Optimising the Use of Synaesthetic Metaphors in Advertising: The Roles of Metaphor Construction and Complexity
Metaphors; Synaesthetic Metaphors; Advertising; Persuasiveness
Metaphors are commonly employed in advertising to increase its persuasive effects. Research suggests that metaphors are most effective when conveyed visually, however linguists believe that additionally providing a linguistic cue, designed to help metaphor interpretation, can increase their effectiveness. In addition, metaphors of medium complexity are believed to drive higher effectiveness than simpler or more complex metaphors. This research aims to investigate how these issues relate to synaesthetic metaphors, those that reference two sensory modalities. Participants were presented with print adverts, the visual and linguistic elements of which were adapted to contain literal messages or synaesthetic metaphors. Participants provided ratings of appreciation, purchase intentions, and perceived advert complexity. Synaesthetic metaphors were shown to produce significantly stronger persuasive effects, measured via appreciation and purchase intentions, when conveyed visually and when rated highly on complexity. Implications for advertisers, who wish to incorporate and optimise the use of synaesthetic metaphors in print advertising, are discussed.
Participants This research recruited 122 participants via opportunistic sampling. Participants were native speakers of English aged 18 or over, with no history of disabilities in any of the sensory domains (sight, hearing, smell, taste and touch). Twelve participants were excluded due to incomplete survey responses and/or ineligibility according to the inclusion criteria, resulting in a sample of 110 participants (88 female, 20 male, 2 other; age: M = 38.11, SD = 18.60) who were randomly assigned to complete one of four surveys (see Design). The demographics per survey are detailed in Table 1. Table 1 The Sample Size and Demographics Per Survey N Gender Age Male Female Other Mean SD Survey 1 28 4 24 - 43.68 18.94 Survey 2 29 7 21 1 32.90 17.77 Survey 3 28 5 22 1 35.07 17.09 Survey 4 25 4 21 - 41.32 19.48 Materials Advert Stimuli The advert stimuli used in this research were gathered and modified by previous researchers at Francesca Citron’s laboratory (Chen, 2019; Pan, 2019). The researchers obtained real adverts containing synaesthetic metaphors from the dataset of Bolognesi and Strik Lievers (2018). These base adverts were labelled 1-8 (see Appendix A). The researchers produced three modified versions of each base advert. They edited the visual and linguistic elements, of product images and slogans respectively, to contain, or not contain, a synaesthetic metaphor, in accordance with the ‘Metaphor Category’ they represented. One version of each base advert conveyed a synaesthetic metaphor in both the visual and linguistic advert elements (Visual-Linguistic SM; labelled “VL”). One version contained a synaesthetic metaphor in the visual, but not linguistic, advert elements (Visual SM Only; labelled “V). One version contained a synaesthetic metaphor in the linguistic, but not visual, advert elements (Linguistic SM Only; labelled “L”). The final version served as a control as a synaesthetic metaphor did not appear in the visual or linguistic advert elements (No SM; labelled “N”). These metaphor categories are illustrated by the example of Advert 2 (see Figure 1). In 2VL, the image displays a lemon wearing a studded mask whilst the slogan writes “A PLEASINGLY SHARP TASTE”. This synaesthetic metaphor, conveyed by the image and slogan, attributes the lemonade as having a sharp taste, which references the sensory modalities of touch (via “sharp” in the slogan, and the studded mask in the image) and taste (via “taste” in the slogan, and the lemon in the image). In 2V, the synaesthetic metaphor containing the image of 2VL is retained, however the slogan, “A PLEASINGLY SOUR TASTE”, no longer contains a synaesthetic metaphor since it a) is literal and b) only references one sense (via “sour taste”). In contrast, 2L retains the synaesthetic metaphor-containing slogan of 2VL (“A PLEASINGLY SHARP TASTE”) but contains a literal product image. The synaesthetic metaphor here therefore only appears in the linguistic advert elements. In 2N, the image of 2L and the slogan of 2V appear, meaning that a synaesthetic metaphor is not conveyed in either the visual or linguistic elements. This process, of creating four versions per base advert, resulted in 32 advert stimuli. Within this, eight adverts, one per base advert, represented each metaphor category. The advert stimuli were labelled according to their base advert number (1-8) and their metaphor category (VL; V; L; N). For example, 1VL presents the version of base advert 1 belonging to the visual-linguistic SM category. The full stimuli set can be viewed in Appendix A. The synaesthetic metaphors constructed in the stimuli, and the sensory domains referenced (see Table 2), are briefly explained in Appendix B. All adverts were written in English and printed in full colour. Online Survey This research used a modified version of a Qualtrics (Provo, UT) survey produced by Chen (2019) and Pan (2019). The original survey featured 11 bipolar Likert scales per advert stimuli, all intended to contain 5-points but with some mistakenly containing 7-points. This was corrected in the present research, with all scales measured 0-5. The first four scales, measuring “Appreciation”, asked participants whether they liked the advert (Agree – Disagree) and whether they perceived it as “Bad”–“Good”; “Unpleasant”-“Pleasant”; and “Unappealing”-“Appealing”. The two following questions measured “Perceived Complexity” and concerned participants’ perception of the advert as “Unclear”–“Straightforward” and as “Difficult to Understand”– “Easy to Understand”. The next three questions measured “Purchase Intentions”. In the original survey, these focused on the purchase intentions of the respondent. This was modified in this research, following Pan (2019) and Chen’s (2019) finding that purchase intentions were merged with appreciation in PCA, and the belief that personal factors influence purchase intentions (Habich-Sobiegalla et al., 2019). The current survey instead asked respondents whether others would like to purchase the product, soon and in the future, and whether the advert would make others more likely to purchase the product (“Disagree”-“Agree”). On the final two questions, measuring “Perceived Realism”, participants rated the advert as “Unrealistic”–“Realistic” and “Fictitious”– “Real”. This question set was presented per advert stimulus, resulting in a total of 88 questions per survey. Figure 1 The Four Versions of Advert 2 Table 2 The Sensory Domains Referenced by Each Advert, When Sensory Metaphors Were and Were Not Present Sensory Domains Referenced SM Present No SM Present Source Target Advert 1 Auditory Taste Taste Advert 2 Tactile Taste Taste Advert 3 Tactile Taste Taste Advert 4 Visual Auditory Auditory Advert 5 Visual Auditory Auditory Advert 6 Visual Smell Smell Advert 7 Auditory Taste Taste Advert 8 Tactile Taste Taste Design In an independent groups design, participants were randomly assigned to complete one of four online surveys. The independent variable was the metaphor category of each advert. Each survey presented eight adverts, one belonging to each of the eight base adverts and two belonging to each of the four metaphor categories. For example, Survey 1 presented two Visual-SM only adverts (Adverts 1 and 5), two Linguistic-SM Only adverts (Adverts 2 and 6), two Visual-Linguistic SM adverts (Adverts 3 and 7), and two No-SM adverts (Adverts 4 and 8), with one version of each base advert appearing only once. Table 3 lists the advert stimuli presented per survey. The four dependent variables, of ‘Appreciation’, ‘Purchase Intentions’, ‘Perceived Realism’ and ‘Perceived Complexity’, are further detailed in Materials and Variable Construction. Table 3 The Adverts Displayed per Survey, In Order of Appearance Survey 1 Survey 2 Survey 3 Survey 4 1V 3N 5VL 7L 2L 4V 6N 8VL 3VL 5L 7V 1N 4N 6VL 8L 2V 5V 7N 1VL 3L 6L 8V 2N 4VL 7VL 1L 3V 5N 8N 2VL 4L 6V Procedure The entirety of this study was completed on Qualtrics (Provo, UT). Participants were informed of the researchers' background and requirements, and briefed of their anonymity, confidentiality and right to withdraw (Appendix C), before providing informed consent (Appendix D). Participants declared their age and gender and confirmed that English was their native language and that they did not suffer from any sensory inabilities. Participants viewed each of the eight adverts in turn and answered 11 five-point Bipolar Likert scales per advert (see Materials, Survey). Finally, participants were debriefed, reminded of their terms of participation, and provided with further reading (Appendix E). The study took 10 minutes to complete.
