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A ‘Naturalistic Neuroimaging Database’ for understanding the brain using ecological stimuli

Sarah Aliko, Jiawen Huang, Florin Gheorghiu, Stefanie Meliss, View ORCID ProfileJeremy I Skipper
doi: https://doi.org/10.1101/2020.05.22.110817
Sarah Aliko
1London Interdisciplinary Biosciences Consortium, University College London, UK
2Experimental Psychology, University College London, UK
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  • For correspondence: sarah.aliko.17@ucl.ac.uk jeremy.skipper@ucl.ac.uk
Jiawen Huang
2Experimental Psychology, University College London, UK
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Florin Gheorghiu
2Experimental Psychology, University College London, UK
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Stefanie Meliss
2Experimental Psychology, University College London, UK
3School of Psychology and Clinical Language Sciences, University of Reading, UK
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Jeremy I Skipper
2Experimental Psychology, University College London, UK
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  • ORCID record for Jeremy I Skipper
  • For correspondence: sarah.aliko.17@ucl.ac.uk jeremy.skipper@ucl.ac.uk
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Abstract

Neuroimaging has advanced our understanding of human psychology using reductionist stimuli that often do not resemble information the brain naturally encounters. It has improved our understanding of the network organization of the brain mostly through analyses of ‘resting-state’ data for which the functions of networks cannot be verifiably labelled. We make a ‘Naturalistic Neuroimaging Database’ (NNDb v1.0) publically available to allow for a more complete understanding of the brain under more ecological conditions during which networks can be labelled. Eighty-six participants underwent behavioural testing and watched one of 10 full-length movies while functional magnetic resonance imaging was acquired. Resulting timeseries data are shown to be of high quality, with good signal-to-noise ratio, few outliers and low movement. Data-driven functional analyses provide further evidence of data quality. They also demonstrate accurate timeseries/movie alignment and how movie annotations might be used to label networks. The NNDb can be used to answer questions previously unaddressed with standard neuroimaging approaches, progressing our knowledge of how the brain works in the real world.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://openneuro.org/datasets/ds002837

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted May 25, 2020.
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A ‘Naturalistic Neuroimaging Database’ for understanding the brain using ecological stimuli
Sarah Aliko, Jiawen Huang, Florin Gheorghiu, Stefanie Meliss, Jeremy I Skipper
bioRxiv 2020.05.22.110817; doi: https://doi.org/10.1101/2020.05.22.110817
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A ‘Naturalistic Neuroimaging Database’ for understanding the brain using ecological stimuli
Sarah Aliko, Jiawen Huang, Florin Gheorghiu, Stefanie Meliss, Jeremy I Skipper
bioRxiv 2020.05.22.110817; doi: https://doi.org/10.1101/2020.05.22.110817

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