Dear Users
Please do not smoke just outside the entrance to YNiC.
Thank you
Gary
--
Gary Green
York Neuroimaging Centre
The Biocentre
York Science Park
Innovation Way
Heslington
York
YO10 5DG
http://www.ynic.york.ac.ukhttps://www.ynic.york.ac.uk/about-us/people/ggrg
tel. +44 (0) 1904 435349
PA +44 (0) 1904 435329 or reception(a)ynic.york.ac.uk
fax +44 (0) 1904 435356
mobile +44 (0) 788 191 3004
This email to the FSL mailserver list may be of interest to local YNiC
FSL users
Gary
----------------------------------
Dear David,
The short answer is, no, there is no way to justify Z=1.7 as a
cluster-forming threshold in FEAT.
The problem is that the cluster size P-values are based on Random Field
Theory (RFT), and RFT makes various approximation that are only valid
for high thresholds. While one early reference (Petersson et al, 1999)
specified cluster-forming threshold P=0.01 / Z=2.33 as a practical lower
limit for accurate results, later work (Hayasaka & Nichols, 2003; Silver
et al, 2010; K. Worsley personal communication) found even that level
was unstable, and instead recommended P=0.001 / Z=3.09 as a lower limit
on a cluster-forming threshold to ensure accurate inferences.
On the other hand, if you are using randomise, you can safely use any
cluster-forming threshold (though if you go too low, the clusters might
be too extended and spindly to be interpretable). If using randomise,
though, check out TFCE as away to avoid specifying any particular
cluster-forming threshold.
To answer your second question, the cluster-forming threshold used at
lower-levels is only used to make inferences *at* the lower level, and
is ignored at higher levels. Only the cluster-forming
threshold specified in the top-level FEAT analysis matters for the
top-level results.
-Tom
Petersson, K. M., Nichols, T. E., Poline, J.-B., & Holmes, A. P. (1999).
Statistical limitations in functional neuroimaging II. Signal detection
and statistical inference. /Phil. Trans. R. Soc. Lond. B/, /354/, 1261-1281.
Hayasaka, S., & Nichols, T. (2003). Validating cluster size inference:
random field and permutation methods. /NeuroImage/, /20/, 2343-2356.
Silver, M., Montana, G., & Nichols, T. E. (2010). False positives in
neuroimaging genetics using voxel-based morphometry data. /NeuroImage/.
Elsevier Inc. doi: 10.1016/j.neuroimage.2010.08.049.
On Mon, May 9, 2011 at 1:06 PM, David Soto <d.soto.b(a)gmail.com
<mailto:d.soto.b@gmail.com>> wrote:
Hello,
I am finding that when I use a Z<1.7 to define the cluster size at
he highest level analyses, I am getting some interesting activations
in regions that I don't see when I use Z<2.3. In both cases I use
cluster thresholding and p<0.05 whole brain corrected.....
I know the Z value used to define cluster size prior to correction
for multiple comparisons is arbitrary, but is it there any paper
that I can use to justify
in my study why a Z<1.7 was used instead of Z<2.3?
Would it be right to say that poststat results with a Z<1.7 are more
lenient than with a Z<2.3? I feel it this is not necessarily right
but can you please advise?
A second question I have is about poststats as implemented in FEAT....
Say that I have done a lower level analyses - for session, a 2nd
level -across session within subjects- and 3rd level -across subjects-
do I need to set up the Z<1.7 at the first and second level and
third level analyses - or does FEAT bring the unthresholded data
from lower level analyses to the higher levels and then use the Z
score specified at the highest level analyses? in other words, will
I get the same results if I specify
Z<1.7 across all levels or whether I do Z<2.3 for first and second
level and Z<1.7 at the higher level?
Many thanks,
David
--
____________________________________________
Thomas Nichols, PhD
Principal Research Fellow, Head of Neuroimaging Statistics
Department of Statistics & Warwick Manufacturing Group
University of Warwick
Coventry CV4 7AL
United Kingdom
Email: t.e.nichols(a)warwick.ac.uk <mailto:t.e.nichols@warwick.ac.uk>
Phone, Stats: +44 24761 51086, WMG: +44 24761 50752
Fax: +44 24 7652 4532
Dear All,
Today's external seminar will be delivered by Prof. Michelle Ryan from Exeter. Her talk will follow on nicely from last wednesday's Athena Swan talk, as she will be presenting her research on the "Glass Cliff", a precarious and obscured obstacle faced by women in leadership. As usual there will be drinks in the foyer afterwards.