Follow up on previous research in Francesca Citron's lab
An investigation into automatic imitation: Comparing live and video setups, the effect of prior training and the influence on affective empathy
automatic imitation, empathy, imitation training, inhibition training, mirror neuron system, self-other distinction
If decreased Automatic Imitation(AI) improves empathetic abilities, then selfother distinction processes are probably the mediating factor between imitation and empathy. But if increased AI improves empathy, then probably imitation is at the core of the socio-cognitive functions. Until now, it was shown that decreased AI improved visual perspective taking, corticospinal empathy and self-reported empathy. Also, the studies until now focus on video AI stimuli. But to understand whether AI has a more direct relation to mimicry, I developed also live paradigm. My research questions were firstly, what effect will imitation training and inhibition training have on AI. Secondly, whether live stimuli AI will have the same effects on AI testing (inhibition versus imitation) and arousal empathy testing. Thirdly, whether the effects are transferable on arousal empathy. As expected, there was a significant decrease of AI in the video inhibition condition in comparison to the video imitation condition. Unexpectedly, a significant, but weak increase in arousal empathy was observed in the video imitation condition and not in the video inhibition group. The difference in AI and arousal empathy between the life imitation group and the life inhibition group were not significant. The results give a new perspective on the topic of AI. If the results can be reproduced by more studies, then probably imitation is more important than self-other distinction processes or maybe arousal empathy is different from other forms of empathy. Finally, the insignificant results in the life imitation versus life inhibition training indicate that there are maybe confounding factors in live AI research or that the video AI designs are more artificial than it is assumed.
Participants Sixty(N=60) participants were recruited in a two-by-two factorial design, and divided equally among two between-subject factors. The first factor is Stimulus, whereby AI will be measured in response hand actions performed by an experimenter sat across a table from the participant (Live) or to the actor’s pre-recorded hand-action stimuli presented on a monitor. The second factor is Training, whereby participants will undertake a brief period of imitating the actions of the live or videoed handaction stimuli (IMI) or performing the opposite actions (IMI-IN). The participants were recruited from students of the University of Lancaster. Random selection could not be used, because of practical and logistical difficulties. Hence, most of the participants were Masters students and some were PhD students. The participants were either friends and acquaintances or they had the motivation to win a 10 pounds amazon voucher. In many cases they had the motivation to participate in my study, because they also wanted me to participate in their study. Firstly, we conducted the experiments with the video paradigm (15 participants in the imitation training condition and 15 participants in the inhibition training condition) and then we conducted the experiments of the live paradigm (15 participants in the imitation training condition and 15 participants in the inhibition training condition). We use random assignment for the recruitment in the training condition, thusly, every participant was randomly assigned in either the imitation training or in the inhibition training condition. For instance, we did not conduct first 15 experiments in the imitation training condition and then 15 experiments in the inhibition training condition, but every participant was in a different training condition. Nevertheless, one possible limitation may be that we did not do the same for the stimulus condition, as we conducted first the experiments of the video condition and then the experiments of the real condition. Materials The experiment was conducted on the personal laptop of the researcher. No specific room was needed for the experiment to have more flexibility with the data collection. The software Mathlab and the program Cogent were used to code and make the script. In order to measure affective empathy, we used the Multi-faceted empathy test (MET). It consisted of 40 images, but it was split in two METS to include also a pre-test approach. For imitation training and for inhibition training we used three images of the hand of the researcher. In one image, the hand of the participant was in the neutral position. In the second image, the index finger was lifted and in the third image the middle finger was lifted. Design and Procedure First, we conducted the experiments of the video paradigm (30 participants) and then we conducted the experiments of the live paradigm. The experimental procedure was divided into four phases: First, participants will do the MET (Multifaceted empathy test). The first Met had 22 images. The MET tests affective empathy. Participants must choose from a scale from 1 until 4 how strong is their affective arousal when they see the image. The MET took approximately 5-10 minutes, depending on the participants. After the first MET, participants did either imitation training or imitation inhibition training. The default position for the participants in this task was to press two buttons all the time with their right-hand index and middle finger. In the video condition, they pressed button A and button Z -with their right-hand index and middle finger, and in the live paradigm they pressed the left and right arrow button -with their right-hand index and middle finger respectively. In imitation testing, they had to lift their index finger when they saw a lifted index finger (video or live) and to lift their middle finger when they saw a lifted middle finger (video or live). Both actions should be done as quickly as possible. In the inhibition training the participants did the opposite actions of the observed movements. Thus, when they saw a lifted index finger, they lifted their middle finger as quickly as possible. When they saw a lifted middle finger, then they lifted their index finger, again, as quickly as possible. The training phase consisted of two tasks and a small break. Every task had a duration of 6 minutes approximately. After the training, there was the testing phase. Here we tested the effects of training on Automatic Imitation. The training phase consisted of two 6 minutes tasks with a break between the two tasks. In the first task, the participants had to lift only their index finger as quickly as possible, irrespective of the lifted finger they saw (either in video or in the live condition). In the second testing task, they had to lift their middle finger as quickly as possible, again irrespective of the lifted fingers that they saw. Automatic imitation is measured as the difference in their latency to lift the pre-defined finger when the observed action is the same in relation to when the observed action is the opposite finger movement. For instance, when the participant lifts his index finger, we measure the reaction time of his movement, when he sees a lifted index finger and when he sees a lifted middle finger. Automatic imitation is the difference of those two reaction times. This testing phase lasted 10 minutes, comprising 100 trials divided among two blocks. After the lifting of the finger, the participants pressed the button again (default position). Thusly, the reaction times were measured by how fast the participant would lift his finger. To ensure that the training and the testing really focused on Automatic Imitation and to exclude the spatial compatibility confounds, the participants were perpendicular to the stimuli (in both the video and the live condition). Sadly, we could not have the same perpendicular angle for both conditions, but the difference of the degrees was very small. In the video condition, the angle was approximately 45 degrees (the fingers of the participants were at the buttons A and Z and the stimuli were on the laptop screen) and on the live condition, the stimuli were approximately 90 degrees perpendicular (the fingers of the participants were on the right and left arrow and the real stimulus of the experimenter was at the buttons “tab” and “shift”). In the final phase, the participants did a second MET test. It was exactly like the first, only with different images. The order of the MET tests was changed with every participant. In other words, one participant did first the MET.1 and in the end the MET.2, while the other participants did first MET.1 and in the end, they did the MET.2. Both MET tests different parts of the same MET test, but we splitted the test arbitrarily in the middle to have also a pretest empathy base. I changed the order of the MET tests with every participant to exclude the factor that some pictures of the Test are less difficult than the others. Thus, if we find a large and statistical significant difference in the final MET between the imitation and the inhibition training group, then we can say that in both training conditions we changed equally the order of the MET tests, so the observed change in empathy performance does not have to do with some images being easier or more difficult than the others. In the IMI condition, the participants were required to lift their index finger when they see the stimulus hand (live or videoed) perform an index-finger action, or lift their middle finger when they observe a middle-finger action; in the IMI-IN condition they will do the opposite - they will lift their index finger when they observe a middle-finger action or lift their middle finger when they see an indexfinger action. In the second phase, the participants performed AI testing, during which they will be required to make a pre-defined finger-lifting movement (index- or middlefinger lifting action) as soon as the stimulus hand (live or videoed) moves, regardless of whether the observed movement is an index- or middle-finger lifting action. In the third phase, participants will perform the Multi-Faceted Empathy Test, during which they will be presented with 30 images of individuals expressing emotions and asked to judge which emotion is being expressed. The accuracy of their responses will be recorded. This final phase takes 10 minutes.
