OpenfMRI has been deprecated. For new and up to date datasets please use

Old dataset pages are available at

Neural responses to naturalistic clips of behaving animals in two different task contexts

Functional MRI was used to measure hemodynamic responses while participants viewed brief naturalistic clips of behaving animals under two task contexts. Twelve right-handed adults participated in the study. Functional and structural images were acquired using a 3 T Philips Intera Achieva MRI scanner with a 32-channel phased-array head coil (functional: TR/TE = 2000/35 ms, flip angle = 90°, resolution = 3 mm isotropic; structural: TR/TE = 8.2/3.7 ms, flip angle = 8°, resolution = 0.9375 × 0.9375 × 1.0 mm voxels). In total, stimuli comprised 40 unique 2 s video clips and their horizontally flipped counterparts for 80 visually unique clips. Ten unique runs were created and run order was counterbalanced across participants. Stimuli were presented in pseudorandom order and each of the 80 stimuli occurred once per run. Each event consisted of a 2 s stimulus presentation followed by 2 s fixation. Stimuli were organized into five taxonomic categories (birds, insects, reptiles, primates, and ungulates), and four behavioral categories (eating, fighting, running, and swimming) in a factorial design for 20 total category-level conditions. Participants were instructed to maintain fixation between trials, but freely viewed the video clips. Participants performed two different 1-back category repetition tasks. In half of the runs, participants were instructed to press a button when they noticed a taxonomic category repetition, and in the other half of the runs they were instructed to press the button when they noticed a behavioral category repetition. Repetition events were sparse by design (~4 per run of each type) and participants were instructed to ignore task-irrelevant repetitions.


001 n-back task


  • James V. Haxby
  • Andrew C. Connolly
  • Yaroslav O. Halchenko
  • Samuel A. Nastase

Contact Information:

Name: Samuel A. Nastase

Acknowledgements and Funding:

We thank Jason Gors, Kelsey G. Wheeler J. Swaroop Guntupalli, Matteo Visconti di Oleggio Castello, M. Ida Gobbini, Terry Sacket, and the rest of the DBIC (Dartmouth Brain Imaging Center) personnel for assistance in data collection/curation.

External Publication Links:

Attention Selectively Reshapes the Geometry of Distributed Semantic Representation

Sample Size:


Scanner Type:

Philips Intera Achieva



Accession Number:


How to cite this dataset:

In addition to any citation requirements in the dataset summary please use the following to cite this dataset:

This data was obtained from the OpenfMRI database. Its accession number is ds000233



Browse Data For All Revisions on S3

Direct Links to data:

Revision: 1.0.0 Date Set: July 25, 2017, 5:02 p.m.


- Initial Release