Detecting cocaine use? The autobiographical implicit association test (aIAT) produces false positives in a real-world setting

Autobiographical Implicit Association Test and eye movements: fixations topography enables detection of autobiographical memories

Introduction

Autobiographical memory is the capacity to recollect memories of personally experienced events. The detection of such memories plays a key role in criminal trials. Among behavioral memory-detection methods, the autobiographical Implicit Association Test (aIAT) has gained popularity for its flexibility and suitability for forensic applications. The aIAT is a reaction time-based methodology aiming to assess whether information about an event is encoded in the respondent's mind. Here, we introduced the eye-D index, a measure based on the topography of fixations while performing the aIAT, as an additional measure to detect autobiographical memories covertly.

Methods

In this study, participants were involved in a mock-crime experiment in which they could act as Guilty or Innocent. One week later all participants underwent the aIAT combined with eye-tracking to investigate the presence of the crime-related memory.

Results

Guilty participants showed a higher number of fixations towards the category labels in the block in which true sentences shared the same response key with crime-related sentences, as compared to the block in which true sentences were paired with sentences describing an alternative version. Innocent participants showed the opposite pattern. This unbalanced allocation of attention to the category labels was quantified by the eye-D index and was found to be highly correlated to the standard aIAT-D index.

Discussion

This suggests that more fixations to the category labels could indicate increased cognitive load and monitoring of response conflicts. These preliminary results highlight eye-tracking as a tool to detect autobiographical memories covertly while performing the aIAT.

Two Cases of Malingered Crime-Related Amnesia

Amnesia is a frequent claim in major crimes, and it is estimated that the complete or partial absence of memory following a crime ranges from 25% to 50% of total cases. Although some cases may constitute a genuine form of amnesia, due to organic-neurological defects or psychological causes, and possibly combined with a dissociative or repressive coping style after an extreme experience, malingering is still fairly common in offenders. Therefore, one of the main goals in medico-legal proceedings is to find methods to determine the credibility of crime-related amnesia. At present, a number of lie and memory detection techniques can assist the forensic assessment of the reliability of declarative proof, and have been devised and improved over the past century: for example, modern polygraphs, event-related potentials, thermal imaging, functional magnetic resonance imaging, kinematic, and facial analysis. Other ad hoc psychological tests, such as the so-called Symptom Validity Test (SVT) and Performance Validity Test (PVT), as well as the autobiographical Implicit Association Test (aIAT), can also be used. To date, however, there is little evidence or case reports that document their real usefulness in forensic practice. Here, we report two cases of crime-related amnesia, whereby both defendants, who were found guilty of homicide, appeared to exhibit dissociative amnesia but where the application of SVTs, PVTs, and aIAT detected a malingered amnesia.

The Neural Correlates of Implicit Cognitive Bias Toward Internet-Related Cues in Internet Addiction: An ERP Study

Internet addiction is a sort of non-psychoactive substance dependence. The Implicit Association Test (IAT) is used to measure implicit cognition. Event-related potential (ERP) is one of the most widely used methods in cognitive neuroscience research to investigate the physiological correlates of cognitive activity associated with processing information. Further investigating the ERP characteristics of implicit cognitive bias in Internet addiction would be helpful in understanding the nature of Internet addiction. This study investigated the ERP characteristics of implicit cognitive bias in Internet addiction. The participants included 60 Internet-addicted individuals (IAG) and 60 normal controls (NCG). All participants were measured with ERPs using the IAT. The results showed that there was a significant difference in the Internet-related IAT effect for reaction times between IAG and NCG, and there were stronger positive implicit associations toward Internet related cues in IAG than NCG. Using P1, N2, P3, and N4 as dependent variables, a mixed repeated-measures analysis of variance (ANOVA) on the mean latencies and mean amplitudes revealed a significant interaction between the groups (IAG vs. NCG) and stimulus condition (compatible trials vs. incompatible trials) for the N2 and P3 amplitudes; the simple effects analysis showed that the N2 and P3 amplitudes were larger under the IAG-compatible trial conditions than under the IAG-incompatible trial conditions. In the IAG group, the positive implicit associations with Internet-related cues elicited larger N2 and P3 amplitudes at the occipital lobe sites. These results indicated that Internet addictive individuals show stronger positive implicit associations toward Internet-related cues, and the positive implicit associations toward Internet-related cues elicited ERP changes at occipital lobe sites.

