Environmental complexity and regularity shape the evolution of cognition.

The environmental complexity hypothesis suggests that cognition evolves to allow animals to negotiate a complex and changing environment. By contrast, signal detection theory suggests cognition exploits environmental regularities by containing biases (e.g. to avoid dangerous predators). Therefore, two significant bodies of theory on cognitive evolution may be in tension: one foregrounds environmental complexity, the other regularity. Difficulty in reconciling these theories stems from their focus on different aspects of cognition. The environmental complexity hypothesis focuses on the reliability of sensors in the origin of cognition, while signal detection theory focuses on decision making in cognitively sophisticated animals. Here, we extend the signal detection model to examine the joint evolution of mechanisms for detecting information (sensory systems) and those that process information to produce behaviour (decision-making systems). We find that the transition to cognition can only occur if processing compensates for unreliable sensors by trading-off errors. Further, we provide an explanation for why animals with sophisticated sensory systems nonetheless disregard the reliable information it provides, by having biases for particular behaviours. Our model suggests that there is greater nuance than has been previously appreciated, and that both complexity and regularity can promote cognition.

Signal Detection Theoretic Estimates of the Murine Absolute Visual Threshold Are Independent of Decision Bias.

Decision bias influences estimates of the absolute visual threshold. However, most psychophysical estimates of the murine absolute visual threshold have not taken bias into account. Here we developed a one-alternative forced choice (1AFC) assay to assess the decision bias of mice at the absolute visual threshold via the theory of signal detection and compared our approach with the more conventional high-threshold theoretic approach. In the 1AFC assay, mice of both sexes were trained to signal whether they detected a flash stimulus. We directly measured both hit and false alarm rates, which were used to estimate d' Using the theory of signal detection, we obtained absolute thresholds by interpolating the intensity where d' = 1 from d'-psychometric functions. This gave bias-independent estimates of the absolute visual threshold which ranged over sixfold, averaging ∼1 R* in 1,000 rods (n = 7 mice). To obtain high-threshold theoretic estimates of the absolute visual threshold from the same mice, we estimated threshold intensities from the frequency of seeing curves, corrected for guessing. This gave us thresholds that were strongly correlated with decision bias, ranging over 13-fold and averaged ∼1 R* in 2,500 rods. We conclude that the theory of signal detection uses false alarms to overcome decision bias and narrow the range of threshold estimates in mice, providing a powerful tool for understanding detection behavior near absolute visual threshold.

Effects of expectations and sensory unreliability on voice detection - A preregistered study.

The phenomenon of "hearing voices" can be found not only in psychotic disorders, but also in the general population, with individuals across cultures reporting auditory perceptions of supernatural beings. In our preregistered study, we investigated a possible mechanism of such experiences, grounded in the predictive processing model of agency detection. We predicted that in a signal detection task, expecting less or more voices than actually present would drive the response bias toward a more conservative and liberal response strategy, respectively. Moreover, we hypothesized that including sensory noise would enhance these expectancy effects. In line with our predictions, the findings show that detection of voices relies on expectations and that this effect is especially pronounced in the case of unreliable sensory data. As such, the study contributes to our understanding of the predictive processes in hearing and the building blocks of voice hearing experiences.

The role of perspective in refereeing: Insights from a video-based decision-making experiment.

Decision accuracy is a crucial factor in the evaluation of refereeing performance. In sports research, officials' decision-making is frequently assessed outside real games through video-based decision experiments, where they evaluate recorded game situations from a third-person perspective. This study examines whether the inclusion of the first-person perspective influences decision accuracy and certainty. Twenty-four professional officials from the first and second German basketball leagues participated in the study. The officials assessed 50 game situations from both first-person and third-person perspectives, indicating their decisions and certainty levels. The statistical analysis utilises signal detection theory to evaluate the efficacy of the first-person perspective compared to the third-person perspective in identifying rule violations and no-calls in video recordings. The findings indicate that the first-person perspective does not yield superior accuracy in identifying foul calls. However, scenes from the first-person perspective exhibit a significant 9% increase in correctly identifying no-calls. Furthermore, officials report significantly higher levels of decision certainty and comfort when using the first-person perspective. The study suggests that sports officials may benefit from incorporating additional scenes from the first-person perspective into video-based decision training. Future studies should explore whether this additional perspective improves the training effect and translates into enhanced in-game performance.

