CRCNS 2017 FINAL PROGRAM
| 8:00-8:40 | BREAKFAST and REGISTRATION | |
| 8:40-9:00 | Opening Remarks | Matthew Harrison and Stephanie Jones Brown University |
| 9:00-10:15 | S E S S I O N 1 | CHAIR: Michael Frank, Brown University |
| 9:00-9:50 | Keynote Lecture Deep reinforcement learning: Recent developments in AI and their implications for neuroscience [PDF] | Matthew Botvinick DeepMind and University College London |
| 9:50-10:15 | Toward socially aware computing and artificial intelligence | Ming Hsu University of California, Berkeley |
| 10:15-10:45 | BREAK | |
| 10:45-12:00 | S E S S I O N 2 | CHAIR: Carl Saab, Brown University |
| 10:45-11:10 | Pain intensity coding in the anterior cingulate cortex | Jing Wang New York University Langone Medical Center |
| 11:10-11:35 | Magnetic resonance elastography for brain studies with intrinsic actuation | Keith Paulsen Dartmouth University |
| 11:35-12:00 | What wakes us up? Networked circadian clocks | Erik Herzog Washington University, St. Louis Hans-Peter Herzel Institute for Theoretical Biology, Berlin |
| 12:00-1:00 | LUNCH | |
| 1:00-2:15 | S E S S I O N 3 | CHAIR: Wael Asaad, Brown University |
| 1:00-1:25 | Striatal interneuron subtypes coordinate distinct aspects of network dynamics and motor plans | Xue Han Boston University |
| 1:25-1:50 | Cell-Specific Pallidal Intervention Induces Long-Lasting Motor Recovery in Dopamine Depleted Mice | Aryn Gittis Carnegie Mellon University |
| 1:50-2:15 | Force encoding in muscle spindles: Towards a multiscale model for sensorimotor feedback control | Lena Ting Emory University and Georgia Institute of Technology |
| 2:15-2:45 | BROADER IMPACTS PANEL | CHAIR: Thomas Serre, Brown University |
| 2:15-2:45 | Broader Impacts Panel: Undergraduate training in computational neuroscience | Rick Gerkin[PDF] Arizona State University Venkatesh Gopal[PDF] Elmhurst College John Hale[PDF] Cornell University Mitra Hartmann Northwestern University Michael Spezio Scripps College |
| 2:45-3:15 | BREAK | |
| 3:15-4:30 | S E S S I O N 4 | CHAIR: David Sheinberg, Brown University |
| 3:15-3:40 | Optogenetic probing of glycinergic neuron function in brainstem respiratory circuits | Yaroslav Molkov Georgia State University |
| 3:40-4:05 | Patient-specific models of local field potentials recorded from deep brain stimulation electrodes | Cameron McIntyre Case Western Reserve University |
| 4:05-4:30 | OPTISTIM - Combining computational neuroscience and electrophysiology for optimal cortical electric stimulation | Dana Brooks University of Utah and Northeastern University |
| 4:30-5:00 | LEISURE TIME | |
| 5:00-8:00 | POSTER PRESENTATIONS/RECEPTION | |
| 8:15-8:55 | BREAKFAST and REGISTRATION | |
| 8:55-9:00 | Opening Remarks | Matthew Harrison and Stephanie Jones Brown University |
| 9:00-10:15 | S E S S I O N 5 | CHAIR: Takeo Watanabe, Brown University |
| 9:00-9:50 | Keynote Lecture Data-driven mimicking neural encoding/decoding systems | Shin Ishii Kyoto University |
| 9:50-10:15 | A fast, foveated, fully convolutional network model for human peripheral vision | Ruth Rosenholtz Massachusetts Institute of Technology |
| 10:15-10:45 | BREAK | |
| 10:45-12:00 | S E S S I O N 6 | CHAIR: Amitai Shenhav, Brown University |
| 10:45-11:10 | A two-stage model of sensory discrimination: An alternative to drift-diffusion | Michael Landy New York University |
| 11:10-11:35 | Learning symbolic representations for planning in hierarchical reinforcement learning | George Konidaris Brown University |
| 11:35-12:00 | Modelling theory of mind in the volunteer's dilemma using Partially Observable Markov Decision Processes (POMDPs) | Rajesh Rao University of Washington |
| 12:00-1:00 | LUNCH/POSTER PRESENTATIONS | |
| 1:00-2:45 | S E S S I O N 7 | CHAIR: Wilson Truccolo, Brown University |
| 1:00-1:25 | Finding essential nodes for integration in the brain using network optimization theory | Hernan Makse City College of New York |
| 1:25-1:50 | Neural dynamics of the of the formation of spatial maps during fully-mobile human navigation | Scott Makeig University of California, San Diego |
| 1:50-2:15 | Dynamic network analysis of human seizures for therapeutic intervention | Eric Kolaczyk Boston University |
| 2:15-2:45 | Funding Q&A [PDF] | Michele Ferrante, NIMH (US) [PDF] Takahisa Taguchi, NICT (Japan) Kenneth Whang, NSF (US) [PDF] |
| 2:45-3:15 | BREAK | |
| 3:15-4:55 | S E S S I O N 8 | Theresa Desrochers, Brown University |
| 3:15-3:40 | Correlated variability in cerebral cortex at criticality during vision | Ralf Wessel Washington University in St Louis |
| 3:40-4:05 | The generation and subtraction of predictions enhances neural coding and behavioral detection of external stimuli in an electric fish | Nathaniel Sawtell Columbia University |
| 4:05-4:30 | Using high-order acoustic and neural response statistics to categorize sounds in that mammalian auditory midbrain | Heather Read University of Connecticut |
| 4:30-4:55 | Maximum entropy models of population codes based on random projections | Elad Schneidman Weizmann Institute of Science |
| 4:55-6:30 | LEISURE TIME | |
| 6:30-9:00 | BANQUET at the DORRANCE | |
Workshop on Integrating Dynamics and Statistics in Neuroscience
Friday, June 16, 2017 – optional
To be held at the Institute for Computational and Experimental Research in Mathematics (ICERM), adjacent to Brown’s campus.
| 8:15-9:00 | BREAKFAST and REGISTRATION | |
| 9:00-9:10 | Opening Remarks | |
| 9:10-9:45 | The problem of dynamic network analysis | Robert Kass Carnegie Mellon University |
| 9:45-10:20 | Integrating physical and statistical models in neuroscience: some examples | Mark Kramer Boston University |
| 10:20-10:50 | BREAK | |
| 10:50-11:25 | Building functional nervous system networks from the bottom up | Henry Abarbanel University of California, San Diego |
| 11:25-12:00 | Dynamics to coding through biophysics of single neurons | Adrienne Fairhall University of Washington |
| 12:00-1:00 | LUNCH | |
| 1:00-1:35 | Neurobiology, brain imaging and information processing | Dimitris Pinotsis Massachusetts Institute of Technology |
| 1:35-2:10 | Inferring the source of fluctuation in neuronal activity | Shigeru Shinomoto Kyoto University |
| 2:10-2:40 | BREAK | |
| 2:40-3:15 | Data-driven geometry learning for parametrically-dependent dynamical systems with application to neuronal dynamics | Ronald Coifman Yale University |
| 3:15-3:30 | FORMAL DISCUSSION in lecture hall | |
| 3:30-5:00 | Informal discussion at ICERM | |