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.

Verbal lie detection using Large Language Models.

Human accuracy in detecting deception with intuitive judgments has been proven to not go above the chance level. Therefore, several automatized verbal lie detection techniques employing Machine Learning and Transformer models have been developed to reach higher levels of accuracy. This study is the first to explore the performance of a Large Language Model, FLAN-T5 (small and base sizes), in a lie-detection classification task in three English-language datasets encompassing personal opinions, autobiographical memories, and future intentions. After performing stylometric analysis to describe linguistic differences in the three datasets, we tested the small- and base-sized FLAN-T5 in three Scenarios using 10-fold cross-validation: one with train and test set coming from the same single dataset, one with train set coming from two datasets and the test set coming from the third remaining dataset, one with train and test set coming from all the three datasets. We reached state-of-the-art results in Scenarios 1 and 3, outperforming previous benchmarks. The results revealed also that model performance depended on model size, with larger models exhibiting higher performance. Furthermore, stylometric analysis was performed to carry out explainability analysis, finding that linguistic features associated with the Cognitive Load framework may influence the model's predictions.

Language models and psychological sciences.

Large language models (LLMs) are demonstrating impressive performance on many reasoning and problem-solving tasks from cognitive psychology. When tested, their accuracy is often on par with average neurotypical adults, challenging long-standing critiques of associative models. Here we analyse recent findings at the intersection of LLMs and cognitive science. Here we discuss how modern LLMs resurrect associationist principles, with abilities like long-distance associations enabling complex reasoning. While limitations remain in areas like causal cognition and planning, phenomena like emergence suggest room for growth. Providing examples and increasing the dimensions of the network are methods that further improve LLM abilities, mirroring facilitation effects in human cognition. Analysis of LLMs errors provides insight into human cognitive biases. Overall, we argue LLMs represent a promising development for cognitive modelling, enabling new explorations of the mechanisms underlying intelligence and reasoning from an associationist point of view. Carefully evaluating LLMs with the tools of cognitive psychology will further understand the building blocks of the human mind.

Does cognitive decline influence signing?

OBJECTIVE: The study explored the change in handwritten signature in neurodegenerative diseases by using of a rater-based approach. METHODS: Four independent observers were required to compare a pair of signatures (on average, 5 years elapsed between the two signatures) made by 103 patients (mean age 72 years) with Alzheimer's disease (AD) or frontotemporal dementia (FTD) and by 31 healthy participants (HC; mean age 73 years), judging their change according to a 0-1 rating scale (0 = similar or 1 = different). If a signature change was detected, the rater had also to report which signature features (spatial layout, omitted/added/switched letters or names, shape of letter, pen-flow) changed on the same 0-1 scale. For the AD and FTD groups, one signature was collected prior to the diagnosis of dementia, the other subsequent. RESULTS: A signature change was reported by raters in 36% of AD patients, 44% of FTD, and 17% of HC, with significant differences between both clinical groups and HC (vs. AD, p = .01; vs. FTD, p = .001). There was not a distinctive marker of the signature change (i.e., feature change) in patients with dementia. Moreover, the signature changes in neurological patients were unrelated to their clinical and demographic characteristics (age, sex, education, time elapsed between the two signatures, Mini-mental State Examination score). CONCLUSION: The findings suggest a resistance of handwritten signature in neurodegenerative diseases and in physiological aging, also suggesting that the signature may be an unreliable indicator of the cognitive status in AD and FTD, at least if subjectively evaluated.

Reconstructing individual responses to direct questions: a new method for reconstructing malingered responses.

