Multi-subject event-related fMRI - Repetition priming

These data sets comprise contrast images from single-subject fMRI analyses or 'first-level' analyses from the repetition priming experiment described here. In the summary statistic approach to Random Effects Analysis (RFX) these contrast images are then used in a 'second-level' analysis allowing you to make inferences about the population from which the subjects were drawn.

These contrasts are for the overall effect of faces, characterised using either (i) a canonical HRF (single con image per subject), (ii) an informed basis set (three con images per subject) and (iii) an FIR basis set (12 con images per subject).


Overview of the dataset, and step-by-step description of analysis:
SPM12: manual.pdf
SPM8: manual.pdf
ZIP archive: (71Mb)


SPM12 batch script:
SPM5 batch script (compatible with SPM8):

Analyses with previous SPM versions


Instructions for analysing the data using SPM2 are available here and as a word file.


Further details of the simple random effects analysis (1 con image per subject) and its equivalent using nonparametric statistics are available here.

This dataset contains 12 contrast images (of the contrast faces versus baseline) from the study:

Henson, R.N.A, Shallice, T., Gorno-Tempini, M.-L. & Dolan, R.J (2002). 
Face repetition effects in implicit and explicit memory tests as measured by fMRI. 
Cerebral Cortex, 12, 178-186.

Download the archive rfx.tar.gz and extract the contents to a new directory. The archive contains the contrast images con_0006.img to con_0017.img, a plot of the first-level design matrix and group fixed-effects results (ffx_mip.jpg), and a README file. You can also download just the README file.

Following the instructions in the README file will allow you to do a (parametric) random effects analysis.

We also show you how to do a nonparametric random effects analysis. You can check the results of your analysis by downloading the archive spm99_rfx.tar.gz for the parametric approach (SPM) and snpm_rfx.tar.gz for the nonparametric approach (SnPM). There is also an archive of results for a nonparametric analysis using the `variance-smoothing' option snpm_rfx_vsm.tar.gz

Last modified $Date: 2018/09/25 11:35:47 $ by $Author: spm $

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