Investigating the effects of dimensionality and referent variability on word learning in autism and typical development.
Dimensionality, referent variability, word learning.
The ability to learn words from pictures could give children another forum to develop their lexical understanding and vocabulary. This is particularly important for children with developmental disorders such as Autism. This research investigated how word learning processes (referent selection, retention and generalisation) in autism and typical development are influenced by learning from pictures and objects, including single and multiple exemplars of symbols. The participants in this study were 16 typically developing children, M age=3.68, the TD group was composed of 7 males (43.75%) and 8 females (56.25%). And 16 children diagnosed with ASD, M age=9.37, 8 males (50%) and 8 females (50%). Participants looked at pictorial and object referents. This was to differentiate whether there was a preference in word acquisition and retention, depending on the structure of the stimuli. It was expected that word referent selection, retention and generalisation would be more accurate in the object condition compared to the picture condition, as participants would not be relying of picture-word-associations. Participants also examined words paired with either single or multiple exemplars of referents, to determine whether multiple exemplars of shaped matched referents would promote shape-based generalisation in the ASD group, which has been shown to be impaired (Hartley and Allen, 2014). It was expected that retention would be superior when learning directly from objects in both the ASD and TD groups, which was found in this research. We also anticipated that labelling from multiple exemplars, rather than single exemplars, may scaffold more consistent shape-based generalisation. We found that referent selection was more accurate in both groups in the multiple exemplar condition compared to the single exemplar condition. The implications of this research are that we can further understanding of how symbols or objects benefit word learning, retention and generalisation in ASD or TD children. And whether there are any cognitive differences in the ASD and TD groups when it comes to word learning processes.
Participants The participants in this study were 16 minimally verbal children with ASD (M age = 10.42 years, SD = 3.29) and 16 typically developing children (M age = 3.64, SD = 1.64). Children with ASD were recruited from the specialist schools Dee Banks School in Chester, and Hinderton School in Ellesmere Port. Typically developing children were recruited via opportunity sampling, via the social media platform Facebook through advertisement. All the children with ASD received their diagnosis from a qualified clinical or educational psychologist. This was obtained using standardised instruments (i.e. Autism Diagnostic Observation Scale and Autism Diagnostic Interview—Revised; (Lord, Rutter & Le Couteur, 1994, Lord, Rutter, DiLavore & Risi, 2002) and expert judgment. Clinical diagnosis was confirmed for children with autism using the Childhood Autism Rating Scale (CARS; Schopler, Van Bourgondien, Wellman & Love, 2010), which was completed by a class teacher (Raw Score M score = 37.26, Raw Score range = 27 – 53.5). The ASD were tested for non-verbal vocabulary using the British Picture Vocabulary Scale (BPVS; Dunn, Dunn, Whetton, & Burley, 1997), which was conducted by the experimenter. Mean receptive vocabulary of children with autism was years 2.84 (range = 6 years – 2 years 4 months). Some of the children diagnosed with ASD who participated in this study were current PECS-users with impaired expressive language skills. Most of the children with ASD who participated in this study were functionally non-verbal (no spoken words), although, some produced speech of 1–2 words in length (however, much of this was echolalia) and one child could speak some short phrases over three words in length. Therefore, the sample was linguistically representative of children with ASD who receive and may benefit from picture-based communication interventions. Participants had 1–6 years’ experience of using PECS. When recruiting the children diagnosed with ASD, the experimenter emailed specialist schools, explaining the study and whether the school would be interested in participating. When recruiting the TD children, advertisements were put on social media platforms such as Facebook (see Appendix A). The information poster instructed the parents to contact the experimenter via email if they were interested in their child participating. The study was approved by the Lancaster University Ethics Committee and informed consent was obtained from parents before children were included in the study. See Appendix B for completed and approved Lancaster University Ethics Committee form Materials For the warm up test trials in all tests the participants were shown three familiar objects (for example; dog, bus, chair), these were small laminated pictorial symbols. In the picture, single and multiple exemplar conditions the participants were shown 12 laminated pictorial symbols, 6 familiar and 4 novel. The participants saw each novel symbol once and the novel symbol twice. Participants saw the same named novel symbols in the retention test trial, in this trial the named novel objects were shown to each participant twice. In the generalisation test trial, the participants saw shape matches (same object or picture, for example both would be paperclips) to the named novel objects from the referent selection test trial and retention test trial, however they were different colour variations (for example a red and blue paperclip). In the object condition participants followed the same test layout and number of referents as the other conditions, the difference being that the stimuli were actual objects compared to pictorial symbols. The words for the familiar stimuli were gathered using the CDI database (Fenson, Dale, Reznick, Bates, Thal, Pethick, Stiles, 1994) and appropriately aged matched to the non-verbal age range of the ASD children and the chronological age of the TD children (See Appendix C). The words for the novel stimuli were picked from the NOUN database (Horst & Hout, 2016), these were picked to all be two syllables long and words to have different phonological sounds per set. In the picture condition were, Gloop, Virdex, Akar and Teebu. For the novel words for the object condition were, Fiffin, Tranzer, Brisp and Pentants. For the single exemplar condition the novel word were, Tulver, Kaki, Jefa and Blicket. For the multiple exemplar condition the novel word were, Zepper, Toma, Modi and Chatten (see Appendix D) Objects were obtained through the equipment assistant at Lancaster University and purchased through amazon. Appendix E is an example warm up selection trial which a participant saw, and the response form completed by the experimenter. Appendix F is an example of a referents selection trial, which participant saw, and the response form completed by the experimenter. Appendix G is an example of a retention test trial a participant will have seen, and the response form completed by the experimenter. Appendix H is an example of the generalisation test trial which a participant saw, and the response form completed by the experimenter. All test trials were pseudorandomised per participant per condition and trial. Therefore, while all the participants will have seen the same number of familiar and novel objects or pictures. And each picture or object will have had the same name per shape matched object they will have been in a different order. Therefore, a different response form was required per participant, for the change in referent location and set order. Procedure Prior to the children participating the parents received, the information sheet (see Appendix I), and the consent form (see Appendix J). On the last day of experiments the experimenter brought the debrief forms (see Appendix K). Participants were test individually, in their schools for the children with ASD or in their own homes for the TD children, and were always accompanied by a familiar adult, teaching assistant or parent. The participants were seated at a table opposite the experimenter; the materials were placed within reaching distance of the participants. Children were reinforced throughout the session; correct performance was only reinforced during the warm up trial. The first test examined the picture condition vs the object condition, the second test examined single vs multiple exemplars. The tasks were between participants, as they were examining the results of the TD group compared to the ASD group, however for the analysis some within participants analysis was carried out to determine accuracy between test conditions (e.g. picture vs object). Each task always consisted of a warm up stage, referent selection trial, distracter familiarisation trial, retention test trial and generalisation test trial. The test trials were based on that done by Horst and Samuelson in 2008, with the extension of the generalisation trial which was not included in the Horst and Samuelson (2008) study. Picture Condition vs Object Condition Tests Warm Up Stage Participants were shown three sets of three familiar objects, in the object condition, in the picture condition participants were shown three familiar pictures. Participants were asked to identify each in turn, the warm up objects or pictures were pseudorandomised per participant, changing the order and location per participant per condition. The pictures or objects were removed and reordered after each set, and the participants