Multidimensional signal detection modeling reveals Gestalt-like perceptual integration of face emotion and identity.

Numerous studies have tested the hypothesis that facial identity and emotional expression are independently processed, but a solid conclusion has been difficult to reach, with the literature showing contradictory results. We argue that this is partly due to different researchers using different definitions of perceptual integration and independence, usually vague and/or simply operational, and also due to lack of proper stimulus control. Here, we performed a study using three-dimensional realistic computer-generated faces for which the discriminability of identities and expressions, the intensity of the expressions, and low-level features of the faces were controlled. A large number of participants, distributed across twelve experimental groups, performed identification tasks for the six basic emotional expressions and the neutral expression (between 2018 and 2019). A multidimensional signal detection model was utilized to analyze the data, which allowed us to dissociate between multiple formally defined notions of independence and holism. Results showed strong and robust violations of perceptual independence that were consistent across all experiments and suggest Gestalt-like perceptual integration of face identity and expression. To date, our results provide the strongest evidence for holistic/Gestalt processing found among face perception studies that have used formal definitions of independence and holism. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The effects of filler similarity and lineup size on eyewitness identification.

A photo lineup, which is a cross between an old/new and a forced-choice recognition memory test, consists of one suspect, whose face was either seen before or not, and several physically similar fillers. First, the participant/witness must decide whether the person who was previously seen is present (old/new) and then, if present, choose the previously seen target (forced choice). Competing signal-detection models of eyewitness identification performance make different predictions about how certain variables will affect a witness's ability to discriminate previously seen (guilty) suspects from new (innocent) suspects. One key variable is the similarity of the fillers to the suspect in the lineup, and another key variable is the size of the lineup (i.e., the number of fillers). Previous research investigating the role of filler similarity has supported one model, known as the Ensemble model, whereas previous research investigating the role of lineup size has supported a competing model, known as the Independent Observations model. We simultaneously manipulated these two variables (filler similarity and lineup size) and found a pattern that is not predicted by either model. When the fillers were highly similar to the suspect, increasing lineup size reduced discriminability, but when the fillers were dissimilar to the suspect, increasing lineup size enhanced discriminability. The results suggest that each additional filler adds noise to the decision-making process and that this noise factor is minimized by maximizing filler dissimilarity. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Familiarity Alters the Bandwidth of Perceptual Awareness.

Results from paradigms like change blindness and inattentional blindness indicate that observers are unaware of numerous aspects of the visual world. However, intuition suggests that perceptual experience is richer than these results indicate. Why does it feel like we see so much when the data suggests we see so little? One possibility stems from the fact that experimental studies always present observers with stimuli that they have never seen before. Meanwhile, when forming intuitions about perceptual experience, observers reflect on their experiences with scenes with which they are highly familiar (e.g., their office). Does prior experience with a scene change the bandwidth of perceptual awareness? Here, we asked if observers were better at noticing alterations to the periphery in familiar scenes compared with unfamiliar scenes. We found that observers noticed changes to the periphery more frequently with familiar stimuli. Signal detection theoretic analyses revealed that when observers are unfamiliar with a stimulus, they are less sensitive at noticing (d') and are more conservative in their response criterion (c). Taken together, these results suggest that prior knowledge expands the bandwidth of perceptual awareness. It should be stressed that these results challenge the widely held idea that prior knowledge fills in perception. Overall, these findings highlight how prior knowledge plays an important role in determining the limits of perceptual experience and is an important factor to consider when attempting to reconcile the tension between empirical observation and personal introspection.

A guide to measuring expert performance in forensic pattern matching.

