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Emerging Tools for Acquisition and Interpretation of Whole-Brain Functional Data

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Emerging Tools for Acquisition and Interpretation of Whole-Brain Functional Data

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November 5 - 8, 2017
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A follow-up to the first conference held at Janelia in 2015, this meeting focuses on emerging optical techniques enabling near-simultaneous acquisition of neuronal activity at the whole-brain level with single-cell resolution in a variety of model organisms. These techniques will advance our understanding of how the information underlying behavior is dynamically represented and processed by neuronal networks at the whole-brain level. Analysis of the big data sets generated from microscopic imaging requires a combination of machine learning, statistics, mathematical modeling and a robust IT infrastructure. This meeting gathers experts and pioneers in these fields to identify synergies and new opportunities and to discuss challenges in moving forward.

APPLICATION DEADLINE: JUNE 28, 2017 (11:59 p.m.).

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Philipp Keller, Janelia Research Campus/HHMI
Alipasha Vaziri, Rockefeller University

Invited Participants
Misha Ahrens, Janelia Research Campus/HHMI
Kristin Branson, Janelia Research Campus/HHMI
Dmitri Chklovskii, Simons Center for Data Analysis
David Cox, Harvard University
Karl Deisseroth, HHMI/Stanford University
Shaul Druckmann, Janelia Research Campus/HHMI
Florian Engert, Harvard University
Jeremy Freeman, Chan Zuckerberg Initiative
Winrich Freiwald, Rockefeller University
Charles Gilbert, Rockefeller University
Michael Hausser, University College London
Fritjof Helmchen, University of Zurich
Elizabeth Hillman, Columbia University
Na Ji, Janelia Research Campus/HHMI
David Kleinfeld, University of California, San Diego
Konrad Körding, Northwestern University
Eftychios Pnevmatikakis, Simons Foundation
Clay Reid, Allen Institute for Brain Science
Aravinthan Samuel, Harvard University
Hari Shroff, National Institute of Biomedical Imaging and Bioengineering/NIH
Karel Svoboda, Janelia Research Campus/HHMI
David Tank, Princeton University
Chris Xu, Cornell Univeristy
Rafael Yuste, Columbia University