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 National Science
Foundation Award #0306202 |
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Statistical Analysis of Networked Point Processes |
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| Investigator(s): |
Catherine Loader (PI)
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| Sponsor: |
Case Western Reserve University, OH 44106 2163684510
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| Start Date/Expiration Date |
2003-06-01 to 2006-05-31 (amended 2005-05-19) |
| Awarded Amount to Date: |
$257,032 |
| Abstract: Motivated by problems arising in the analysis of neural data, the investigator and colleagues will develop new statistical methods for the analysis of functional data, and in particular to study multiple replications of point processes. The main question of interest is understanding the structure of the rate functions, and understanding how the rate functions relate to covariates. Particular attention will be given to the time distortion, or latency problem, where differences in the time scale among different replications are considered. Such time-scale differences are of particular interest in neural data applications, as they represent different speeds at which subjects complete tasks in response to a stimulus. The research will develop new methods, based on tools from extreme value theory, for functional regression and analysis of variance problems.
Nerve cells, or neurons, are fundamental to communication between the brain and other parts of the body. When a subject receives an external stimulus, for example, a visual stimulus may consist of showing an object to the subject, nerve cells react and transmit information about the stimulus to the brain through a series of electrical pulses. The proposed research will advance understanding of this communication process by developing new methods for analyzing the neural signals. The statistical methods developed during the proposed research will study how the response to a stimulus differs among different subjects, and how these differences relate to factors such as species, age and gender. The proposed research has applications in product design. As an example, a warning device such as a traffic signal may be required to generate a stimulus to warn users of potential hazard. Understanding the response of different individuals to a given stimulus, and the different responses to different stimuli, will lead to improved products and safety for a wider variety of users. |
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| NSF Org: |
DMS - Division of Mathematical Sciences |
| Award Number: |
0306202 |
| Award Instrument: |
Continuing grant |
| Program Manager: |
Robert J. Serfling
DMS Division of Mathematical Sciences
MPS Directorate for Mathematical & Physical Sciences
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| NSF Program(s): |
STATISTICS |
| Field Application(s): |
Other nsf.applications NEC |
| Program Reference Code(s): |
UNASSIGNED, 0000 |
| Program Element Code(s): |
1269 |
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