xoZ4MDhwN5m0&utm_campaign=jobnewsletter&utm_medium=nl&utm_source=2019-02-21&wt_zmc=nl.int.aca.jobnewsletter.2019-02-21.acade.textlink.stellenanzeige_supertreffer.job" id="LPlnk863368" previewremoved="true">https://www.academics.de/jobs/wissenschaftlicher-mitarbeiter-post-doc-m-w-d-am-institut-fuer-psychologie-universitaet-zu-luebeck-luebeck-1004361?user_token=SFMyNTY.g3QAAAACZAAEZGF0YWIAAG6AZAAGc2lnbmVkbgYAt8Q1EGkB.yJa3d_6Otl3R_0t0GvEOLq-etYWIp13xoZ4MDhwN5m0&utm_campaign=jobnewsletter&utm_medium=nl&utm_source=2019-02-21&wt_zmc=nl.int.aca.jobnewsletter.2019-02-21.acade.textlink.stellenanzeige_supertreffer.job</a>
<<a href="https://www.academics.de/jobs/wissenschaftlicher-mitarbeiter-post-doc-m-w-d-am-institut-fuer-psychologie-universitaet-zu-luebeck-luebeck-1004361?user_token=SFMyNTY.g3QAAAACZAAEZGF0YWIAAG6AZAAGc2lnbmVkbgYAt8Q1EGkB.yJa3d_6Otl3R_0t0GvEOLq-etYWIp13xoZ4MDhwN5m0&utm_campaign=jobnewsletter&utm_medium=nl&utm_source=2019-02-21&wt_zmc=nl.int.aca.jobnewsletter.2019-02-21.acade.textlink.stellenanzeige_supertreffer.job" id="LPlnk374353" previewremoved="true">https://www.academics.de/jobs/wissenschaftlicher-mitarbeiter-post-doc-m-w-d-am-institut-fuer-psychologie-universitaet-zu-luebeck-luebeck-1004361?user_token=SFMyNTY.g3QAAAACZAAEZGF0YWIAAG6AZAAGc2lnbmVkbgYAt8Q1EGkB.yJa3d_6Otl3R_0t0GvEOLq-etYWIp13xoZ4MDhwN5m0&utm_campaign=jobnewsletter&utm_medium=nl&utm_source=2019-02-21&wt_zmc=nl.int.aca.jobnewsletter.2019-02-21.acade.textlink.stellenanzeige_supertreffer.job</a>>
<br>
<br>
<br>
Jonas Obleser<br>
Professor<br>
Chair in Physiological Psychology and Research Methods<br>
<br>
University of Lübeck<br>
Department of Psychology<br>
MFC 8, Maria-Goeppert-Straße 9a<br>
23562 Lübeck, Germany<br>
<br>
Phone +49 (0)451 3101 3620<br>
Mobile +49 (0)171 6993337<br>
jonas.obleser@uni-luebeck.de<br>
<a href="http://jonasobleser.com" id="LPlnk666504" previewremoved="true">http://jonasobleser.com</a><br>
<br>
---Schedule a meeting with me? <a href="https://calendly.com/jonasobleser" id="LPlnk850001" previewremoved="true">
https://calendly.com/jonasobleser</a> ---<br>
<br>
<br>
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------------------------------<br>
<br>
Message: 2<br>
Date: Thu, 21 Feb 2019 15:10:18 +0000<br>
From: "Schoffelen, J.M. (Jan Mathijs)" <jan.schoffelen@donders.ru.nl><br>
To: FieldTrip discussion list <fieldtrip@science.ru.nl><br>
Subject: Re: [FieldTrip] Error in source localisation statistics<br>
Message-ID: <21612B35-BED5-4A31-8206-CAC578C72109@donders.ru.nl><br>
Content-Type: text/plain; charset="utf-8"<br>
<br>
Hi Xavier,<br>
<br>
I see. Unfortunately you happened to end up in a corner of the code that is a bit shaky, and possibly not well tested (although once upon a time it may have worked). This may be due to the fact that you are trying to ‘fool’ fieldtrip into treating a multiple
subject design as if it’s a single subject design with multiple trials (where each of the trials represents a single condition estimate for a subject), correct? (as a side note: you would want to use ‘depsamplesT’ rather than ‘indepsamplesT’ as your test statistic).<br>
<br>
I think that you should not do this. First, as you have noticed this leads to downstream problems (specifically handcrafting combined data could easily lead to a user-error causing the data to deviate according to what FieldTrip can handle, but also using the
cfg.rawtrial option of ft_sourceanalaysis historically and notoriously is a dysfunctional (or at least unpredictable in its behavior) option. (nominated to be removed once we find the time). Next to this, even though it seems your geometrical data (i.e. electrode
