The application of subliminal priming in lie detection...

The application of subliminal priming in lie detection:

Scenario for identification of members of a terrorist ring

MING LUIa,b and J. PETER ROSENFELDa

aDepartment of Psychology, Northwestern University, Evanston, Illinois, USAbDepartment of Psychology, National University of Singapore, Singapore

Abstract

We studied a lie detection protocol immune to countermeasures. The 4 stimulus conditions were (1 and 2) supra-

liminal acquaintance name primed by subliminal acquaintance name (A-A) versus subliminal nonacquaintance name

(N-A) and (3 and 4) supraliminal nonacquaintance name primed by subliminal acquaintance name (A-N) versus

subliminal nonacquaintance name (N-N). In Experiment 1 and replication, principal components analysis-derived

event-related potential components revealed significant differences between dishonestly answered supraliminal

acquaintance conditions with differing primes (A-A vs. N-A). In Experiment 2 subjects were required to lie in A-N

and N-N conditions, in contrast to Experiment 1, in which subjects lied in A-A and N-A conditions. No significant

effects were found. In Experiment 3, the lying task was removed and no significant differences were found. We

conclude that subliminal primes modulate ERPs in conditions with supraliminal acquaintance name when the task

involves lying.

Descriptors: Cognition, Learning/memory, Unconscious processes, EEG/ERP

There is a recent growth of cognitive neuroscience studies in

deception using different experimental paradigms, including

mock crime scenarios (Kozel et al., 2005; Mohamed et al., 2006;

Lui & Rosenfeld, 2008), autobiographical information (Ganis,

Kosslyn, Stose, Thompson, & Yurgelun-Todd, 2003; Nunez,

Casey, Egner, Hare, & Hirsch, 2005; Spence et al., 2001), guilty

knowledge tests (Langleben et al., 2002, 2005), and malingering

tests (Lee et al., 2005). Past studies approached deception by

investigating the related cognitive processes, including attention,

memory, and response generation processes. For instance, a

piece of information that a person intends to lie about (guilty

information) is usually more attention catching. And one may

involuntarily and automatically retrieve the related contextual

memory when perceiving the guilty information. Lying is also

supposed to pose more demand on executive control than truth

telling (Johnson, Barnhardt, & Zhu, 2005). Before lying, one

must hold and manipulate competing pieces of truthful and

false information in working memory. To give a lying response,

one needs to suppress the prepotent truthful response. The in-

hibition (Falkenstein, Hoormann, Christ, & Hohnsbein, 2000;

Gehring, Goss, Coles,Meyer, &Donchin, 1993) andmonitoring

of response conflicts involves executive control (Botvinick,

Nystrom, Fissell, Carer, & Cohen, 1999; Carter et al., 1998).

Neuroimaging data supported the involvement of executive con-

trol brain regions in deception. In a recent study by Ganis and

colleagues, there were stronger activations in anterior prefrontal

cortices (bilaterally), parahippocampal gyrus (bilaterally), the

right precuneus, and the left cerebellum in the lying compared to

truth-telling conditions. Enhanced activations in the anterior

cingulate cortex (ACC) and the superior frontal gyrus were also

found in another fMRI deception study (Langleben et al., 2002).

It is believed that that there is no specific brain region or

electrophysiological marker responsible for lying alone; rather,

there is a combination of emotional and cognitive processes re-

lated to lying. The present study aimed at developing a paradigm

to detect lies by capturing the lie-related memory processes at the

individual level.

Past ERP Studies on Deception

Many previous event-related potential (ERP) studies of decep-

tion focused on the P300 component. The P300 is a positive-

going component that occurs between 300 and 800 ms after

stimulus onset. It is an endogenous ERP component related to

meaningfulness and rareness of stimuli (Donchin &Coles, 1988).

In previous studies of deception, diagnoses depended upon the

comparison of the P300 amplitude in response to meaningful ver-

sus to other (irrelevant) stimuli on the assumption that the former

have more salience than the latter (Allen, Iacono, & Danielson,

1992; Farwell & Donchin, 1991; Rosenfeld, Angell, Johnson, &

Qian, 1991; Rosenfeld et al., 1988). These P300-based tests are

This research was supported by the Department of Defense Poly-

graph Institute Grants DODP198-P-0001 and DoDPI04-P-0002

awarded to J. Peter Rosenfeld. We thank Andreas Keil and an anon-

ymous reviewer for excellent suggestions regarding an earlier draft of this

report.Address reprint requests to: Dr. Ming Lui, Department of Psy-

chology, National University of Singapore, SG117570, Singapore.E-mail: [email protected]

Psychophysiology, 46 (2009), 889–903. Wiley Periodicals, Inc. Printed in the USA.Copyright r 2009 Society for Psychophysiological ResearchDOI: 10.1111/j.1469-8986.2009.00810.x

889

based on the fact that a rarely presented item of concealed,

meaningful information, a probe, which is recognized by the

subject (even if behaviorally denied), will elicit the familiar P300

response, whereas other, frequently presented and nonmeaning-

ful items of information (irrelevants) will not elicit an increased

P300 (Donchin&Coles, 1988). Only guilty subjects are supposed

to show a significant difference between the guilty (probe) and

nonguilty (irrelevant) conditions.

Countermeasure to Lie Detection and the Use of

Subliminal Stimuli

Nevertheless, recent studies (Mertens & Allen, 2008; Rosenfeld,

Soskins, Bosh, & Ryan, 2004) found successful countermeasures

to this lie detection paradigm. A countermeasure is anything a

subject attempts to do during the test that tends to prevent the

detection of concealed information (Honts, Devitt, Winbush, &

Kircher, 1996). The countermeasure studies have involved train-

ing subjects to make concealed responses (e.g., wiggling the toe)

to the nonmeaningful items, which significantly increased the

P300 response to these irrelevant stimuli, and, therefore, no

difference was found between guilty and irrelevant stimulus con-

ditions. This makes it virtually impossible to distinguish probe

and irrelevant P300s, whose differences would otherwise be usu-

ally diagnostic for deception.

An obviously important requirement of physiologically based

methods for identifying deception is that such methods be resis-

tant to subjects’ attempts to defeat them, that is, with counter-

measures. In view of this, subliminal stimuli are here proposed to

be used in lie detection because they should be immune to coun-

termeasure use: If a key stimulus is presented subliminally, be-

cause it cannot be consciously perceived, subjects would not be

able to apply specific countermeasures to it. The current study

uses the paradigm of subliminal priming. Priming is a phenom-

enon of faster and more accurate response to stimuli that have

had prior exposure (e.g., Tulving & Schacter, 1990). Priming of

semantically related and unrelated words was found tomodulate

the amplitude and duration of ERP components (e.g., Besson,

Kutas, & van Petten, 1992). In the present study, a priming test

stimulus is presented subliminally prior to a supraliminally pre-

sented stimulus that evokes an ERP. It is expected that the sub-

liminal presentation of key test stimuli subliminally processed

uniquely by guilty subjects will affect ERP responses to the su-

praliminally presented stimuli in such a way as to allow discrim-

ination of guilty versus innocent subjects. (However, another

novel approach to P300-based deception detection which is re-

sistant to countermeasures was recently reported by Rosenfeld

et al. (2008).)

Outline of the Present Study

We attempt here to model a lie detection test for someone sus-

pected of being a terrorist, the aim being to identify members of a

terrorist ring. If stimuli were names of other terrorists in the

secret ring, only fellow terrorists (guilty subjects) should show a

difference of brain response between terrorists’ names and non-

terrorists’ names. In our study, college students were recruited

as subjects, and stimuli were supraliminal acquaintance names

preceded by a different subliminal acquaintance name versus a

nonacquaintance name. Other stimuli were supraliminal nonac-

quaintance names preceded by a subliminal acquaintance name

versus a different subliminal nonacquaintance name. It was

hypothesized that the subliminal priming of acquaintance and

nonacquaintance names would modulate ERP amplitude. Given

that task demand was found tomodulate subliminal priming in a

previous study (Nakamura et al., 2006), the current study ex-

amined the effect of the task demand associated with lying on

subliminal priming. It is hypothesized that lying would orient

subjects’ sensitivities toward the familiarity of the names, which

would increase the ERP difference between conditions primed

with acquaintance versus nonacquaintance names.

In this study, there were five groups of participants. Two of

these (Experiment 1 and the replication study) are near replica-

tions of each other and attempt to demonstrate a specific sub-

liminal priming effect during deception. Two other groups

(Experiments 2 and 3) were intended to control for two differing

respective effects that do not involve subliminal priming or

deception, but which could mediate putative priming effects in

Experiment 1 and its replication. The fifth groupwas an innocent

(nondeceptive) control group that allowed us to estimate the false

positive rate. We note that the groups were actually run in the

following order: Experiment 1, Experiment 2, Replication of 1,

Experiment 3, and, finally, the innocent group.

