UH Biocomputation Group - Electrical Engineering and Systems Sciencehttp://biocomputation.herts.ac.uk/2022-03-16T22:39:10+00:00Uncovering the Topology of Time-Varying fMRI Data Using Cubical Persistence2022-03-16T22:39:10+00:002022-03-16T22:39:10+00:00Emil Dmitruktag:biocomputation.herts.ac.uk,2022-03-16:/2022/03/16/uncovering-the-topology-of-time-varying-fmri-data-using-cubical-persistence.html<p class="first last">Emil Dmitruk's Journal Club session where he will talk about a paper "Uncovering the Topology of Time-Varying fMRI Data Using Cubical Persistence"</p>
<p>This week on Journal Club session Emil Dmitruk will talk about a paper "Uncovering the Topology of Time-Varying fMRI Data Using Cubical Persistence".</p>
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<p>Functional magnetic resonance imaging (fMRI) is a crucial technology
for gaining insights into cognitive processes in humans. Data amassed
from fMRI measurements result in volumetric data sets that vary over
time. However, analysing such data presents a challenge due to the
large degree of noise and person-to-person variation in how
information is represented in the brain. To address this challenge, we
present a novel topological approach that encodes each time point in
an fMRI data set as a persistence diagram of topological features,
i.e. high-dimensional voids present in the data. This representation
naturally does not rely on voxel-by-voxel correspondence and is robust
to noise. We show that these time-varying persistence diagrams can be
clustered to find meaningful groupings between participants, and that
they are also useful in studying within-subject brain state
trajectories of subjects performing a particular task. Here, we apply
both clustering and trajectory analysis techniques to a group of
participants watching the movie 'Partly Cloudy'. We observe
significant differences in both brain state trajectories and overall
topological activity between adults and children watching the same
movie.</p>
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<p>Papers:</p>
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<li>B. Rieck, T. Yates, C. Bock, K. Borgwardt, G. Wolf, N. Turk-Browne, S. Krishnaswamy, <a class="reference external" href="http://arxiv.org/abs/2006.07882">"Uncovering the Topology of Time-Varying fMRI Data Using Cubical Persistence"</a>, 2020, arXiv:2006.07882 [cs, eess, math, q-bio, stat],</li>
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<p><strong>Date:</strong> 2022/03/18 <br />
<strong>Time:</strong> 14:00 <br />
<strong>Location</strong>: online</p>