Psychophysiological correlates of the misinformation effect · PSYCHOPHYSIOLOGICAL CORRELATES OF THE MISINFORMATION EFFECT 2 Abstract The misinformation effect refers to memory impairment

PSYCHOPHYSIOLOGICAL CORRELATES OF THE MISINFORMATION EFFECT 1

Psychophysiological correlates of the misinformation effect

Katja Volz *, Rainer Leonhart **, Rudolf Stark ***, Dieter Vaitl *, Wolfgang Ambach *

* Institute for Frontier Areas of Psychology and Mental Health, Wilhelmstraße 3a, D-

79098 Freiburg, Germany

** Institute of Psychology, University of Freiburg, Engelbergerstraße 41, D-79085

Freiburg, Germany

*** Bender Institute of Neuroimaging, University of Giessen, Otto-Behaghel-Straße

10h, D-35394 Giessen, Germany

Correspondence: Katja Volz

Institut für Grenzgebiete der Psychologie und Psychohygiene,

Freiburg, Germany

Wilhelmstraße 3a

D-79098 Freiburg

Germany

E-Mail: [email protected]


Abstract

The misinformation effect refers to memory impairment that arises after

exposure to misleading information (Loftus, 2005, p. 361). The present study focuses

on the peripheral psychophysiology of false memories induced in a misleading

information paradigm. On the basis of Sokolov’s orienting reflex and studies

concerning the Concealed Information Test (CIT, Lykken, 1959), the main hypothesis

assumes differences between true and false memories in terms of the accompanying

autonomic measures. It also is assumed that a cued recall of original information

preceding the recollection phase reduces misinformation effects. Seventy-five

participants watched a video that included nine randomized details. After a ten-

minute retention phase, the subjects read a narrative text. Six out of the nine details

were replaced by misleading details. Following this, the participants completed a

cued recall task for three of the original items. In a subsequent CIT with truthful

answering electrodermal responses, phasic heart rate, respiration, and response

behavior were measured. Finally, the level of confidence and source monitoring were

assessed. The misinformation effect was replicated with newly developed materials

in three recollection tasks. Cued recall had no influence on the misinformation effect.

Autonomic measures did not differ between true and false memories in the CIT.

Electrodermal responses reflected the subjective importance the participants

attributed to details in the source monitoring task. Therefore, electrodermal

responses are interpreted as a correlate of subjective remembering in a

misinformation paradigm.

Keywords: False memory, Concealed information test, Misinformation

paradigm, Electrodermal activity, Cued recall, Autonomic

measures


1 Introduction

Eyewitness testimony is crucial for concluding police investigations (Coupe &

Griffiths, 1996; Paulo, Albuquerque, & Bull, 2013). However, most police officers do

not know that eyewitness memory is often distorted (Kebbell & Milne, 1998). If

memory impairment arises after exposure to misleading information, this is called a

misinformation effect (Loftus, 2005, p. 361). The vulnerability to false memories has

been a focus of memory and forensic research for nearly four decades. However, to

date, there have been few studies investigating the physiological correlates of false

memory (for a review, see Johnson, Raye, Mitchell, & Ankudowich, 2012; Schacter &

Slotnick, 2004). In the present study, we examined peripheral physiological measures

as possible indicators of false memories in a misinformation paradigm. Additionally,

we aimed to reduce misinformation effects using a cued recall procedure.

1.1 The misinformation effect

False memory research dates to the 1970s. In a series of five experiments,

Loftus, Miller, and Burns (1978) evoked false memories of a traffic sign. The three-

stage procedure applied was named the misinformation paradigm and has since

been used by various research groups (e.g., Belli, Lindsay, Gales, & McCarthy, 1994;

McCloskey & Zaragoza, 1985; Tversky & Tuchin, 1989). In the misinformation

paradigm, the subjects first watch a video or slides typically showing crime or crime-

related plots. After a distractor or retention phase, the researchers introduced

misinformation hidden in a narrative or questions about the event (e.g., “How fast

was the car going when it ran the stop sign?” Loftus et al., 1978, p.19). Finally, the

subjects complete memory tasks about the event. Typically, forced-choice,

recognition, source identification, or level-of-confidence tests are used to gather

memory data (Johnson, Hashtroudi, & Lindsay, 1993; Tversky & Tuchin, 1989). If

misleading information successfully provoked a misinformation effect, this is reflected

in two ways: in reduced recall of original information and enhanced recall of

misleading information (Loftus, 2005).

