Learning Naturalistic Structure: Processed fMRI datasetThis data was obtained from OpenNeuro as ds001545. We would like to thank the authors for their generosity in sharing their data, and we point interested users towards their paper describing its acquisition: Aly M, Chen J, Turk-Browne NB, & Hasson U (2018). Learning naturalistic temporal structure in the posterior medial network. Journal of Cognitive Neuroscience, 30(9): 1345-1365. Experimental design In this dataset, subjects were scanned while watching repeated presentations of intact and scrambled clips from Wes Anderson's 2014 film, The Grand Budapest Hotel. Scrambled clips were presented in either a 'fixed' (i.e., consistent scrambling from run to run) or 'random' (i.e., random scrambling from run to run) condition. An overview of the experimental design is shown in this figure from Aly and colleagues (2018) Preprocessing After downloading from OpenNeuro using DataLad, data was preprocessed using fMRIPrep 1.5.0rc1. A complete transcript of the fMRIPrep processing is available as a README file in the repository. Post-processing was performed using Nilearn. Briefly, functional files were masked with the fMRIPrep-derived brain mask and trimmed to discard non-steady state...Access is restricted by the data custodian. The collection's description and structure are public; the data is not available for querying through this network.Learning Naturalistic Structure: Processed fMRI dataset is published on Viral AI.