Introduction: The false consensus effect consists of an overestimation of how common a subject opinion is among other people. This research demonstrates that individual endorsement of questions may be predicted by estimating peers' responses to the same question. Moreover, we aim to demonstrate how this prediction can be used to reconstruct the individual's response to a single item as well as the overall response to all of the items, making the technique suitable and effective for malingering detection. Method: We have validated the procedure of reconstructing individual responses from peers' estimation in two separate studies, one addressing anxiety-related questions and the other to the Dark Triad. The questionnaires, adapted to our scopes, were submitted to the groups of participants for a total of 187 subjects across both studies. Machine learning models were used to estimate the results. Results: According to the results, individual responses to a single question requiring a "yes" or "no" response are predicted with 70-80% accuracy. The overall participant-predicted score on all questions (total test score) is predicted with a correlation of 0.7-0.77 with actual results. Discussion: The application of the false consensus effect format is a promising procedure for reconstructing truthful responses in forensic settings when the respondent is highly likely to alter his true (genuine) response and true responses to the tests are missing.

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.

Acquired Pedophilia: international Delphi-method-based consensus guidelines.

Idiopathic and acquired pedophilia are two different disorders with two different etiologies. However, the differential diagnosis is still very difficult, as the behavioral indicators used to discriminate the two forms of pedophilia are underexplored, and clinicians are still devoid of clear guidelines describing the clinical and neuroscientific investigations suggested to help them with this difficult task. Furthermore, the consequences of misdiagnosis are not known, and a consensus regarding the legal consequences for the two kinds of offenders is still lacking. The present study used the Delphi method to reach a global consensus on the following six topics: behavioral indicators/red flags helpful for differential diagnosis; neurological conditions potentially leading to acquired pedophilia; neuroscientific investigations important for a correct understanding of the case; consequences of misdiagnosis; legal consequences; and issues and future perspectives. An international and multidisciplinary board of scientists and clinicians took part in the consensus statements as Delphi members. The Delphi panel comprised 52 raters with interdisciplinary competencies, including neurologists, psychiatrists, neuropsychologists, forensic psychologists, expert in ethics, etc. The final recommendations consisted of 63 statements covering the six different topics. The current study is the first expert consensus on a delicate topic such as pedophilia. Important exploitable consensual recommendations that can ultimately be of immediate use by clinicians to help with differential diagnosis and plan and guide therapeutic interventions are described, as well as future perspectives for researchers.

Machine learning item selection for short scale construction: A proof-of-concept using the SIMS.

ObjectiveThis proof-of-concept paper provides evidence to support machine learning (ML) as a valid alternative to traditional psychometric techniques in the development of short forms of longer parent psychological tests. ML comprises a variety of feature selection techniques that can be efficiently applied to identify the set of items that best replicates the characteristics of the original test. MethodsIn the present study, we integrated a dataset of 329 participants from published and unpublished datasets used in previous research on the Structured Inventory of Malingered Symptomatology (SIMS) to develop a short version of the scale. The SIMS is a multi-axial self-report questionnaire and a highly efficient psychometric measure of symptom validity, which is frequently applied in forensic settings. Results State-of-the-art ML item selection techniques achieved a 72% reduction in length while capturing 92% of the variance of the original SIMS. The new SIMS short form now consists of 21 items. ConclusionsThe results suggest that the proposed ML-based item selection technique represents a promising alternative to standard psychometric correlation-based methods (i.e. item selection, item response theory), especially when selection techniques (e.g. wrapper) are employed that evaluate global, rather than local, item value.

Identifying single-item faked responses in personality tests: A new TF-IDF-based method.

Faking in a psychological test is often observed whenever an examinee may gain an advantage from it. Although techniques are available to identify a faker, they cannot identify the specific questions distorted by faking. This work evaluates the effectiveness of term frequency-inverse document frequency (TF-IDF)-an information retrieval mathematical tool used in search engines and language representations-in identifying single-item faked responses. We validated the technique on three datasets containing responses to the 10-item Big Five questionnaire (total of 694 participants, respectively 221, 243, and 230) in three faking situations. Each participant responded twice, once faking to achieve an objective in one of three contexts (one to obtain child custody and two to land a job) and once honestly. The proposed TF-IDF model has proven very effective in separating honest from dishonest responses-with the honest ones having low TF-IDF values and the dishonest ones having higher values-and in identifying which of the 10 responses to the questionnaire were distorted in the dishonest condition. We also provide examples of the technique in a single-case evaluation.