To date, there is no clear explanation of how false memories emerge in a

misinformation paradigm. Initially, it was assumed that misleading information

replaces the original memory (Loftus, 1979; Loftus & Loftus, 1980). Later, an

integration of misleading and original information into one mixed memory was


considered (Loftus & Hoffman, 1989). However, the coexistence of original and

misleading information has been demonstrated by several research groups (e.g.,

Bekerian & Bowers, 1983; Belli, 1988; Wright, 1993). Lindsay and Johnson (1989)

assumed that the sources of information are confused during retrieval. In the source

monitoring framework (Johnson et al., 1993; for a summary, see Lindsay, 2008) false

memory occurs when misleading information is misattributed to the source of the

original information. Such source monitoring is driven by judgment processes that

interact with several characteristics of memories, which are typical of a specific

source that a memory could have (Johnson et al., 1993). Based on the assumptions

of the source monitoring framework, the present study employed a cued recall task to

reduce misinformation effects.

1.2 Reduction of misinformation effects

As it is still unclear which exact processes drive the misinformation effect, it is

an open question how it can be reduced reliably. Per the discrepancy detection

principle, warnings before the misleading information (Eakin, Schreiber, & Sergent-

Marshall, 2003; Greene, Flynn, & Loftus, 1982) or misinformation received from an

unreliable source (Bodner, Musch, & Azad, 2009; Dodd & Bradshaw, 1980) can

reduce misinformation effects. However, the evidence the evidence concerning

warnings given in between the misleading information phase and the recollection

phase is still equivocal (for a review, see Blank & Launay, 2014).

The search for a procedure that can be applied after misleading information

was given and that reduces the effect of misleading information on memory, is still

ongoing. In applied forensic research, this is pursued with two approaches: the

Cognitive Interview (CI; Fisher & Geiselman, 1992) and the Self-administered

Interview (SAI; Gabbert, Hope, & Fisher, 2008). Both approaches rely mainly on a

mental reinstatement of the crime (mentally recreating the context of an event, as

well as the physiological, cognitive, and emotional states at the time of an event), that

supports correct source identification (Fisher, Geiselman, & Amador, 1989; Memon &

Bull, 1991; Paulo et al., 2013). Both interviews were investigated in applied contexts

and achieved large effect sizes (Dodson, Powers, & Lytell, 2015; Fisher et al., 1989;

Gabbert et al., 2008; Hope, Gabbert, Fisher, & Jamieson, 2014; Köhnken, Thürer, &

Zoberbier, 1994; Köhnken, Milne, Memon, & Bull, 1999). For example, a recent meta-

analysis found average effect sizes of d = 1.20 for comparisons between correctly


reported details in the Cognitive Interview compared to control interviews (Memon,

Meissner, & Fraser, 2010).

In our study, we employed a simple task preceding the recollection phase that

aimed to strengthen correct source identification in a misinformation paradigm. We

designed the task using the mental reinstatement principle that is utilized in both

interview forms of applied forensic research. The simple procedure used the original

scene in the video as a cue to facilitate correct source identification. This process

resulted in a cued recall task, which will be described later.

1.3 Physiological correlates of false memory

The main goal of our study was to examine peripheral physiological measures

as possible indicators of false memories in a misleading information paradigm. Past

research has mainly comprised studies using functional magnetic resonance imaging

(fMRI), positron emission tomography (PET), or event-related potential (ERP) and

other false memory paradigms (for a review, see Johnson et al., 2012). To the

authors’ knowledge, only one study has used autonomic measures (Baioui, Ambach,

Walter, & Vaitl, 2012). Also, only few studies used the misinformation paradigm (e.g.,

Okado & Stark, 2005). The combination of autonomic measures and the

misinformation paradigm, however, is promising. Autonomic measures might function

as sensible indicators of false memories, which rely on the principles of the orienting

reflex (OR; Sokolov, 1963).

The OR is the physiological, cognitive, and behavioral response to a given

stimulus (Sokolov, 1963). Autonomic measures like electrodermal activity (EDA),

respiration line length (RLL), and phasic heart rate (pHR) are discussed to reflect this

basal process (Sokolov, 1963). The strength of an OR is influenced by the novelty,

intensity, and signficance of the stimulus (Sokolov, 1963). The stimulus significance

is the special importance and meaning a subject attributes to an item (see also

Ambach, Dummel, Lüer, & Vaitl, 2011), and, for this study, the stimulus significance

is crucial for examining the physiological responses to true memories compared with

false memories. The difference between less and highly significant stimuli is well-

reflected, particularly by EDA (Barry, 1996). A method that uses autonomic measures

to differentiate between stimuli of different significance is the Concealed Information

Test (CIT; Lykken, 1959).


