**Scripts and data for manuscript:**
Activity in the Fronto-Parietal Multiple-demand Network is Robustly Associated with Individual Differences in Working Memory and Fluid Intelligence
https://doi.org/10.1101/110270
**Folders description**
**1. analysis_scripts**
Scripts to create the figures in the manuscript. Before running these scripts, make sure to add the folder matlab_data to the matlab path.
**2. matlab_data**
Behavioral and fMRI summary data used by scripts in *analysis_scripts*.
**3. brain_data**
*3.1.group_activation_maps*
Volumetric group average maps for the H>E and S>N contrasts. Anatomical masks are available for download from Fedorenko’s lab website (https://evlab.mit.edu/funcloc/download-parcels).
*3.2.individual_activation_maps*
**Activation_maps.zip**: Individual subjects’ volumetric maps for the H>E and S>N contrasts.
**Activation_maps_X_Fix.zip**: Individual subjects’ volumetric maps for the task>fix contrasts (i.e., H>Fix, E>Fix, S>Fix, and S>Fix).
**N.B.** After the publication of the manuscript, it came to our attention that data for 3 of the 216 subjects (591_FED_20170422d_3T2, 593_FED_20170423c_3T2, 594_FED_20170423d_3T2 had been preprocessed with a slightly different pipeline (a newer pipeline based on SPM12, cf. the older, SPM5-based, pipeline). We have previously established that the results based on preprocessing+analysis carried out in the two pipelines are extremely similar (e.g., see Fig. SI-4 in Diachek et al., 2020). We re-preprocessed these 3 subjects in the older pipeline and repeated the critical brain-behavior correlations. The changes were negligible (only in the second decimal place): MD-accuracy old_r = 0.441, new_r =0.435; MD-RT old_r =-0.286, new_r =-0.278; Lang-accuracy old_r=0.18, new_r=0.16; Lang-RT old_r=-0.08, new_r=-0.05). Further, these 3 subjects were not part of the subset used for the brain-IQ correlations, so those results were not affected. For completeness, we also uploaded the individual activation maps for these 3 subjects analyzed in the older pipeline.
**4. stimuli_presentation_scripts**
For the spatial working memory task, a python-based version was used (set up using a VisionEgg libary; http://visionegg.org). We make the script available; however, because the VisionEgg library is no longer supported, the script may not run for some people. As a result, we additionally provide a video recording of a sample run for illustrative purposes, and a MatLab implementation (with the same procedure+timing as the python version), which we recommend using in future studies.
For the language localizer task, a few different variants were used in the current study. Any of these are available from Ev Fedorenko upon request, and some versions are already available at evlab.mit.edu.
