Multiple-Demand Network encoding geometry balances generalization and dimensionality during novel task assembly.

This dataset contains the raw fMRI BIDS dataset from the work "Multiple-Demand Network encoding geometry balances generalization and dimensionality during novel task assembly." by Ana F. Palenciano, Paula Pena, Carlos González-García, Alexandra Woolgar and María Ruz. The dataset includes, per participant (N = 40): - De-faced anatomical T1-weighted and T2-weighted scans (/anat). - T2* EPI images from 9 functional runs (/func), 8 of them corresponding to the main experimental paradigm (novel instruction following paradigm, "instcomp") and 1 additional localizer run ("loc"). TSV event files containing onset and durations of the main events of interest are also included. - Field mapping phase and magnitud images (/fmap). The ROI-based individual and group-level fMRI data, the full behavioral dataset, and the scripts used for the analyses are available on OSF (https://osf.io/j5erw/) For a full description of the experimental tasks and methodology employed in our work, please read the preprint manuscript: (https://doi.org/10.64898/2026.04.22.720093 )