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High-probability grants
According to our matching algorithm, Jeffrey J. Starns is the likely recipient of the following grants.
Years |
Recipients |
Code |
Title / Keywords |
Matching score |
2015 — 2020 |
Starns, Jeffrey |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Career: Modeling Response-Time Distributions to Test Theories of Event Memory @ University of Massachusetts Amherst
Memory for previously experienced events can take many forms, such as deciding whether a person's face was seen previously versus deciding where a person's face was seen previously. Different theories make different assumptions about how these various forms of memory come about. Whereas some theories assume that the ability to call to mind a prior experience is all-or-none (it either occurs or does not), other theories assume that bits of information accumulate in a continuous manner from less to more. Yet other theories assume that both an all-or-none ability to call something to mind and a process of continuously accumulating information co-exist, and either mechanism can underlie memory in a given situation (it is a matter of teasing them apart). Determining the true state of affairs is important for a number of reasons, including the development of appropriate methods for assessing eyewitness memory, the development of appropriate tools for assessing cognitive functions in cases of memory impairment, and the development of appropriate memory tasks for use in research on the neural underpinnings of memory.
This CAREER project by an early career stage investigator aims to differentiate among existing models of human event memory by imposing constraints not typically used by researchers. Previous modeling efforts have led to somewhat of an impasse regarding understanding human event memory because vastly different models are all able to accommodate human data patterns produced in empirical studies of how memory accuracy varies across experimental conditions. In addition to the typically-used accuracy measures of memory, this project will use response time measures to further constrain the data needing to be accommodated by the models in order to better force differentiation among the possible theoretical alternatives. Across a number of experiments, various experimental manipulations will be used in conjunction with these measures to provide even further constraints to help to rule models out and potentially identify a candidate model for how human event memory most likely operates. As part of the education component of the CAREER plan, the investigator will create a computational modeling concentration within the Psychology major, providing undergraduate students with a unique opportunity to develop cognitive modeling skills. He will also make the modeling tools from the research available to the research community via a website.
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