positions, headmodel, sourcemodel) are shared across subjects, the covariance structure of the data will for sure be subject-specific, and I don’t think that it is a good idea to combine data across subjects before sourceanalysis.<br>
<br>
This is what I would do:<br>
<br>
for each subject do:<br>
<br>
ft_timelockanalysis with the subject-specific data combined across conditions<br>
ft_timelockanalysis with the subject-specific data for each of the conditions separately<br>
<br>
ft_sourceanalysis with the subject-specific data combined across conditions AND cfg.lcmv.keepfilter = ‘yes’; (and don’t specify cfg.keeptrials or cfg.rawtrial)<br>
<br>
input the source.avg.filter from the previous step into the cfg<br>
<br>
for each condition (in each subject) do:<br>
ft_sourceanalysis<br>
<br>
<br>
after this you should have a set of Nsubject times number of conditions source structures<br>
<br>
then you should be able to use ft_sourcestatistics with cfg.statisti = ‘depsamplesT’:<br>
<br>
ft_sourcestatistics(cfg, source{:}); % if in the previous for-loop you have stored the individual source-objects into a cell-array this syntax works (and is much cleaner than either ft_sourcestatistics(cfg, source1a, source2a ,…etc), and cleaner than going
through ft_sourcegrandaverage).<br>
<br>
ft_sourcedescriptives should not be needed in this recipe.<br>
<br>
Good luck,<br>
Jan-Mathijs<br>
<br>
<br>
J.M.Schoffelen, MD PhD<br>
Senior Researcher, VIDI-fellow - PI, language in interaction<br>
Telephone: +31-24-3614793<br>
Physical location: room 00.028<br>
Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands<br>
<br>
<br>
<br>
On 20 Feb 2019, at 21:32, Xavier Vrijdag <x.vrijdag@auckland.ac.nz<mailto:x.vrijdag@auckland.ac.nz>> wrote:<br>
<br>
Hi Jan-Mathijs,<br>
<br>
Thank you for your help. I went in to have a look at what is going on inside those loops and found that the error is occurring in iteration 6, when the field source.trial(1).label is concatenated. It uses the indexes for the big data cells (ori, mom & filter)
which clearly doesn’t work on the small cell with the labels. This seems to me that this is a bug.<br>
<br>
I added a piece of code in front of the loop that was giving the error (before line 177 and make the if and elseif.<br>
if isequal(fn{i}, 'label')<br>
for j=1:nrpt<br>
source_new.label(:,j) = source.trial(j).label;<br>
end<br>
elseif iscell(dat)<br>
<br>
This worked to circumvent the problem. However, I do get the warning that the dimord of “ori” and “df” could not be determined. When using this cleaned source struct in source statistics I get further errors.<br>
<br>
It looks like an issue with how the source struct is built by the source analysis function with trials, and lateron needs to be restructured. SO I would like to know what is the needed structure for ft_sourcestatistics, so we can adjust the code correctly.<br>
<br>
Regards,<br>
<br>
Xavier<br>
<br>
<br>
From: fieldtrip <fieldtrip-bounces@science.ru.nl<mailto:fieldtrip-bounces@science.ru.nl>> on behalf of "Schoffelen, J.M. (Jan Mathijs)" <jan.schoffelen@donders.ru.nl<mailto:jan.schoffelen@donders.ru.nl>><br>
Reply-To: FieldTrip discussion list <fieldtrip@science.ru.nl<mailto:fieldtrip@science.ru.nl>><br>
Date: Wednesday, 20 February 2019 at 2:59 AM<br>
To: FieldTrip discussion list <fieldtrip@science.ru.nl<mailto:fieldtrip@science.ru.nl>><br>
Subject: Re: [FieldTrip] Error in source localisation statistics<br>
<br>
Hi Xavier,<br>
<br>