A court ruled case on therapy-induced false memories.

We report on a unique Italian criminal case in which a court ruled that a therapist implanted false memories of abuse in a young girl. Using therapeutic excerpts, we show that the therapist used a multitude of problematic interventions that are all linked to false memory creation. Specifically, an analysis of the therapeutic excerpts showed that across many sessions, the therapist asked highly suggestive questions to the girl, implying that she was abused by her father. In addition, the girl underwent EMDR techniques that have been associated with memory undermining effects. Our analyses showed that although before treatment the girl did not have any recollection of being abused by her father, she gradually started to remember the abuse and identified the father as her abuser during the therapeutic sessions. Our case report clearly shows the danger of suggestive pressure in a therapeutic context causing patients to form false memories of abuse and supports the need to prevent the therapeutic practice of suggestive techniques.

Disentangling interoceptive abilities in alexithymia.

In recent years, research on interoceptive abilities (i.e., sensibility, accuracy, and awareness) and their associations with emotional experience has flourished. Yet interoceptive abilities in alexithymia-a personality trait characterized by a difficulty in the cognitive interpretation of emotional arousal, which impacts emotional experience-remain under-investigated, thereby limiting a full understanding of subjective emotional experience processing. Research has proposed two contrasting explanations thus far: in one model, the dimensions of interoceptive sensibility and accuracy in alexithymia would increase; in the other model, they would decrease. Surprisingly, the contribution of interoceptive awareness has been minimally researched. In this study (N = 182), the relationship between participants' level of alexithymia and the three interoceptive dimensions was tested. Our results show that the higher the level of alexithymia is, the higher interoceptive accuracy and sensibility (R2 = 0.29 and R2 = 0.14); conversely, the higher the level of alexithymia is, the lower interoceptive awareness (R2 = 0.36). Moreover, an ROC analysis reveals that interoceptive awareness is the most accurate predictor of alexithymia, yielding over 92% accuracy. Collectively, these results support a coherent understanding of interoceptive abilities in alexithymia, whereby the dissociation of interoceptive accuracy and awareness may explain the underlying psycho-physiological mechanisms of alexithymia. A possible neurocognitive mechanism is discussed which suggests insurgence of psychosomatic disorders in alexithymia and related psychotherapeutic approaches.

Assessing the impact of previous experience on lie effects through a transfer paradigm.

Influential lines of research propose dual processes-based explanations to account for both the cognitive cost implied in lying and for that entailed in the resolution of the conflict posited by Simon tasks. The emergence and consistency of the Simon effect has been proved to be modulated by both practice effects and transfer effects. Although several studies provided evidence that the lying cognitive demand may vary as a function of practice, whether and how transfer effects could also play a role remains an open question. We addressed this question with one experiment in which participants completed a Differentiation of Deception Paradigm twice (baseline and test sessions). Crucially, between the baseline and the test sessions, participants performed a training session consisting in a spatial compatibility task with incompatible (condition 1) or compatible (condition 2) mapping, a non-spatial task (condition 3) and a no task one (condition 4). Results speak in favour of a modulation of individual performances by means of an immediate prior experience, and specifically with an incompatible spatial training.

The detection of malingering in whiplash-related injuries: a targeted literature review of the available strategies.

OBJECTIVE: The present review is intended to provide an up-to-date overview of the strategies available to detect malingered symptoms following whiplash. Whiplash-associated disorders (WADs) represent the most common traffic injuries, having a major impact on economic and healthcare systems worldwide. Heterogeneous symptoms that may arise following whiplash injuries are difficult to objectify and are normally determined based on self-reported complaints. These elements, together with the litigation context, make fraudulent claims particularly likely. Crucially, at present, there is no clear evidence of the instruments available to detect malingered WADs. METHODS: We conducted a targeted literature review of the methodologies adopted to detect malingered WADs. Relevant studies were identified via Medline (PubMed) and Scopus databases published up to September 2020. RESULTS: Twenty-two methodologies are included in the review, grouped into biomechanical techniques, clinical tools applied to forensic settings, and cognitive-based lie detection techniques. Strengths and weaknesses of each methodology are presented, and future directions are discussed. CONCLUSIONS: Despite the variety of techniques that have been developed to identify malingering in forensic contexts, the present work highlights the current lack of rigorous methodologies for the assessment of WADs that take into account both the heterogeneous nature of the syndrome and the possibility of malingering. We conclude that it is pivotal to promote awareness about the presence of malingering in whiplash cases and highlight the need for novel, high-quality research in this field, with the potential to contribute to the development of standardised procedures for the evaluation of WADs and the detection of malingering.

