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Detecting Salient Information Using RSVP and the P3: Computational and EEG Explorations

Alsufyani, Abdulmajeed (2015) Detecting Salient Information Using RSVP and the P3: Computational and EEG Explorations. Doctor of Philosophy (PhD) thesis, University of Kent,. (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:50751)

Language: English

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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 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.

Item Type: Thesis (Doctor of Philosophy (PhD))
Uncontrolled keywords: Gulity Knowledge Test, The P300, lie detection
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Users 1 not found.
Date Deposited: 02 Oct 2015 11:00 UTC
Last Modified: 16 Feb 2021 13:28 UTC
Resource URI: (The current URI for this page, for reference purposes)
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