Assessing autobiographical memory: the web-based autobiographical Implicit Association Test

By assessing the association strength with TRUE and FALSE, the autobiographical Implicit Association Test (aIAT) [Sartori, G., Agosta, S., Zogmaister, C., Ferrara, S. D., & Castiello, U. (2008). How to accurately detect autobiographical events. Psychological Science, 19, 772-780. doi: 10.1111/j.1467-9280.2008.02156.x ] aims to determine which of two contrasting statements is true. To efficiently run well-powered aIAT experiments, we propose a web-based aIAT (web-aIAT). Experiment 1 (n = 522) is a web-based replication study of the first published aIAT study [Sartori, G., Agosta, S., Zogmaister, C., Ferrara, S. D., & Castiello, U. (2008). How to accurately detect autobiographical events. Psychological Science, 19, 772-780. doi: 10.1111/j.1467-9280.2008.02156.x ; Experiment 1]. We conclude that the replication was successful as the web-based aIAT could accurately detect which of two playing cards participants chose (AUC = .88; Hit rate = 81%). In Experiment 2 (n = 424), we investigated whether the use of affirmative versus negative sentences may partly explain the variability in aIAT accuracy findings. The aIAT could detect the chosen card when using affirmative (AUC = .90; Hit rate = 81%), but not when using negative sentences (AUC = .60; Hit rate = 53%). The web-based aIAT seems to be a valuable tool to facilitate aIAT research and may help to further identify moderators of the test's accuracy.

Neural Patterns of the Implicit Association Test

The Implicit Association Test (IAT) is a reaction time based categorization task that measures the differential associative strength between bipolar targets and evaluative attribute concepts as an approach to indexing implicit beliefs or biases. An open question exists as to what exactly the IAT measures, and here EEG (Electroencephalography) has been used to investigate the time course of ERPs (Event-related Potential) indices and implicated brain regions in the IAT. IAT-EEG research identifies a number of early (250-450 ms) negative ERPs indexing early-(pre-response) processing stages of the IAT. ERP activity in this time range is known to index processes related to cognitive control and semantic processing. A central focus of these efforts has been to use IAT-ERPs to delineate the implicit and explicit factors contributing to measured IAT effects. Increasing evidence indicates that cognitive control (and related top-down modulation of attention/perceptual processing) may be components in the effective measurement of IAT effects, as factors such as physical setting or task instruction can change an IAT measurement. In this study we further implicate the role of proactive cognitive control and top-down modulation of attention/perceptual processing in the IAT-EEG. We find statistically significant relationships between D-score (a reaction-time based measure of the IAT-effect) and early ERP-time windows, indicating where more rapid word categorizations driving the IAT effect are present, they are at least partly explainable by neural activity not significantly correlated with the IAT measurement itself. Using LORETA, we identify a number of brain regions driving these ERP-IAT relationships notably involving left-temporal, insular, cingulate, medial frontal and parietal cortex in time regions corresponding to the N2- and P3-related activity. The identified brain regions involved with reduced reaction times on congruent blocks coincide with those of previous studies.

