Automated verbal credibility assessment of intentions: The model statement technique and predictive modeling

Recently, verbal credibility assessment has been extended to the detection of deceptive intentions, the use of a model statement, and predictive modeling. The current investigation combines these 3 elements to detect deceptive intentions on a large scale. Participants read a model statement and wrote a truthful or deceptive statement about their planned weekend activities (Experiment 1). With the use of linguistic features for machine learning, more than 80% of the participants were classified correctly. Exploratory analyses suggested that liars included more person and location references than truth‐tellers. Experiment 2 examined whether these findings replicated on independent‐sample data. The classification accuracies remained well above chance level but dropped to 63%. Experiment 2 corroborated the finding that liars' statements are richer in location and person references than truth‐tellers' statements. Together, these findings suggest that liars may over‐prepare their statements. Predictive modeling shows promise as an automated veracity assessment approach but needs validation on independent data.     

The dimensions of deception detection: Self‐reported deception cue use is underpinned by two broad factors

Many perceived cues to deception have been reported in the literature, but little attention has been paid to how they are combined when making deception judgments. The present research used a data‐driven approach to investigate how cues are integrated when evaluating veracity. Two hundred fifteen participants performed a deception detection task before completing a deception cue use questionnaire. A factor analysis of the questionnaire data produced two dimensions, one associated with nonverbal cues to anxiety and the other associated with detail and level of involvement. The present work extends our understanding of deception detection processes and underlines the importance of examining not only the cues that people use but also the way in which they use them.     

Detecting Clusters/Communities in Social Networks

Cohen's κ, a similarity measure for categorical data, has since been applied to problems in the data mining field such as cluster analysis and network link prediction. In this paper, a new application is examined: community detection in networks. A new algorithm is proposed that uses Cohen's κ as a similarity measure for each pair of nodes; subsequently, the κ values are then clustered to detect the communities. This paper defines and tests this method on a variety of simulated and real networks. The results are compared with those from eight other community detection algorithms. Results show this new algorithm is consistently among the top performers in classifying data points both on simulated and real networks. Additionally, this is one of the broadest comparative simulations for comparing community detection algorithms to date.     

Word Detection in Sung and Spoken Sentences in Children With Typical Language Development or With Specific Language Impairment

Background: Previous studies have reported that children score better in language tasks using sung rather than spoken stimuli. We examined word detection ease in sung and spoken sentences that were equated for phoneme duration and pitch variations in children aged 7 to 12 years with typical language development (TLD) as well as in children with specific language impairment (SLI ), and hypothesized that the facilitation effect would vary with language abilities. Method: In Experiment 1, 69 children with TLD (7–10 years old) detected words in sentences that were spoken, sung on pitches extracted from speech, and sung on original scores. In Experiment 2, we added a natural speech rate condition and tested 68 children with TLD (7–12 years old). In Experiment 3, 16 children with SLI and 16 age-matched children with TLD were tested in all four conditions. Results: In both TLD groups, older children scored better than the younger ones. The matched TLD group scored higher than the SLI group who scored at the level of the younger children with TLD . None of the experiments showed a facilitation effect of sung over spoken stimuli. Conclusions: Word detection abilities improved with age in both TLD and SLI groups. Our findings are compatible with the hypothesis of delayed language abilities in children with SLI , and are discussed in light of the role of durational prosodic cues in words detection.     

Mimicry and Investigative Interviewing: Using Deliberate Mimicry to Elicit Information and Cues to Deceit

We examined the effect of deliberate mimicry on eliciting (accurate) information and cues to deceit. Mimicry is considered to facilitate cooperation and compliance in truth tellers, whereas liars are constrained to provide detail. We therefore expected truth tellers to be more detailed than liars, particularly after being mimicked. A total of 165 participants told the truth or lied about a meeting they attended. During the interview, an interviewer mimicked half of the participants. Truth tellers were more detailed than liars, but only in the ‘mimicry present’ condition. Truth tellers also gave more accurate units of information than liars, and the difference was most pronounced in the ‘mimicry present’ condition. Mimicry as a tool for eliciting information and cues to deceit fits well with the emerging ‘interviewing to detect deception’ literature, particularly in the ‘encouraging interviewees to say more’ approach. Copyright © 2015 John Wiley & Sons, Ltd.     