Decisions in forensic science are often binary. A firearms expert must decide whether a bullet was fired from a particular gun or not. A face comparison expert must decide whether a photograph matches a suspect or not. A fingerprint examiner must decide whether a crime scene fingerprint belongs to a suspect or not. Researchers who study these decisions have therefore quantified expert performance using measurement models derived largely from signal detection theory. Here we demonstrate that the design and measurement choices researchers make can have a dramatic effect on the conclusions drawn about the performance of forensic examiners. We introduce several performance models - proportion correct, diagnosticity ratio, and parametric and non-parametric signal detection measures - and apply them to forensic decisions. We use data from expert and novice fingerprint comparison decisions along with a resampling method to demonstrate how experimental results can change as a function of the task, case materials, and measurement model chosen. We also graphically show how response bias, prevalence, inconclusive responses, floor and ceiling effects, case sampling, and number of trials might affect one's interpretation of expert performance in forensics. Finally, we discuss several considerations for experimental and diagnostic accuracy studies: (1) include an equal number of same-source and different-source trials; (2) record inconclusive responses separately from forced choices; (3) include a control comparison group; (4) counterbalance or randomly sample trials for each participant; and (5) present as many trials to participants as is practical.

Influence of reinforcement and its omission on trial-by-trial changes of response bias in perceptual decision making.

Discrimination performance in perceptual choice tasks is known to reflect both sensory discriminability and nonsensory response bias. In the framework of signal detection theory, these aspects of discrimination performance are quantified through separate measures, sensitivity (d') for sensory discriminability and decision criterion (c) for response bias. However, it is unknown how response bias (i.e., criterion) changes at the single-trial level as a consequence of reinforcement history. We subjected rats to a two-stimulus two-response conditional discrimination task with auditory stimuli and induced response bias through unequal reinforcement probabilities for the two responses. We compared three signal-detection-theory-based criterion learning models with respect to their ability to fit experimentally observed fluctuations of response bias on a trial-by-trial level. These models shift the criterion by a fixed step (1) after each reinforced response or (2) after each nonreinforced response or (3) after both. We find that all three models fail to capture essential aspects of the data. Prompted by the observation that steady-state criterion values conformed well to a behavioral model of signal detection based on the generalized matching law, we constructed a trial-based version of this model and find that it provides a superior account of response bias fluctuations under changing reinforcement contingencies.

Benefits of multinomial processing tree models with discrete and continuous variables in memory research: an alternative modeling proposal to Juola et al. (2019).

Signal detection theory (SDT) and two-high threshold models (2HT) are often used to analyze accuracy data in recognition memory paradigms. However, when reaction times (RTs) and/or confidence levels (CLs) are also measured, they usually are analyzed separately or not at all as dependent variables (DVs). We propose a new approach to include these variables based on multinomial processing tree models for discrete and continuous variables (MPT-DC) with the aim to compare fits of SDT and 2HT models. Using Juola et al.'s (2019, Memory & Cognition, 47[4], 855-876) data we have found that including CLs and RTs reduces the standard errors of parameter estimates and accounts for interactions among accuracy, CLs, and RTs that classical versions of SDT and 2HT models do not. In addition, according to the simulations, there is an increase in the proportion of correct model selections when relevant DV are included. We highlight the methodological and substantive advantages of MPT-DC in the disentanglement of contributing processes in recognition memory.

Response uncertainty influences response bias in the sustained attention to response task: a signal detection theory perspective.

In the current investigation, we modified the high Go, low No-Go Sustained Attention to Response Task (SART) by replacing the single response on Go trials with a dual response to increase response uncertainty. In three experiments, a total of 80 participants completed either the original SART with no response uncertainty regarding the Go stimuli, or versions of the dual response SART in which response probabilities for the two possible responses to the Go stimuli varied from 0.9-0.1, 0.7-0.3, to 0.5-0.5. This resulted in a scale of increasing response uncertainty based on information theory to the Go stimuli. The probability of No-Go withhold stimuli was kept.11 in all experiments. Using the Signal Detection Theory perspective proposed by Bedi et al. (Psychological Research: 1-10, 2022), we predicted that increasing response uncertainty would result in a conservative response bias shift, noted by decreased errors of commission and slower response times to both Go and No-Go stimuli. These predictions were verified. The errors of commission in the SART may not be a measures of conscious awareness per se, but instead indicative of the level of participant trigger happiness-the willingness to respond quickly.

