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BigNeuro 2015: Making sense of big neural data
Eva Dyer · Joshua T Vogelstein · Konrad Koerding · Jeremy Freeman · Andreas S. Tolias

Sat Dec 12 05:30 AM -- 03:30 PM (PST) @ 511 e
Event URL: http://neurodata.io/bigneuro2015 »

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.

Author Information

Eva Dyer (Northwestern University)

Eva Dyer is an Assistant Professor in the Wallace H. Coulter Department of Biomedical Engineering at the Georgia Institute of Technology and Emory University. Dr. Dyer completed her M.S. and Ph.D degrees in Electrical & Computer Engineering at Rice University in 2011 and 2014, respectively. Eva's research interests lie at the intersection of data science, machine learning, and neuroscience.

Joshua T Vogelstein (The Johns Hopkins University)
Konrad Koerding
Jeremy Freeman (HHMI Janelia Farm)
Andreas S. Tolias (Baylor College of Medicine)

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