Behavioral Variant of Frontotemporal Dementia and Homicide in a Historical Case.

Criminal behavior is a clinical feature of the behavioral variant of frontotemporal dementia (bvFTD), ranging from socially inappropriate behavior and minor offenses (such as shoplifting, driving-related violations, housebreaking, trespassing) to the more extreme acts of sex crimes and violence. To our knowledge, no homicide case involving bvFTD is well illustrated in the scientific literature, and only a few anecdotal annotations are available about bvFTD and homicide. This is surprising considering the inclination of individuals with bvFTD to lack impulse control, to manifest disinhibition, to display diminished emotional awareness and loss of empathy, and to show behavior indicative of disordered moral reasoning. Here, we describe the 19th-century homicide case of Benjamin Reynaud, a man whose clinical characteristics suggest the bvFTD diagnosis. Reynaud's case may represent a rare instance of homicide committed by an individual with bvFTD and provide a basis for some reflections regarding the relationship between homicidal behavior and bvFTD.

A model to differentiate WAD patients and people with abnormal pain behaviour based on biomechanical and self-reported tests.

The prevalence of malingering among individuals presenting whiplash-related symptoms is significant and leads to a huge economic loss due to fraudulent injury claims. Various strategies have been proposed to detect malingering and symptoms exaggeration. However, most of them have been not consistently validated and tested to determine their accuracy in detecting feigned whiplash. This study merges two different approaches to detect whiplash malingering (the mechanical approach and the qualitative analysis of the symptomatology) to obtain a malingering detection model based on a wider range of indices, both biomechanical and self-reported. A sample of 46 malingerers and 59 genuine clinical patients was tested using a kinematic test and a self-report questionnaire asking about the presence of rare and impossible symptoms. The collected measures were used to train and validate a linear discriminant analysis (LDA) classification model. Results showed that malingerers were discriminated from genuine clinical patients based on a greater proportion of rare symptoms vs. possible self-reported symptoms and slower but more repeatable neck motions in the biomechanical test. The fivefold cross-validation of the LDA model yielded an area under the curve (AUC) of 0.84, with a sensitivity of 77.8% and a specificity of 84.7%.

Translational Application of a Neuro-Scientific Multi-Modal Approach Into Forensic Psychiatric Evaluation: Why and How?

A prominent body of literature indicates that insanity evaluations, which are intended to provide influential expert reports for judges to reach a decision "beyond any reasonable doubt," suffer from a low inter-rater reliability. This paper reviews the limitations of the classical approach to insanity evaluation and the criticisms to the introduction of neuro-scientific approach in court. Here, we explain why in our opinion these criticisms, that seriously hamper the translational implementation of neuroscience into the forensic setting, do not survive scientific scrutiny. Moreover, we discuss how the neuro-scientific multimodal approach may improve the inter-rater reliability in insanity evaluation. Critically, neuroscience does not aim to introduce a brain-based concept of insanity. Indeed, criteria for responsibility and insanity are and should remain clinical. Rather, following the falsificationist approach and the convergence of evidence principle, the neuro-scientific multimodal approach is being proposed as a way to improve reliability of insanity evaluation and to mitigate the influence of cognitive biases on the formulation of insanity opinions, with the final aim to reduce errors and controversies.

Numerical Activities of Daily Living - Financial: a short version.

