Mathematical Sciences Research Institute

Home » Breaking the Neural Code


Breaking the Neural Code October 29, 2014 - November 01, 2014
Parent Program: --
Location: MSRI: Baker Board Room, Atrium
Organizers Larry Abbott (Columbia University), Ingrid Daubechies (Duke University), Michael Jordan (University of California), LEAD Liam Paninski (Columbia University)
For decades, neuroscientists have dreamed about the possibility of recording from all the neurons in a brain, or of having access to a complete large brain wiring diagram, or ideally to obtain both of these datasets simultaneously, in the same brain.  Recent technical advances have brought this dream close to reality in some cases.  Now the challenge will be to understand these massive datasets.  A few domains will be particularly relevant: Inferring network structure from noisy and incomplete data Inferring computational input-output function from structure Optimal experimental design (incl. compressive sensing methods) for observation of networks Modeling structured stochastic network dynamics Optimal control of network dynamics Inferring low-dimensional dynamics from high-dimensional observations There’s a strong need in neuroscience for deep new ideas from mathematics and statistics, and our hope is that this small, focused workshop without many formal talks will spark collaborations that will lead to breakthroughs in the areas described above. This workshop is by invitation only. This workshop is supported by a generous donation from Sanford Grossman.  
Keywords and Mathematics Subject Classification (MSC)
Primary Mathematics Subject Classification No Primary AMS MSC
Secondary Mathematics Subject Classification No Secondary AMS MSC
Funding & Logistics Show All Collapse

Show Directions to Venue

Show Reimbursement Guidelines