Examining the relationship between skilled music training and attention

While many aspects of cognition have been investigated in relation to skilled music training, surprisingly little work has examined the connection between music training and attentional abilities. The present study investigated the performance of skilled musicians on cognitively demanding sustained attention tasks, measuring both temporal and visual discrimination over a prolonged duration. Participants with extensive formal music training were found to have superior performance on a temporal discrimination task, but not a visual discrimination task, compared to participants with no music training. In addition, no differences were found between groups in vigilance decrement in either type of task. Although no differences were evident in vigilance per se, the results indicate that performance in an attention-demanding temporal discrimination task was superior in individuals with extensive music training. We speculate that this basic cognitive ability may contribute to advantages that musicians show in other cognitive measures.     

The own‐age face recognition bias is task dependent

The own‐age bias (OAB) in face recognition (more accurate recognition of own‐age than other‐age faces) is robust among young adults but not older adults. We investigated the OAB under two different task conditions. In Experiment 1 young and older adults (who reported more recent experience with own than other‐age faces) completed a match‐to‐sample task with young and older adult faces; only young adults showed an OAB. In Experiment 2 young and older adults completed an identity detection task in which we manipulated the identity strength of target and distracter identities by morphing each face with an average face in 20% steps. Accuracy increased with identity strength and facial age influenced older adults' (but not younger adults') strategy, but there was no evidence of an OAB. Collectively, these results suggest that the OAB depends on task demands and may be absent when searching for one identity.     

Hemispheric predominance assessment of phonology and semantics: a divided visual field experiment

The aim of the present behavioural experiment was to evaluate the most lateralized among two phonological (phoneme vs. rhyme detection) and the most lateralized among two semantic ("living" vs. "edible" categorization) tasks, within the dominant hemisphere for language. The reason of addressing this question was a practical one: to evaluate the degree of the hemispheric lateralization for several language tasks, by using the divided visual presentation of stimuli, and then choose the most lateralized semantic and phonological for mapping language in patients by using fMRI in future studies. During the divided visual field experiment by using words (semantic tasks) and pseudo-words (phonological tasks) as stimuli, thirty-nine right-handed participants were examined. Our results have shown that all tasks were significantly left hemisphere lateralized. Furthermore, the rhyme was significantly more lateralized than phoneme detection and "living" was significantly more lateralized than "edible" categorization. The rhyme decision and "living" categorization will be used in future fMRI studies for assessing hemispheric predominance and cerebral substrate for semantics and phonology in patients. Our results also suggest that the characteristics of stimuli could influence the degree of the hemispheric lateralization (i.e., the emotional charge of stimuli for words and the position of the phoneme to be detected, for pseudo-words).     

Visual working memory and threat monitoring: Spider fearfuls show disorder-specific change detection

Previous studies of biased information processing in anxiety addressed biases of attention and memory, but little is known about the processes taking place between them: visual working memory (VWM) and monitoring of threat. We investigated these processes with a change detection paradigm. In Experiment 1, spider fearfuls (SF) and non-anxious controls (NAC) judged two subsequently presented displays as same or different. The displays consisted of several pictures, one of which could depict a spider. In Experiment 2, SF and NAC, both without snake fear, were tested with displays including either a spider or a snake image to determine the material-specificity of biased VWM. Both groups showed increased change detection for threat images. This effect was significantly stronger in SF, for spider images only, indicating a threat-specific VWM bias. Thus, contrary to the assumptions made by most cognitive models of anxiety, an explicit memory bias was found.     

On the statistical and theoretical basis of signal detection theory and extensions: Unequal variance, random coefficient, and mixture models

Basic results for conditional means and variances, as well as distributional results, are used to clarify the similarities and differences between various extensions of signal detection theory (SDT). It is shown that a previously presented motivation for the unequal variance SDT model (varying strength) actually leads to a related, yet distinct, model. The distinction has implications for other extensions of SDT, such as models with criteria that vary over trials. It is shown that a mixture extension of SDT is also consistent with unequal variances, but provides a different interpretation of the results; mixture SDT also offers a way to unify results found across several types of studies.