My recommendation here would be to use the matlab debugger and inspect the cause of the error. The ‘Index exceeds array bounds’ is quite a clear error message, and suggests that there is a mismatch between the number of elements in dat/val, and the numbers
represented in indx(k).<br>
<br>
Good luck,<br>
<br>
Jan-Mathijs<br>
<br>
<br>
On 18 Feb 2019, at 07:23, Xavier Vrijdag <x.vrijdag@auckland.ac.nz<mailto:x.vrijdag@auckland.ac.nz>> wrote:<br>
<br>
Hello,<br>
<br>
I have a dataset from an experiment where 12 participants were exposed to 3 levels of nitrous oxide, while I measured their EEG. I also have a baseline recording. I took for each exposure (and baseline) a 1 minute sample for further analysis. I want to do source
localization to better understand which parts of the brain are involved. I don’t have MRI scans of my participants, so I used the standard MRI and BEM. I would like to thanks the persons who made the various manuals and analysis examples on the website, as
they helped me tremendously to do this analysis.<br>
<br>
After cleaning and preprocessing, I combined the datasets into one for further analysis. I also chose to make 5 sec “trials” for further analysis. For this source analysis I loaded the data of 1 exposure and the baseline data, to compare them.<br>
<br>
%Calculate the channel covariance matric<br>
cfg = [];<br>
cfg.covariance = 'yes';<br>
cfg.covariancewindow = 'all';<br>
cfg.keeptrials = 'yes';<br>
timelock = ft_timelockanalysis(cfg, data_filt);<br>
<br>
%Global filter<br>
cfg = [];<br>
cfg.headmodel = vol;<br>
cfg.elec = elec_aligned;<br>
cfg.grid = grid;<br>
cfg.method = 'lcmv';<br>
cfg.lcmv.projectnoise='yes'; %needed for neural activity index<br>
cfg.lcmv.fixedori = 'yes'; %Project onto largest variance orientation<br>
cfg.lcmv.keepfilter = 'yes'; %Keep the beamformer weights<br>
cfg.lcmv.lambda = '5%'; %Regularise a little<br>
cfg.rawtrial = 'yes'; % project each single trial through the filter.<br>
cfg.keeptrials = 'yes';<br>
source = ft_sourceanalysis(cfg, timelock);<br>
<br>
cfg = [];<br>
cfg.dim = source.dim;<br>
cfg.method = 'montecarlo';<br>
cfg.statistic = 'ft_statfun_indepsamplesT';<br>
cfg.parameter = 'pow';<br>
cfg.correctm = 'cluster';<br>
cfg.numrandomization = 1000;<br>
cfg.alpha = 0.05; % note that this only implies single-sided testing<br>
cfg.tail = 0;<br>
cfg.design(1,:) = [1:nTrials 1:nTrials];<br>
cfg.design(2,:) = [ones(1,nTrials) ones(1,nTrials).*2];<br>
cfg.uvar = 1; % row of design matrix that contains unit variable (in this case: trials)<br>
cfg.ivar = 2; % row of design matrix that contains independent variable (the conditions)<br>
stat = ft_sourcestatistics(cfg, source);<br>
<br>
After the source analysis the source statistics script calls the checkdata script and I get the following error:<br>
<br>
Index exceeds array bounds.<br>
<br>
Error in ft_datatype_source (line 183)<br>
val{indx(k)}(1,:,:,:) = dat{indx(k)};<br>
<br>
Error in ft_checkdata (line 278)<br>
data = ft_datatype_source(data);<br>
<br>
Error in ft_sourcestatistics (line 94)<br>
varargin{i} = ft_checkdata(varargin{i}, 'datatype', 'source', 'feedback', 'no');<br>
<br>
Error in sourcelocalisation_N2O (line 114)<br>
stat = ft_sourcestatistics(cfg, source);<br>
<br>
The source struct has the following content:<br>
time: [1×15360 double]<br>
dim: [24 31 25]<br>
inside: [18600×1 logical]<br>
pos: [18600×3 double]<br>
method: 'rawtrial'<br>
trial: [1×24 struct]<br>
df: 24<br>
cfg: [1×1 struct]<br>
<br>
With source.trial:<br>
1×24 struct array with fields:<br>
ori<br>
pow<br>
mom<br>
noise<br>