The CIT is a well-designed and valid method to detect information using

physiological measures (for a review, see Ben-Shakhar & Elaad, 2003; Meijer, klein

Selle, Elber, & Ben-Shakhar, 2014). The CIT assumes that physiological responses

differ between crime-relevant and crime-irrelevant information if a subject has

knowledge about a crime (Lykken, 1959). Besides other approaches, the OR is

discussed as the main explanation of this difference (Verschuere, Ben-Shakhar, &

Meijer, 2011). The CIT asks several questions referring to different crime-relevant

categories. Typically, a question (e.g., “Was this fruit lying on the window sill?”) is

combined with five items showing possible alternatives. Only subjects with crime-

related knowledge will recognize the right answer and react differently to crime-

related items. In a typical response pattern, test subjects respond to crime-relevant

(significant) items with greater EDA and smaller RLL and pHR (Ambach, Stark,

Peper, & Vaitl, 2008; Ben-Shakhar & Elaad, 2003; Elaad & Ben-Shakhar 2008;

Gamer, Rill, Vossel, & Gödert, 2006; Verschuere, Crombez, de Clercq, & Koster,

2004). The CIT also reflects recognition if the information is not concealed. This

outcome is especially true for EDA, which mainly reflects OR, whereas, pHR and RLL

are also discussed in the light of concealment processes (Ambach et al., 2008; klein

Selle, Verschuere, Kindt, Meijer, & Ben-Shakhar, 2015).

In misinformation paradigms, the recognition of original information is impaired

by misinformation. Based on orienting theory, we assumed that a special importance

and meaning is attributed to the original but not the misleading information; therefore,

original information is more significant to the person than misleading information.

Referring to the typical response patterns in studies dealing with concealed

information, it is assumed that the original information will be accompanied by greater

EDA as well as smaller pHR and RLL responses, compared to the misleading or

unknown information.

Baioui and his colleagues (2012) already examined data on autonomic

measures gathered in a Deese-Roediger-McDermott paradigm (DRM, Deese, 1959;

Roediger & McDermott, 1995). In a DRM paradigm, participants first learn lists of

closely related words (e.g., bed, pillow, sheet) and are asked to recognize the

learned words in an upcoming recognition phase. Often, participants then falsely

remember words related to the categories they have studied before (e.g., sleep)

(Roediger & McDermott, 1995). In contrast to the misleading information paradigm,


false memories in a DRM paradigm are not evoked by misleading information but by

the activation of a conceptual scheme of the studied items. Baioui and his colleagues

(2012) also suggested that false memories are accompanied by less subjective

importance and meaning and, thus, by a smaller OR in contrast to true memories.

Their results yielded greater EDA responses associated with true memories rather

than false memories. No significant effects of pHR or RLL were found. It is still an

open question whether this response pattern can be replicated and transferred to a

misinformation paradigm.

1.4 Aims of the present study

1.4.1 Methodologically advanced replication of the misinformation effect

A methodologically advanced version of the typical misinformation paradigm

was applied. The original information was presented in a video instead of slides

because of advances in external validity; a video presents motion sequences of

action and is thus easier for a person to perceive than slides, which only show a

series of snapshots (for a review, see Takarangi, Parker, & Garry, 2006).

Additionally, a fully randomized and balanced stimulus set with nine classes of

objects comprising five objects each was created. Regarding the approach of an

enhanced stimulus set by Takarangi and her colleagues (2006), we shot a video and

filmed every scene in five variants, each containing a different critical object of the

same object class. Each subject watched a different video, which was composed

using a randomization scheme. Subjects were misled by a narrative that was also

adjusted by the randomization scheme. Recollection tasks involved recognition, level-

of-confidence, source identification, and forced-choice, thereby controlling the effects

of single objects or classes. Furthermore, by using different memory tests and

examining control categories as well as control items in each class of objects, a great

range of memory data could be collected. It was investigated whether the described

materials were appropriate to induce a misinformation effect. Also, all classes of

objects used underwent exploratory analyses to examine which of them scored

highest in evoking false memories.

1.4.2 Reducing misinformation effects by cued recall

As a further question, it is proposed that, per the source monitoring framework,

a cued recall before the recollection phase may reduce misinformation effects. The


cued recall task was adapted from the concept of mental reinstatement used in

applied forensic research. For this study, the original source of information (i.e.,

visual information from the video) was used to support the recall of the original

information. Successful recall is meant to strengthen the relation between the original

source and the original information, which should reduce source confusion in the

subsequent recollection tasks.

1.4.3 Autonomic correlates of the misinformation effect

A CIT with truthful answering is used to differentiate between the autonomic

responses of different types of items and memories. The core assumption of the

study is that misinformation and false memories are accompanied by decreased

physiological responses of recognition compared to the original information and true

memories. This should be reflected in smaller EDA and greater pHR and RLL

responses. It is further investigated whether the autonomic correlates differ between

source confusion errors (confusing an original source with misleading one) and

correct source identifications.

2 Methods

2.1 Participants

Seventy-five healthy student participants (49 f., 26 m., age: 23.7 ± 2.7 y.) from

different faculties except psychology and neuroscience were recruited via student

services and university bulletins. Written consent was obtained prior to the

experiment, which met all the ethical requirements per the declaration of Helsinki.

Sixteen Euros were paid for participation.

