Hi again Giles,
by mistake I sent you an intermediate version of the m-files.
Please ignore the scripts from the previous e-mail and please find the
proper version attached here.
Best
Giorgos
On 12/02/2015 12:48, Giles Colclough wrote:
Hi,
I have two queries I'm looking for help with.
Dear Beth,
the head shape files are not provided with the data.
The reason for this is that headshape digitization includes points
around the nose, the eyes, the forehead and the entire head. This means
that this information could lead to identification of a subjects identity.
This is also the
to Neuromag space. The transforms
provided could then be used to map the sensors to the source models
created in MNE.
Any hint wold be appreciated.
Best,
Denis
2015-05-15 15:35 GMT+02:00 Georgios Michalareas
giorgos.michalar...@esi-frankfurt.de
mailto:giorgos.michalar...@esi-frankfurt.de
Yes
On 5/25/2016 1:03 PM, Dev vasu wrote:
Dear Sir,
Are these requirements for RAM ? .
Thanks
Vasudev
On 25 May 2016 at 12:58, Georgios Michalareas
<giorgos.michalar...@esi-frankfurt.de
<mailto:giorgos.michalar...@esi-frankfurt.de>> wrote:
Hi,
the recommended me
Hi Denis,
I have contacted the appropriate people in HCP in order to arrange to
put them in ConnectomeDB so that users can download them from there.
I ll post an update on the issue as soon as I get news.
Best
Giorgos
On 4/18/2016 4:31 PM, Denis-Alexander Engemann wrote:
Dear HCPers,
we're
Hi,
the recommended memory for MEG pipelines is:
hcp_baddata 32 gb
hcp_icaclass 32 gb
hcp_tmegpreproc 32gb
hcp_eravg 32 gb
hcp_tfavg 32 gb
hcp_srcavglcmv 16gb
hcp_srcavgdics 16gb
hcp_tmegconnebasic 16 gb
Best
Giorgos
Hi again,
I thought you were asking more about the process rather the actual
sphere durface files.
These files are inside the MEG pipeline code distributed in connectomedb in
https://www.humanconnectome.org/documentation/HCP-pipelines/meg-pipeline.html
If you download from "Pipeline
Hi again,
another question. I am trying to compute pairwise correlation with
-cifti-pairwise-correlate between two pconn files.
One has been derived by parcellating (-cifti-parcellate) with a given
parcellation , i.e. Yeo11, the dconn file in 32K space , i.e.
;hcp-users-boun...@humanconnectome.org on behalf of
> Georgios Michalareas" <hcp-users-boun...@humanconnectome.org on behalf of
> giorgos.michalar...@esi-frankfurt.de> wrote:
>
>> Hi everyone,
>>
>> i am trying for the MEG prac
Hi everyone,
i am trying for the MEG practicals to downsample a 32K dconn fMRI group
functional connectivity cifti:
HCP_S900_820_rfMRI_MSMAll_groupPCA_d4500ROW_zcorr.dconn.nii
into a dconn cifti in the 4K space that we use in the MEG analysis in OT4.
I am trying to use cifti-resample to do
onnectome would
> only be appropriate for tractography data. For fMRI data, you want to
> average the timeseries prior to running functional connectivity at the
> lower resolution.
>
> Peace,
>
> Matt.
>
> On 7/16/16, 9:59 AM, "Georgios Michalareas"
> &l
Dear Olu,
in source level we only have released power time-series. So if you want
to correlate high frequency power to low frequency phase , then you
cannot do this with the released source level time-series. In this case
you would need to take the clean sensor level data , do the projection
Dear Jeff,
if I have understood correctly you want to import a structural MRI scan
for a given HCP subject into Brainstorm for creating the EEG source model.
I guess you follow a procedure similar to
http://neuroimage.usc.edu/brainstorm/Tutorials/HCP-MEG
and Brainstorm cannot find the
un...@humanconnectome.org
<mailto:hcp-users-boun...@humanconnectome.org>
[mailto:hcp-users-boun...@humanconnectome.org] *On Behalf Of *Georgios
Michalareas
*Sent:* Friday, February 10, 2017 3:05 PM
*To:* hcp-users@humanconnectome.org <mailto:hcp-users@humanconnectome.org>
*Subje
Hi,
the tMEG source-level single-trial power time-series are not part of the
released material of HCP.
This is because for the tMEG until now the focus has been on analysis
locked on different reference events within the trial, i.e. stimulus
onset or response of the participant. That is why
Hi again,
I think I misunderstood your question before.
I think by noise you mean a baseline compared to which you compare your
actual activity.
Well the problem with resting state is that there is no baseline and
doing a singular value decomposition and taking the smaller eigenvalue
of the
Hi ,
I think you can still do it with ft_timelockanalysis.
I assume that the resting state data you mention has only one trial.
then if you just do:
cfg=[];
cfg.covariance='yes';
pseudoavg=ft_timelockanalysis(cfg, data);
then it will just compute the average across trials but as there is
The sensor locations originally are in the raw data files of each scan
so you can read them from there with ft_read_sens.
But they are also in the processed data in the field .grad in the data
structure.
For the icamne pipeline and other processing pipelines you only need to
define the raw
Hi Didier,
I had a thorough look into your problem.
It occurs because the conditions you impose on trial selection,
0B_face_target , result in a small number of trials. For the subject
102816 in Run1 there were 8 clean trials in this conditions but the
participant response was wrong in all
? Or maybe there is an appropriate way to call
hcp_eravg_contrasts.m to do this automatically ?
Many thanks anyway !!
JD
Le 11/10/2017 à 15:20, Georgios Michalareas a écrit :
Hi Jean-Didier,
If you need a subset of 0-Back i.e. Faces you ll have to compute the
average yourself . The way to do
ient>
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<#DAB4FAD8-2DD7-40BB-A1B8-4E2AA1F9FDF2>
--
Dr. Georgios Michalareas
Neuroscience Department
Max Plan
t;
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Dr. Georgios Michalareas
Neuroscience Department
Max Planck
I just use the ft_resampledata
Fieldtrip function in order to go from the 165K or 32K to the 4K
dlabel files, or am I missing something?
Regards,
Benjamin
*De :*Georgios Michalareas <g...@ae.mpg.de>
*Envoyé :* lundi 26 mars 2018 19:20
*À :* Benjamin Chiêm <benjamin.ch...@uclouvain.be>;
hcp-use
il_source=link_campaign=sig-email_content=emailclient>
<#DAB4FAD8-2DD7-40BB-A1B8-4E2AA1F9FDF2>
--
----
Dr. Georgios Michalareas
Neuroscience Department
Max Planck Institute for Empirical Aesthetics
email: g...@aesthetics.mpg.de
phone:
Hi,
We are trying to run the latest version of HCP pipelines on a Centos 7 machine.
According to instructions we are using HCP custom version of FreeSurfer
(5.3.0-HCP).
Pipeline crashed when running
mris_make_surfaces
with error
mris_make_surfaces: error while loading shared libraries:
---
Dr. Georgios Michalareas
Neuroscience Department
Max Planck Institute for Empirical Aesthetics
email: g...@aesthetics.mpg.de
phone: +49 69 8300479-325
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