Saturday, September 14, 2013

[Comp-neuro] NIPS 2013 Workshop on "Acquiring and analyzing the activity of large neural ensembles"


NIPS 2013 Workshop Announcement
"Acquiring and analyzing the activity of large neural ensembles"

Lake Tahoe, Nevada, United States
10th December, 2013

with partial support from
Bernstein Center for Computational Neuroscience, Tübingen, Germany


For many years, measurements of neural activity have either been restricted to recordings from single neurons or a very small number of neurons, and anatomical reconstructions to very sparse and incomplete neural circuits. Major advances in optical imaging (e.g. 2-photon and light-sheet microscopic imaging of calcium signals) and new electrode array technologies are now beginning to provide measurements of neural activity at an unprecedented scale. High-profile initiatives such as BRAIN (Brain Research through Advancing Innovative Neurotechnologies) will fuel the development of ever more powerful techniques for mapping the structure and activity of neural circuits.

Computational tools will be important to both the high-throughput acquisition of these large-scale datasets and in the analysis. Acquiring, analyzing and integrating these sources of data raises major challenges and opportunities for computational neuroscience and machine learning:
• 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?
• Algorithmic methods have played an important role in data acquisition, e.g. spike-sorting algorithms or spike-inference algorithms from calcium traces. In the future, what role will computational tools play in the process of high-throughput data acquistion?
• One of the key-challenges is to link anatomical with functional data -- what computational analysis tools will help in providing a link between these two disparate source of data? What can we learn by measuring 'functional connectivity'?
• What have we really learned from high-dimensional recordings that is new? What will we learn? What theories could we test, if only we had access to recordings from more neurons at the same time?

We have invited scientists whose research addresses these questions including prominent technologists, experimental neuroscientists, theorists and computational neuroscientists. We foresee active discussions amongst this multi-disciplinary group of scientists to catalyze exciting new research and collaborations.

Confirmed speakers include:
• Terry Sejnowski, Salk Institute (Keynote)
• Misha Ahrens, HHMI Janelia Farm Research Campus
• Mitya Chklovskii, HHMI Janelia Farm Research Campus
• Konrad Koerding, Northwestern University
• Jonathan Pillow, University of Texas at Austin
• Andreas Tolias, Baylor College of Medicine
• Joshua Vogelstein, Duke University

Submission details:
We invite abstract submissions for poster presentation at the workshop. Please submit abstracts (1 page max in pdf format) by email to by October 9th, 2013.

Important dates:
Abstract submission deadline (for poster presentations): October 9th, 2013
Acceptance for poster presentation will be announced by October 23th, 2013

Organizing Committee:
• Srini Turaga (Gatsby Unit & WIBR, University College London)
• Lars Büsing (Gatsby Unit, University College London)
• Maneesh Sahani (Gatsby Unit, University College London)
• Jakob Macke (Max Planck Institute for Biological Cybernetics and Bernstein Center for Computational Neuroscience, Tübingen, Germany)_______________________________________________
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