2.2 Design

Three different types of categories were varied within subjects: Categories in

which no misleading information was induced (three control categories) were

compared with categories in which misleading information was introduced (six misled

categories). Whether a cued recall task reduces misinformation effects within the

mislead categories or not, was investigated in three misled categories with cued

recall and three misled categories without cued recall. Each misled category

comprised three different types of items: Original items introduced as original

information in a video, misleading items serving as misleading information in a


narrative text, and unknown information used as control items in the recollection

phase. Control categories comprised one original and four control items. All factors

were manipulated within-subject.

2.3 Materials and procedure

The memory-related focus of the study was disguised by the cover story ‘moral

sense and cognition’. The experimenter did not mention memory tests in advance.

The video that was used to introduce original information lasted approximately

6.5 minutes and showed a young woman stealing a ring and money prior to a job

interview. Nine particular items, each drawn from a different class of objects per a

randomization procedure described later on, served as the original information.

Object classes were name on a door plate, time, picture of a landscape, box, fruit,

key pendant, color of an envelope, drink, and playing card. As one class of objects

comprised five possible items, each scene showing a relevant object was filmed five

times. Finally, the participants viewed a video composed of a basic plot and nine

randomized video fragments, twice. They were asked to divide it into meaningful

sections and rate every section on a scale of 0 (“morally not reprehensible”) to 100

(“morally reprehensible”).

The subsequent distractor tasks were labeled as ‘cognitive performance

tasks’. Subjects completed a five-minute Stroop-test and a five-minute two-back-task.

Length and difficulty were adapted from former misinformation studies (e.g., Loftus,

1977; McCloskey & Zaragoza, 1985; Belli et al., 1994; Chambers & Zaragoza, 2001;

Wilford, Chan, & Tuhn, 2014).

Subsequently, a narrative text describing the video plot served as

misinformation source: Six out of nine original items were randomly replaced by

misleading items (e.g., “kiwi” replacing “apple”); the remaining three were described

by naming the object class (e.g., “fruit”) and served as control categories. Subjects

were asked to read the narrative text, first divide it into meaningful sections, then rate

every section (analog to the video task) and assign a brief title to each.

Next, the participants received the cued recall disguised as a ‘scenic

imagination’ task. Covering each misled category with cued recall, the participants

viewed a screenshot of the video with the particular item (e.g., an apple lying on the


window sill) blackened out. They were asked to imagine the video scene as precisely

and in as much detail as possible. Twenty seconds after onset of the screenshot, a

verbal question was asked to indicate the class of objects of the searched item (e.g.,

“Which fruit was lying on the window sill?”), to facilitate the participants’ active recall

of the original item. After a self-chosen delay (30 seconds minimum; no maximum),

the participants wrote down a description of the blackened object and continued with

the next screenshot.

Subsequently, the participants were led to an experimental chamber and

connected to polygraph leads to complete the CIT with truthful answering. The CIT

consisted of nine blocks referring to nine categories. In each block, a question

appeared two seconds before the presentation of a particular item (e.g., “Did she

take the money out of this envelope?”). Items were presented for 10 seconds as

textual pictures (640 x 480 pixels) on a 19-inch monitor at a distance of 90

centimeters, followed by a blank screen lasting for 8 to 10 seconds. Simultaneous

with the presentation of an item, two indication fields (yes and no) prompted the

participant to answer. If no answer was given, after two seconds, the indication fields

disappeared. If an answer was given, the respective field remained visible for the rest

of this trial. The participants were required to indicate whether the item shown was

included in the video by giving a verbal yes or no answer and pressing one of the two

response keys as quickly as possible. The key assignment was balanced between

subjects. For each misled category, one original item, one misleading item, and three

control items were shown one after the other. In control categories, one original and

four control items were shown. The main run was preceded by a training run

consisting of two blocks with five neutral items each. This resulted in a total of 55

item presentations. The first item of a category was always a control item, which was

discarded from the analysis of physiological measures.

The subjects were then detached from the leads and asked to complete three

different memory tests. In all these tests, the items were presented as textual

pictures. First, the subjects were told to indicate on a scale from -3 (“definitely not

seen”) to +3 (“definitely seen”) whether the item appeared in the video (level of

confidence). Second, the participants were instructed to decide if the shown item was

presented in the video, the text, or during the physiological measurement (source

identification). Third, all items of a class of objects were presented simultaneously


and the participants were asked to choose the item which appeared in the video

(forced choice).

Each participant received an individually cut video, an individual narrative text,

and individual item sequences in all recollection tasks per a randomization scheme.

Randomization procedures warranted that the role of each item as original,

misleading, or control was balanced across subjects. For the CIT, the sequence of

categories was balanced as well as the item sequence within categories; particularly,

the relative position of crime-relevant and misleading items was balanced.

Randomization was also applied to item sequences in the concluding three-fold

memory test.