4:15 in B020. Please come.
Julian
Julian Oldmeadow, PhD
Department of Psychology
University of York
York, YO10 5DD
julian.oldmeadow(a)york.ac.uk
FYI
----------------------------------
Applications are invited for a position at a Hospital Research Center in
Barcelona, Spain. The position is full-time for 15 months (with a
probable extension to 18 months). It entails working mainly on
neuroimaging data.
The postholder will help in analyzing functional, structural, and
diffusion tensor data. Essential skills include knowledge of fMRI and/or
structural MRI techniques, a proficient management of SPM and
programming skills in MATLAB.
The position is available to start 1st of September 2011. Annual salary
will be around €26,000 (plus social security, health and unemployment
benefits).
Please send enquiries or applications (which must include a covering
letter detailing professional objectives and interests, CV, all in one
pdf file) to cenicogni(a)gmail.com, with the subject line "Neuroimaging
position".
--
Gary
FYI
-----------------------
Positions to be based at The Centre for Functional Magnetic Resonance
Imaging of the Brain (FMRIB), Oxford University.
From June 2011 part of my lab (primarily at UC Berkeley) will be based
at The Centre for Functional Magnetic Resonance Imaging of the Brain
(FMRIB), Oxford University. I am looking for two postdoctoral
researchers to join the group there. The positions are to play a key
role in a programme of research aimed at identifying and retraining the
brain mechanisms underlying disrupted attentional and associative
processing in anxiety. The research is supported by funding from the
European Research Council and conducted in collaboration with Drs K
Weich, I Tracey and E Holmes.
Candidates are sought with a doctorate in a relevant discipline and
research experience in neuroimaging and programming (ideally in matlab
or python). Employment is for an initial period of 1 year with the
possibility of extension for an addition 2-4 years. Salary is from
£33084. Start date is flexible between July 1 and Dec 1 2011. Further
details can be obtained from sbishop(a)berkeley.edu
<mailto:sbishop@berkeley.edu>.
Prof. Sonia Bishop Assistant Professor Dept Psychology & Helen Wills
Neuroscience Institute, UC Berkeley; visiting Senior Researcher, FMRIB,
Oxford University
FYI
--------------------------------------------------------------------------------------------------------------
The Central Institute of Mental Health in Mannheim, Germany, is an
internationally renowned research institute in the field of psychiatry
and neuroscience, home of the Department of Psychiatry and Psychotherapy
of the Medical Faculty Mannheim of the University of Heidelberg, and a
psychiatric hospital with 255 inpatient and 52 day-clinic beds.
To strengthen our recently established independent neuroscience research
group funded by the Federal Ministry of Education and Research (BMBF),
the Clinic for Psychiatry and Psychotherapy (Medical Director: Prof. Dr.
med. Andreas Meyer-Lindenberg) offers
* *
*1 PostDoc and 1 PhD-Student Position*
* *
in the area of functional and structural magnetic resonance imaging
(MRI). Positions are initially limited to 2 years, a prolongation is
intended.
The Central Institute of Mental Health is equipped, among others, with
two Siemens 3 Tesla research MR scanners. Our research group consists of
an interdisciplinary team of psychologists, psychiatrists, neurologists,
biologists and technical assistants
(http://www.zi-mannheim.de/ag_imaging.html).
The main goal of the international research project is to examine
fronto-striatal plasticity processes and their molecular genetic basis
in healthy individuals and psychiatric patients using multimodal
magnetic resonance imaging techniques (fMRI, morphometry, DTI,
spectroscopy).
Ideally, potential applicants will have previous experience with the
acquisition, processing and analysis of MRI data, as well as a strong
interest in the application of systems neuroscience methods in the
context of neuropsychiatric research questions.
