Statistical Analysis of Neuronal Data (SAND5)
University of Pittsburgh
- We expect travel support will be available.
- Several sessions will be devoted to presentations by young investigators.
- All participants are encouraged to present posters.
- We expect selected papers to be published in a special issue of the Journal of Computational Neuroscience.
- All talks will be held in Lawrence Hall 120 at the University of Pittsburgh.
| Studies of the neural
basis of behavior typically use time-varying stimuli and produce time-varying
neuronal responses. Statistically, the setting involves both continuous
multiple time series and inhomogeneous point processes, sometimes dozens
or hundreds of them observed simultaneously. There are many challenging
analytical issues, including that of combining information obtained from
multiple modalities (EEG, fMRI, MEG, and extracellular recordings). This
workshop series aims to |
- define important
problems in neuronal data analysis and useful strategies for attacking
- evaluate analytical methods by their ability to yield insightful results in
- foster communication
between experimental neuroscientists and those trained in statistical
and computational methods;
- encourage young
researchers, including graduate students, to present their work;
- expose 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.
- Jack Gallant (UC Berkeley)
- Stu Geman (Brown U.)
- Sonja Gruen (Riken)
- Partha Mitra (Cold Spring Harbor)
- Tirin Moore (Stanford)
- Clay Reid (Harvard)
- Walt Schneider (Pittsburgh)
- Matt Smith (Pittsburgh)
- Garrett Stanley (Georgia Tech)
- Mriganka Sur (MIT)