EXPERIMENT 1

Method

Participants

Fourteen (average age: 19.3 years, 9 men) Northwestern Uni-

versity undergraduate students participated in the present study

for the fulfillment of an introductory Psychology course require-

ment. They were all right-handed and had normal or corrected

vision. All signed an Institutional Review Board (IRB)-approved

consent form.

Procedures

Subjects were first asked to provide the last names of five people

they knew very well. They were also asked to select 4 names from

a list of 20 last names that did not have any personal meaning to

them. These 5145 9 names were the stimuli they would view

subliminally and supraliminally on the ERP test (see Table 1a).

They sat about 1 m from a computer screen. On the screen, brief

(subliminal) and long (supraliminal) presentations of last names

and symbols were shown. As shown in Figure 1 (trial structure),

in each trial, a name appeared on screen for 17 ms (subliminal),

preceded by a 100-ms forward mask and followed by a 17-ms

890 M. Lui and J.P. Rosenfeld

Table 1a. Experiments 1 and 3 Stimulus Arrangement and Response Requirement

Condition Symbol Subliminal prime Supraliminal target Expt. 1 task Expt. 3 task (half of the subjects)

1 A-A Acquaintance Acquaintance No Right2 N-A Nonacquaintance Acquaintance No Right3 A-N Acquaintance Nonacquaintance No Right4 N-N Nonacquaintance Nonacquaintance No Right5 Asterisks Acquaintance Yes Left

backward mask composed of symbols ‘‘$$##$$##$$##$$.’’

These were followed by another name, which appeared for

150 ms (supraliminal). Subjects were asked to respond to the

supraliminally presented names with a ‘‘yes’’ or ‘‘no’’ button

press. They were told that ‘‘yes’’ means ‘‘I DO know a person by

this name,’’ and ‘‘no’’ means ‘‘I DONOT know a person by this

name.’’ In the ERP collection session, subjects were instructed to

choose only one of the supraliminally presented acquaintance

names to respond truthfully to by pressing the ‘‘yes’’ button. For

the other four acquaintance names, they denied knowing themby

pressing the ‘‘no’’ button. For the 4 nonacquaintance names they

selected from the list, they responded truthfully by pressing the

‘‘no’’ button. They were asked to respond as soon as they could

following the supraliminal stimulus.

There were five stimulus-response conditions with different

response requirements and stimulus arrangements (see Table 1a)

in this first experiment and the replication: (1) supraliminal

acquaintance name preceded/primed by subliminal acquaintance

name (A-A), (2) supraliminal acquaintance name preceded/

primed by subliminal nonacquaintance name (N-A), (3) supra-

liminal nonacquaintance name preceded/primed by subliminal

acquaintance name (A-N), (4) supraliminal nonacquaintance

name preceded/primed by subliminal nonacquaintance name

(N-N), and (5) supraliminal acquaintance name preceded by as-

terisks, with no priming (this was simply an attention forcing

condition). Again, subjects responded ‘‘no’’ to the first four

conditions, but ‘‘yes’’ to the fifth. The stimuli were ordered in a

way such that no exact repetition occurred in a single trial. That

is, in conditions (A-A) and (N-N), the subliminal prime and

supraliminal target were always different even though they were

both acquaintance or nonacquaintance names (i.e., the priming

was ‘‘conceptual’’). Condition 5 served as a condition to main-

tain subjects’ attention by varying the response requirement

(‘‘yes’’ instead of ‘‘no,’’ which was the response in the other four

conditions); the data from this conditionwere not included in any

analysis. There were 20 practice trials and 360 actual trials, with

80 trials in each of the Conditions 1–4 and only 40 trials for

Condition 5.

After all the experimental trials, subjects were given an

awareness test (see below) to check the visibility of the subliminal

stimuli in individual subjects. Stimuli were similar to those in the

experimental trials except the subliminal stimuli were either non-

sense character strings (e.g., dfgiaesfr) or acquaintance names.

Subjects were required to do a lexical decision task by deciding

whether the subliminal stimuli were words or nonwords. Before

the awareness test each subject was also asked whether he/she

saw any of the subliminal stimuli, and their subjective reports

were recorded. In the awareness test, subjects were given

10 practice trials and 120 actual trials.

In subsequent material, because the data from the five groups

are meant to be compared, some methods used for all five

experiments are described together.

Statistical Analysis Procedures: PCA and BootstrappingMethods

(Used in All Five Experiments)

Spatial principal component analysis (PCA) on various sites on

the scalp is amethod utilized to identify clusters of electrodes that

are highly intercorrelated. It linearly combines the highly corre-

lated electrodes to form a virtual component or factor. The

component or factor yields the ‘‘virtual site’’ data to be used in

later analyses. This has the advantage of capturing most of the

relevant variance and therefore preserving the information from

the many actual electrodes, and at the same time reducing the

redundancy among them (Spencer, Dien, & Donchin, 2001).

Additionally, the linear combination method of PCA can pro-

duce orthogonal factors. Follow up, temporal PCA uses the same

principles except that the virtual temporal components are

formed by grouping of highly intercorrelated time point data

within each spatial component.

Subliminal priming in lie detection 891

Table 1b. Experiment 2 Stimulus Arrangement and Response

Requirement

Condition SymbolSubliminal

primeSupraliminal

targetExpt. 2task

1 A-A Acquaintance Acquaintance Yes2 N-A Nonacquaintance Acquaintance Yes3 A-N Acquaintance Nonacquaintance Yes4 N-N Nonacquaintance Nonacquaintance Yes5 Asterisks Nonacquaintance No

$$##$$##$

$$##$$##$

Baseline Recording

104 ms

100 ms

17 ms

EEG Epoch2048 ms

Yes or NoResponse

1660 ms

Mask

Mask

17 ms

150 ms

SubliminalName

SupraliminalName

Figure 1. Timing of mask and stimulus presentations in a single ERP epoch.

The present PCA data sets were obtained from an average

of ERPs at each time point within a given window of all trials of

the same stimulus type. First, spatial factors were extracted by

Varimax rotation, which produces factors with high loadings on a

small number of variables and low loadings on other variables

(Kaiser, 1960). Also, factors remain uncorrelated after Varimax

rotation, which prevents the problem of multicollinearity among

factors. Standardized factor loadings were the correlations be-

tween a variable (original site) and its corresponding factor (vir-

tual electrode). A site variable was selected only if its factor

loading exceeded 0.6 and if such a high loading for this site vari-

able was restricted to one factor. The factor scores were formed

by summing the site values multiplied by respective factor score

coefficients (Spencer et al., 2001). The spatial ERP components

were then subjected to a subsequent temporal PCA. For each

individual subject, spatial temporal components were formed

from the factor loadings obtained from the group spatial tem-

poral PCA. The spatial temporal components were first analyzed

by multivariate analysis of variance (ANOVA) on group data

with appropriate follow-up analysis to localize effects. The spa-

tial-temporal PCA andANOVAswere donewith SPSS software.

Individual diagnoses using bootstrapping procedures and

t tests on spatial-temporal components followed. A bootstrap-

ping procedure was applied to the spatial temporal components

in each individual. For example, assume there were x and y trials

in Conditions 1 and 2, respectively, in one subject. X and y trials

were drawn randomly (with replacement) from the actual pool of

spatial temporal component data in each of the Conditions,

1 and 2 separately and respectively, and an ERP average was

calculated for each randomly selected trial set within each con-

dition. The random selection process is repeated 100 times to get

100 sets of bootstrapped averages in each trial set. The boot-

strapping and averaging procedure was done with a MATLAB

script written by the first author. T tests were then applied to test

possible amplitude differences between mean amplitudes of

bootstrapped distributions for various pairs of conditions.

We note that in these experiments, PCAs were performed on

databases developed in two ways: (1) Within-study PCA: Each

group in each experiment yielded one data set for all conditions

within that specific experiment. (2) Combined PCA: Data from

all five groups were combined into one database, and a single set

of spatial-temporal components was determined for all studies.

The first method allows analyses optimized for each group, and

the variance source is principally the condition differences within

the group. The secondmethod allows differences between groups

as well to be a source of variance. It was found that the com-

bined-PCAmethod did not perform better than the within-study

PCA method in group analyses and in individual diagnoses. We

therefore report the statistical results of the within-study PCA

only hereafter.