filter<br>
label<br>
filterdimord<br>
<br>
I would like your help to understand the error and how to fix it.<br>
<br>
Regards,<br>
<br>
Xavier Vrijdag<br>
<br>
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------------------------------<br>
<br>
Message: 3<br>
Date: Thu, 21 Feb 2019 16:16:47 +0000<br>
From: Pierre Bastien Megevand <Pierre.Megevand@unige.ch><br>
To: "fieldtrip@science.ru.nl" <fieldtrip@science.ru.nl><br>
Subject: [FieldTrip] issue with FieldTrip-SimBio pipeline for EEG FEM<br>
forward solution<br>
Message-ID: <617c8035ce184327b4ed18a9caa3a033@unige.ch><br>
Content-Type: text/plain; charset="iso-8859-1"<br>
<br>
Dear all,<br>
<br>
<br>
I think I have found an inconsistency in the way Fieldtrip handles the building of a FEM forward solution. I am following the procedure described in Vorwerk, Oostenveld et al., The FieldTrip-SimBio pipeline for EEG forward solutions. Biomed Eng Online. 2018
(<a href="https://biomedical-engineering-online.biomedcentral.com/articles/10.1186/s12938-018-0463-y" id="LPlnk333930" previewremoved="true">https://biomedical-engineering-online.biomedcentral.com/articles/10.1186/s12938-018-0463-y</a>). This procedure suggests
to build the forward solution by calling the following Fieldtrip functions:<br>
<br>
ft_read_mri<br>
<br>
ft_volumerealign<br>
<br>
ft_volumereslice<br>
<br>
ft_volumesegment<br>
<br>
ft_prepare_mesh<br>
<br>
ft_prepare_headmodel<br>
<br>
ft_read_header (to get electrode data)<br>
<br>
ft_electroderealign<br>
<br>
ft_prepare_vol_sens<br>
<br>
ft_prepare_sourcemodel<br>
<br>
ft_prepare_leadfield<br>
<br>
<br>
My issue is the following: the FieldTrip-SimBio pipeline explicitly calls ft_prepare_vol_sens, which takes very long to execute (over 6 hours in the case of the published paper, which used about 80 electrodes). However, ft_prepare_leadfield later calls (line
165) prepare_headmodel, which itself calls (line 113) ft_prepare_vol_sens again, with the same parameters as far as I can tell (and again taking ages to run).<br>
<br>
<br>
Is this redundancy intended? If not, can it be circumvented?<br>
<br>
<br>
Thank you in advance,<br>
<br>
<br>
Pierre<br>
<br>
<br>
Pierre Mégevand, MD, PhD<br>
Senior research associate, Dept. of basic neurosciences<br>
Faculty of medicine, University of Geneva, Switzerland<br>
T. +41 76 693 65 22 | pierre.megevand@unige.ch<br>
<br>
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------------------------------<br>
<br>
Message: 4<br>
Date: Fri, 22 Feb 2019 15:44:42 +0530<br>
From: Neeraj kumar <neeraj750kumar@gmail.com><br>
To: fieldtrip@science.ru.nl<br>
Subject: [FieldTrip] Parcellate the reconstructed source time series<br>
Message-ID:<br>
<CA+pWvbqu5QoCWvoiEy1xjB8bQa9hFWBMJ3657G6C59JSO7y6VA@mail.gmail.com><br>
Content-Type: text/plain; charset="utf-8"<br>
<br>
Hello all,<br>
<br>
I want to parcellate the reconstructed source time series (~ 1000ms).<br>
I have moments in source.avg.mom for around 6000 grids.<br>
Additionally, do I need to perform some normalization on time series before<br>
or after parcellation to perform network analysis?<br>
<br>
Thanks in advance.<br>
<br>
Neeraj Kumar,<br>
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Message: 5<br>
Date: Fri, 22 Feb 2019 11:40:28 +0100<br>
From: Johannes <j.vorw01@gmail.com><br>
To: FieldTrip discussion list <fieldtrip@science.ru.nl><br>
Subject: Re: [FieldTrip] issue with FieldTrip-SimBio pipeline for EEG<br>
FEM forward solution<br>
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<CAMtnjmVNo7PDn062vPAzg14LGmgOXGsBdW5+QxN5cXSt4cOFFw@mail.gmail.com><br>
