New approaches to spike train analysis and neuronal coding
(note one last-minute change,
unfortunately Dr. Principe had to cancel)
There are a few (2-4) slots available for shorter contributed talks (15+5 min).
Thomas Kreuz (email@example.com)
Deadline is May 13, 2013 (which is also the workshop deadline for CNS).
*** The call is now closed. ***
Twenty-second Annual Computational Neuroscience Meeting CNS 2013
July 13, 2013: Tutorials
July 14-16, 2013: Main meeting
July 17/18, 2013: Workshops
July 17, 2013: This workshop
Spike trains are central to signaling and computation in the brain; they are frequently the data collected in neuroscientific experiments and recent advances in electrophysiological techniques mean that they are now being collected across large neuronal populations and for synaptically connected neurons. As a consequence, describing and analyzing spike trains and quantifying their properties is a common challenge and one that is important in our efforts to understanding how the brain codes, integrates and processes information. Nonetheless, spike train analysis remains difficult and even immediate questions such as the degree to which spike trains carry a temporal or rate code are not only difficult to answer, they are difficult to ask in an unambiguous way. The purpose of this workshop is to discuss how different approaches, such as measures of spike train (dis)similarity and methods from information theory, can be used to define quantitative properties of neuronal signaling. Such properties could be used to analyze the large quantities of experimental data now available in a way that would help specify and address questions about neuronal coding and processing. Contributions will include experimental and theoretical studies, data analysis as well as modeling.
The workshop will include presentations by seven invited speakers (35 + 5 min each). In addition, three slots for contributed talks (15 + 5 min) have been assigned. At the end ample time for discussion will be provided.
Department of Computer Science
University of Bristol
Institute for Complex Systems (ISC)
National Research Council (CNR)