When presented with a lineup, the witness is tasked with identifying the culprit or indicating that the culprit is not present. The witness then qualifies the decision with a confidence judgment. But how do witnesses go about making these decisions and judgments? According to absolute-judgment models, witnesses determine which lineup member provides the strongest match to memory and base their identification decision and confidence judgment on the absolute strength of this MAX lineup member. Conversely, relative-judgment models propose that witnesses determine which lineup member provides the strongest match to memory and then base their identification decision and confidence judgment on the relative strength of the MAX lineup member compared to the remaining lineup members. We took a critical test approach to test the predictions of both models. As predicted by the absolute-judgment model, but contrary to the predictions of the relative-judgment model, witnesses were more likely to correctly reject low-similarity lineups than high-similarity lineups (Experiment 1), and more likely to reject biased lineups than fair lineups (Experiment 2). Likewise, witnesses rejected low-similarity lineups with greater confidence than high-similarity lineups (Experiment 1) and rejected biased lineups with greater confidence than fair lineups (Experiment 2). Only a single pattern was consistent with the relative model and inconsistent with the absolute model: suspect identifications from biased lineups were made with greater confidence than suspect identifications from fair lineups (Experiment 2). The results suggest that absolute-judgment models better predict witness decision-making than do relative-judgment models and that pure relative-judgment models are unviable.

The discriminability measure d \' is widely used in psychology to estimate sensitivity independently of response bias. The conventional approach to estimate d \' involves a transformation from the hit rate and the false-alarm rate. When performance is perfect, correction methods must be applied to calculate d \' , but these corrections distort the estimate. In three simulation studies, we show that distortion in d \' estimation can arise from other properties of the experimental design (number of trials, sample size, sample variance, task difficulty) that, when combined with application of the correction method, make d \' distortion in any specific experiment design complex and can mislead statistical inference in the worst cases (Type I and Type II errors). To address this problem, we propose that researchers simulate d \' estimation to explore the impact of design choices, given anticipated or observed data. An R Shiny application is introduced that estimates d \' distortion, providing researchers the means to identify distortion and take steps to minimize its impact.

Researchers dispute the cause of errors in high Go, low No Go target detection tasks, like the Sustained Attention to Response Task (SART). Some researchers propose errors in the SART are due to perceptual decoupling, where a participant is unaware of stimulus identity. This lack of external awareness causes an erroneous response. Other researchers suggest the majority of the errors in the SART are instead due to response leniency, not perceptual decoupling. Response delays may enable a participant who is initially unaware of stimulus identity, perceptually decoupled, to become aware of stimulus identity, or perceptually recoupled. If, however, the stimulus presentation time is shortened to the minimum necessary for stimulus recognition and the stimulus is disrupted with a structured mask, then there should be no time to enable perception to recouple even with a response delay. From the perceptual decoupling perspective, there should be no impact of a response delay on performance in this case. Alternatively if response bias is critical, then even in this case a response delay may impact performance. In this study, we shortened stimulus presentation time and added a structured mask. We examined whether a response delay impacted performance in the SART and tasks where the SART\'s response format was reversed. We expected a response delay would only impact signal detection theory bias, c, in the SART, where response leniency is an issue. In the reverse formatted SART, since bias was not expected to be lenient, we expected no impact or minimal impact of a response delay on response bias. These predictions were verified. Response bias is more critical in understanding SART performance, than perceptual decoupling, which is rare if it occurs at all in the SART.

