www.studyforrest.org/content/pages/index.html

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<h2>What is <em>StudyForrest</em>?</h2>
<p>The <strong>human brain</strong> processes vast amounts of diverse
input that are continuously gathered across the senses. However, most
experiments study the brain via simplified stimuli that do little to
resemble the complexity of a <strong>natural environment</strong>
&mdash; a mismatch that must be addressed if we are to better
understand how the brain works.</p>
<p>This project centers around the use of <strong>the movie Forrest
Gump</strong>, which provides complex sensory input that is both
reproducible and is also richly laden with real-life-like content and
contexts.</p>
<p>Since its initial release, the <em>StudyForrest</em> dataset has grown
and been extended substantially, and now encompasses many <strong>hours
of fMRI scans</strong>, structural brain scans, <strong>eye-tracking</strong>
data, and extensive <strong>annotations</strong> of the movie. Explore
the <a href="/data.html">Data Page</a> to more closely examine the data
we have available.</p>
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<h2>How Can You Use It?</h2>
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<h3>Neuroscience Researchers</h3>
<p>This is a <strong>one-of-a-kind resource</strong> for studying
high-level cognition in the human brain under complex, natural
stimulation. Furthermore, the versatility of the provided data (some
individuals have nearly ten hours of fMRI data) enables studies far
beyond this main focus. This covers a vast range from studies of
low-level signal properties and brain structure, to sensory
integration and attentional processes, to computational modeling of
representational spaces and brain area interactions. Take a look the
<a href="/publications.html">List of Publications</a> to get
inspired.</p>
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<h3>Scientific Developers</h3>
<p>The <em>StudyForrest</em> project provides <strong>ideal reference
datasets</strong> for brain imaging. It's a comprehensive, modular,
multi-modal, real-world dataset &mdash; making it an optimal choice
when benchmarking algorithms or comparing implementations across
projects.</p>
<p>Liberally licensed (<a href="https://opendatacommons.org/licenses/pddl/1-0/">PDDL</a>)
and hosted across many <a href="/access.html">different services</a>
(OpenNeuro, GIN, etc) with fine-grained access options, the
<em>StudyForrest</em> dataset is easily accessible and is ready to be
integrated into your CI infrastructure.</p>
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<h3>Everyone &mdash;&nbsp;and&nbsp;You</h3>
<p>Not keen on brain research? This project still has something to offer
to you! Our effort to analyze the <strong>structure of the movie
<em>Forrest Gump</em></strong> and annotate its properties greatly
expands the breadth of topics that can be explored. Check out the
<a href="/data.html">Data Page</a> for more specifics.</p>
<p>What we're most interested in is applications and inquiries that we
have not anticipated &mdash; both within the field of neuroscience
and beyond. So please, invent applications and <strong>explore ideas
you have</strong> that we aren't even aware of... and do tell us
about them!</p>
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<h2>How are People Using It?</h2>
<p>The <em>StudyForrest</em> dataset has been used in over two dozen
<a href="publications.html">studies</a> to investigate particular
research questions or to validate novel tools and algorithms.</p>
<blockquote> [&hellip;] we use fMRI activity evoked by an emotionally
charged movie and continuous ratings of the perceived emotion
intensity to reveal the topographic organization of affective states.
<br>&mdash;
<a href="https://doi.org/10.1038/s41467-019-13599-z">
Lettieri et al., Nature Comm., 2019</a>
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<blockquote>[&hellip;] high replicability in region-of-interest
[&hellip;] analyses is essential for [&hellip;] biomarkers of
good health or disease. [&hellip;] A critical analysis
of cortical parcellation protocols from FreeSurfer, BrainSuite,
BrainVISA and BrainGyrusMapping revealed major limitations.
<br>&mdash;
<a href="https://doi.org/10.1016/j.neuroimage.2017.02.082">
Mikhael et al., NeuroImage, 2018</a>
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<blockquote>[&hellip;] We reveal here that hippocampal activity measured
by fMRI during film watching is both sensitive and specific to event
boundaries, identifying a potential mechanism whereby event
boundaries shape experience by modulation of hippocampal activity.
<br>&mdash;
<a href="https://doi.org/10.1523/JNEUROSCI.0524-18.2018">
Ben-Yakov &amp; Henson, J Neuroscience, 2018</a>
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<blockquote>[&hellip;] magnetic resonance advection imaging might have future
potential to contribute to the modeling of the cerebrovascular system and
to serve as a biomarker for cerebrovascular disease. <br>&mdash;
<a href="https://doi.org/10.1177/0271678X16651449">
Voss et al., Journal of Cerebral Blood Flow & Metabolism, 2016</a>
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<blockquote>This also opens the door for the identification of shared and
individual [brain] responses [&hellip;] to assess the degree to which
functional topography is shared across subjects. We posit that this
technique can be adapted to examine an array of situations where group
differences are the key experimental variable. <br>&mdash;
<a href="https://papers.nips.cc/paper/5855-a-reduced-dimension-fmri-shared-response-model.pdf">
Chen et al, NIPS, 2015</a>
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