response recorded. Referent Selection Trial Participants were shown four sets of stimuli (pictures for the picture condition and objects for the object condition) the sets of stimuli were different per condition, each consisting of two familiar items and one novel item, each set was shown four times, the novel referent was shown twice and the two familiar referents once. The order and location of the sets was pseudorandomised for each participant, the location of the novel object was never in the same location twice consecutively, and a novel or familiar object or picture was never requested more than twice consecutively. Sets were not presented twice in a row. Distractor Familiarisation To control for novelty or familiarity preferences in the subsequent test trials, children were shown all the novel objects that used in generalisation test trials. The new novel objects were a different colour variation of a previously seen novel object, which was named in the referent selection trial. Novel objects or pictures were shown against a previously named novel objects or pictures, which was not a shape or colour match to the new novel object. Objects or pictures were shown so one previous named novel object was shown against a new novel object or picture. The objects were not shape or colour matched, the objects or pictures were placed in front of the participant, they were not asked to identify them just to “look”. Retention Test Trial Retention trials will assess children’s memory of the newly-learned word-referent pairings. Participants were shown four sets; each set was shown twice with the target object requested twice. The sets were made up of three named novel objects, names were picked from the NOUN database (Horst & Houst, 2016), each made up of two syllables, objects or pictures were picked on the basis that participants items that would be novel to them, for instance gym or plumbing equipment. Objects and pictures which were not shape or colour matches to each other and were shown in the referent selection test trial. The order and location of each object or picture per set was pseudorandomised per participant per trial. The location of the novel object was never in the same location twice consecutively, and a novel or familiar object or picture was never requested more than twice consecutively. Sets were not presented twice in a row. Generalisation Test Trial Generalisation trials will assess children’s extension of labels to new items. Participants were shown four sets; each consisting of three objects or pictures, each set was shown twice with the target object being requested twice. The objects or pictures in the sets were shape matches to the objects or pictures shown in the referent selection, and retention trials, but different colour variations. All the shape matched objects or pictures were also colour matched to a non-shape matched object from the previous conditions. The order and location of each object or picture per set was pseudorandomised per participant per trial. The location of the novel object was never in the same location twice consecutively, and a novel or familiar object or picture was never requested more than twice consecutively. Sets were not presented twice in a row. Single vs Multiple Exemplars Tests Warm Up Trial Participants were shown three sets of three familiar pictures in both the single and multiple exemplar conditions. Participants were asked to identify each in turn, the pictures were pseudorandomised per participant, changing the order and location per participant per condition. The pictures were removed and reordered after each set, and the participants response recorded. Referent selection Trial Participants were shown four sets of stimuli, the sets of stimuli were different per condition, each consisting of two familiar items and one novel item, each set was shown four times, the novel referent was shown twice and the two familiar referents once. In the multiple exemplar trial, two differently-coloured versions of each unfamiliar object were named (one per novel trial for each set). The order of the sets was pseudorandomised for each participant. The order and location of each object or picture per set was pseudorandomised per participant per trial. The location of the novel object was never in the same location twice consecutively, and a novel or familiar object or picture was never requested more than twice consecutively. Sets were not presented twice in a row. The order and location of the sets was pseudorandomised for each participant, the location of the novel object was never in the same location twice consecutively, and a novel or familiar object or picture was never requested more than twice consecutively. Sets were not presented twice in a row. Distractor Familiarisation To control for novelty or familiarity preferences in the subsequent test trials, children were shown all the novel pictures that used in generalisation test trials. The new novel pictures were a different colour variation of a previously seen novel picture referent, which was named in the referent selection trial. Novel pictures were shown against a previously named novel pictures, which was not a shape or colour match to the new novel picture. Pictures were shown so one previous named novel referent was shown against a new novel picture. The referents were not shape or colour matched, the pictures were placed in front of the participant, they were not asked to identify them just to “look”. Retention Test Trial Retention trials will assess children’s memory of the newly-learned word-referent pairings. Participants were shown four sets; each set was shown twice with the target referent requested twice. The sets were made up of three named novel objects, names were picked from the NOUN database (Horst & Houst, 2016), each made up of two syllables, pictures were picked on the basis that participants items that would be novel to them, for instance gym or plumbing equipment. Pictures which were not shape or colour matches to each other and were shown in the referent selection test trial. The order and location of each picture per set was pseudorandomised per participant per trial. The location of the novel object was never in the same location twice consecutively, and a novel or familiar object or picture was never requested more than twice consecutively. Sets were not presented twice in a row. Generalisation Test Trial Generalisation trials will assess children’s extension of labels to new items. Participants were shown four sets; each consisting of three pictures, each set was shown twice with the target object being requested twice. The pictures in the set were shape matches to the picture shown in the referent selection, and retention trials, but different colour variations. All the shape matched pictures were also colour matched to a non-shape matched object from the previous conditions. The order and location of each picture per set was pseudorandomised per participant per trial. The location of the novel object was never in the same location twice consecutively, and a novel or familiar picture was never requested more than twice consecutively. Sets were not presented twice in a row. In the multiple exemplar condition the generalisation test trial introduced the shape matched referent in a third colour that was coloured matched to a referent of a different shape matched seen in the referent selection or retention test trial.
Accessing Cortical Hyperexcitatbility and Its Predisposition Using Two Types of Measurements
This study aimed to explore in depth about the cortex hyperexcitability. In order to do so, the study will use the pattern glare task and three questionnaires. These three questionnaires include the Cortex Hyperexcitability Index II, Cardiff Anomalous Perceptions scale, and the Multi-Modality Unusual Sensory Experiences Questionnaire. The pattern glare task induces on-spot hallucinations and distortions, while the questionnaires measure the long-term daily unusual sensory experiences one may have experienced. In this study, both the questionnaires and the task measured the same underlying factor, the cortex hyperexcitability. In the sense that it was hypothesized that the predisposition of seizure-like hallucinations and distortions and of daily-based hallucinations and anomalous experiences should be associated in a particular way. The pattern glare task had two blocks in the experiment, one with a blindfold and the other without. They were presented to participants in different orders to counterbalance the order effect. In between the two blocks, the participants answered the three questionnaires. The result of the study showed no significant effect of the blindfold, suggesting that wearing the blindfold for five minutes neither increased the sensitivity of the eyes nor the visual cortex. Most of the relationships between the pattern glare and questionnaires failed to be significant. The investigation on the association between the predispositions of the two types of hallucinations also failed to show any significance, only MUSEQ and pattern glare has a significant correlation. The migraine and migraine with aura groups appeared to be more sensitive to the phosphene phenomena. Their sensitivity, though the results were not significant, could be clearly observed through descriptive statistics. Although the results and findings failed to prove the research hypothesis, probably due to the main limitation of the poorly presented stimuli, the current study to some extent was able to expand the current understanding of cortex hyperexcitability demonstrated by the previous works, and further offered more possibilities for future studies.
