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<h1><a href="./">Automatic Discovery of Cell Types <strong></strong></a></h1>
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<h1></h1>
<h2><a href="http://elifesciences.org/content/4/e04250">Automatic discovery of cell types and microcircuitry from neural connectomics</a></h2>
<p><a href="http://www.ericjonas.com">Eric Jonas</a> and <a href="http://www.koerding.com/">Konrad Kording</a></p>
<p>eLife 2015, Published April 30, 2015. DOI: <a href="http://dx.doi.org/10.7554/eLife.04250">10.7554/eLife.04250</a></p>
<blockquote>
<p>Neural connectomics has begun producing massive amounts of data,
necessitating new analysis methods to discover the biological and
computational structure. It has long been assumed that discovering
neuron types and their relation to microcircuitry is crucial to
understanding neural function. Here we developed a nonparametric
Bayesian technique that identifies neuron types and microcircuitry
patterns in connectomics data. It combines the information
traditionally used by biologists in a principled and
probabilistically-coherent manner, including including connectivity,
cell body location and the spatial distribution of synapses. We show
that the approach recovers known neuron types in the retina and
enables predictions of connectivity, better than simpler
algorithms. It also can reveal interesting structure in the nervous
system of C. elegans and a historic microprocessor. Our approach
extracts structural meaning from connectomics, enabling new
approaches of automatically deriving anatomical insights from these
emerging datasets.</p>
</blockquote>
<h3>Talks and Press</h3>
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<li>
<p><a href="https://medium.com/the-physics-arxiv-blog/connectomics-how-the-emerging-revolution-in-neural-wiring-diagrams-is-about-to-change-biology-2a267b576e99">Connectomics—How The Emerging Revolution In Neural Wiring Diagrams Is About To Change Biology Forever</a></p>
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<p>One of us (Jonas) spoke at the <a href="http://mmds-data.org/">Workshop on Algorithms for Modern Massive Data Sets (MMDS)</a> on an earlier version of this work :</p>
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