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Workshop
Sat Dec 12th 08:30 AM -- 06:30 PM @ 511 e
BigNeuro 2015: Making sense of big neural data
Eva L Dyer · Joshua T Vogelstein · Konrad Koerding · Jeremy Freeman · Andreas S. Tolias





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Advances in optics, chemistry, and physics have revolutionized the development of experimental methods for measuring neural activity and structure. Some of the next generation methods for neural recording, promise extremely large and detailed measurements of the brain’s architecture and function. The goal of this workshop is to provide an open forum for the discussion of a number of important questions related to how machine learning can aid in the analysis of these next generation neural datasets. What are some of the new machine learning and analysis problems that will arise as new experimental methods come online? What are the right distributed and/or parallel processing computational models to use for these different datasets? What are the computational bottlenecks/challenges in analyzing these next generation datasets?

In the morning, the goal will be to discuss new experimental techniques and the computational issues associated with analyzing the datasets generated by these techniques. The morning portion of the workshop will be organized into three hour-long sessions. Each session will start with a 30 minute overview of an experimental method, presented by a leading experimentalist in this area. Afterwards, we will have a 20 minute follow up from a computational scientist that will highlight the computational challenges associated with the technique.

In the afternoon, the goal will be to delve deeper into the kinds of techniques that will be needed to make sense of the data described in the morning. To highlight two computational approaches that we believe hold promise, we will have two 50 minute long methods talks. These talks will be followed by a scientist with big-data experience outside of neuroscience with the goal of thinking about organization, objectives, and pitfalls. Lastly we will have plenty of time for free form discussion and hold a poster session (open call for poster submissions). We envision that this workshop will provide a forum for computational neuroscientists and data scientists to discuss the major challenges that we will face in analyzing big neural datasets over the next decade.

09:00 AM Methods overview: High-density electrical recordings
Andreas Schaefer
09:30 AM Computational discussion: High-density electrical recordings
Konrad Koerding
10:20 AM Methods overview: Studying the function and structure of microcircuits
Andreas Tolias
11:20 AM Methods overview: Light field microscopy
Aaron S Andalman
11:50 AM Computational discussion: Challenges in analyzing large neuroimaging datasets
Guillermo Sapiro
12:20 PM Spotlight
Furong Huang, Will Gray Roncal, Tom Goldstein
02:00 PM Lessons learned from big data projects in cosmology
Alex Szalay
03:00 PM Sketching as a tool for numerical linear algebra
David Woodruff
04:30 PM Low-dimensional inference with high-dimensional data
Richard Baraniuk