Electroencephalogram Recordings (All Five Groups)

The electroencephalogram (EEG) data were referentially re-

corded from 30 tin electrodes in an Electrocap (Electrocap

International, Inc). The reference electrode was put on the nose

tip, with the forehead connected to the chassis of the isolated side

of the amplifier system (ground). A 0.3-Hz high-pass and a

30-Hz low-pass filter were used (Contact Precision Instruments

EEG 8 system). The sampling rate was at 125 Hz, and the EEG

signal was amplified by a factor of 50,000. Electrooculogram

(EOG) was recorded differentially from two electrodes diago-

nally placed above and below the left eye, so as to monitor both

vertical and horizontal eye movement. Trials containing 80 mVor

more deflections in the EOG electrodes were automatically re-

jected (without subject’s knowledge). Also, off-line visual in-

spection was done on individual trials to remove trials with

especially subtle eyemovement artifacts. All electrode resistances

weremaintained at or below 5 kO. As shown in Figure 1, all trials

began with a 104-ms baseline recording window, followed by a

forward mask (100 ms), a subliminal name (17 ms), a backward

mask (17 ms), a supraliminal name (150 ms), and a response

window (1660 ms). The length of an epoch was 2048 ms. The

latencies of ERPs in analyses were timed from the onset of the

subliminal stimulus, as we presumed that the ERP elicited by

supraliminal stimulus would be affected by the preceding sub-

liminal stimulus.

For all group analyses and displays, single sweeps and aver-

ages were digitally filtered off-line to remove higher frequencies;

3 db point5 4.23 Hz. Separate sets of group analyses were done

on 10-Hz low-pass data. No significant effects were found.1 We

therefore report only the analysis results of the 4.23-Hz low-pass

data in the result session.

Results

Behavioral

All subjects responded correctly (i.e., pressing ‘‘yes’’ to Condi-

tion 5 stimuli and pressing ‘‘no’’ to all others) in more than 97%

of trials. There was no significant difference in mean reaction

times between all conditions (p4.05).

Awareness Test

The d0 indices ranged from � .32 to 1.38. Chi-squared test

showed that only 1 out of the 15 subjects had a significant

difference in response to word and nonword conditions

(w2 5 5.17, p5 .023). This awareness test result was also consis-

tent with the subject’s subjective report. The subject’s data were

excluded from further analysis.

ERP Data and PCA

Figure 2 shows a graphical illustration of the ERP (pre-PCA)

grand averages of 4 (Fz, Cz, Pz, and Oz) out of 30 electrode sites

for Experiment 1. For the within-study PCA in Experiment 1, a

covariance-based PCA was applied on the 30-sites data from 0

ms to 1396 ms after stimulus onset for extraction of spatial

components. The data matrix consisted of 30 (number of elec-

trodes) � 4 (number of conditions) � 176 (number of time

points per trial) � 14 (number of subjects) cases. The spatial

PCA extracted four spatial components (accounting for 88.3%

of the variance): frontal-central-parietal (34.6%), occipital-

parietal (31.4%), frontal (14.7%), and prefrontal (7.8%). The

actual sites included in each component were (1) frontal-central-

parietal component (FCP: Pz, C3, P3, Fz, Fc1, Fc5, Cp1, Cp5,

C4, Cz, Fc2, Cp2), (2) occipital-parietal component (OP: O1, P7,

Oz, P4, O2, P8, Cp6), (3) frontal component (F3, F7, Af3, F4, F8,

Fc6) and (4) prefrontal component (Fp2, Fp1, Af4). It is noted


1In previous P300 studies, low-pass filterwas usually set lower than 10Hz. For instance, Fabiani, Gratton, Karis, and Donchin (1987) filtered(low-passed) P300 averages at 6.29 Hz and single sweeps at 3.13 Hz. Webelieved that the main ERP component that revealed the difference be-tween conditions in the current study was the P300, which has a meanfrequency under 2 Hz (Duncan-Johnson & Donchin, 1979). The inclu-sion of high frequency noise in 10 Hz low-pass datamay have diminishedthe P300 effect.

that components have names in common (e.g., frontal, central)

but these components have different actual electrodes contrib-

uting to the component. A temporal PCAwas then performed on

the four spatial component data. The temporal PCA resulted in

five temporal components (accounting for 91.39% of the vari-

ance): 36–324 ms (12.4%), 332–516 ms (20.2%), 524–668 ms

(13.4%), 676–908 ms (16.1%), and 916–1396 ms (29.4%).

Group ERP Analysis and Individual Diagnosis

Table 2a–d shows the analytic results for the components ex-

tracted with the within-study PCA. In each of the five temporal

components, a separate multivariate analysis of variance

(MANOVA) was done. In each MANOVA, the four spatial

components were four dependent variables. Condition (i.e., the

stimulus–response condition) was the independent variable. The

omnibus MANOVAs showed that the effect of condition was

significant in the following temporal components: (1) 332–516

ms: Wilks’ l5 .48, F(12,96)5 2.59, p5 .005; (2) 524–668 ms:

Wilks’ l5 .38, F(12,96)5 3.55, po.001; (3) 916–1396 ms:

Wilks’ l5 .47, F(12,96)5 2.61, p5 .005 (see Table 2a).

For the component 332–516 ms, the effect of condition was

significant in all spatial components (po.05). However, Bon-

feronni pairwise comparisons showed no other significant differ-

ences between any meaningful pairwise comparisons excepting a

marginal p value for the OP component (see Table 2c).


significant in the frontal-central-parietal, F(3,39)5 10.12,

po.001, and occipital-parietal, F(3,39)5 14.43, po.001, spatial

components. Bonferroni pairwise comparison showed that

Condition 2 (N-A) was significantly more positive than Condi-

tion 1 (A-A) for the frontal-central-parietal component

(p5 .035) and the occipital-parietal component (po.001).

Because the conservative Bonferonni tests revealed some signifi-

cant pairwise group differences at 524–668 ms, we did individual


–200 0 200 400 600 800 1000 1200 1400

–5

0

5

10

ms

mic

ro-v

olts

FZ–5

0

5

10

CZ

–5

0

5

10

mic

ro-v

olts

PZ–5

0

5

10

OZ

–200 0 200 400 600 800 1000 1200 1400

–200 0 200 400 600 800 1000 1200 1400–200 0 200 400 600 800 1000 1200 1400

mic

ro-v

olts

mic

ro-v

olts

ms

msms

Figure 2. Experiment 1 raw (pre-PCA) grand averages from 4 of the 30 actual sites.

Table 2a. Experiment 1 Omnibus MANOVAs: Main Effect of

Condition

Temporal component (ms)

36–324 332–516 524–668 676–908 916–1396

Wilk’s l .615 .475 .377 .683 .473Fstatistic 1.607 2.587 3.545 1.236 2.607p .103 .005nn .000nn .270 .005nn

Note: Results based on within-study PCA-extracted components.nnpo.01.

Table 2b. Experiment 1 Univariate ANOVAs p Values


36–324 332–516 524–668 676–908 916–1396

FCP .319 .022n .000nn .493 .017n

OP .011n .028n .000nn .079 .014n

F .589 .047n .049n .914 .629Pre-F .534 .009nn .043n .764 .813

Note: Results based on within-study PCA-extracted components. FCP:frontal-central-parietal component; OP: occipital-parietal component; F:frontal component; Pre-F: prefrontal component.npo.05, nnpo.01.

diagnoses in these cases (and also in some other near significant

cases in Table 2c): Bootstrapping of amplitude difference was

done between Condition 1 (A-A) and Condition 2 (N-A). Table

2d shows that 11 of 14 (78.6%) subjects have significantly more

positive frontal-central-parietal amplitude for Condition 2

(N-A) than for Condition 1 (A-A), whereas 12 out of 14 (85.7%)

subjects had significantly more positive occipital-parietal ampli-

tude for Condition 2 (N-A) than for Condition 1 (A-A). It is

noted that for A-N versus N-N, no Bonferonni tests were sig-

nificant, so no follow-up individual diagnostics were performed.


significant only in the frontal-central-parietal, F(3,39)5 3.83,

p5 .017, and the occipital-parietal,F(3,39)5 3.99, p5 .014) com-

ponents. Bonferroni pairwise comparison showed that Condition

2 (N-A) was significantly more positive than Condition 1 (A-A)

for the occipital-parietal (p5 .026) but not for the frontal-

central-parietal component. Bootstrapping of amplitude differences

was done on the occipital-parietal component. Table 2d shows that

11 out of 14 subjects (78.6%) had significantly more positive

amplitude in Condition 2 (N-A) than in Condition 1 (A-A).