Avaliação e ensino de emoções com crianças e jovens adultos com autismo ou síndrome de down mediado pela família / Assessment and teaching of emotions with children and young adults with autism or down syndrome mediated by family / Evaluación y enseñanza de las emociones con niños y jóvenes con autismo o síndrome de down mediadas por la familia

Este estudo avaliou o reconhecimento (imitação, identidade e identificação) e a nomeação de estímulos emocionais de valência negativa (raiva e tristeza) e positiva (alegria e surpresa) em conjunto com a influência dos tipos de estímulos utilizados (social-feminino, social-masculino, familiar e emoji) em crianças e jovens adultos com autismo ou síndrome de Down, por meio de tarefas aplicadas pela família e mediadas por recursos tecnológicos durante a pandemia de covid-19. Participaram cinco crianças e dois jovens adultos com autismo e uma criança e dois jovens adultos com síndrome de Down. Foram implementadas tarefas de identidade, reconhecimento, nomeação e imitação, com estímulos faciais de função avaliativa (sem consequência diferencial) e de ensino (com consequência diferencial, uso de dicas e critério de aprendizagem), visando a emergência da nomeação emocional por meio do ensino das tarefas de reconhecimento. Os resultados da linha de base identificaram que, para os participantes que apresentaram menor tempo de resposta para o mesmo gênero, a diferença de tempo de resposta foi em média 57,28% menor. Em relação à valência emocional, 50% dos participantes apresentaram diferenças nos acertos, a depender da valência positiva e negativa, sendo que 66,66% apresentaram diferenças para o tempo de resposta a depender da valência emocional. Após o procedimento de ensino, os participantes mostraram maior número de acertos nas tarefas, independentemente do gênero de estímulo e valência emocional, criando ocasião para generalização da aprendizagem de reconhecimento e nomeação de emoções, além de consolidar a viabilidade de estratégias de ensino mediadas por recursos tecnológicos e aplicadas por familiares.(AU)

This study evaluated the recognition (imitation, identity, and identification) and naming of negative (anger and sadness) and positive (joy and surprise) emotional stimuli alongside the influence of the types of stimuli (social-female, social-male, family, and emoji) in children and young adults with autism and Down syndrome, via tasks applied by the family and mediated by technological resources, during the COVID-19 pandemic. Five children and two young adults with autism and one child and two young adults with Down syndrome participated. Identity, recognition, naming, and imitation tasks were planned and implemented using facial stimuli with evaluative (without differential consequence) and teaching (with differential consequence, tips, and learning criteria) functions, aiming at the emergence of emotional naming from the recognition teaching tasks. The baseline results showed that, for participants who had a shorter response time for the same gender, the response time difference was on average 57.28% lower. Regarding the emotional valence, 50% of the participants showed differences in the correct answers, depending on the positive and negative valence, and 66.66% showed differences in the response time depending on the emotional valence. After the teaching procedure, the participants showed a greater number of correct answers in the tasks, regardless of the stimulus type and emotional valence, creating an opportunity for generalizing learning of emotion recognition and naming, in addition to consolidating the feasibility of teaching strategies mediated by technological resources and applied by family members.(AU)