In many decision tasks, we have a set of alternative choices and are faced with the problem of how to use our latent beliefs and preferences about each alternative to make a single choice. Cognitive and decision models typically presume that beliefs and preferences are distilled to a scalar latent strength for each alternative, but it is also critical to model how people use these latent strengths to choose a single alternative. Most models follow one of two traditions to establish this link. Modern psychophysics and memory researchers make use of signal detection theory, assuming that latent strengths are perturbed by noise, and the highest resulting signal is selected. By contrast, many modern decision theoretic modeling and machine learning approaches use the softmax function (which is based on Luce\'s choice axiom; Luce, 1959) to give some weight to non-maximal-strength alternatives. Despite the prominence of these two theories of choice, current approaches rarely address the connection between them, and the choice of one or the other appears more motivated by the tradition in the relevant literature than by theoretical or empirical reasons to prefer one theory to the other. The goal of the current work is to revisit this topic by elucidating which of these two models provides a better characterization of latent processes in m -alternative decision tasks, with a particular focus on memory tasks. In a set of visual memory experiments, we show that, within the same experimental design, the softmax parameter β varies across m -alternatives, whereas the parameter d \' of the signal-detection model is stable. Together, our findings indicate that replacing softmax with signal-detection link models would yield more generalizable predictions across changes in task structure. More ambitiously, the invariance of signal detection model parameters across different tasks suggests that the parametric assumptions of these models may be more than just a mathematical convenience, but reflect something real about human decision-making.

Emotion recognition is central in prosocial interaction, enabling the inference of mental and affective states. Individuals who have committed sexual offenses are known to exhibit socio-affective deficits, one of the four dynamic risk assessment dimensions found in the literature. Few research focused on emotion recognition. The available literature, exclusively on individuals in prison who have committed sexual offenses, showed contrasting results. Some found a global (across all emotions) or specific (e.g., anger, fear) deficit in emotion recognition. In contrast, others found no difference between individuals in prison who have committed sexual offenses and those who have committed non-sexual offenses. In addition, no such study has been undertaken among forensic inpatients who exhibit socio-affective deficits. This study aims to investigate the recognition of dynamic facial expressions of emotion in 112 male participants divided into three groups: forensic inpatients who have committed sexual offenses (n = 37), forensic inpatients who have committed non-sexual offenses (n = 25), and community members (n = 50), using the Signal Detection Theory indices: sensitivity (d\') and response bias (c). In addition, measures related to reaction time, emotion labeling reflection time, task easiness, and easiness reflection time were also collected. Non-parametric analyses (Kruskall-Wallis\' H, followed by Mann-Whitney\'s U with Dunn-Bonferroni correction) highlighted that the two forensic inpatient groups exhibited emotion recognition deficits when compared to community members. Forensic inpatients who have committed sexual offenses were more conservative in selecting the surprise label than community members. They also took significantly more time to react to stimuli and to select an emotional label. Despite emotion recognition deficits, the two forensic inpatient groups reported more stimuli easiness than community members.

Previous research has reported diverging patterns of results with respect to discriminability and response bias when comparing the simultaneous lineup to two different lineup procedures in which items are presented sequentially, the sequential stopping rule lineup and the UK lineup. In a single large sample experiment, we compared discriminability and response bias in six-item photographic lineups presented either simultaneously, sequentially with a stopping rule, or sequentially requiring two full laps through the items before making an identification and including the ability to revisit items, analogous to the UK lineup procedure. Discriminability was greater for the simultaneous lineup compared to the sequential stopping rule lineup, despite a non-significant difference in empirical discriminability between the procedures. There was no significant difference in discriminability when comparing the simultaneous lineup to the sequential two lineup and the sequential two lap lineup to the sequential stopping rule lineup. Responding was most lenient for the sequential two lap lineup, followed by the simultaneous lineup, followed by the sequential lineup. These results imply that sequential item presentation may not exert a large effect in isolation on discriminability and response bias. Rather, discriminability and response bias in the sequential stopping rule lineup and UK lineup result from the interaction of sequential item presentation with other aspects of these procedures.