Discussion and Introduction to the Replication Study

The results of the first experiment revealed dramatic subliminal

priming effects reaching diagnostic utility levels. Experiments

2 and 3 below were directed at controlling and investigating

possible confounding factors, but it seemed important to us to

be able to replicate the results in the original study. Therefore,

Experiment 1 was replicated as fully as possible in a new group of

subjects. In the replication, the procedures were similar to those

in Experiment 1, except that the new subjects were asked to pick

4 names from a pool of 100 names rather than only 20 names as

in Experiment 1. Another difference was that subjects were asked

to pick nonacquaintance names that had equal numbers of syl-

lables as the acquaintance names they had written down. The

stimulus arrangements, procedures, and task requirements were

otherwise identical to those in Experiment 1.

REPLICATION STUDY

Results

PCA Results

The spatial, within-study PCA in this replication extracted three

spatial components (accounting for 90.7% of the variance):

frontal-central-parietal (38.3%), occipital-parietal (31.5%), and

frontal (20.9%). The actual sites included in each components

were frontal-central-parietal (Cp1, C3, Cz, Fc1, Cp2, Pz, Fc2,

C4, Cp5, P3, Fc5), occipital-parietal (O2, Oz, O1, P7, P4, Cp6),

and frontal (Fp2, Af4, F8, Fp1, Af3, F4, Fz, F3, Fc6). This

result was very similar to that of Experiment 1 (see above). A

temporal PCA was then performed on the three spatial compo-

nent data. The temporal PCA resulted in four temporal compo-

nents (accounting for 87.9% of the variance): 12–316 ms

(20.6%), 324–508 ms (27.5%), 588–796 ms (15.4%), and 804–

1396 ms (24.4%). This was also similar, though not identical, to

the results of the original study, Experiment 1 (see Figure 3).

Behavioral RT Data

The mean reaction time in the replication was 438.45 ms, almost

identical to the value from Experiment 1 at 435.77 ms. There

were no differences among conditions.

Awareness Test

The d0 indices ranged from � .40 to 1.30, and no significant

results were found in the chi-squared tests (all p4.05), showing

that subjects could not discriminate subliminal words from sub-

liminal nonwords.

ERP Data

The grand average ERPs for the two spatial components and two

condition contrasts are shown in Figures 4 and 5 along with data

from other experimental groups. Table 3a–d shows the detailed

analysis results for the replication, just as for Table 2a–d for

Experiment 1. Only the 588–796-ms temporal component at

FCP shows a significant Bonferonni result: Again, Condition 2

(N-A) was found to be significantly more positive than Condi-

tion 1 (A-A) whereas no difference was found between Condi-

tions 3 (A-N) and 4 (N-N). This time the significant difference

was restricted to the 588–796-ms temporal component of the

frontal-central-parietal spatial component (p5 .032). This com-

pares reasonably, given slight procedural differences (see above)

and a new subject sample, to the result found in the same spatial

component in the original study, which had a slightly earlier

temporal component at 524–668 ms. In individual diagnosis, 12

out of 14 (85.7%) of the subjects had significantly more positive

N-A than A-A conditions. (It is also the case that, in the Ex-

periment 1, the occipital-parietal component additionally

showed significant pairwise effects that were not observed in

the replication.)

EXPERIMENT 2

As we reported above, in Experiment 1, no priming effect was

found in conditions with supraliminal nonacquaintance names

(Condition 3 and Condition 4 in Table 1a). Because in Exper-

iment 1, subjects were lying in Conditions 1 (A-A) and 2 (N-A),


Table 2c.Experiment 1 Bonferroni Tests: Condition 1 (A-A) versus

Condition 2 (N-A)


36–324 332–516 524–668 676–908 916–1396

FCP 1.000 .673 .035n 1.000 .506OP .065 .056 .000nn .051 .026n

F 1.000 1.000 1.000 1.000 1.000Pre-F 1.000 1.000 1.000 1.000 1.000

Note: Results based on within-study PCA-extracted components. FCP:frontal-central-parietal component; OP: occipital-parietal component;F: frontal component; Pre-F: prefrontal component.npo.05, nnpo.01.

Table 2d. Experiment 1 Individual Diagnosis Based on A-A

versus N-A

Temporalcomponent (ms) Spatial component Detection rate

524–668 frontal-central-parietal 11/14 (78.6%)524–668 occipital-parietal 12/14 (85.7%)916–1396 occipital-parietal 11/14 (78.6%)332–516 occipital-parietal 11/14 (78.6%)676–908 occipital-parietal 10/14 (71.4%)

conditions with supraliminal acquaintance names, but telling the

truth in Conditions 3 (A-N) and 4 (N-N), conditions with su-

praliminal nonacquaintance names, two possible, non-mutually-

exclusive explanations for the findings are viable: It could be that

lying is necessary to get the effect, which occurs when the subjects

say ‘‘no’’ to supraliminal acquaintance names but not to non-

acquaintance names. However, it may also be the case that less

familiar supraliminal nonacquaintance names are not primed. To

investigate these possibilities, in Experiment 2, the response re-

quirement was reversed: subjects lied in conditions with supra-

liminal nonacquaintance names rather than in conditions with

supraliminal acquaintance names. The attention demanding

condition (Condition 5) was also a supraliminal nonacquain-

tance name (see Table 1b). It was predicted that no priming effect

would be found in conditions with supraliminal nonacquaintance

names (A-N and N-N) due to the lack of familiarity and long-

term memory representation for nonacquaintance names.

Methods

Participants

Thirteen (average age: 19.2 years, 7 men) Northwestern Uni-

versity undergraduate students who were not in Experiment 1

participated in Experiment 2 for the fulfillment of an introduc-

tory Psychology course requirement. They were all right-handed

and had normal or corrected vision. All signed an IRB-approved

consent form.

Stimuli and Procedures

The timing and construction of stimuli were similar to that in

Experiment 1 except that the attention catching condition was a

nonacquaintance name instead of an acquaintance name (see

Table 1b). Subjects were required to press ‘‘yes’’ to all conditions

and ‘‘no’’ to one of the nonacquaintance names they chose. In

that way subjects were lying to the conditions with supraliminal

nonacquaintance names (Conditions 3 and 4), and they were

telling the truth to conditions with supraliminal acquaintance

names (Conditions 1 and 2).

Results

Behavioral Data

All subjects responded correctly to over 95% of trials. There was

no significant difference in reaction times among all conditions.

Awareness Test

The d0 indices ranged from � .34 to 1.31, and no significant

results were found in the chi-squared tests (all p4.05), showing

that subjects could not discriminate subliminal words from sub-

liminal nonwords.

PCA

A covariance-based, within-study PCA was applied on the 30-

sites data from 0ms to 1396ms after stimulus onset for extraction

of spatial components. The data matrix consisted of 30 (number

of electrodes) � 4 (number of conditions) � 176 (number of

time points per trial) � 13 (number of subjects) cases. The spa-

tial PCA extracted three spatial components (accounting for

88.7% of the total variance): frontal-central-parietal (36.8%),

occipital-parietal (31.2%), and frontal (20.7%). The actual sites

included in each components are frontal-central-parietal (Pz, C3,

P3, Fc1, Fc5, Cp1, Cp5, C4, Cz, Fc2, Cp2), occipital-parietal

(O1, P7, Oz, P4, O2, T8, P8, Cp6), and frontal (F3, F7, Fz, Af3,

Fp2, F4, F8, Fp1, Af4, Fc6). A temporal PCA was then per-

formed on the three spatial component data. The temporal PCA

resulted in six temporal components (accounting for 93.7% of

the variance): 0–236 ms (16.5%), 244–340 ms (5.4%), 348–556

ms (25.7%), 564–732 ms (17.2%), 740–1060 ms (16.2%), and

1068–1396 ms (12.8%). The spatial components found in Ex-

periment 2 are similar to those found in Experiment 1 except that

the prefrontal sites (which were grouped to a separate prefrontal

component in Experiment 1) were included in the frontal com-

ponent in Experiment 2. For the temporal PCA, Experiments 1

and 2 obtained similar first two components (see Figure 3), but

the later temporal component structure appears different.

Group Analysis and Individual Diagnosis

Figures 4 and 5 show that, for both the FCP and OP spatial

components, differences between waveforms are restricted to

later portions on the epoch, after 700 ms. In each of the six


Figure 3.Diagram indicating statistical significance in different temporal regions. Time 0 is the subliminal stimulus onset. The areas

shaded in black are temporal regions with significant effects among experimental conditions. Significant effects were only found in

Experiment 1 and the replication study.

temporal components, separate MANOVAs were done as de-

scribed previously for Experiment 1 and its near replication. In

each MANOVA, the three spatial components were three de-

pendent variables, condition was the independent variable. The

omnibusMANOVAs showed that the effect of conditionwas not

significant in any analyses. No significant effects were found in

univariate ANOVAs. Therefore no further analysis was done.

