Program

07.30 The organizers: Opening remarks

07.45 Terry Sejnowski (Salk Institute): Keynote

Session 1: Recording neural activity with light

08.30 Andreas Tolias (Baylor College of Medicine)

09.00-09.30 Break 1 & Posters

09.30 Misha Ahrens (Janelia Farm/HHMI): Whole-brain functional imaging and motor learning in the larval zebrafish

Session 2: Probabilistic models of neural activity

10.00 Jonathan Pillow (University of Texas, Austin): Flexible models for binary spike patterns in large-scale neural recordings

10.30 David Greenberg (MPI Tübingen and CAESAR Bonn)

11.00 Discussion

11.30-15.00 Ski break

Session 3: Other large-scale recording methods

15.00 Jorg Scholvin (MIT): High-density electrode arrays

15.30 Konrad Kording (Northwestern University)

16.00 Jakob Macke (MPI & BCCN Tübingen)

16.30 Discussion

16.45-17.15 Break 2 & Posters

Session 4: Neural connectivity

17.15 Joshua Vogelstein (Duke University): Statistical Models and Inference for Big Brain-Graphs

17.45 Mitya Chklovskii (Janelia Farm/HHMI):

18.15 Final discussion: What will we learn with all this new data? Dream experiments?

Posters

  • Ari Pakman, Ben Shababo and Liam Paninski, Bayesian Probit Factor Models with Sparse Latent Variables For Neural Population Spiking Data.

  • Evan Archer, Jonathan Pillow and Jakob H. Macke, Low-dimensional models of neural population recordings with complex stimulus selectivity.

  • David Pfau, Jeremy Freeman, Misha Ahrens and Liam Paninski, Scalable ROI Detection for Calcium Imaging.

  • Jeremy Freeman, Nikita Vladimirov, Takashi Kawashima and Misha Ahrens, Mapping the brain at scale.

  • Christopher Hillar and Urs Köster, Characterizing high-dimensional neural recordings with Hopfield networks.

  • Urs Köster and Bruno Olshausen, Testing V1 receptive field models with polytrode recordings.

  • Scott W. Linderman and Ryan P. Adams, Fully-Bayesian Inference of Structured Functional Networks in GLMs.

  • Ferran Diego, Susanne Reichinnek, Martin Both and Fred A. Hamprecht, Automated Identification of Neuronal Activity From Calcium Imaging By Sparse Dictionary Learning.