2.4 Physiological recording

Physiological data was recorded in a dimly lit, electrically, and acoustically

shielded experimental chamber (Industrial Acoustics GmbH, Niederkrüchten,

Germany). The temperature was maintained by air conditioning and was set to

approximately 22.4°C at the beginning with a maximum increase of 0.9°C throughout

the recording. The subjects sat in an upright position; so they could easily reach the

keyboard and watch the 19’-inch’-monitor.

Skin conductance, electrocardiogram, respiratory activity, and finger

plethysmogram were measured. Physiological data were logged using the

Physiological Data System I 410-BCS (J&J Engineering, Poulsbo, Washington), and

converted from analog to digital at a resolution of 14 bits, allowing skin conductance

to be measured with a resolution of 0.01µS. Stimulus on-/offsets and physiological

data were sampled at a rate of 510Hz. Standard Ag/AgCl electrodes (Hellige;

diameter 0.8cm), electrode paste of 0.5% saline in a neutral base (TD 246 Skin

Resistance, Mansfield R&D, St. Albans, Vermont, UK), and a constant voltage of

0.5V were used for recording skin conductance. Electrodes were placed over the

thenar and hypothenar muscles of the non-dominant hand. Electrocardiogram (ECG)

was measured using Hellige electrodes (diameter 1.3cm) according to Einthoven II.

The thoracic and abdominal respiratory activity was registered by two PS-2

biofeedback respiration sensor belts (KarmaMatters, Berkeley, CA) with a built-in

length-dependent electrical resistance. An infrared pulse sensor in a cuff around the


end phalanx of the middle finger of the non-dominant hand was used to record the

finger plethysmogram.

2.5 Data analysis

The recorded finger plethysmogram was not analyzed because of insufficient

signal quality. Skin conductance data from eight subjects had to be discarded from

the analysis because of electrodermal non-response (> 85% of responses < 0.01µS).

Responses in skin conductance were defined as an increase in conductance that

was initiated within a time period of one to five seconds after image onset. The

amplitude of the response was automatically evaluated as the difference between

response onset and the subsequent maximal value in the set time window (Furedy,

Posner, & Vincent, 1991). Phasic heart rate data from one subject had to be

discarded from analysis because of frequent extrasystoles. The remaining data were

notch filtered at 50 Hz and underwent an automatic R-wave peak detection prior to

visual inspection of the resulting data. The R-R intervals were transformed into heart

rate and real-time scaled (Velden & Wölk, 1987). The heart rate during the last

second before trial onset served as the pre-stimulus baseline. The phasic heart rate

was calculated by subtracting this value from each second-per-second post-stimulus

value. For extracting the trial-wise information of the phasic heart rate, the mean

change in heart rate within 15 seconds after trial onset compared with the pre-

stimulus baseline was calculated (Bradley & Janisse, 1981; Verschuere, Crombez,

Koster, van Bockstaele, & de Clercq, 2007). Respiratory data was manually scanned

and low-pass filtered (10dB at 2.8 Hz) for eliminating the artifacts. A method from

Timm (1982), modified by Kircher and Raskin (2003) was used to process the data:

RLL was computed over a time interval of ten seconds after trial onset. It integrates

information on the frequency and depth of respiration. RLL data from both bolts were

averaged. In all analyses within-subject z-standardized physiological data were used

(Lykken & Venables, 1971; Ben-Shakhar, 1985; Gamer et al., 2006).

2.6 Statistical analysis

All statistical analyses were conducted using SPSS 23 (IBM Corp., Armonk,

NY). A sensitivity analysis was conducted using G*Power (version 3.1.9.2, Faul,

Erdfelder, Lang, & Buchner, 2007). As defined a priori, all subjects with conspicuous

values on at least three depending variables were discarded from analysis.


Conspicuous values were defined as all values more than one-and-a-half interquartile

range above the seventy-fifth or below the twenty-fifth percentile (Tukey, 1977). This

resulted in the exclusion of three subjects. However, no changes in significance

occurred when the analyses were conducted with all subjects. Prior to every analysis,

the requirements were tested: If variables were not distributed normally a Wilcoxon-

test instead of a t-test for paired samples was used. For Wilcoxon-tests Cohen’s d

(Cohen, 1988) was calculated using the formulas r = z/ (Field, 2009, p. 550) and d

= (Rosenthal, 1994, p. 239). If the Mauchly’s test indicated a violation of the

assumption of sphericity, the degrees of freedom were corrected according to

Greenhouse-Geisser. All tests were conducted with an alpha level of 0.05; the alpha

level of all comparisons using t-tests was corrected per the Bonferroni-Holm method

(Holm, 1979).