Este estudio evaluó el reconocimiento (imitación, identidad e identificación) y la denominación de estímulos emocionales negativos (enfado y tristeza) y positivos (alegría y sorpresa) y la influencia de los tipos de estímulos utilizados (social-femenino, social-masculino, familiar y emoji ) de niños y jóvenes con autismo o síndrome de Down, a través de tareas aplicadas por la familia, mediadas por recursos tecnológicos durante la pandemia de la covid-19. Participaron cinco niños y dos adultos jóvenes con autismo, y un niño y dos adultos jóvenes con síndrome de Down. Se planificaron e implementaron tareas de identidad, reconocimiento, nombramiento e imitación con estímulos faciales con función evaluativa (sin consecuencia diferencial) y enseñanza (con consecuencia diferencial, uso de ayudas y criterios de aprendizaje), buscando la emergencia del nombramiento emocional después de la enseñanza de tareas de reconocimiento. Los resultados de la línea de base identificaron que para los participantes que tenían un tiempo de respuesta más corto para el mismo género, la diferencia en el tiempo de respuesta fue un 57,28% menor. En cuanto a la valencia emocional, el 50% de los participantes mostraron diferencias en las respuestas correctas, en función de la valencia positiva y negativa, y el 66,66% tuvieron diferencias en el tiempo de respuesta, en función de la valencia emocional. Después del procedimiento de enseñanza, los participantes mostraron mayor número de aciertos en las tareas evaluadas, independientemente del tipo de estímulo o valencia emocional, lo que genera una oportunidad para la generalización del aprendizaje de reconocimiento y denominación de emociones, además de consolidar la viabilidad de estrategias de enseñanza mediadas por recursos tecnológicos y aplicadas por la familia.(AU)

Linking paranormal and conspiracy beliefs to illusory pattern perception through signal detection theory.

Previous research indicates that irrational beliefs (Paranormal beliefs & conspiracy theory endorsement) are associated with the perception of patterns in noise, but the previous findings do not conclusively describe this relationship. This study aims to disentangle the underlying parameters of this association by applying a signal detection theory approach, thus allowing to distinguish illusory pattern perception (false alarms) from perceptual sensitivity and response tendencies-while also taking base rate information into account. Results from a large sample (N = 723) indicate that paranormal beliefs relate to a more liberal response bias and a lower perceptual sensitivity, and that this relationship is driven by illusory pattern perception. Such a clear pattern could not be observed for conspiracy beliefs, for which the increase in false alarm rates was moderated by the base rate. The associations between irrational beliefs and illusory pattern perception were however less substantial compared to other sources of variance. Implications are discussed.

On why we lack confidence in some signal-detection-based analyses of confidence.

Signal-detection theory (SDT) is one of the most popular frameworks for analyzing data from studies of human behavior - including investigations of confidence. SDT-based analyses of confidence deliver both standard estimates of sensitivity (d'), and a second estimate informed by high-confidence decisions - meta d'. The extent to which meta d' estimates fall short of d' estimates is regarded as a measure of metacognitive inefficiency, quantifying the contamination of confidence by additional noise. These analyses rely on a key but questionable assumption - that repeated exposures to an input will evoke a normally-shaped distribution of perceptual experiences (the normality assumption). Here we show, via analyses inspired by an experiment and modelling, that when distributions of experience do not conform with the normality assumption, meta d' can be systematically underestimated relative to d'. Our data highlight that SDT-based analyses of confidence do not provide a ground truth measure of human metacognitive inefficiency. We explain why deviance from the normality assumption is especially a problem for some popular SDT-based analyses of confidence, in contrast to other analyses inspired by the SDT framework, which are more robust to violations of the normality assumption.

A zero-cost attention-based approach to promote cleaner streets: A Signal Detection Theory approach in Parisian streets.

In an effort to inform interventions targeting littering behaviour, we estimate how much a change in trash-bag colour increases trash can visibility in Paris. To that end, we applied standard Signal Detection techniques to test how much changing trash-bag colour affects subjects' trash can detection rates. In three pre-registered studies, we found that changing trash bag colour from grey to either red, green or blue considerably increases the perception of bins in British (tourist) and Parisian (resident) samples. We found that changing the bag colour from grey to blue increased visibility the most.

Recognition receiver operating characteristic asymmetry: Increased noise or information?

