Recent deception detection approaches (e.g., lie detector tests) rely upon a brainwave sensitive to concealed information, such as a murder weapon at a crime scene, called the P3. Yet this concealed information approach does not apply in many circumstances where concealed information is important. For example, it has no screening potential. Therefore, researchers have begun to investigate other approaches that can use the P3 signal and that are sensitive to additional information such as attitudes, rather than just information about objects. However, important questions remain, such as how to elicit other brainwaves, which could enhance the accuracy of the test.

The primary intellectual merit of this project is its extension beyond prior concealed attitude studies. They advance the field by outlining both practical implementations and techniques for better understanding the basic neural processes of deception. Through use of a scenario known to elicit the memory-related brain wave and a brain wave for competing responses to deception, the research builds upon prior studies using brain signals to detect knowledge, extending them here to detect intentions.

These findings have important implications for law enforcement practice because, unlike other tests of concealed information, this test may be a useful security screening tool to detect when someone has an extreme attitude. Therefore this doctoral research project will contribute to detecting deception about attitudes and intentions, rather than objects. In addition, the research will be conducted at a Hispanic Serving Institution, thus potentially expanding opportunities for science research among members of underrepresented groups.

Project Report

Previous physiological detection studies have focused on memory-based applications (e.g., detecting knowledge of a stolen item), which have a strong theoretical basis but are largely impractical for legal authorities. The aim of the current study was to develop a brain-based measure for detecting individual attitudes (i.e., likes/dislikes). The detection of attitudes lends more readily to physiological detection given the close correspondence between attitudes and intentions (e.g., liking illicit drugs and therefore the intention to use them). Using a novel paradigm, the current brain-based classification scheme correctly identified 78% of participants' attitudes. This modest classification rate provides a starting point for researchers using physiological measures in the detection of attitudes. Taken together, the current paradigm has important screening implications. The current research had several important broader impacts. First, this research gave the co-P.I. opportunities to promote teaching and training of undergraduate students in scalp recorded brain signals. Second, the co-P.I. provided teaching and training to underrepresented Hispanic undergraduates. And third, this study enhanced the infrastructure of research helping establish collaborations with national institutions by allowing the co-P.I. to travel to conferences. Specifically, portions of this work were disseminated at the Psychonomic Society (October, 2013) and the Society for Psychophysiological Research conference (September, 2013).

National Science Foundation (NSF)
Division of Social and Economic Sciences (SES)
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Susan Sterett
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University of Texas at El Paso
United States
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