Along with the pattern glare task, there were three more questionnaires used in the study, these are MUSEQ (Mitchell et al., 2017), CAPS (Bell et al., 2006), and CHI II (Fong et al., in press). This study has been ethically approved by the Department of Psychology in Lancaster University on 11th May 2018. Participants The current study screened participants before they could take part in the experiment, the screening standard is whether they have been diagnosed with photosensitive epilepsy, epilepsy, or that they recently had a brain or eye surgery. This criterion was created as the viewing of the striped pattern of particular spatial frequencies may induce seizures in patients with photosensitive epilepsy (Wilkins et al., 1984). It turned out none were excluded due to disease or had a history of diseases. There was a total of 43 participants who took part in the study. Among them, 15 were males and 28 were females. The age ranged from 19 to 36, with a standard deviation of 2.92, and around half of the participants were native English speakers. The six participants who self-reported having a migraine or a migraine with aura were noted before the study, as the pattern glare task may induce or intensify their symptoms, which can cause visual discomfort, visual distortions, or a headache. Among the six participants who reported they had migraineur, three of them were migraineurs with aura. Stimuli and Procedure The current study used stimuli that were printed onto cards, and the stimuli were presented to the participants from around 50 cm away at eye level. The patterns were the same size at 20mm * 15 mm, all in black and white, and with the shape of the ellipse. According to the given conditions, the visual angle was calculated to be 12.84 degrees. The three questionnaires were all printed on paper, and the participants were asked to read aloud their answers instead of writing it down. The plain black blindfold which participants were asked to wear during the study was bought from the drugstore. Material There were three different patterns used in this study, the spatial frequency gratings for these patterns are 11 cpd (cycles-per-degree), 3 cpd, and 0.7 cpd respectively. All the patterns were achromatic, with a fixation dot in the centre of them. After each of the stimulus was presented, there were 17 questions which the participants had to answer. The questions asked about the intensity of the anomalous visual phenomena, the types of visual hallucinations, and whether they have a headache or dizziness after the experiment. The materials were adapted from the previous works of Braithwaite et al. (2014). The three questionnaires in between the two blocks of stimuli presentations were MUSEQ, CAPS, and CHI II. MUSEQ (Mitchell et al., 2017) has 43 items of six factors, including Auditory, Visual, Olfactory, Gustatory, Bodily sensations, and Sensed presence; the measurement is a five-point Likert scale which targets the frequency of USE. CAPS (Bell et al., 2006) has 32 items, also addressing the anomalous experiences from different modalities. For each item, if the participants confirmed that they have had related experiences, they then rated their experiences out of three five-point scales on distress, intrusiveness, and frequency. CHI II has 30 items, and each one will be questioned about its frequency and intensity. The measurement is a seven-point Likert scale, with zero as never or not intense and six as all the time or extremely intense. The questionnaire is the recently updated version of the original CHI, and the 30 items in it can be loaded onto three non-overlapping factors, includes heightened visual sensitivity and discomfort (HVSD), aura-like hallucinatory experience (AHE), and distorted visual perception (DVP). For the MUSEQ and CAPS, the original unrevised questionnaire was used during the experiments, however, only parts of the answers given was used in the analysis. This decision was made as the data analysis would be too complicated to take all the factors into consideration, especially when they are just partially related to the research question. Therefore, for the MUSEQ questionnaire, only Visual, Auditory, and Bodily modality were analysed, and for CAPs, the primary concern is exclusively about the temporal lobe experience factor. For the non-blindfold block, all three stimuli were presented; but for the blindfold block, only the medium and high CPD stimuli were included. The low frequency stimulus is excluded because it was too mild to induce any hallucination on the participants. Including it in the blindfold condition is more for its suggestibility; participants who have given a high rating for the low frequency stimulus may produce unreliable scores on the other measures as well (Wilkins et al., 1984). Therefore, participants with too high low PG value would be excluded from the analysis. Procedure Prior to the experiment, the participants were asked to sit in a specific spot where the distance between them and the stimuli was fixed at around 50cm. Then they were given the information sheet and consent form, which contained the information they needed to know in order to proceed with the study. On the consent form, there was a list of questions asking about specific medical conditions including epilepsy, photosensitive epilepsy, neuro and eye surgery, and migraine and migraine with aura. The researchers then confirmed that the participants did not suffer or had suffered from those conditions before the experiment could take place. The first phase of the experiment was the pattern glare test that comprised of two blocks, one with the blindfold and the other without. Participants were labelled with a number which was used as their order of participation. Participants with odd numbers had non-blindfold block first, and the ones with even numbers had blindfold block first. The numbering and manipulation of the block presentation were kept unknown from the participants. The blindfold block contained two stimuli presentation, one was the medium spatial frequency (SF), and the other was the high SF. The reason why the low SF one was not included is that it worked as a control in the non-blindfold block, as there is minor to no effect of this stimulus (Braithwaite et al., 2013, 2015). The blindfold wearing was prior to the presentation of the stimuli; thus, participants wore the blindfold for five minutes before the blindfold block. After the participants finished viewing each pattern, they would answer the 17 questions about the associated visual distortions. They were asked to read aloud the answers and the answers would be immediately recorded using a computer. There was no break in between each trial, and the participants would keep on viewing the next one once they finished all the questions. In between the two stimuli present blocks, the participants were asked to finish the three questionnaires: MUSEQ (Mitchell et al., 2017), CAPS (Bell et al., 2006) and CHI II (Braithwaite et al., in press). It takes approximately 20 minutes to complete the three questionnaires. After the questionnaires are completed, the next block of stimuli was presented with a blindfold or no blindfold respectively. After both of the blocks and the three questionnaires were completed, the debrief sheet was given to participants at the end of the experiment. The entire process took about 30 minutes for a native English speaker, for participants who speak English as their second language, the duration took slightly longer, at around 35 to 40 minutes.
