Here we present the first deliverable of this project: a high-resolution functional magnetic resonance (fMRI) dataset — 20 participants recorded at high field strength (7-Tesla) during prolonged stimulation with an auditory feature film ("Forrest Gump"). In addition, a comprehensive set of auxiliary data (T1w, T2w, DWI, susceptibility-weighted image, angiography) as well as measurements to assess technical and physiological noise components have been acquired (see overview). An initial analysis confirms that these data can be used to study common and idiosyncratic brain response patterns to complex auditory stimulation.

Response pattern similarity distribution rendered on the cortical surface

Inter-subject brain response pattern similarity

BOLD time series correlation and pattern similarity estimated from representational similarity analysis on anatomically aligned data reveal consistent brain responses to quasi natural auditory stimulation across all participants. Areas of maximum similarity in both hemispheres are centered on the anterolateral portion of the Planum Temporale — part of the auditory ventrolateral pathway and known to be involved in processing complex sounds and speech.

Among the potential uses of this dataset are the study of auditory attention and cognition, language and music perception, and social perception. The auxiliary measurements enable a large variety of additional analysis strategies that relate functional response patterns to structural properties of the brain. Alongside the acquired data, we provide source code and detailed information on all employed procedures — from stimulus creation to data analysis. In order to facilitate replicative and derived works, only free and open-source software was utilized.

A detailed data descriptor has been published in the inaugural issue of Scientific Data, the new open-access journal of the Nature Publishing Group. As of now, the full dataset with its 355 GB is available from and from a file server at the University of Magdeburg.


This research was funded by the German Federal Ministry of Education and Research (BMBF) as part of a US-German collaboration in computational neuroscience (CRCNS), co-funded by the BMBF and the US National Science Foundation (BMBF 01GQ1112; NSF 1129855).


Hanke, M., Baumgartner, F.J., Ibe, P., Kaule, F.R., Pollmann, S., Speck, O., Zinke, W. & Stadler, J. (2014). A high-resolution 7-Tesla fMRI dataset from complex natural stimulation with an audio movie. Scientific Data, 1.