"I didn't want to do it!" The detection of past intentions

In daily life and in courtrooms, people regularly analyze the minds of others to understand intentions. Specifically, the detection of intentions behind prior events is one of the main issues dealt with in courtrooms. To our knowledge, there are no experimental works focused on the use of memory detection techniques to detect past intentions. This study aims at investigating whether reaction times (RTs) could be used for this purpose, by evaluating the accuracy of the autobiographical Implicit Association Test (aIAT) in the detection of past intentions. Sixty healthy volunteers took part in the experiment (mean age: 36.5 y; range: 18-55; 30 males). Participants were asked to recall and report information about a meeting with a person that had occurred at least 1 month before. Half of the participants were required to report about an intentional meeting, whereas the other half reported on a chance meeting. Based on the conveyed information, participants performed a tailored aIAT in which they had to categorize real reported information contrasted with counterfeit information. Results demonstrated that RTs can be a useful measure for the detection of past intentions and that aIAT can detect real past intentions with an accuracy of 95%.

A call for policy guidance on psychometric testing in doping control in sport

One of the fundamental challenges in anti-doping is identifying athletes who use, or are at risk of using, prohibited performance enhancing substances. The growing trend to employ a forensic approach to doping control aims to integrate information from social sciences (e.g., psychology of doping) into organised intelligence to protect clean sport. Beyond the foreseeable consequences of a positive identification as a doping user, this task is further complicated by the discrepancy between what constitutes a doping offence in the World Anti-Doping Code and operationalized in doping research. Whilst psychology plays an important role in developing our understanding of doping behaviour in order to inform intervention and prevention, its contribution to the array of doping diagnostic tools is still in its infancy. In both research and forensic settings, we must acknowledge that (1) socially desirable responding confounds self-reported psychometric test results and (2) that the cognitive complexity surrounding test performance means that the response-time based measures and the lie detector tests for revealing concealed life-events (e.g., doping use) are prone to produce false or non-interpretable outcomes in field settings. Differences in social-cognitive characteristics of doping behaviour that are tested at group level (doping users vs. non-users) cannot be extrapolated to individuals; nor these psychometric measures used for individual diagnostics. In this paper, we present a position statement calling for policy guidance on appropriate use of psychometric assessments in the pursuit of clean sport. We argue that, to date, both self-reported and response-time based psychometric tests for doping have been designed, tested and validated to explore how athletes feel and think about doping in order to develop a better understanding of doping behaviour, not to establish evidence for doping. A false 'positive' psychological profile for doping affects not only the individual 'clean' athlete but also their entourage, their organisation and sport itself. The proposed policy guidance aims to protect the global athletic community against social, ethical and legal consequences from potential misuse of psychological tests, including erroneous or incompetent applications as forensic diagnostic tools in both practice and research.

It is not just memory: propositional thinking influences performance on the autobiographical IAT

INTRODUCTION

The autobiographical Implicit Association Test (aIAT) is a variant of the Implicit Association Test reportedly capable of detecting an individual's concealed autobiographical event with very high accuracy. A previous attempt to utilize this measurement technique for the identification of cocaine users rendered an alarming rate of false positives. In this study, we aimed to explore the potential reasons behind the measurement's inaccuracy.

METHODS

Two versions of the cocaine aIAT were devised with different category labels (descriptive 'guilty/innocent' and self-referenced 'as if you were/were not'). Forty-one cocaine abstinent participants (43.9% male; mean age = 28.17 ± 7.36) were randomly assigned to one of the two conditions. Self-declared cocaine abstinence was confirmed for the 12-month period preceding data collection through hair analysis. Participants were also administered bespoke implicit and explicit cocaine user attitude measures, the self-esteem IAT and the Rosenberg self-esteem scale.

RESULTS

The category labels which elicited self-referenced knowledge showed low accuracy (19%) compared to the 65% of the 'guilty/innocent' labels proposed by original authors. The self-referenced aIAT version significantly correlated with the self-concept measures. The aIAT outcomes were independent from attitudes toward cocaine users.

CONCLUSIONS

Category labels play an influential role in determining the test's accuracy, demonstrating that participants' propositional knowledge and self-concept are involved during test performance. The aIAT does not appear to tap directly into an individual's implicit memory when relevant memory is not available. Although the test cannot be recommended for detecting drug use, further research should investigate underlying mechanisms and other potentials of the technique.