N1 Adaptation: Exploring the Neuronal Basis of the Interaction Between Auditory Sensory Memory and Attention
neuropsychology, attention, auditory sensory memory, N1 adaptation, sensory processing, neural responses
The aim was to explore whether voluntarily focusing on repetitive auditory stimuli influences the lifetime of N1 adaptation, which indexes the lifetime of auditory sensory memory. Twenty-six neurotypical participants with self-reported normal hearing were recruited from Lancaster University. Electroencephalogram (EEG) recording took place in a sound-attenuated laboratory. A two-by-two factorial design was employed, where one factor manipulated the presence or absence of attention, whereas the other factor manipulated the stimulus-onset interval (SOI), which primarily served to calculate the lifetime of adaptation. Three different amplitude measurement methods were used to calculate the N1 amplitude, therefore three sets of statistical analyses were performed for each investigation. For the preliminary investigation, two-way ANOVAs were conducted to evaluate the impact of attentional focus (presence or absence) and SOI (short or long) on the amplitude of N1. For the primary investigation, paired-samples t-tests were conducted to evaluate whether the presence or absence of attention influences the N1 adaptation lifetime. The preliminary results indicated no significant difference in N1 amplitude between the presence and absence of attentional focus. There was also no significant difference in the SOI, except for one of the amplitude measurement methods, which showed greater N1 amplitudes in the Long SOI condition. The primary results indicated that whether attention was present or not showed no significant effect on the adaptation lifetime across all three amplitude measurement methods. However, the study suffered from low statistical power and possible issues with the methodological design due to the combined use of visual and auditory modalities to manipulate attentional focus. Therefore, it is inappropriate to draw conclusions from the findings of this study. Methodological improvements and theoretical implications were discussed.
Methods Section: Participants Twenty-six neurotypical participants with self-reported normal hearing (9 males, 16 females, 1 prefer not to say), all of whom were students from Lancaster University, were recruited using opportunity sampling via advertising on social media platforms and SONA. The age range of the participants spanned from 18 to 34 years (M = 22.85, SD = 2.55). Sixteen participants were excluded due to excessive electric noise, resulting in a remaining pool of 10 participants. All participants provided written consent and volunteered to participate in the experiment. The study received ethical approval from Lancaster University’s Department of Psychology. Stimuli The experiment employed the oddball paradigm to elicit auditory responses. The standards were presented at a constant rate of 210 repetitions per condition, while the deviants appeared unpredictably at a 5% probability (10 deviants per condition). The sequence of standards and deviants remained consistent across all conditions. The standards were presented as a 500-Hz pure tone, while the deviants were a 503-Hz pure tone. The duration of each tone was 100 milliseconds, with 10 milliseconds of linear onset and offset ramps. All tones were presented at a consistent and comfortable volume level (28% volume on Windows 10). The auditory stimuli were programmed and delivered using MATLAB. Design The study followed a two-by-two factorial design (see Figure 1). It included two attention conditions: Active and Passive. In the Active condition, participants were presented with a stream of standards and deviants while focusing on a fixation cross. Their objective was to count the occurrences of deviants. In the Passive condition, participants viewed a nature documentary displayed on a smartphone screen. Their objective was to count the number of animal species featured in the documentary while ignoring the stream of auditory stimuli playing simultaneously in the background. Both the fixation cross and the smartphone screen were positioned one metre in front of the participants. Additionally, there were two SOI conditions: Short SOI (1.7 seconds) and Long SOI (3.4 seconds). The oddball paradigm was integrated into a stimulus block design - with two types of stimulus blocks, each having a specific SOI. Note that the order of the conditions was randomized among participants. The purpose of the design was to manipulate attention towards repetitive auditory stimuli and calculate adaptation lifetime. The counting tasks in the Active and Passive conditions manipulated attentional focus. In the Active condition, the count-the-deviants task aimed to maintain participants’ attention on the repetitive auditory stimuli. In the Passive condition, the count-the-animal-species task aimed to divert participants’ attention away from the repetitive auditory stimuli using visual stimuli in the form of a nature documentary. Additionally, the counting tasks served as a quality control measure, excluding participants whose answer substantially differed from the correct answer. Conversely, the inclusion of both short and long SOI measured adaptation lifetime using the amplitude ratio (explained below in Data Analysis). Figure 1. A visual representation of the study’s two-by-two factorial design, encompassing four distinct conditions: Active with Short SOI (1.7s), Passive with Short SOI (1.7s), Active with Long SOI (3.4s), and Passive with Long SOI (3.4s). Procedure EEG was used as the method of data collection. The Enobio NIC2 suite recorded EEG data, using three dry electrodes (Fpz, Cz, and Fz) to capture neuroelectrical activity in the auditory cortex (Neuroelectrics, n.d.). Data recording was conducted in a sound-attenuated laboratory. The entire experiment lasted approximately 60 minutes, which included a 20-minute preparation period. Before the experiment, participants were sent an information sheet online and completed a consent form upon arrival. They were then fitted with an electrode cap and headphones, and instructed to avoid excessive movement during recording to minimise muscle artifacts. When recording was ongoing, participants were verbally given instructions at the start of each condition, and they were asked about their answers to the counting tasks after each condition. Short breaks were allowed when transitioning between conditions. After the experiment, participants were inquired about their age and gender, and received a verbal and written debrief regarding the true purpose of the study. Data Analysis We conducted a priori power analyses using G*Power 3.1. to determine the required sample size for testing the two hypotheses (Faul et al., 2007). For the preliminary investigation, results indicated that the required sample size to achieve 80% power for detecting a medium effect, at a significance criterion of α = .05 was N = 36 for a two-way ANOVA. For the primary investigation, results indicated that the required sample size to achieve 80% power for detecting a medium effect, at a significance criterion of α = .05 was N = 34 for a paired-sample t-test. Our recruitment target of 36 participants was based on the larger of the two required sample sizes. In data preprocessing, we discarded the first few trials from each condition to minimise initial variability in orienting and habituation effects, and excluded any unidentifiable N1 responses. Measuring the N1 amplitude is essential for estimating adaptation lifetime and conducting the planned data analysis. There are three methods available - N1, N1-P2, and mean voltage displacement. Notably, baseline correction was performed as a standard initial procedure, addressing a baseline that extended over 100 milliseconds within this experiment. The first method identifies and measures the N1 amplitude as the point of maximum negativity (Marton et al., 2018). The second method measures the peak-to-peak amplitude difference between N1 and P2, as it captures the relationship between the two and avoids the problem of a noisy baseline by not depending on the pre-stimulus baseline (Al-Abduljawad et al., 2008; Scaife et al., 2006). The third method estimates the mean voltage displacement (absolute amplitude value) over a specific time frame, particularly useful when the N1 component is difficult to identify, or the stimulus onset is ambiguous (Hoehne et al., 2020; Komssi et al., 2004). All three methods were employed to conduct a more comprehensive data analysis, given that consistent findings across different methods increase the reliability of results and inconsistencies can guide further investigation. In the traditional approach for estimating adaptation lifetime, one uses multiple stimulus blocks, each featuring varying SOIs ranging from 0.5 to 10 seconds. The ERP is derived separately for each stimulus block, and notably, the peak N1 amplitude is plotted as a monotonically increasing function of SOI. This relationship between the N1 amplitude and the SOI can be described as an exponentially saturating function, represented by the model equation A(1-e-(t-to)/τ), where A (amplitude), τ (time constant), and to (time origin) represent fitting parameters (Lü et al., 1992). Graphically, one fits the exponentially saturating curve to the measured N1 amplitudes. Here, the fitting parameter τ characterizes the steepness of the curve in seconds. τ signifies the SOI at which the amplitude curve reaches 66% of its way towards the saturation limit, indicating the lifetime of adaptation. However, this method is time-consuming and difficult for participants, insofar as boredom-induced mind wandering may confound the effects of attentional focus (Eastwood et al., 2012; Meier et al., 2023). An alternative approach of amplitude ratio only used two stimulus blocks with contrasting SOIs. By graphically plotting the amplitude ratio of a short SOI against a long SOI over a range of τ values (measured in seconds), it shows that the ratio is a monotonically increasing function of τ. Although this ratio-to-τ relationship is not strictly linear, it can be used to estimate the adaptation lifetime rather than the conventional time constant, given that the ratio increases as τ increases. In practical terms, both SOI conditions produced a clear difference in amplitude. The short SOI of 1.7 seconds ensures a distinct ERP with an observable N1 component (if the SOI is less than 300 milliseconds, it would render the N1 response too minute and difficult to observe), while the long SOI of 3.4 seconds brings the N1 amplitude closer to its saturation limit. By shortening the experiment duration, this ‘dimensionless’ measure addressed the limitations of the traditional approach without significantly compromising estimation accuracy. Two-way ANOVAs were conducted to assess how the N1 amplitude is influenced by attentional focus (presence or absence) on repetitive auditory stimuli and SOIs (short or long). Paired samples t-tests were conducted to assess if the presence or absence of attentional focus on repetitive auditory stimuli significantly affects adaptation lifetime (calculated via amplitude ratio).
