In principle, standardisation and agreement has to be a good thing - I guess
time will tell when the field is 'ripe' for it... For now, I'll add my
couple of thoughts -
Do we need to give more detail than, for example, papers based on
behavioural or ERP data? It's not usually considered necessary to include
residual plots in these cases.
Do we want to make imaging papers intelligible to non-expert-imagers and to
non-imagers? I think this is important, and so would want to avoid too much
technical detail in papers - such as design matrices, which in any case are
software-specific - just enough to enable replication and to make it clear
that the important issues have been dealt with appropriately.
I don't know about supplementary web-based information - it's nice, but I
imagine that not everyone has easy access to it - and one can always contact
the authors. If it's really important, shouldn't it be in the paper?
If anyone's interested, something like this was done for ERPs by Picton et
al (2000, Psychophysiology. 2000 Mar;37(2):127-52)
Alexa
-----Original Message-----
From: SPM (Statistical Parametric Mapping) [mailto:[log in to unmask]]On
Behalf Of Torben Ellegaard Lund
Sent: 16 February 2005 01:17
To: [log in to unmask]
Subject: Re: [SPM] Any Papers on Presenting fMRI Results?
Interesting discussion this one
I guess Tom will be too polite to mention this. But I think it would be
very convincing if statistic maps were accompanied by results of an SPMd
analysis to demonstrate normal and white residuals (or lack thereof!).
Unfortunately for first level analysis it is really only an option for the
SPM folks. But I think SPMd would serve as a great quality check.
best
torben
Torben E. Lund
Danish Research Centre for MR
Copenhagen University Hospital
Kettegaard Allé 30
2650 Hvidovre
Denmark
email: [log in to unmask]
webpage: http://www.drcmr.dk
On 16 Feb 2005, at 01:35, Matthew Brett wrote:
Hi,
I would put in a plea for continuous activation maps to be made
available - and displayed in the paper or supplementary material. The
thresholded maps we are all used to can be seriously misleading:
Jernigan TL, Gamst AC, Fennema-Notestine C, Ostergaard AL. More
"mapping" in brain mapping: statistical comparison of effects. Hum
Brain Mapp. 2003 Jun;19(2):90-5
In my experience, continuous maps also give a much clearer picture of
the quality of the data.
Also, it seems to me that any ROIs used should be made available online.
Best,
Matthew
On Mon, 14 Feb 2005 17:36:23 -0500, Thomas E Nichols <[log in to unmask]>
wrote:
Max,
Is anyone aware of papers about presenting results for fMRI studies?
Specifically I'm looking for any attempts that have been made to
standardize what is reported and how.
I don't know of any such efforts, but I think it's badly needed. I
was once asked by an editor for such standards and started to make a
list of statistical and non-statistical issues. I'd love to hear
comments on such guidlines.
-Tom
-- Thomas Nichols -------------------- Department of Biostatistics
http://www.sph.umich.edu/~nichols University of Michigan
[log in to unmask] 1420 Washington Heights
-------------------------------------- Ann Arbor, MI 48109-2029
All papers should give sufficient detail so that if the reader were
armed with the authors' data they could reproduce the results. Some
important items:
1. What voxel-wise statistic image threshold was used? Corrected or
uncorrected? FWE or FDR?
2. Was cluster size inference used? If so, what is the
cluster-defining statistic image threshold? What is the cluster
size threshold (in voxels) and significance (corrected or
uncorrected).
3. How many voxels corrected for? Whole brain voxel count, or
sub-volume count for 'Small Volume Correction'. If small volume
correction, define how the sub-region was defined.
4. If random field theory is used, what is the smoothness (FWHM,
x,y,z)? What is the RESEL count? (This allows one to independly
recompute the corrected threshold)
Not directly related to the statistics, but crucial for any complete
reporting are:
a. Basic image properties: image dimensions and voxel size.
Properities of data as acquired *and* after intersubject
registration (aka Spatial Normalization). For PET/SPECT, image
reconstruction smoothness parameter (e.g. 'ramp filtered', 'Hanning
filter, *** mm cutoff').
b. Was slice timeing correction used?
c. Smoothing applied. At 1st level and 2nd level if done twice.
d. Basic intrasubject registration info. What software, what sort of
interpolation.
e. Basic itersubject registration parmaeters. Affine/Linear? If so,
how many parameters (9 or 12, typically). If Nonlinear, 'how'
nonlinear? (E.g. with AIR, you specify a polynomial order; with
SPM, you specify a basis size, like 3x2x3). Regularization
setting. What interpolation?
This may sound like a lot, but they are all very basic parameters and
can be concisely reported. They also can be reported in detail in one
publication from a lab and then cite that publication for details that
haven't changed.