We offer an interesting job in a pleasant working environment at a
leading German research institute. Salary is according to the German
TV-L pay scale, including the social benefits of the German public
service sector.
For further information please contact Dr. Dr. Heike Tost, Tel. +49 621
1703-6508, E-Mail heike.tost(a)zi-mannheim.de
<mailto:heike.tost@zi-mannheim.de>.
____________________________________
Maria Zangl, PhD-Student
Central Institute of Mental Health
Research Group Imaging in Psychiatry
J5, 68159 Mannheim, Germany
Phone: +49-621-1703-6514
Email:maria.zangl@zi-mannheim.de <mailto:maria.zangl@zi-mannheim.de>
Dear all,
does anyone have a recent edition of Niedermeyer's Electroencephalography:
Basic Principles, Clinical Applications and Related Fields? If so, would I
be able to borrow it?
Thanks,
Michael
FYI
----------------------
Postdoctoral Fellowship: Multimodal Neuroimaging -MGH/Harvard Medical School
Job Description
A postdoctoral position is available with the TRANSCEND Research Program
(www.transcendresearch.org <http://www.transcendresearch.org/>) at the
Martinos Center for Biomedical Imaging in Charlestown, MA
(www.martinos.org <http://www.martinos.org/>) which is affiliated with
the Massachusetts General Hospital, Harvard Medical School and MIT.
We are seeking a candidate with a strong basis in magnetic resonance
imaging. Emphasis will be on MRI (DTI, spectroscopy, morphometry, ASL as
well as resting state fMRI), and on co-registering MEG with MRI. This
position will involve analysis of existing multimodal imaging data and
collection of new data. The emphasis of the postdoctoral fellowship
will be analysis of existing datasets with secondary activity in
piloting data for new studies. It will involve working closely with a
multidisciplinary team and with children, and will also involve some
research oriented analysis of data collected for clinical purposes.
After initial phase-in, ample opportunity will also be provided to the
candidate to self-explore and lead research.
Datasets to be analyzed include:
MRI (including DTI and 1H-spectroscopy) and MEG data on 6-12 and teenage
matched autism spectrum and control subjects with phenotyping data
MRI data ( (morphometry, DTI, spectroscopy) plus laboratory and
phenotyping data) on 70 children with autism plus epilepsy and/or
mitochondrial dysfunction, along with one or more overnight EEGs on each
patient
data from children ages 2-10 with and without autism.
Overall objectives:
To perform multimodal analyses of research and clinical research data,
to develop new approaches for performing these analyses, and to design
pipelines for data analysis.
To write papers and grants which will be high priorities all along the
way and will be actively supported by senior faculty.
To take advantage of the world class faculty and facilities of the
Martinos Center for Biomedical Imaging to perform the above activities
to their maximal potential.
The program’s emphasis is on pathophysiologically grounded brain
research and application of advanced imaging acquisition and analysis
techniques to neurological and sensory aspects of autism spectrum disorders.
Requirements:
Candidates must have PhD in neuroscience, physics, biomedical
engineering, electrical engineering, computer science or other related
fields. Prior experience in MRI analysis is required. Experience with
EEG will be an added advantage. Salary will be consistent with
Massachusetts General Hospital, Harvard Medical School policies for
Postdoctoral trainees and will range between $45,000 to $55,000
depending upon qualifications and experience. Compensation also includes
full staff benefits, including health insurance, and vacation time.
Contact:
Interested applicants may send a CV and statement of interest addressing
background and specific pertinence of the candidate’s interest to Dr.
Martha R. Herbert at mherbert1(a)partners.org
<mailto:mherbert1@partners.org> and cc transcend(a)partners.org
<mailto:transcend@partners.org>.
Applications will be considered until the position is filled.