Detection canines serve critical roles to support the military, homeland security and border protection. Some explosive detection tasks are physically demanding for dogs, and prior research suggests this can lead to a reduction in olfactory detection sensitivity. To further evaluate the effect of exercise intensity on olfactory sensitivity, we developed a novel olfactory paradigm that allowed us to measure olfactory detection thresholds while dogs exercised on a treadmill at two different exercise intensities. Dogs (n = 3) showed a decrement in olfactory detection for 1-bromooctane at 10-3 (v/v) dilutions and lower under greater exercise intensity. Dogs\' hit rate for the lowest concentration dropped from 0.87 ± 0.04 when walking at low intensity to below 0.45 ± 0.06 when trotting at moderate intensity. This decline had an interaction with the duration of the session in moderate intensity exercise, whereby dogs performed near 100% detection in the first 10 min of the 8 km/h session, but showed 0% detection after 20 min. Hit rates for high odor concentrations (10-2) were relatively stable at both low (1 ± 0.00) and moderate (0.91 ± 0.04) exercise intensities. The paradigm and apparatus developed here may be useful to help further understand causes of operationally relevant olfactory detection threshold decline in dogs.

In patients with mood disorders, negative affective biases - systematically prioritising and interpreting information negatively - are common. A translational cognitive task testing this bias has shown that depressed patients have a reduced preference for a high reward under ambiguous decision-making conditions. The precise mechanisms underscoring this bias are, however, not yet understood. We therefore developed a set of measures to probe the underlying source of the behavioural bias by testing its relationship to a participant\'s reward sensitivity, value sensitivity and reward learning rate. One-hundred-forty-eight participants completed three online behavioural tasks: the original ambiguous-cue decision-making task probing negative affective bias, a probabilistic reward learning task probing reward sensitivity and reward learning rate, and a gambling task probing value sensitivity. We modelled the learning task through a dynamic signal detection theory model and the gambling task through an expectation-maximisation prospect theory model. Reward sensitivity from the probabilistic reward task (β = 0.131, p = 0.024) and setting noise from the probabilistic reward task (β = -0.187, p = 0.028) both predicted the affective bias score in a logistic regression. Increased negative affective bias, at least on this specific task, may therefore be driven in part by a combination of reduced sensitivity to rewards and more variable responses.

Models of recognition memory often assume that decisions are made independently from each other. Yet there is growing evidence that consecutive recognition responses show sequential dependencies, whereby making one response increases the probability of repeating that response from one trial to the next trial. Across six experiments, we replicated this response-related carryover effect using word and nonword stimuli and further demonstrated that the content of the previous trial-both perceptual and conceptual-can also bias the response to the current test probe, with both perceptual (orthographic) and conceptual (semantic) similarity boosting the probability of consecutive \"old\" responses. Finally, a manipulation of attentional engagement in Experiments 3a and 3b provided little evidence these carryover effects on recognition decisions are merely a product of lapses in attention. Taken together, the current study reinforces prior findings that recognition decisions are not made independently, and that multiple forms of information perseverate across consecutive trials.

UNASSIGNED: Event-related potential (ERP) studies have identified two time windows associated with recognition memory and interpreted them as reflecting two processes: familiarity and recollection. However, using relatively simple stimuli and achieving high recognition rates, most studies focused on hits and correct rejections. This leaves out some information (misses and false alarms) that according to Signal Detection Theory (SDT) is necessary to understand signal processing.
UNASSIGNED: We used a difficult visual recognition task with colored pictures of different categories to obtain enough of the four possible SDT outcomes and analyzed them with modern ERP methods.
UNASSIGNED: Non-parametric analysis of these outcomes identified a single time window (470 to 670 ms) which reflected activity within fronto-central and posterior-left clusters of electrodes, indicating differential processing. The posterior-left cluster significantly distinguished all STD outcomes. The fronto-central cluster only distinguished ERPs according to the subject\'s response: yes vs. no. Additionally, only electrophysiological activity within the posterior-left cluster correlated with the discrimination index (d\').
UNASSIGNED: We show that when all SDT outcomes are examined, ERPs of recognition memory reflect a single-time window that may reveal a bottom-up factor discriminating the history of items (i.e. memory strength), as well as a top-down factor indicating participants\' decision.