Spm matlab 2017 code#
smoothing versus no smoothing, or physiological noise correction versus not doing it).īecause I am partial to Matlab and SPM, I created a Matlab-SPM12-only version of The Plot (the one shown in the figure), by adapting code from Jonathan Power and adding some of my own scripts. I routinely use my script to assess new data that we acquire at our lab, or open datasets that I work with, and I would recommend all fMRI researchers to use some version of The Plot for routine fMRI quality assessment.Īdditionally it can be a nice way to assess differences in visual data quality outcome based on some change to the preprocessing pipeline (e.g. It has since been incorporated into an AFNI function by Box Cox and it’s also used in the visual summary report of MRIQC.
Spm matlab 2017 full#
Thus, The Plot is a great (and simple and easy) way to visualize multiple quality metrics and time-series data related to a full fMRI dataset, and will allow you to make a number of quality judgements based on a single look. For breath hold tasks, the intensity changes are particularly visible, and distinct from changes related to head motion. (At some point I’ll add code to plot these as well, for now we only have the FD trace).įinally, with the correct preprocessing, parameter selections and plot scaling, you might even be able to see voxel intensity fluctuations mirroring subtle breathing or heart rate changes of the subject, as Jonathan Power explains in his paper.
Spm matlab 2017 series#
More traces like FD could be added to add value to the visual inspection of your fMRI data, including differential variance (DVARS), subject physiology traces like heart and breathing rates, and the time series of the 6 realignment parameters. This can be used as a nice (and automated) indicator of movement outliers, and as you can see on the figure it correlates visually with sudden intensity changes in The Plot. Using The Plot, one can actually visualize the effect that motion has on the intensity of brain voxels over time, as well as identify high-motion outliers.Īnother useful addition to The Plot is the time series of framewise displacement (FD), which is an indication of how much the subject’s head moved (apparent movement) during each frame or time point. Typically, this step entails realigning all images in the series to the first or mean image of the series using a 6 degree of freedom rigid body transformation, but it could also involve removing (scrubbing) certain bad-quality time points from your time series if motion is particularly bad at those points. If you are familiar with fMRI processing, you will know that it is important to correct for subject head motion during the preprocessing step of the analysis. In this way, one can see how the voxel intensity values change over time for grouped (and directional) areas of the brain. Voxels are ordered into segmented bins, typically grey matter, white matter and CSF, all of which could be ordered into deeper cortical-level parcellations. The Plot is essentially a 2D plot of scaled fMRI voxel intensity values over time, with voxels on the vertical axis and time on the horizontal. In this post, I’ll first explain my understanding of the use of The Plot, and then present some SPM12 and Matlab code (with explanations) that you can use to generate it for your own fMRI data. Jonathan Power wrote a nice paper in 2017 explaining its use: “ A simple but useful way to assess fMRI scan qualities“.Īdditionally, you can find more resources related to The Plot (including code) here on this website, which also contains multiple other (very useful) resources for fMRI quality, denoising and analysis. “The Plot” (also referred to as a carpet plot, grey scale plot or intensity plot) is a great way to visualize your fMRI time series data in order to easily highlight quality issues.
It’s great how a shift in attention can change one’s demeanor – another reason why you should write blog posts or code when temperamental science delivers its regular dose of non-nice things.
I was getting increasingly frustrated with whatever I was busy doing the past few days, so I decided to write this post instead, now I feel much better. spmversion = 'spm12'įor a more permanent solution that applies to all functions from the FieldTrip toolbox, you can set SPM12 as the default version in your startup. You can specify the use of SPM12 with cfg. Most mex file issues are resolved using the latest version of SPM12. You can use the maintenance version of SPM8, which has newer mex files, see. A makefile and instructions are provided on. dylib Referenced from : / Users / roboos / matlab / fieldtrip / external / spm8 / spm_conv_vol. mexmaci64, 6 ): Library not loaded : loader_path / libmex.
mexmaci64 dlopen (/ Users / roboos / matlab / fieldtrip / external / spm8 / spm_conv_vol. Invalid mex - file ' / Users / roboos / matlab / fieldtrip / external / spm8 / spm_conv_vol.