Regarding the analysis of the misinformation effect, the number of affirmations

in the CIT, level of confidence ratings, and the number of correct source

identifications of original items were compared between the control and misled

categories using a Wilcoxon test. It was further analyzed, if in misled categories with

cued recall, source identification errors increased or source identification accuracy

decreased, when compared with misled categories without cued recall. One-way

repeated measurement ANOVAs were used to analyze the effects of the item type

(original vs. misleading vs. control) on the physiological variables. The comparison of

physiological variables between true (affirmed original items) and false (affirmed

misleading items) memories was conducted using a t-test for paired samples. Finally,

the answers in the source identification task were subdivided into confusing (original

items attributed to text; misleading items to video), correct (original items to video;

misleading items to text), and incorrect (original or misleading items to CIT) source

identifications. For all physiological measures a one-way repeated measures ANOVA

was used to compare the source identifications (confusing vs. correct vs. incorrect).

3 Results and discussion

3.1 Replication of the misinformation effect

Regarding the behavioral data, the misinformation effect should be reflected in

three measures: The number of affirmations in the CIT, the level of confidence (LOC)

ratings, and the number of correct source identifications. Descriptive statistics of


affirmations in the CIT and LOC ratings are provided in Table 1; descriptive statistics

of source identifications are presented in figure 1. In the CIT, 9.4% of misleading

items were (falsely) affirmed (“false memory rate”). 3.0% of control items were

(falsely) affirmed (“basic error rate”). False memory rate exceeded basic error rate, z

= -3.37, p < .001, d = 0.57. In the misled compared with control categories the

original items were less often affirmed, z = -2.60, p = .009, d = 0.64, the level of

confidence for these items was lower, z = -3.19, p = .001, d = 0.81, and the correct

source identification of these items decreased, z = -5.41, p < .001, d = 0.78.

Figure 1. Answers to original items in the source identification task: percentage of correct

(“video”), incorrect (“CIT”), and confusing (“text”) answers, seperately for the three types of

categories (left). Answers to misleading items in the source identification task: percentage of

correct (“text”), incorrect (“CIT”), and confusing (“video”) answers, seperately for the two

types of categories (right). (Error bars represent 95% confidence intervals.)


Table 1.

Percentage of affirmations in the CIT and mean level of confidence (LOC) ratings, separate

for control, original, and misleading items of the three types of categories.

Category Control Misled without cued recall Misled with cued recall

Item Control Original Control Original Misleading Control Original Misleading

M SEM M SEM M SEM M SEM M SEM M SEM M SEM M SEM

CIT 0.030 0.006 0.838 0.026 0.029 0.007 0.773 0.030 0.088 0.020 0.030 0.058 0.743 0.032 0.100 0.021

LOC 1.527 0.066 6.285 0.107 1.505 0.074 6.000 0.125 1.861 0.115 1.491 0.066 5.778 0.147 2.014 0.129

M = mean; SEM = standard error of the mean; LOC rating scale from 1 (“definitely not seen”) to 7 (“definitely

seen”)

This indicates that a misinformation effect was successfully induced, as

reflected in the CIT answers, in the level of confidence, and in the source

identifications. The newly developed materials proved to be suitable in replicating the

misinformation effects, which were repeatable across three different recollection

tasks.

To test for differences between the employed classes of objects, the

descriptive statistics of the misinformation effect (affirmations to original items in

misled vs. control categories in the CIT) and of false memories (affirmations to

misleading items in the CIT) were computed separately, for each of the nine classes.

Adding up both criteria, drink, name on a doorplate, time, fruit, and key pendant

scored highest in distorting memory. This outcome might indicate that memory for

numeric or textual classes (e.g., time or name) may be impaired more easily than for

pictorial classes (e.g., picture). It is tempting to speculate that visual original

information is encoded better, and therefore, is less vulnerable to memory

impairment than textual or numeric information. In line with the previous literature

(Heath & Erickson, 1998; Paz-Alonso & Goodman, 2008) peripheral classes (not

focused in the video, e.g., drink or key pendant) appeared to score higher than the

central classes (e.g., box). In field applications of the CIT, it also is assumed that

memory of places of stolen items (e.g., box or envelope) are typically remembered

better than peripheral details (e.g., time) (Nakayama, 2002; Osugi, 2011).


3.2 Influence of the cued recall on the misinformation effect

In misled categories with cued recall, the original and misleading items were

not significantly better attributed to the correct source compared to the misled

categories without cued recall, z = -.726, p = .468, d = 0.16. There is no difference

between categories with or without cued recall with respect to the occurrence of

source-confusing errors (original items attributed to the text or misleading items

attributed to the video), z = -.061, p = .952, d = 0.01. This outcome indicates that

there is no influence of the cued recall task on the misinformation effect.

Evidence from former attempts made to decrease misinformation effects is equivocal.

