The eighth international workshop on Statistical Analysis of Neural Data (SAND8) will take place May 31-June 2, 2017, in Pittsburgh, PA. Experimental methods for discovering the neural basis of behavior have been advancing rapidly and, as a result, brain data sets are increasing in size and complexity. Methods for better understanding such rich data sets, which can enable design of ever-more informative experiments, are desperately needed. This workshop series is concerned with identifying, discussing, and disseminating many of the most promising approaches to analysis of neural data of all kinds. It also encourages young researchers, including graduate students, to present their work; exposes young researchers to important challenges and opportunities in this interdisciplinary domain, while providing a small meeting atmosphere to facilitate the interaction of young researchers with senior colleagues; and includes as participants women, under-represented minorities and persons with disabilities, who might benefit from the small workshop environment.
The data discussed in this workshop range from anatomy to electrophysiology, to neuroimaging. Cross-disciplinary communication between experimental neuroscientists and those trained in statistical and computational methods is a priority. SAND8 will bring together neurophysiologists, statisticians, mathematicians, engineers, physicists, and computer scientists who are interested in quantitative analysis of neural data. SAND8 will begin with a morning-long panel discussion on "Emerging Challenges of Brain Science Data," and end with several talks that connect statistical analysis to mathematical modeling. In between there will be keynote talks by senior investigators and shorter presentations by junior investigators, the latter selected on a competitive basis. There will also be a poster session, to which all participants are invited to contribute. Talks and posters may involve new methodology, investigation of existing methods, or application of state-of-the-art analytical techniques. In addition, there will be a lunchtime discussion devoted to opportunities and challenges for women in computational neuroscience. For further information please see http://sand.stat.cmu.edu.