Testing the Heat Hypothesis: The Relationship between Temperature and Violent Crime Rates
This paper explored the relationship between temperature and behaviour. In particular the effect heat has on violent crimes. The heat hypothesis states that increased ambient temperatures can cause increased aggressive motives and behaviours. The current study was longitudinal and archival. Data was collated from four different countries: U.S., Japan, Jamaica and Finland over a period of 40 years. Data was collected from reliable online sources for: Temperature in degrees Celsius (℃), rainfall in millimetres (mm), intentional homicide rates, assault rates, rape rates and burglary rates. Rainfall and burglary were control variables. Analyses revealed a significant and positive relationship between temperature and intentional homicide, assault and rape rates. Temperature and burglary were not significantly related. Such results provide support for the heat hypothesis. The relationship between heat and violent crime should be investigated further; as the effects of global warming increase, so may violent crime rates worldwide.
Data In accord with Anderson et al’s., (1997) methods, data of the following crimes were collected: intentional homicide, assault, rape and burglary within a specified 40 years. This crime data was sampled from the following countries databases: U.S., Japan, Jamaica and Finland. The inclusion criteria were to include the countries which had the most available data on crime. There were no data exclusions as the current study was retrospective, meaning all data had already been collected. The 40 years analysed within each country differed depending on data availability. Crime rates were collected in the U.S. between the years 1960 and 2000. Crime rates were collected in Japan between the years 1975 and 2015. Crime rates were collected in Jamaica between the years 1970 and 2010. Crime rates were collected in Finland between the years 1976 and 2016. Therefore there would have been 160 full observations of intentional homicide, assault, rape and robbery. However, due to limited data available there were gaps in the data. For the U.S., 40 full observations of intentional homicide, assault, rape and robbery were obtained. For Japan, 23 full observations were obtained and 17 partial. For Jamaica, 11 full observations were obtained and 29 partial. For Finland, 22 full observations were obtained and 18 partial. The crime data was police reported and per 100,000 of the population, as smaller figures were easier to manage. Crime data was collected from the following reliable online resources: Bourne et al., (2015), Burns (2013), (Knoema, 2011), (Nation Master, 2003), (Statista, n.d.), (Uniform Crime Reporting, 1930), (United Nations World Surveys, 2006), (UNODC Statistics, 1997). Websites were considered reliable if they were established official government data repositories. Temperature (℃) and rainfall (mm) data were also collected. This data was obtained from an online climate data portal (Climate Change Knowledge Portal, n.d.). Rainfall was included as a control variable to ensure that any significant effect was a consequence of increased temperatures, rather than reduced rainfall as a consequence of increased temperatures. If rainfall was not controlled for, it would be impossible to decipher whether the observed effect was caused by increased temperature or reduced rainfall. Apparatus Microsoft excel and the Statistical Package for the Social Sciences (SPSS) were used for data analyses. Analytical approach This study was a longitudinal archival study which analysed existing data. The dependent variable (DV) was crime rates per 100,000 people, collated from reliable online data sources. The independent variables (IV) were: temperature and rainfall. The question asked was whether crime rates can be predicted by temperature and rainfall. The control variables were burglary and rainfall. Burglary was a control dependent variable, as it was expected that temperature would affect violent crime and not non-violent crime such as burglary. Rainfall was a control independent variable, so that rainfall could be controlled for and this made it possible to detect whether temperature alone had an effect on crimes. The data collected required certain properties: the source had to be reliable, crimes had to be police reported and crime rates needed to be reported per 100,000 of the population. Pre-existing data available online was collected and sorted into an excel spreadsheet. Each variable had a column on the spreadsheet: country, year, intentional homicide, assault, rape, burglary, temperature and rainfall. The country variable was categorical. Countries were coded: 1 for the U.S., 2 for Japan, 3 for Jamaica and 4 for Finland. The remaining variables were continuous. There were 160 observations, 40 years per country. Some observations included data on all four crimes; some were partially completed due to limited data. Firstly scatter graphs were plotted with crime against temperature for each country. This revealed the general direction of the relationships between the temperature and crimes. The main analysis was a linear mixed-effects model, where temperature and rainfall were fixed effects and country and year were random effects. This analysis was chosen because of the structure of data. For this study there were multiple samples of crime rate data over 40 different years for each country, and multiple samples of crime rate data for the four different countries for each year. Magezi (2015) described how linear mixed-effects models can include such multiple, nested groups and accommodates for missing data. This was useful because the current study was a longitudinal archival study and consequently had missing data. Analyses were conducted using SPSS. An alpha level of .05 was used for each linear mixed-effects model. +1 lag model analyses for each crime were also implemented, to account for a possible delay of the effect caused by exposure to temperature. To achieve this, the DV columns were shifted down one row using SPSS. It was necessary to check that all values still aligned with the correct country.
Do trustworthiness judgements help people to recognise synthetic faces?
StyleGAN, synthetic face, trustworthiness perception, facial trustworthiness
Recent advances in digital image generative models have allowed for artificial creation of fake imagery such as synthesising highly photorealistic human faces. Style-based Generative Adversarial Networks (StyleGAN) is one of the most state-of-the-art generative models in this field, and has been widely used on facial image generation. However, with the increasing ease of using such image generative models, the security in many domains, such as forensic, border control and mass media, is vulnerable in front of the potential threats resulted from the misuse of image generative technologies. To date there has only been limited empirical research into the facial characteristics of StyleGAN-generated faces to support the design of detection methods against such synthetic faces. This study used StyleGAN2 (an improved version of StyleGAN) to generate faces and invited people to complete two facial image evaluation tasks, 1) Discrimination task, 2) Trustworthiness rating task. The study results demonstrated that, in the discrimination task, subjects had trouble recognising synthetic faces by direct/explicit judgement; while in the trustworthiness rating task, subjects perceived the synthetic faces as significantly more trustworthy than real faces. The study further analysed gender bias and ethnicity bias on the perception of facial trustworthiness, with results showing some differences between different levels of gender and ethnicity. In conclusion, people’s ability to recognise synthetic faces is poor, but it is possible that people rely on the perception of facial trustworthiness to discriminate synthetic from real faces. The findings in this study have implications for the development of detection methods against digitally generated faces.