Priming of original information, but not of neutral or misleading information alters

misinformation effects (Gordon & Shapiro, 2012). In some studies, warnings before

the recollection phase reduced misinformation effects (Bodner et al., 2009; Eakin et

al., 2003; Echterhoff, Hirst, & Hussy, 2005), in others they did not (Meade &

Roediger, 2002; for a review see Blank & Launay, 2014). Echterhoff and his

colleagues (2005) concluded that there were cognitive processes that could be

influenced prior to the recollection to decrease false memories. The cued recall task

may not have influenced the cognitive processes in a way that neither improved nor

impaired memory recollection. The instructions and visual cues used (i.e.,

screenshots of the video) were apparently not sufficient to support the strengthening

of the original source memory. Rather, it may have acted as a first recollection task.

On summarizing, there is no reliable method yet, to reduce misinformation effects

prior to the recollection phase. In the current state of research, the mechanisms

leading to false memory are still unclear. No cognitive processes are known that may

explain the majority of the mixed study results. The results of our study, therefore,

numbers among in the mixed state of research concerning the mechanisms and

decrease of the misinformation effect.

3.3 Autonomic correlates of the misinformation effect

Table 2 provides an overview of the raw physiological data separated by item

type. Figure 2 shows the temporal course of the phasic heart rate separately for each

item type. In all following analyses, within-subject z-standardized physiological data

were used (Lykken & Venables, 1971; Ben-Shakhar, 1985; Gamer et al., 2006). A

significant effect of item type was found for EDA, F (1.76, 66) = 80.89, p < .001, =


0.55, but it was not found for pHR, F (1.81, 70) = 0.98, p = .371, = 0.01, or for

RLL, F (1.63, 70) = 0.02, p = .976, = 0.00. The original items were accompanied

by greater EDA responses when compared with the control items, t (65) = 12.06, p <

.001, d = 2.63, and when compared with the misleading items, t (65) = 8.46, p < .001,

d = 1.69. The misleading items were associated with greater EDA responses in

contrast to the control items, t (65) = 2.61, p = .011, d = 0.50.

Figure 2. Temporal course of the phasic heart rate separately for each item type.


Table 2.

EDA, pHR, and RLL separated for each item type

Item type

Original Misleading Control

M SEM M SEM M SEM

EDA [nS] 229.21 29.78 137.67 23.94 115.64 19.50

pHR [BPM] 0.49 0.23 0.79 0.21 0.63 0.18

RLL [arb. units] 371.99 15.78 386.75 19.54 380.32 17.29

M = mean; SEM = standard error of the mean

This indicates that the typically observed CIT effect (i.e., response differences

between the known original and unknown control items) is replicated for EDA, but not

for pHR or for RLL. These findings are in line with the former evidence from CIT

studies: When subjects answer truthfully instead of deceptively, the RLL and pHR

typically show much smaller effects, whereas, EDA shows equally large effects

(Ambach et al., 2008; klein Selle et al., 2015). In those studies, it was argued that

pHR and RLL do not reflect orienting, but rather inhibition or concealment-related

processes. As a result, EDA can be regarded as the most sensible parameter in this

study.

As a new finding, EDA responses to the misleading items were greater than

those to the control items, but smaller than those to the original items. In line with our

hypothesis, the participants showed greater ORs to the original items than to the

misleading ones. The original items must have gained special importance and

meaning for the individual participant but not the misleading ones. A possible

explanation is that the visual encoding of the original items might have been better

than the textual encoding of the misleading items. It was found earlier that visual

encoding exceeds textual encoding in depth, although textual encoded items were

treated as familiar (Dodson & Markham, 1993). Furthermore, the answer given in the


CIT is an important confound of this finding: More original than misleading items were

affirmed. Consequently, a direct comparison of the affirmed original items and

affirmed misleading items was conducted.

For the following analysis, false memories in the CIT refer to trials in which a

misleading item was affirmed, whereas, correct memories refer to affirmations of

original items. We selected participants who affirmed at least one misleading item

and had valid physiological data; this reduced the sample size to 26 (EDA) and 31

(pHR, RLL), respectively. False memories compared to correct memories were not

accompanied by smaller EDA, t (25) = 0.54, p = .298, d = 0.16 (see Figure 3), or by

greater pHR, t (30) = 0.52, p = .305, d = 0.14, or by greater RLL responses, t (30) =

0.46, p = .328, d = 0.14. A sensitivity analysis was conducted using G*Power (version

3.1.9.2). For a two-tailed t-test for paired samples, assuming a power of 95 %, an

alpha level of 5 %, and a sample size of 26, only effects of d = 0.74 or greater could

be found, with a probability of 95 %. Hence, more participants showing false

memories and more false memories per participant would have yielded more

meaningful results.

Figure 3. Z-transformed EDA of false (affirmed misleading items) and true memories

(affirmed original items) in the CIT. (Error bars represent 95% confidence intervals.)