The recognition memory receiver operating characteristic (ROC) is typically asymmetric with a characteristic elevation of the left-hand portion. Whereas the unequal variance signal detection model (uvsd) assumes the asymmetry results because old item evidence is noisier than new item evidence, the dual process signal detection model (dpsd) assumes it results because old items convey more useful information than new items. To test these assumptions, the models were fit to old/new recognition data and their evidence parameters were used to predict performance on a novelty, three-alternative forced-choice (N3AFC) recognition task. Critically, under the uvsd model, increased old item variance (sigma) predicts poorer N3AFC performance, whereas under the dpsd model, increased recollection rates (Ro) predict better N3AFC performance. Hence, the asymmetry parameters of the two models make divergent predictions. In two experiments the dpsd model's predictions were supported, whereas the uvsd model yielded unpredicted (from that model's perspective) patterns. Through simulation it was also shown that the dpsd model predicted the uvsd model's mispredictions, which resulted because increases in old item noise markedly depress the upper portion of the ROC. Overall, the data demonstrate that increasing ROC asymmetry is not a function of increasingly noisier target evidence, but instead increasingly informative target evidence. These findings invalidate the uvsd model, which heretofore has been primarily supported by its post-hoc fitting ability, not its construct validity. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Incorporating Functional Response Time Effects into a Signal Detection Theory Model.

Signal detection theory (SDT; Tanner & Swets in Psychological Review 61:401-409, 1954) is a dominant modeling framework used for evaluating the accuracy of diagnostic systems that seek to distinguish signal from noise in psychology. Although the use of response time data in psychometric models has increased in recent years, the incorporation of response time data into SDT models remains a relatively underexplored approach to distinguishing signal from noise. Functional response time effects are hypothesized in SDT models, based on findings from other related psychometric models with response time data. In this study, an SDT model is extended to incorporate functional response time effects using smooth functions and to include all sources of variability in SDT model parameters across trials, participants, and items in the experimental data. The extended SDT model with smooth functions is formulated as a generalized linear mixed-effects model and implemented in the gamm4 R package. The extended model is illustrated using recognition memory data to understand how conversational language is remembered. Accuracy of parameter estimates and the importance of modeling variability in detecting the experimental condition effects and functional response time effects are shown in conditions similar to the empirical data set via a simulation study. In addition, the type 1 error rate of the test for a smooth function of response time is evaluated.

Drugs That Interact With Colchicine Via Inhibition of Cytochrome P450 3A4 and P-Glycoprotein: A Signal Detection Analysis Using a Database of Spontaneously Reported Adverse Events (FAERS).

BACKGROUND: Colchicine has a narrow therapeutic index. Its toxicity can be increased due to concomitant exposure to drugs inhibiting its metabolic pathway; these are cytochrome P450 3A4 (CYP3A4) and P-glycoprotein (P-gp). OBJECTIVE: To examine clinical outcomes associated with colchicine drug interactions using the spontaneous reports of the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). METHODS: We conducted a disproportionality analysis using FAERS data from January 2004 through June 2020. The reporting odds ratio (ROR) and observed-to-expected ratio (O/E) with shrinkage for adverse events related to colchicine's toxicity (ie, rhabdomyolysis/myopathy, agranulocytosis, hemorrhage, acute renal failure, hepatic failure, arrhythmias, torsade de pointes/QT prolongation, and cardiac failure) were compared between FAERS reports. RESULTS: A total of 787 reports included the combined mention of colchicine, an inhibitor of both CYP3A4 and P-gp drug, and an adverse event of interest. Among reports that indicated the severity, 61% mentioned hospitalization and 24% death. A total of 37 ROR and 34 O/E safety signals involving colchicine and a CYP3A4/P-gp inhibitor were identified. The strongest ROR signal was for colchicine + atazanavir and rhabdomyolysis/myopathy (ROR = 35.4, 95% CI: 12.8-97.6), and the strongest O/E signal was for colchicine + atazanavir and agranulocytosis (O/E = 3.79, 95% credibility interval: 3.44-4.03). CONCLUSION AND RELEVANCE: This study identifies numerous safety signals for colchicine and CYP3A4/P-gp inhibitor drugs. Avoiding the interaction or monitoring for toxicity in patients when co-prescribing colchicine and these agents is highly recommended.