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Title: Detecting salient information using RSVP and the P3 : computational and EEG explorations
Author: Alsufyani, Abdulmajeed
ISNI:       0000 0004 5366 111X
Awarding Body: University of Kent
Current Institution: University of Kent
Date of Award: 2015
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This thesis investigates the efficacy of employing the Rapid Serial Visual Presentation (RSVP) technique for stimulus presentation in brain activity-based deception detection tests. One reason for using RSVP is to present stimuli on the fringe of awareness (e.g. 10 per second), making it more difficult for a guilty person to confound the test by use of countermeasures. It is hypothesized that such a rapid presentation rate prevents the vast majority of RSVP stimuli from being perceived at a level sufficient for encoding into working memory, but that salient stimuli will break through into consciousness and be encoded. Such ‘breakthrough’ perceptual events are correlated with a P300 Event Related Potential (ERP) component that can be used as an index of perceiving/processing a salient stimulus (e.g. crime-relevant information). On this basis, a method is proposed for detecting salience based on RSVP and the P300, which will be referred to as the Fringe-P3 method. The thesis then demonstrates how the Fringe-P3 method can be specialized for application to deception detection. Specifically, the proposed method was tested in an identity deception study, in which participants were instructed to lie about (i.e. conceal) their own-name. As will be shown, experimental findings demonstrated a very high hit rate in terms of detecting deceivers and a low false alarm rate in misdetecting non-deceivers. Most significantly, a review of these findings confirms that the Fringe-P3 identity detector is resilient against countermeasures. The effectiveness of the Fringe-P3 method in detecting stimuli of lower salience (i.e. famous names) than own-name stimuli was then evaluated. In addition, the question of whether faces can be used in an ERP-based RSVP paradigm to infer recognition of familiar faces was also investigated. The experimental results showed that the method is effective in distinguishing broadly familiar stimuli as salient, resulting in the generation of a detectable P300 component on a per-individual basis. These findings support the applicability of the proposed method to forensic science (e.g. detecting knowledge of criminal colleagues). Finally, an ERP assessment method is proposed for performing per-individual statistical inferences in deception detection tests. By analogy with functional localizers in fMRI, this method can be viewed as a form of functional profiling. The method was evaluated on EEG data sets obtained by use of the Fringe-P3 technique. Additionally, simulated data were used to explore how the method’s performance varies with parametric manipulation of the signal-to-noise ratio (SNR). As will be demonstrated, experimental findings confirm that the proposed method is effective for detecting the P300, even in ERPs with low SNR.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
Keywords: QA Mathematics (inc Computing science)