Discussion

Results indicated that the effect of subliminal priming was

absent even when subjects lied in conditions with supraliminal

nonacquaintance names (i.e., A-N and N-N). The lack of long-

term memory representation for nonacquaintance names possi-

bly prevented priming from taking effect (discussed further

below). Moreover, when subjects were instructed to tell the truth

in conditions with supraliminal acquaintance names (i.e., A-A

andN-A), the effect of subliminal priming found inExperiment 1

disappeared. Lying is therefore not sufficient to produce the

subliminal priming effects seen in Experiment 1 and its replica-

tion. But lying may be necessary to produce the effect. Exper-

iment 3 was intended to test this hypothesis, by replicating the

conditions of Experiment 1 except with the lying behavior

removed.


AA vs NA AN vs NN

Expt 1

0 500 1000 1500

–15

–10

–5

0

5

10

15

20

msm

icro

-vol

ts

Replication

Expt 2

Expt 3 Frontal-Central-Parietal

mic

ro-v

olts

mic

ro-v

olts

mic

ro-v

olts

mic

ro-v

olts

mic

ro-v

olts

mic

ro-v

olts

mic

ro-v

olts

–15

–10

–5

0

5

10

15

20

–15

–10

–5

0

5

10

15

20

–15

–10

–5

0

5

10

15

20

–15

–10

–50

510

15

20

–15

–10

–5

0

5

10

15

20

–15

–10

–5

0

5

10

15

20

–15

–10

–5

0

5

10

15

200 500 1000 1500

0 500 1000 1500

0 500 1000 1500

0 500 1000 1500 0 500 1000 1500

0 500 1000 1500

0 500 1000 1500

ms

msms

ms ms

msms

Frontal-Central-Parietal

Frontal-Central-ParietalFrontal-Central-Parietal

Frontal-Central-Parietal Frontal-Central-Parietal

Frontal-Central-ParietalFrontal-Central-Parietal

Figure 4. ERPs of the frontal-central-parietal component in Experiments 1–3 and the replication study.

EXPERIMENT 3

Lying was removed in this experiment; hence the possible mod-

ulation of task requirement (i.e., deception) on stimulus-driven

subliminal priming effects could be observed by comparing the

results of Experiments 1 and 3.With the elimination of the lying

task and the associated meaning of lies, in Experiment 3 we

expected that the processing of acquaintance and nonacquain-

tance names would be different and the subliminal priming

effect would be attenuated. No difference was expected between

Conditions 1 (A-A) and 2 (N-A), and no difference was ex-

pected for the comparison between Conditions 3 (A-N) and

4 (N-N).

Methods

Participants

Twelve (average age: 19.3 years, 6 men)NorthwesternUniversity

undergraduate students who were not in Experiment 1 or 2 par-

ticipated in Experiment 3 for the fulfillment of an introductory

Psychology course requirement. They were all right-handed and

had normal or corrected vision. All signed an IRB-approved

consent form.


The timing and construction of stimuli were identical to that in

Experiment 1 except that subjects were required to press a right


Expt 1

0 500 1000 1500

–15

–10

–5

0

5

10

15

20

msm

icro

-vol

ts

AA vs NA AN vs NNOccipital-Parietal Occipital-Parietal

Replication

Expt 2

Expt 3

Occipital-Parietal Occipital-Parietal

Occipital-ParietalOccipital-Parietal

Occipital-Parietal Occipital-Parietal

ms

msms

ms ms

msms

mic

ro-v

olts

mic

ro-v

olts

mic

ro-v

olts

mic

ro-v

olts

mic

ro-v

olts

mic

ro-v

olts

mic

ro-v

olts

–15

–10

–5

0

5

10

15

20

–15

–10

–5

0

5

10

1520

–15

–10

–5

0

5

10

15

20

–15

–10

–5

0

5

10

15

20

–15

–10

–5

0

5

10

15

20

–15

–10

–5

0

5

10

15

20

–15

–10

–5

0

5

10

1520

0 500 1000 1500

0 500 1000 15000 500 1000 1500

0 500 1000 1500 0 500 1000 1500

0 500 1000 15000 500 1000 1500

Figure 5. ERPs of the occipital-parietal component in Experiments 1–3 and the replication study.

button to all conditions and to press a left button to one of the

acquaintance names which they chose (see Table 1a). (The left/

right key assignment was counterbalanced across subjects.) That

is, there were no ‘‘yes’’ and ‘‘no’’ buttons, just ‘‘right’’ and ‘‘left’’

buttons. This procedure excluded the admitting and denying of

acquaintance name recognition as in Experiment 1. Also, sub-

jects in Experiment 3 were asked to select four names from a list

of 100 common names rather than only 20 names as in Exper-

iment 1, and they were asked to pick the nonacquaintance names

that have equal numbers of syllables to the acquaintance names

they wrote down.

Results

Behavioral Data

All subjects responded correctly (i.e., pressing one button to

Condition 5 stimuli and pressing another button to all others) to

over 95% of trials. There was no significant difference in RT

among all conditions (p4.05).

Awareness Test

The d0 indices ranged from � .34 to 1.42, and chi-squared tests

showed none of the subjects responded significantly differently in

response to word and nonword conditions.

PCA

Figure 6 shows a graphical illustration of the ERP (pre-PCA)

grand averages of 4 (Fz, Cz, Pz, and Oz) out of 30 eletrode sites

for Experiment 3. A covariance-based within-study PCA was

applied on 30 sites data from 0ms to 1396ms after stimulus onset

for extraction of spatial components. The data matrix consisted

of 30 (number of electrodes) � 4 (number of conditions) �176 (number of time points per trial) � 12 (number of subjects)

cases. The spatial PCA extracted three components which ac-

counted for 85.6% of total variance: frontal-central-parietal

(36.1%), frontal (28.0%), and occipital-parietal (21.4%). The

actual sites included in each component are frontal-central-

parietal (C3, Cp1, Cz, Fc5, Fc1, Fc2, Cp2, Cp5, C4, Pz, P3, F3,

Fz, T7, Fc6, P4), frontal (Fp2, Af3, F7, F4, T8, Fp1, F8, Af4),

and occipital-parietal (O2, P8, O1, Oz, P7, Cp6). A temporal

PCA was then performed on the three spatial components. The

temporal PCA resulted in four temporal components (92.1% of

the variance explained): 0–348ms (20.4%), 356–596ms (17.7%),

604–1012 ms (34.0%), and 1020–1396 ms (20.0%).

Spatial components obtained in Experiment 3 are very similar

to those in Experiment 2. However, the temporal components

obtained in Experiment 3 are different from those in Experiment

1 and its replication and Experiment 2 starting from 500–600 ms.

In Experiments 1 and 2, three components were obtained after

around 500–600 ms (e.g., 524–668 ms, 676–908 ms, and 916–

1396 ms) whereas in Experiment 3 only two components were

obtained (604–1012 ms and 1020–1396 ms; see Figure 3).

Group Analysis and Individual Diagnosis

Figures 4 and 5 show grand average ERPs from virtual compo-

nent sites. It appears from visual inspection that the ERPs are not

different among all conditions at both virtual sites.

In each of the four temporal components, a separate

MANOVA was done as before. In each MANOVA, the three

spatial components were three dependent variables. Condition

was the independent variable. The omnibusMANOVAs resulted

in no significant effects in all analyses (p4.05). Therefore no

individual diagnosis was carried out.

Discussion

Removal of the deception requirement in Experiment 3 led to an

absence of subliminal priming effects, and therefore, an inability

to find any significant pairwise comparisons of interest, which

would suggest that deception is a necessary element in the pro-

tocol of Experiment 1 ( Table 1a) that produces ERP differences

between differentially primed, dishonest denials of acquaintance

recognition.


Table 3a. Replication Study Omnibus MANOVAs: Main Effect

of Condition


12–316 324–580 588–796 804–1396

Wilk’s l .703 .852 .739 .557Fstatistic 1.560 0.683 1.326 2.726p .140 .723 .235 .007nn

Note: Results based on within-study PCA-extracted components.nnpo.01.

Table 3b. Replication Study Univariate ANOVAs p Values


12–316 324–580 588–796 804–1396

FCP .078 .328 .047n .001nn

F .260 .206 .053 .091OP .234 .711 .145 .100

Note: Results based on within-study PCA-extracted components. FCP:frontal-central-parietal component; OP: occipital-parietal component; F:frontal component.npo.05, nnpo.01.

Table 3c. Replication Study Bonferroni Tests: Condition 1 (A-A)

versus Condition 2 (N-A)


12–316 324–580 588–796 804–1396

FCP .548 .651 .032n .187F 1.000 1.000 .145 .903OP 1.000 1.000 .168 .944

Note: Results based on within-study PCA-extracted components. FCP:frontal-central-parietal component; F: frontal component; OP: occipital-parietal component.npo.05.

