P300 Scalp amplitude distribution as an index of deception in a simulated cognitive deficit model

Rosenfeld, J. Peter; Ellwanger, Joel; Nolan, Kevin D.; Wu, Sally P. W.; Bermann, R. G.; Sweet, Jerry J.

doi:10.1016/s0167-8760(99)00021-5

Cited by 56 publications

(43 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Once again malingerers showed no difference between old and new items. In a review of existing studies in this area, Rosenfeld and Ellwanger (1999) theorized that the lack of difference in ERPs for different items in malingerers may be due to the increased workload that occurs when test-takers manipulate their responses (e.g. deliberately select incorrect answers).…”

mentioning

confidence: 99%

“…To date, several research publications have investigated the application of P300 and the pattern of visual evoked potentials to detection of malingered memory deficits, including reports by Ellwanger, Rosenfeld, Sweet & Bhatt (1996), Ellwanger, Tenhula, Rosenfeld & Sweet (1999), Rosenfeld, Ellwanger, Nolan, Wu, Bermann & Sweet (1999), Rosenfeld, Reinhart, Bhatt, et al (1998), Rosenfeld, Sweet, Chuang, Ellwanger & Song (1996), Tardiff, Barry, Fox & Johnstone (2000), Tardiff, Barry & Johnstone (2002). Results from these studies were somewhat mixed and limited in part by the relatively rare inclusion of a neurologic patient group answering honestly.…”

mentioning

confidence: 99%

See 1 more Smart Citation

New measures to detect malingered neurocognitive deficit: Applying reaction time and event-related potentials

Vagnini

Berry

Clark

et al. 2008

Journal of Clinical and Experimental Neuropsychology

View full text Add to dashboard Cite

The ability of the Test of Memory Malingering (TOMM), reaction times (RT) and Event-Related Potentials (ERP) to detect malingered neurocognitive deficit (MNCD) was examined in 32 normal individuals answering under honest (HON; n = 16) or malingering instructions (MAL; n = 16) as well as in 15 patients with Traumatic Brain Injury (TBI) who answered under honest instructions. Overall, the TOMM was the most effective at classifying groups. However, new accuracy, RT, and ERP measures reached promising hit rates in the range of 71%-88%. In particular, the difference in frontal versus posterior ERP obtained during an old-new task was effective at classifying MAL vs. TBI (hit rate = 87%).In the Diagnostic and Statistical Manual of Mental Disorders, IVth Edition, Text Revision (APA, 2000), malingering is defined as the deliberate fabrication or gross exaggeration of physical or psychological symptoms in pursuit of external goals such as avoiding duty or obtaining financial compensation. Malingering is distinguished from Somatoform Disorders in that in the latter, symptoms are not thought to be under voluntary control and are produced in pursuit of internal goals, such as resolving unconscious conflicts. Malingering is discriminated from Factitious Disorder in that in the latter, although symptoms are consciously produced, they appear to be in pursuit of internal goals such as achieving the sick role.Malingered symptoms have been of increasing concern in neuropsychological assessment because most cognitive tests require optimal effort from the evaluee in order to achieve results that accurately reflect brain functioning. In situations in which patients are being evaluated for disability pensions or monetary compensation for damages sustained in accidents, the potential motivation to exaggerate or even fabricate problems is obvious. In fact, surveys of forensic neuropsychologists have suggested that up to 40% of individuals undergoing evaluations following mild head injuries may be malingering deficits (Mittenberg, Patton, Canyock & Condit, 2002).Neuropsychologists have responded to this concern by developing and validating a number of tests for the identification of inadequate effort during neuropsychological examinations. Vickery et al. (2001) published a meta-analysis of widely studied malingering tests and found that most had large effect sizes, high specificity (percentage of honest patients correctly classified) and moderate sensitivity (percentage of feigners correctly classified). However, recently, concerns have been raised that unscrupulous parties to legal proceedings may be "coaching" plaintiffs to avoid being detected by commonly used malingering tests TOMM;Tombaugh, 1996), other approaches have explored aspects of the evaluee's responses that are under less conscious control, such as reaction time (RT) and brain activity using electroencephalograph (EEG). In general, these two approaches hypothesize that the physiologic markers of neural processes that are normally "automatic" in cooperative test-t...

show abstract

mentioning

confidence: 99%

mentioning

confidence: 99%

New measures to detect malingered neurocognitive deficit: Applying reaction time and event-related potentials

Vagnini

Berry

Clark

et al. 2008

Journal of Clinical and Experimental Neuropsychology

View full text Add to dashboard Cite

show abstract

“…Thus, the ERP signals were decomposed into details D1-D7 and one final approximation, A7. The detail coefficients D7, D6, D5 and approximation coefficients A7 were chosen as feature parameters, which respectively corresponded to theta (4-7 Hz), alpha (8-15 Hz), beta (16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31), and delta(0.5-4 Hz) rhythms. For each electrode, Fz, Cz and Pz, the WCs of 64 dimensions were obtained.…”

Section: Feature Extraction Based On Wavelet Transformmentioning

confidence: 99%

A New Approach for Concealed Information Identification Based on ERP Assessment

2011

View full text Add to dashboard Cite

Recently, numerous concealed information test (CIT) studies have been done with event related potential (ERP) for its sufficient validity in applied use. In this study, a new approach based on wavelet coefficients (WCs) and kernel learning algorithm is proposed to identify concealed information. Totally 16 subjects went through the designed CIT paradigm and the multichannel electroencephalogram (EEG) signals were recorded. Then, the high-dimensional WCs of ERP in delta, theta, alpha and beta rhythms were extracted. For the analysis of the data, kernel principle component analysis (KPCA) and a support vector machines (SVM) classifier are implemented. The results show that WCs features are significant differences between concealed information and irrelevant information (P < 0.05). The KPCA is able to effectively reduce feature dimensionalities and increase generalization performance of SVM. A high accuracy (93.6%) in recognizing concealed information and irrelevant information is achieved, which indicates the combination KPCA and SVM may provide a useful tool for detecting the concealed information.

show abstract

“…We still think it best for diagnostic bootstrap tests of simple amplitude at one site. However, in profile work, for both theoretical and empirical reasons, we use the standard base-to-peak index, although in one of our earliest studies (cited here as Rosenfeld et al, 1999) we used both methods, and Fig. 4 here is based on peak-to-peak values.…”

Section: About Here>mentioning

confidence: 99%

“…4 here is based on peak-to-peak values. The comparisons made across studies in this paper, with the exception of Rosenfeld et al, (1999), all used the base-to-peak method.…”

Section: About Here>mentioning

confidence: 99%

64 Event-related potentials in detection of deception

Rosenfeld¹

1998

International Journal of Psychophysiology

View full text Add to dashboard Cite

P300 Scalp amplitude distribution as an index of deception in a simulated cognitive deficit model

Cited by 56 publications

References 21 publications

New measures to detect malingered neurocognitive deficit: Applying reaction time and event-related potentials

New measures to detect malingered neurocognitive deficit: Applying reaction time and event-related potentials

A New Approach for Concealed Information Identification Based on ERP Assessment

64 Event-related potentials in detection of deception

Contact Info

Product

Resources

About