Financial capacity is the ability to manage money and finances according to a person's values and self-interests. In Italy, the first instrument specifically designed to assess financial capacity has recently been developed: the Numerical Activities of Daily Living - Financial (NADL-F). The aims of this study are (1) to prepare a shorter version of NADL-F and (2) to examine the relationship between the new short version and a measure of general cognitive functioning of comparable length, the MMSE. After an item analysis performed on NADL-F, the items presenting a higher internal consistency were selected. The resulting NADL-F Short is a reliable, easy to use, and quick to administer tool for assessing financial capacity both in clinical and legal practice. Correlation analysis showed a low positive correlation between four NADL-F Short tasks and the MMSE, for the healthy participants group. For the patient group, instead, a low-moderate correlation was found for all the NADL-F Short tasks, except one. Many participants scoring high in the MMSE (both healthy controls and neurological patients) showed low NADL-F Short scores. These findings suggest that it is not correct to use generic tools like the MMSE to make inferences on a person's financial capacity.

Idiopathic and acquired pedophilia as two distinct disorders: an insight from neuroimaging.

Pedophilia is a disorder of public concern because of its association with child sexual offense and recidivism. Previous neuroimaging studies of potential brain abnormalities underlying pedophilic behavior, either in idiopathic or acquired (i.e., emerging following brain damages) pedophilia, led to inconsistent results. This study sought to explore the neural underpinnings of pedophilic behavior and to determine the extent to which brain alterations may be related to distinct psychopathological features in pedophilia. To this aim, we run a coordinate based meta-analysis on previously published papers reporting whole brain analysis and a lesion network analysis, using brain lesions as seeds in a resting state connectivity analysis. The behavioral profiling approach was applied to link identified regions with the corresponding psychological processes. While no consistent neuroanatomical alterations were identified in idiopathic pedophilia, the current results support that all the lesions causing acquired pedophilia are localized within a shared resting state network that included posterior midlines structures, right inferior temporal gyrus and bilateral orbitofrontal cortex. These regions are associated with action inhibition and social cognition, abilities that are consistently and severely impaired in acquired pedophiles. This study suggests that idiopathic and acquired pedophilia may be two distinct disorders, in line with their distinctive clinical features, including age of onset, reversibility and modus operandi. Understanding the neurobiological underpinnings of pedophilic behavior may contribute to a more comprehensive characterization of these individuals on a clinical ground, a pivotal step forward for the development of more efficient therapeutic rehabilitation strategies.

Machine learning in liver transplantation: a tool for some unsolved questions?

Machine learning has recently been proposed as a useful tool in many fields of Medicine, with the aim of increasing diagnostic and prognostic accuracy. Models based on machine learning have been introduced in the setting of solid organ transplantation too, where prognosis depends on a complex, multidimensional and nonlinear relationship between variables pertaining to the donor, the recipient and the surgical procedure. In the setting of liver transplantation, machine learning models have been developed to predict pretransplant survival in patients with cirrhosis, to assess the best donor-to-recipient match during allocation processes, and to foresee postoperative complications and outcomes. This is a narrative review on the role of machine learning in the field of liver transplantation, highlighting strengths and pitfalls, and future perspectives.

Detecting faking-good response style in personality questionnaires with four choice alternatives.

Deliberate attempts to portray oneself in an unrealistic manner are commonly encountered in the administration of personality questionnaires. The main aim of the present study was to explore whether mouse tracking temporal indicators and machine learning models could improve the detection of subjects implementing a faking-good response style when answering personality inventories with four choice alternatives, with and without time pressure. A total of 120 volunteers were randomly assigned to one of four experimental groups and asked to respond to the Virtuous Responding (VR) validity scale of the PPI-R and the Positive Impression Management (PIM) validity scale of the PAI via a computer mouse. A mixed design was implemented, and predictive models were calculated. The results showed that, on the PIM scale, faking-good participants were significantly slower in responding than honest respondents. Relative to VR items, PIM items are shorter in length and feature no negations. Accordingly, the PIM scale was found to be more sensitive in distinguishing between honest and faking-good respondents, demonstrating high classification accuracy (80-83%).