Table 3d. Replication Study Individual Diagnosis Based on A-A

versus N-A

Temporal component (ms) Spatial component Detection rate

588–796 frontal-central-parietal 12/14 (85.7%)

Note: Results based on within-study PCA-extracted components.

INNOCENT GROUP

Methods

Participants

Eleven (average age: 18.5 years, 4 men) Northwestern University

undergraduate students who were not in Experiments 1 or 2 or 3

participated in the innocent group experiment for the fulfillment

of an introductory Psychology course requirement. They were all

right-handed and had normal or corrected vision. All signed an

IRB-approved consent form.


The procedures were similar to that in the replication study ex-

cept that subjects were asked to provide only one acquaintance

name (to be used as ‘‘attention catching’’ or target stimuli) and

choose 8 nonacquaintance names from the list of 100 common

names. They were asked to choose two 1-syllable names, four

2-syllable names, and two 3-syllable names. Half of the names

selected were denoted as ‘‘pseudo acquaintance names’’ and half

of them as nonacquaintance names in the data analyses. The

pseudo acquaintance names and nonacquaintance names

have the same number of syllables (one 1-syllable name, two

2-syllable names, and one 3-syllable name).

The timing and construction of stimuli were similar to that in

the replication study. Subjects were required to press a ‘‘no’’ to all

stimuli except the target, which was an acquaintance name sub-

jects provided. The button positions were counterbalanced (half

of the subjects pressed the left button for ‘‘yes’’ response and the

right button for ‘‘no’’ response and half of the subjects responded

in the other way).

Results

Behavioral Data

All subjects responded correctly (i.e., pressing ‘‘yes’’ to Condi-

tion 5 stimuli (target stimuli; see Table 1) and pressing ‘‘no’’ to all

others) to over 92% of trials. There was no significant difference

among all conditions (p4.05) in RT.

Awareness Test

The d0 indices ranged from � .31 to 1.20, and chi-squared tests

showed none of the subjects responded significantly differently in

response to word and nonword conditions (p4.05).

ERP Data

For the innocent control study, the spatial temporal components

identified in the replication group were utilized to analyze the

data in the control group. We could have used the components

from Experiment 1, but the treatment of the replication group

was more similar in all other ways but guilt and innocence to that

of the control group than was the treatment of the Experiment 1

group. (The components extracted from Experiment 1 and the

replication were relatively similar anyway, as shown in Figure 3

and its discussion below.) The analytic results showed no sig-

nificant main effects in MANOVA or in univariate ANOVA

tests. Consistent with these results, Figure 7 shows virtual site

grand average ERPs for the innocent control group, FCP com-

ponent (top), and OP component (bottom). At FCP, there is not


–200 0 200 400 600 800 1000 1200 1400

–5

0

5

10

15

–5

0

5

10

15

–5

0

5

10

15

–5

0

5

10

15

ms

mic

ro-v

olts

mic

ro-v

olts

mic

ro-v

olts

mic

ro-v

olts

FZ

A-AN-AA-NN-N

ms

CZ

ms

PZ

ms

OZ

A-AN-AA-NN-N

A-AN-AA-NN-N

A-AN-AA-NN-N

–200 0 200 400 600 800 1000 1200 1400

–200 0 200 400 600 800 1000 1200 1400–200 0 200 400 600 800 1000 1200 1400

Figure 6. Experiment 3 raw (pre-PCA) grand averages from 4 of the 30 actual sites.

much difference between A-A and N-A waveforms and, where

there is a difference, A-A appears mostly more positive, unlike the

priming effects seen in Experiment 1 and the replication. The OP

component shows the same null results. For the A-N versus N-N

comparison, both FCP and OP show some apparently more neg-

ative segments for A-N, but as noted above, none of these effects

in the control group reached or approached significance.

We did individual diagnostics in this innocent control group

on components comparable to those utilized in Experiment 1 and

the replication, however, because we wanted to see what the false

positive rates would be. These rates varied from 2/11 to 5/11. In

the replication study most comparable to the innocent group, we

correctly detected 12/14 (86.7%) subjects using the within-rep-

lication study PCA-extracted FCP component, 588–796 ms. The

same spatial and temporal component in the innocent group led

to 4/11 (36.3%) false positives. This yields a Grier (1971) A0

index of test efficiency of .84. (Table 4a,b shows A0 values forvarious pairings of hit rates fromExperiment 1 and its replication

with false positive rates from the innocent control groups.)

Summary of Differences among the Five Groups

In Experiments 1 and 2, subjects were asked to choose nonac-

quaintance names from a list of 20 names, and the number(s) of

syllables of the acquaintance and nonacquaintance names were

not matched. In the replication, Experiment 3, and the innocent

groups, subjects were asked to choose nonacquaintance names

from 100 common surnames in the United States. The names

were selected from a web site (Most Common Names and Sur-

names in the U.S., n.d.) listing all surnames with over .001%

frequency in the U.S. population during the 1990 census. They

were also instructed to choose names thatmatched the number of

syllables of the acquaintance names they provided.

RT Data for All Studies, Averaged across Conditions

These results (in milliseonds) were as follows: Experiment 1:

435.77, Experiment 2: 447.13, Experiment 3: 404.08, Replica-

tion: 438.45, Innocent: 369.4. It is also noted that there were no

significant differences in overall reaction time among the three

experiments plus the replication of Experiment 1. However, a

1 � 5 ANOVA including the innocent group yielded F(4,63)5

5.039, p5 .001. This suggested that the mean RTof the innocent

group was different than the mean of the experimental groups,

and, indeed, F(1,62)5 14.54, po.001, for this test. Clearly, the

lack of lying and related manipulations in the innocent group

affected RTuniquely in the innocent group in comparison to the

other groups.


AA vs NA AN vs NN

Innocent

0 500 1000 1500

–15

–10

–5

0

5

10

15

20

ms

Frontal-Central-Parietal Frontal-Central-Parietal

0 500 1000 1500ms

mic

ro-v

olts

mic

ro-v

olts

mic

ro-v

olts

mic

ro-v

olts

Innocent

0 500 1000 1500ms

Occipital-Parietal

0 500 1000 1500ms

Occipital-Parietal–15

–10

–5

0

5

10

15

20

–15

–10

–5

0

5

10

15

20

–15

–10

–5

0

5

10

15

20

Figure 7. ERPs of the frontal-central-parietal component and occipital-parietal component in the innocent control group data.

Table 4a. Experiment 1 and Innocent Group Individual Diagnosis,

A-A versus N-A, within-study PCA

Temporalcomponent(ms)

Spatialcomponent Detection rate

False positive(innocentgroup) A0

524–668 frontal-central-parietal

11/14 (78.6%) 4/11 (36.4%) .80

524–668 occipital-parietal 12/14 (85.7%) 5/11 (45.5%) .81916–1396 occipital-parietal 11/14 (78.6%) 2/11 (18.2%) .88

Table 4b. Replication and Innocent Group Individual Diagnosis,

A-A versus N-A, within-study PCA

Temporalcomponent(ms)

Spatialcomponent Detection rate

False positive(innocentgroup) A0

588–796 frontal-central-parietal

12/14 (85.7%) 4/11 (36.4%) .84

Qualitative ERP Data in All Studies

Figures 4 and 5 show the grand averages for each experimental

group in the two spatial components, frontal-central-parietal

(FCP, Figure 4) and occipital-parietal (OP, Figure 5), extracted

from the within-study PCAs, respectively, each component ac-

counting for more than 20% of the variance in the data. The two

columns in each figure show superimposed wave forms for the

A-A versus N-A comparison at the left, and A-N versus N-N at

the right. Recall that in Experiment 1 and the replication, priming

was expected for the A-A versus N-A comparison, but not the

A-N versus N-N comparison. For the FCP comparison in Fig-

ure 4, in Experiment 1 and in the replication, the priming effect

appears to be a negative shift throughout, but seenmostly between

500 and 800 ms, which is present only in A-A versus N-A, as

expected. In theOP component (Figure 5), the same differences are

seen; the contrasts between A-A versus N-A and A-N versus N-N

seem very clear. For Experiments 2 and 3, there are no apparent

priming effects for FCP or OP in any contrast, as expected.