Three hundred and fifty-seven subjects (114 males, mean age = 25.2, SD = 5.8; 227 females, mean age = 25.0, SD = 6.3; 10 non-binary, mean age = 23.6, SD = 8.93) were recruited to complete an online survey test delivered on www.qualtrics.com. The responses of subjects who started but did not complete the online survey were eliminated to avoid distorting the research results. We used computer-synthesised facial images in this research as fake faces, mixed with real faces to examine people’s ability to detect fake faces and perceptual differences of trustworthiness between real/fake faces. Subjects did not get rewards for their participation, though they could see the test score of their performances at the end of the survey. The Qualtrics survey was based on a within-subjects design in which all subjects viewed the same two sets of adult facial images and completed each of the two tasks. To eliminate the effect of between-sets difference, the use of each image sets was counterbalanced in the individual test for each subject. Before the survey started, all subjects provided informed consent and completed a demographic questionnaire about their age, gender, ethnicity. In terms of the experimental power of 0.8 and significance level of 0.05, with a small effect, the power calculation indicated that the study needed at least 198 subjects. Stimuli A total of thirty-two human facial images (1024×1024 resolution), including 16 real and 16 synthetic faces, were used as stimuli in the survey. All real faces were taken from a publicly available dataset for high-quality human facial images, Flickr-Faces-HQ (FFHQ), which is created as a benchmark for GAN (see https://github.com/NVlabs/ffhq-dataset), and all synthetic faces were gained from the dataset of the generative image modeling, StyleGAN2 (see https://github.com/NVlabs/stylegan2). To ensure a diverse dataset, in each of the two sets of faces, there were 4 Black, 4 East Asian, 4 South Asian, 4 White, and 2 males and 2 females for each ethnicity. Among the sixteen faces of each set, half of them were real and half were synthetic, but this was unknown to subjects.
Subjects and design Three hundred and fifty-seven subjects (114 males, mean age = 25.2, SD = 5.8; 227 females, mean age = 25.0, SD = 6.3; 10 non-binary, mean age = 23.6, SD = 8.93) were recruited to complete an online survey test delivered on www.qualtrics.com. The responses of subjects who started but did not complete the online survey were eliminated to avoid distorting the research results. We used computer-synthesised facial images in this research as fake faces, mixed with real faces to examine people’s ability to detect fake faces and perceptual differences of trustworthiness between real/fake faces. Subjects did not get rewards for their participation, though they could see the test score of their performances at the end of the survey. The Qualtrics survey was based on a within-subjects design in which all subjects viewed the same two sets of adult facial images and completed each of the two tasks. To eliminate the effect of between-sets difference, the use of each image sets was counterbalanced in the individual test for each subject. Before the survey started, all subjects provided informed consent and completed a demographic questionnaire about their age, gender, ethnicity. In terms of the experimental power of 0.8 and significance level of 0.05, with a small effect, the power calculation indicated that the study needed at least 198 subjects. Stimuli A total of thirty-two human facial images (1024×1024 resolution), including 16 real and 16 synthetic faces, were used as stimuli in the survey. All real faces were taken from a publicly available dataset for high-quality human facial images, Flickr-Faces-HQ (FFHQ), which is created as a benchmark for GAN (see https://github.com/NVlabs/ffhq-dataset), and all synthetic faces were gained from the dataset of the generative image modeling, StyleGAN2 (see https://github.com/NVlabs/stylegan2). To ensure a diverse dataset, in each of the two sets of faces, there were 4 Black, 4 East Asian, 4 South Asian, 4 White, and 2 males and 2 females for each ethnicity. Among the sixteen faces of each set, half of them were real and half were synthetic, but this was unknown to subjects.
Subjects and design Three hundred and fifty-seven subjects (114 males, mean age = 25.2, SD = 5.8; 227 females, mean age = 25.0, SD = 6.3; 10 non-binary, mean age = 23.6, SD = 8.93) were recruited to complete an online survey test delivered on www.qualtrics.com. The responses of subjects who started but did not complete the online survey were eliminated to avoid distorting the research results. We used computer-synthesised facial images in this research as fake faces, mixed with real faces to examine people’s ability to detect fake faces and perceptual differences of trustworthiness between real/fake faces. Subjects did not get rewards for their participation, though they could see the test score of their performances at the end of the survey. The Qualtrics survey was based on a within-subjects design in which all subjects viewed the same two sets of adult facial images and completed each of the two tasks. To eliminate the effect of between-sets difference, the use of each image sets was counterbalanced in the individual test for each subject. Before the survey started, all subjects provided informed consent and completed a demographic questionnaire about their age, gender, ethnicity. In terms of the experimental power of 0.8 and significance level of 0.05, with a small effect, the power calculation indicated that the study needed at least 198 subjects. Stimuli A total of thirty-two human facial images (1024×1024 resolution), including 16 real and 16 synthetic faces, were used as stimuli in the survey. All real faces were taken from a publicly available dataset for high-quality human facial images, Flickr-Faces-HQ (FFHQ), which is created as a benchmark for GAN (see https://github.com/NVlabs/ffhq-dataset), and all synthetic faces were gained from the dataset of the generative image modeling, StyleGAN2 (see https://github.com/NVlabs/stylegan2). To ensure a diverse dataset, in each of the two sets of faces, there were 4 Black, 4 East Asian, 4 South Asian, 4 White, and 2 males and 2 females for each ethnicity. Among the sixteen faces of each set, half of them were real and half were synthetic, but this was unknown to subjects. Procedure First, subjects completed a short questionnaire for demographic information (age, gender, ethnicity), and subjects had to be 18 years of age or older to take part. Prior to the main body of test, there was an example of real and synthetic faces presented to provide subjects with a general impression of what real and synthetic faces look like. Subjects then were asked to complete two face evaluating tasks, 1) Discrimination Task, 2) Trustworthiness Rating Task. The two tasks were presented to subjects in a counterbalanced order to check for any possible order effects. Before the start of each task, participants were informed that they would see a series of 16 facial images, and that they had to carry out their evaluation following the instructions provided. In both tasks, only one image was presented at a time and individual images appeared in a random order. In the discrimination task, participants made their decision between two choices, “real” or “synthetic”, to classify the 16 faces according to whether they thought the presented faces were real or not. Subjects did not receive immediate feedback during the task on the correctness of their classifications. In this task, subjects relied on direct/explicit judgments. In the trustworthiness rating task, subjects were required to rate how trustworthy they thought each of 16 faces looked using a 7-point Likert scale (1 = extremely untrustworthy; 4 = neither untrustworthy nor trustworthy; 7 = extremely trustworthy). We instructed subjects that they did not need to consider face authenticity in this task, and they could just assume that the faces shown to them were all of real people. Although there was no time limit to respond for trustworthiness rating, we encouraged subjects to rely on their intuitions and provide their responses to work as quickly as possible. In this task, we expected to trigger a relatively indirect/implicit approach to evaluate faces as compared to direct/explicit judgement on face authenticity, specifically by trustworthiness perception. At the end of the survey, subjects saw a result report of their own mean trustworthiness rating scores for real and synthetic faces, and their mean accuracy in classifying real and synthetic faces in the discrimination task.