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Dear Pierre,<br>
<br>
if you are running a recent version of FieldTrip (newer than Dec 15, 2018),<br>
there should be a check included in ft_prepare_vol_sens to avoid this<br>
behavior, i.e., if a transfer matrix is detected in the vol-struct provided<br>
to ft_prepare_vol_sens, it is checked if whether this fits to the indicated<br>
sensor configuration and if this is the case no new transfer matrix is<br>
computed. This should also work if a subset of sensors is selected. Thus,<br>
it would be great, if you could check whether this behavior remains when<br>
using a recent checkout of FieldTrip.<br>
<br>
Regarding the time requirement for computing the transfer matrix - the<br>
calculation in sb_transfer can be easily parallelized by replacing l 35 in<br>
sb_transfer with a parfor loop, e.g., parfor(i=2:length(vol.elecnodes),8),<br>
if you want to compute on 8 cores.<br>
<br>
I hope this answer is helpful to you!<br>
<br>
Best,<br>
Johannes<br>
<br>
Am Do., 21. Feb. 2019 um 17:17 Uhr schrieb Pierre Bastien Megevand <<br>
Pierre.Megevand@unige.ch>:<br>
<br>
> Dear all,<br>
><br>
><br>
> I think I have found an inconsistency in the way Fieldtrip handles the<br>
> building of a FEM forward solution. I am following the procedure<br>
> described in Vorwerk, Oostenveld et al., The FieldTrip-SimBio pipeline<br>
> for EEG forward solutions. Biomed Eng Online. 2018 (<br>
> <a href="https://biomedical-engineering-online.biomedcentral.com/articles/10.1186/s12938-018-0463-y" id="LPlnk360864" previewremoved="true">
https://biomedical-engineering-online.biomedcentral.com/articles/10.1186/s12938-018-0463-y</a>).<br>
> This procedure suggests to build the forward solution by calling the<br>
> following Fieldtrip functions:<br>
><br>
> ft_read_mri<br>
><br>
> ft_volumerealign<br>
><br>
> ft_volumereslice<br>
><br>
> ft_volumesegment<br>
><br>
> ft_prepare_mesh<br>
><br>
> ft_prepare_headmodel<br>
><br>
> ft_read_header (to get electrode data)<br>
><br>
> ft_electroderealign<br>
><br>
> ft_prepare_vol_sens<br>
><br>
> ft_prepare_sourcemodel<br>
><br>
> ft_prepare_leadfield<br>
><br>
><br>
> My issue is the following: the FieldTrip-SimBio pipeline explicitly calls<br>
> ft_prepare_vol_sens, which takes very long to execute (over 6 hours in the<br>
> case of the published paper, which used about 80 electrodes). However,<br>
> ft_prepare_leadfield later calls (line 165) prepare_headmodel, which<br>
> itself calls (line 113) ft_prepare_vol_sens again, with the same<br>
> parameters as far as I can tell (and again taking ages to run).<br>
><br>
><br>
> Is this redundancy intended? If not, can it be circumvented?<br>
><br>
><br>
> Thank you in advance,<br>
><br>
><br>
> Pierre<br>
><br>
><br>
> Pierre Mégevand, MD, PhD<br>
> Senior research associate, Dept. of basic neurosciences<br>
> Faculty of medicine, University of Geneva, Switzerland<br>
> T. +41 76 693 65 22 | pierre.megevand@unige.ch<br>
><br>
> _______________________________________________<br>
> fieldtrip mailing list<br>
> <a href="https://mailman.science.ru.nl/mailman/listinfo/fieldtrip" id="LPlnk327283" previewremoved="true">
https://mailman.science.ru.nl/mailman/listinfo/fieldtrip</a><br>
> <a href="https://doi.org/10.1371/journal.pcbi.1002202" id="LPlnk71712" previewremoved="true">
https://doi.org/10.1371/journal.pcbi.1002202</a><br>
><br>
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End of fieldtrip Digest, Vol 99, Issue 22<br>
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