General Discussion

Experiment 1 and its replication demonstrated a protocol in

which ERPs to dishonestly answered primed by subliminal non-

acquaintance names, supraliminally presented acquaintance

probes could be discriminated from primed by subliminal non-

acquaintance names, supraliminally presented acquaintance

probes. (We are noting only results obtaining in both the orig-

inal and replication studies.) The discrimination was good

enough so that about 80%–86% of the subjects (depending on

selection of specific spatial and temporal components analyzed)

could be identified in their dishonest denials of acquaintance

recognition (e.g., saying ‘‘no’’ to supraliminally presented ac-

quaintance names). In addition to the difference in dishonest

behavior between conditions A-A and N-A, on the one hand,

versus A-N and N-N, on the other, is the difference in the nature

of supraliminal stimuli in the pairs of conditions (A in A-A and

N-A vs. N in A-N and N-N). Experiment 2 was directed at

identifying possible key necessary factors for producing the

effects seen in Experiment 1 and its replication. Conditions 1 and

2 in Experiment 2 were exactly like those in Experiment 1 except

that subjects told the truth and did not lie in Conditions 1 and

2 of Experiment 2 (Table 1, cf. a and b). Subliminal A did not

prime supraliminal A in Experiment 2 as it did in Experiment 1,

in the absence of deception. (We assume the priming of one

stimulus by another requires identical types of stimuli. It also

appears that familiar stimuliFacquaintancesFbut not unfa-

miliar stimuli are more effective in priming; see below.) We con-

clude that the specific nature of the subliminal prime is not

sufficient to generate the priming effect. Neither is deception per

se sufficient, as Conditions 3 and 4 produced no priming in

Experiment 2. Experiment 3 reproduced the stimulus conditions

of Experiment 1, but with the deception requirement removed

and, again, no priming occurred.

Taken together, all these results suggest deception is necessary

but not sufficient to produce priming effects. The other necessary

factors likely include whether or not the stimuli are familiar (see

below) as well as the relationship or interaction of subliminal and

supraliminal stimuli. To answer this question, one must perform

further parametric studies. Nevertheless, the present results sug-

gest that a countermeasure-resistant protocol for detecting con-

cealed information may be developed around the protocol of

Experiment 1.

P300 Effects

In Experiments 1–3, we have tried to systematically look at the

effect of the lying task requirement and stimulus type on sub-

liminal priming. In all three experiments, stimuli consisted of

subliminal primes of acquaintance or nonacquaintance names

preceding a supraliminal target of different acquaintance or

nonacquaintance names. Results of Experiment 1 indicated that

the ERP response differed when different subliminal primes pre-

ceded supraliminal acquaintance names (A-A and N-A). The

condition with a congruent prime–target pair (acquaintance

preceding acquaintance names) produced a smaller positive am-

plitude than the condition with an incongruent pair (nonac-

quaintance preceding acquaintance names) in the 524–668-ms

temporal segment, which is in the typical P300 region. It was

hypothesized that P300 is related to decision making (Kutas,

McCathy, & Donchin, 1977) and the end of a decision process

(Donchin & Coles, 1988). The ‘‘context-update hypothesis’’

suggested that P300 signifies the updating of working memory

when processing unexpected events (Donchin, 1981). In Exper-

iment 1 and the replication, the supraliminal stimulus in Con-

dition 2 (N-A) was supposed to be less expected than in

Condition 1 (A-A) due to the incongruency of the prime–target

pair andmay therefore elicit a larger P300 during the updating of

working memory.

In fact, a modulation of P300 by subliminal primes was re-

ported by Dehaene, Kerszberg, and Changeux (1998), though

the modulation was in terms of latency but not amplitude. The

stimuli were numerals 1–9 in Arabic or word form. A suprali-

minal target numeral was preceded by a subliminal prime nu-

meral. Subjects performed a simple semantic categorization task

on the target numeral. Primes and targets were either congruent

or incongruent in the response requirement. The ERP compo-

nent that showed a prime–target congruity effect was the central

positivity at around 600 ms, which was delayed by around 24 ms

in incongruent trials compared with congruent trials.

Top-Down Effects of Long Term Memory

The results in Experiments 1 and 2 revealed that, under the same

task requirement and stimulus conditions, subliminal neural

priming occurs only in conditions with supraliminal acquain-

tances but not with supraliminal nonacquaintances. The present

results of the presence and absence of priming effect in acquain-

tance and nonacquaintance conditions, respectively, may pro-

vide hints about the interaction between perceptual processing of

stimuli and preexisting long-term memory representation (Hen-

son, 2003). Some studies have found priming for both familiar

and unfamiliar words and faces (Bowers, 1994; Goshen-Gott-

stein & Ganel, 2000; Stark & McClelland, 2000). However, be-

havioral priming effects are generally larger for familiar than for

unfamiliar stimuli. Also, there were previous studies that found

priming only for familiar but not for unfamiliar stimuli (e.g.,

Ellis, Young, & Flude, 1990). The findings in conscious priming

generally indicated that priming of stimuli with preexisting rep-

resentation in long-term memory undergoes different mecha-

nisms compared to priming of novel stimuli lacking

representation in long-term memory. The present study differed

from the aforementioned studies in that subliminal stimuli were

used. This may explain why different results of priming were

found in supraliminal acquaintance name conditions (A-A and

N-A) and supraliminal nonacquaintance name conditions (A-N

andN-N). It maybe the case that the signals of subliminal primes

were too weak to activate and facilitate the formation of a new


cortical network representing the nonacquaintance names, and

therefore no subliminal priming effects were found in A-N and

N-N. For supraliminal acquaintance name conditions A-A

and N-A, with preexisting representation, subliminal primes

were able to impose an effect on the supraliminal target and

therefore significantly modulated the ERP amplitude.

Top-Down Effects of Task Requirement

Experiment 1 and Experiment 3 had identical stimuli, and even

the behavioral response requirements were the same: pressing

one button in response to one of the acquaintance names and

pressing another button in response to all the other names. The

only difference between the two experiments was the meaning of

the button pressing. The responses in Experiment 1 involve ad-

mitting and denying the recognition of acquaintance and non-

acquaintance names, whereas responses in Experiment 3 do not.

As mentioned in previous sections, the task requirement may

modulate how the cognitive system processes input stimuli. The

meaning of denying and admitting recognizing the names did

affect how subjects processed subliminally primed acquaintance

names (A-A and N-A), as the neural priming effect was found

only when the task carries the denying/admitting meaning but

not when the task carries no such meaning. It may be the case

that the meaning tuned subjects’ attention to processing the fa-

miliarity of the names, which increased the processing differences

between the subliminal acquaintance and nonacquaintance

names, and therefore a ERP difference was found between

A-A and N-A in Experiment 1 but not in Experiment 3. The

same priming phenomenon was not observed in supraliminal

nonacquaintance conditions (A-N and N-N) in both Experi-

ments 1 and 3. The reason may again be attributed to the lack of

preexisting representation for priming to occur (as mentioned in

the previous paragraph).

To conclude, the paradigm of priming, which is well studied

and has a long history in cognitive psychology, may potentially

be used in individual diagnosis of lying. The present study dem-

onstrated that the priming paradigm may reveal the presence or

absence of memory representation in subjects’ brains during

suspected deception. Acquaintance names, which have long-term

memory representation, were successfully primed by a different

subliminal acquaintance name, as demonstrated by a smaller

positive ERP amplitude. This was not the case in nonacquain-

tance name conditions. The results indicated that information

with and without long-term memory representation can be dis-

tinguished by the presence and absence of the priming effect,

respectively. Moreover, because the primes were subliminal,

subjects are not expected to be able to develop differential covert

responses to conditions with different subliminal primes so as to

implement countermeasures. Further studies may be done so as

to verify the effectiveness of the present paradigm in obviating

countermeasures.

The spatial-temporal PCA and bootstrapping techniques

were used in the present study to improve signal-to-noise ratio

(Kobayashi & Kuriki, 1999), which is particularly important in

individual diagnosis where the amount of data is relatively lim-

ited (Lui & Rosenfeld, 2008). Further development of data pro-

cessing techniques on EEG data is needed to improve the

detection rate and lower the false positives in lie detection. The

multivariate nonlinear high-dimensionality pattern classification

technique (Lao et al., 2004) may potentially be applied to EEG

data in classifying lying and truth telling, as it was used in a fMRI

deception study (Davatzikos et al., 2005).

Compared to most other cognitive neuroscience techniques,

EEG is relatively portable, low cost, and without the need of

extensive medical expertise, which makes it a good candidate in

real-life applications such as police interrogation or employee

screening. Nevertheless, amidst the fast growing interest and re-

search development in lie detection, the authors acknowledge

that the ethical issues of humanmind reading should be carefully

discussed and investigated before further development of the

techniques.

REFERENCES

Allen, J. J., Iacono,W. G., &Danielson, K. D. (1992). The identificationof concealed memories using the event-related potential and implicitbehavioral measures: A methodology for prediction in the face ofindividual differences. Psychophysiology, 29, 504–522.

Besson, M., Kutas, M., & van Petten, C. (1992). An event-related po-tential (ERP) analysis of semantic congruity and repetition effects insentences. Journal of Cognitive Neuroscience, 4, 132–149.

