<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
<html>
<head>
<meta http-equiv="content-type" content="text/html; charset=ISO-8859-1">
</head>
<body bgcolor="#ffffff" text="#000000">
<b>NIPS Workshop on Large scale optical physiology: From
data-acquisition to models of neural coding</b><br>
<br>
Montreal, Quebec. December 12, 2014<br>
<u><br>
- Scope:</u><br>
<br>
Obtaining a detailed understanding of brain function remains a
significant challenge. Major advances in recording technologies --
e.g. imaging calcium signals with 2-photon, light-sheet, or
light-field microscopy -- are beginning to provide measurements of
neural activity at unprecedented scales. Analytical tools will
critical for the high-throughput acquisition and analysis of such
large-scale datasets. In particular, our field needs scalable,
reproducible computational approaches that are general enough to
share and coordinate across groups, but flexible enough to extract
meaning from a variety of problem settings. We also need analyses
that examine the full richness of both single-neuron and
population-level response properties and dynamics.
<br>
The goal of this workshop is to discuss challenges and opportunities
for computational neuroscience and machine learning that arise from
large-scale recording techniques:
<ul>
<li> What kind of data will be generated by large-scale functional
measurements in the next decade? How will it be quantitatively
or qualitatively different to the kind of data we have had
previously? What will the computational bottlenecks be? </li>
<li> What are the key computational tools for high-throughput data
acquisition, e. g. visualization/dimensionality
reduction/information quantification? How can we identify the
best algorithms and what are the limitations of existing
techniques?</li>
<li> What can we learn from large-scale recordings that is
fundamentally new? What theories could we test, if only we had
access to recordings from more neurons? What kind of statistics
will be powerful enough to verify/falsify population coding
theories? What can we infer about network structure and
dynamics?</li>
</ul>
We have invited scientists whose research directly addresses these
questions, including both experimental and computational
neuroscientists. We hope to foster active discussion among this
multidisciplinary group, to clarify priorities and perspective, and
coordinate key directions for future research. The target audience
includes industry and academic researchers interested in machine
learning, neuroscience, big data and statistical inference.<br>
<br>
<u>- Link: </u>
<a class="moz-txt-link-freetext" href="http://hci.iwr.uni-heidelberg.de//Staff/fdiego/LargeScaleOpticalPhysiology/">http://hci.iwr.uni-heidelberg.de//Staff/fdiego/LargeScaleOpticalPhysiology/</a><u><br>
<br>
- Important Dates:</u><br>
<br>
Submission Opens: September 1, 2014<br>
Abstract submission deadline (for poster presentations): October
9, 2014<br>
Acceptance for poster presentation will be announced by October
23, 2014<br>
Workshop Day: December 12, 2014<br>
<br>
<u>- Call for Contributions:</u><br>
<br>
We invite abstract submissions for poster presentation at the
workshop. Please submit abstracts (1 page max in pdf format) by
email to <b>opticalphysiology(at)gmail.com</b>.
<br>
<br>
<u>- Organizers:</u><br>
<br>
<a href="http://hci.iwr.uni-heidelberg.de/Staff/fdiego/"
target="_blank"> </a>Ferran Diego (Heidelberg Collaboratory for
Image Processing, University of Heidelberg) <u>-- primary contact</u><br>
Jeremy Freeman (Janelia Research Campus)<br>
Jakob Macke (Max Planck Institute for Biological Cybernetics and
Bernstein Center for Computational Neuroscience, Tuebingen, Germany)<br>
Il Memming Park (Neural Coding and Computation Lab, University of
Texas at Austin)<br>
Eftychios Pnevmatikakis (Department of Statistics and the Center for
Theoretical Neuroscience at Columbia University) <br>
<pre class="moz-signature" cols="72">--
Multidimensional Image Processing Group
University of Heidelberg, HCI
Speyerer Str. 6, D-69115 Heidelberg
Phone: +49 (0) 6221 – 5280
E-Mail: <a class="moz-txt-link-abbreviated" href="mailto:ferran.diego@iwr.uni-heidelberg.de">ferran.diego@iwr.uni-heidelberg.de</a>
<a class="moz-txt-link-freetext" href="http://hci.iwr.uni-heidelberg.de/Staff/fdiego/">http://hci.iwr.uni-heidelberg.de/Staff/fdiego/</a>
</pre>
</body>
</html>