--
Gary Green
York Neuroimaging Centre
The Biocentre
York Science Park
Innovation Way
Heslington
York
YO10 5DG
http://www.ynic.york.ac.ukhttps://www.ynic.york.ac.uk/about-us/people/ggrg
tel. +44 (0) 1904 435349
PA +44 (0) 1904 435329 or reception(a)ynic.york.ac.uk
fax +44 (0) 1904 435356
mobile +44 (0) 788 191 3004
More about Beamforming files
In a previous mail-list I was told that the *spheres.txt and
*transform.txt file are obtained after coregistration
of the MEG data to the MRI structural before beamforming. So I imagine
that transform.txt matrix takes the NAI voxel values to
the MNI space with a 5mm or 2mm volume grid, from the individual/subject
brain to the MNI standard. Am I right? Is it MNI standard or the MNI
space of the individual structural MRI?
But anyway, (and this is a supposition) coregistration should be done
first between MEG and the individual MRI structure to perform Beamforming
in world/real or physical coordinates (right?). So there should be a
previous space transform in world coordinates to perform beamforming,
then the NAI values are obtained in world coordinates and finally
transformed to MNI space together with the individual structural MRI.
Am I right about this?
The reason why I am to eager to know this, is because I am doing
Beamforming for my project using python-vtk, and so far I have learned
how to extract the cortical voxels of individual structrual MRI using
BET-FAST from FSL. But in order to run my beamforming I need to
transform the structural voxels (in MNI) to world coordinates and also
do coregistration between the fiducial skin points, which I imagine were
obtained using the stylus pen for 3D modelling during the MEG
acquisition with the surface of the subject skin from the MRI.
I was wondering if the transform.txt file does the coregistration
skin-points-to-skin-surface for the Beamforming, Now I know that it does
not.
Maybe I will have to program my own coregistration algorithm anyway. I
only wanted to know If there were a less painful way to do it.
My fifth question is the following. According to the ynic-wiki, it says
that I am able to define any voxel in MNI coordinates to define virtual
electrodes using the Beamforming functions. The problem is that the wiki
does not say how to define this coordinates. From where can I take them?
> From the structural MRI or from the MRI standard? Can they be only the
cortex or any voxel inside the brain?
And my last question is about the sphere.txt file. It is composed of 248
lines, they should be the MEG coils, but I can not imagine the meaning
of the rest of the four columns. I was thinking they where x,y,z
coordinates, but there is a fourth one that tells me I am wrong.
Many thanks,
Luis R. Peraza
More about Beamforming files
In a previous mail-list I was told that the *spheres.txt and
*transform.txt file are obtained after coregistration
of the MEG data to the MRI structural before beamforming. So I imagine
that transform.txt matrix takes the NAI voxel values to
the MNI space with a 5mm or 2mm volume grid, from the individual/subject
brain to the MNI standard. Am I right? Is it MNI standard or the MNI
space of the individual structural MRI?
But anyway, (and this is a supposition) coregistration should be done
first between MEG and the individual MRI structure to perform Beamforming
in world/real or physical coordinates (right?). So there should be a
previous space transform in world coordinates to perform beamforming,
then the NAI values are obtained in world coordinates and finally
transformed to MNI space together with the individual structural MRI.
Am I right about this?
The reason why I am to eager to know this, is because I am doing
Beamforming for my project using python-vtk, and so far I have learned
how to extract the cortical voxels of individual structrual MRI using
BET-FAST from FSL. But in order to run my beamforming I need to
transform the structural voxels (in MNI) to world coordinates and also
do coregistration between the fiducial skin points, which I imagine were
obtained using the stylus pen for 3D modelling during the MEG
acquisition with the surface of the subject skin from the MRI.
I was wondering if the transform.txt file does the coregistration
skin-points-to-skin-surface for the Beamforming, Now I know that it does
not.
Maybe I will have to program my own coregistration algorithm anyway. I
only wanted to know If there were a less painful way to do it.
My fifth question is the following. According to the ynic-wiki, it says
that I am able to define any voxel in MNI coordinates to define virtual
electrodes using the Beamforming functions. The problem is that the wiki
does not say how to define this coordinates. From where can I take them?
>From the structural MRI or from the MRI standard? Can they be only the
cortex or any voxel inside the brain?
And my last question is about the sphere.txt file. It is composed of 248
lines, they should be the MEG coils, but I can not imagine the meaning
of the rest of the four columns. I was thinking they where x,y,z
coordinates, but there is a fourth one that tells me I am wrong.
Many thanks,
Luis R. Peraza