Botvinick, M., Nystrom, L. E., Fissell, K., Carer, C. S., & Cohen, J. D.(1999). Conflict monitoring versus selection-for-action in anteriorcingulated cortex. Nature, 402, 179–181.

Bowers, J. S. (1994). Does implicit memory extend to legal and illegalnon-words? Journal of Experimental Psychology: Learning, Memory,and Cognition, 20, 534–549.

Carter, C. S., Braver, T. S., Barch, D.M., Botvinick, M. M., Noll, D., &Cohen, J. D. (1998). Anterior cingulated cortex, error detection, andthe online monitoring of performance. Science, 280, 747–749.

Davatzikos, C., Ruparel, K., Fan, Y., Shen, D. G., Acharyya, M.,Loughead, J. W., et al. (2005). Classifying spatial patterns of brainactivity with machine learning methods: Application to lie detection.Neuroimage, 28, 663–668.

Dehaene, S., Kerszberg,M., &Changeux, J. (1998). A neuronalmodel ofa global workspace in effortful cognitive tasks. Proceedings of theNational Academy of Sciences, USA, 95, 14529–14534.

Donchin, E. (1981). Surprise! . . . Surprise?Psychophysiology, 18, 493–513.Donchin, E., & Coles, M. G. H. (1988). Is the P300 component a man-

ifestation of context updating? Behavioral and Brain Science, 11,357–374.

Duncan-Johnson, C. C., & Donchin, E. (1979). The time constant inP300 recording Psychophysiology, 16, 53–55.

Ellis, A. W., Young, A. W., & Flude, B. M. (1990). Repetition primingand face processing: Priming occurs within the system that respondsto the identify of a face. Quarterly Journal of Experimental Psychol-ogy, 42, 495–512.

Fabiani, M., Gratton, G., Karis, D., & Donchin, E. (1987). Definition,identification and reliability of measurement of the P300 componentof the event related brain potential. In P. K. Ackles, J. R. Jennings, &M. G. H. Coles (Eds.), Advances in psychophysiology (vol. 2, pp.1–78). Greenwich, CT: JAI Press.

Falkenstein, M., Hoormann, J., Christ, S., & Hohnsbein, J. (2000). ERPcomponents on reaction errors and their functional significance:A tutorial. Biological Psychology, 51, 87–107.

Farwell, L. A., & Donchin, E. (1991). The truth will out: Interrogativepolygraphy (‘‘lie detection’’) with event-related potentials. Psycho-physiology, 28, 531–547.

Ganis, G., Kosslyn, S. M., Stose, S., Thompson, W. L., & Yurgelun-Todd, D. A. (2003). Neural correlates of different types of deception:An fMRI investigation. Cerebral Cortex, 13, 830–836.

Gehring, W. J., Goss, B., Coles, M. G. H., Meyer, D. E., & Donchin, E.(1993). A neural system for error detection and compensation. Psy-chological Science, 4, 385–390.

Goshen-Gottstein, Y., &Ganel, T. (2000). Repetition priming for familiarand unfamiliar faces in a sex-judgment task: Evidence for a commonroute for the processing of sex and identity. Journal of ExperimentalPsychology: Learning, Memory and Cognition, 26, 1198–1214.


Grier, J. B. (1971). Non-parametric indexes for sensitivity and bias:Computing formulas. Psychological Bulletin, 75, 424–429.

Henson, R. N. (2003). Neuroimaging studies of priming. Progress inNeurobiology, 70, 53–81.

Honts, C. R., Devitt, M. K., Winbush, M., & Kircher, J. C. (1996).Mental and physical countermeasures reduce the accuracy of theconcealed information test. Psychophysiology, 33, 84–92.

Johnson, R., Barnhardt, J., & Zhu, J. (2005). Differential effects ofpractice on the executive processes used for truthful and deceptiveresponses: An event-related brain potential study. Cognitive BrainResearch, 24, 386–404.

Kaiser, H. F. (1960). The application of electronic computers tofactor analysis. Educational and Psychological Measurement, 20,141–151.

Kobayashi, T., & Kuriki, S. (1999). Principal component eliminationmethod for the improvement of signal-to-noise in evoked neuromag-netic field measurement. IEEE Transactions on Biomedical Engineer-ing, 46, 951–958.

Kozel, F., Johnson, K., Mu, Q., Grenesko, E., Laken, S., & George, M.(2005). Detecting deception using functional magnetic resonanceimaging. Biological Psychiatry, 58, 605–613.

Kutas, M., McCathy, G., & Donchin, E. (1977). Augmenting mentalchronometry: The P300 as a measure of stimulus evaluation time.Science, 197, 792–795.

Langleben, D. D., Loughead, J. W., Bilker, W. B., Ruparel, K., Chil-dress, A. R., Busch, S. I., et al. (2005). Telling truth from lie in in-dividual subjects with fast event-related potential. Human BrainMapping, 26, 262–272.

Langleben, D. D., Schroeder, L., Maldjian, J. A., Gur, R. C., McDon-ald, S., Ragland, J. D., et al. (2002). Brain activity during simulateddeception: An event-related functional magnetic resonance study.NeuroImage, 15, 727–732.

Lao, Z., Shen, D., Xue, Z., Karacali, B., Resnick, S. M., & Davatzikos,C. (2004). Morphological classification of brains via high-dimen-sional shape transformations and machine learning methods. Neuro-Image, 21, 46–57.

Lee, T. M. C., Liu, H. L., Chan, C. C. H., Ng, Y. B., Fox, P. T., & Gao,J. H. (2005). Neural correlates of feigned memory impairment.NeuroImage, 28, 305–313.

Lui, M., & Rosenfeld, J. P. (2008). Detection of deception about mul-tiple, concealed, mock crime items, based on a spatial-temporal anal-ysis of ERP amplitude and scalp distribution. Psychophysiology, 45,721–730.

Mertens, R., & Allen, J. J. (2008). The role of psychophysiology in fo-rensic assessments: Deception detection, ERPs, and virtual realitymock crime scenarios. Psychophysiology, 45, 286–298.

Mohamed, F. B., Faro, S. H., Gordon, N. J., Platek, S. M., Ahmad, H.,& Williams, J. M. (2006). Brain mapping of deception and truthtelling about an ecologically valid situation: Functional MR imagingand polygraph investigationFInitial experience. Radiology, 238,679–688.

Most Common Names and Surnames in the U.S. (n.d.). Retrieved 2005from http://names.mongabay.com/

Nakamura, K., Hara, N., Kouider, S., Takayama, Y., Hanajima, R.,Sakai, K., et al. (2006). Task-guided selection of the dual neuralpathways for reading. Neuron, 52, 557–564.

Nunez, J. M., Casey, B. J., Egner, T., Hare, T., & Hirsch, J. (2005).Intentional false responding shares neural substrates with responseconflict and cognitive control. NeuroImage, 25, 267–277.

Rosenfeld, J. P., Angell, A., Johnson, M., & Qian, J. (1991). An ERP-based control-question lie detector analog: Algorithms for discrim-inating effects within individual waveforms. Psychophysiology, 28,320–336.

Rosenfeld, J. P., Cantwell, B., Nasman, V. T., Wojdac, V., Ivanov, S., &Mazzeri, L. (1988). A modified, event-related potential-based guiltyknowledge test. International Journal of Neuroscience, 42, 157–161.

Rosenfeld, J. P., Labkovsky, E., Winograd, M., Lui, M., Vandenboom,C., & Chedid, E. (2008). The Complex Trial Protocol (CTP): A novel,countermeasure-resistant, accurate P300-based method for detectionof concealed information. Psychophysiology, 45, 906–919.

Rosenfeld, J. P., Soskins, M., Bosh, G., & Ryan, A. (2004). Simpleeffective countermeasures to P300-based tests of detection of con-cealed information. Psychophysiology, 41, 205–219.

Spence, S. A., Farrow, T. F. D., Herford, A. E., Wikinson, I. D., Zheng,Y., & Woodruff, P. W. R. (2001). Behavioral and functional ana-tomical correlates of deception. NeuroReport, 12, 2849–2853.

Spencer, K., Dien, J., & Donchin, E. (2001). Spatiotemporal analysis ofthe late ERP responses to deviant stimuli. Psychophysiology, 38, 343–358.

Stark, C. E., & McClelland, J. L. (2000). Repetition priming of words,pseudowords, and non-words. Journal of Experimental Psychology:Learning, Memory, and Cognition, 26, 945–972.

Tulving, E., & Schacter, D. L. (1990). Priming and human memory sys-tems. Science, 247, 301–306.

(Received March 18, 2008; Accepted September 5, 2008)


The application of subliminal priming in lie detection...

Documents

Transcript of The application of subliminal priming in lie detection...