Nonparametric Interference of Synaptic Properties from Intracellular Neurophysiological Signals
Abstract
This project will help support the development of statistics, machine learning, and applied and interdisciplinary mathematics research and education programs at City College and CUNY, which are underrepresented but in great demand. It is also synergistic with campus-wide e orts to target neuroscience as a growth area in multiple departments on campus and in the CUNY Advanced Science Research Center, and related e orts to develop theoretical neuroscience at the CUNY Graduate Center (e.g., the new Initiative for Theoretical Sciences). The fundamental research targets areas of speci c interest to DoD basic research programs. These include: mathematical research on biomathematics (particularly neuromathematics), the statistical analysis of networks and network models, techniques for real-time analysis of data streams from nonstationary and poorly-understood distributions, nonparametric and robust statistics, massive data sets, and single-cell and behavioral neurophysiology.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Feb 17, 2016
- Source ID
- W911NF1510426
Entities
People
- Asohan Amarasingham
Organizations
- Army Contracting Command
- City College of New York
- Office of the Secretary of Defense