The lack of differences in the physiological correlates between false and

correct memories is contrary to the findings of Baioui and his colleagues (2012) who

found greater EDA responses associated with true recognition than with false

recognition in a Deese-Roediger-McDermott (DRM) paradigm. It was concluded that

a physiological differentiation of falsely recognized and truly recognized items is

possible. If so, the EDA would reflect the objective knowledge rather than the

subjective belief of having it. Our findings, however, indicate that no differentiation

between false and correct memories is possible by EDA in the misinformation

paradigm. It has to be considered that false memories in the DRM paradigm are

different from false memories induced by misinformation: False memories in the

misinformation studies refer to previously encoded items for which a memory trace

was created. In contrast, false memories in DRM studies occur without such

encoding and memory trace. Assuming that EDA reflects not only the subjective

feeling of recognition but also the objective existence of a memory trace would help

to resolve the apparent contradiction between the findings of both studies. In

misinformation studies, it is debated whether source confusion is involved in the

formation of false memories.

Hence, differences in physiological data between different source identification

types were of special interest. In the source identification task, answers to original

and misleading items were assigned to three categories: Correct (original item

attributed to video, misleading item to text), incorrect (original or misleading item

attributed to CIT), and confusing source identifications (original items attributed to

text; misleading items to video). The physiological data gathered in the CIT then was

assigned to the different types of source identification and compared. A significant

effect of source identification type was found for EDA, F (1.19, 25) = 7.84, p = .007,

= 0.25 (see Figure 4), but not for pHR, F (1.34, 28) = 1.30, p = .275, = 0.05, or

for RLL, F (1.70, 29) = 1.10, p = .334, = 0.04. Compared with incorrect source

identifications, greater EDA responses were found for correct source identifications, t

(62) = 10.57, p < .001, d = 1.97, as well as for confusing source identifications, t (22)

= -2.41, p = .025, d = 0.77. Confusing source identifications did not differ from correct

source identifications, t (23) = 0.37, p = .718, d = 0.11.


Figure 4. Z-transformed EDA of correct, incorrect, and confusing source identifications. (Error

bars represent 95% confidence intervals.)

In summary, greater EDA responses were observed when items, be they

original or misleading, were judged as presented in the video or text, compared to

when items were reported as first seen in the CIT. If, however, original or misleading

items were attributed as first seen in the CIT, they were not recognized as being

significant. Although these items supposedly had gained special meaning during

encoding, the orienting response, which was reflected in the EDA responses,

significantly decreased with this misattribution. This indicates that EDA reflects

subjective identification of items as important rather than their objective importance.

3.4 Limitations

One main limitation restricts the amount of conclusions drawn by this study:

For analyzing physiological correlates of false memories, the number of falsely

affirmed misleading details and the number of source confusions between original

and misleading details was relatively small, resulting in a limited test power. In further

studies, more false memories should be induced so that differences in the


accompanying autonomic measures can be tested with more statistical power. First,

this may be accomplished by optimizing the retention interval. Extending the duration

of the retention interval to one or two weeks might be preferable over distractor tasks,

which were commonly used and also employed in this study. With increasing

retention intervals, higher false memory rates were observed (Pansky, Tenenboim, &

Bar, 2011; Wilford et al., 2014). Additionally, the number of original details presented

in the video should be increased, as meta-analytic studies regarding the CIT showed

that physiological effects increase in power with increasing the number of stimulus

categories (Ben-Shakhar & Elaad, 2003). Furthermore, the details used as original

information should be presented in the video as peripheral instead of central details

(Heath & Erickson, 1998; Paz-Alonso & Goodman, 2008). In this context, it remains

unanswered whether textual or numeric details might be superior to pictorial

information. A replication study is needed to face the main limitation of low statistical

power. Considering the above suggestions might particularly allow differentiating the

EDA correlates of subjective versus objective components of recognition.

Another limitation of the study is the usage of more control than memorized

items. Similar to other studies using the CIT, memorized items (i.e., original or

misleading items) constitute a relative oddball among the more frequent control

items. Differences in physiological responding between control items and memorized

items can be due to any combination of these effects. Yet, this possible confound is

limited to comparisons including control items.

3.5 Conclusion

The present study replicated the misinformation effect with newly developed

study materials. Three different recollection tasks showed similar misinformation

effects. A randomization and balancing scheme methodologically improved the

standard misinformation procedure. With regard to the expected decrease of

misinformation effects by a cued recall task, the procedure employed in this study did

not facilitate the correct source identification to a sufficient degree. It remains

questionable whether cued recall is principally able to reduce misinformation effects

or not. The typical CIT effect was replicated for EDA but not for pHR or RLL, which is

in line with the current understanding of sub-processes ongoing in the CIT: EDA is

discussed as reflecting orienting, whereas, pHR and RLL are related to concealment

and inhibitory processes. As the source identification task revealed, EDA response


relates to the subjective importance a participant attributes to an item rather than its

actual importance. In summing up, combining the misinformation paradigm with the

CIT proved suitable to examine the psychophysiology of false memories.


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