Single-Cell RNA Sequencing Resolves Spatiotemporal Development of Pre-thymic Lymphoid Progenitors and Thymus Organogenesis in Human Embryos.

Generation of the first T lymphocytes in the human embryo involves the emergence, migration, and thymus seeding of lymphoid progenitors together with concomitant thymus organogenesis, which is the initial step to establish the entire adaptive immune system. However, the cellular and molecular programs regulating this process remain unclear. We constructed a single-cell transcriptional landscape of human early T lymphopoiesis by using cells from multiple hemogenic and hematopoietic sites spanning embryonic and fetal stages. Among heterogenous early thymic progenitors, one subtype shared common features with a subset of lymphoid progenitors in fetal liver that are known as thymus-seeding progenitors. Unbiased bioinformatics analysis identified a distinct type of pre-thymic lymphoid progenitors in the aorta-gonad-mesonephros (AGM) region. In parallel, we investigated thymic epithelial cell development and potential cell-cell interactions during thymus organogenesis. Together, our data provide insights into human early T lymphopoiesis that prospectively direct T lymphocyte regeneration, which might lead to development of clinical applications.

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.

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.

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.

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.

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.

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.

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.

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.

Go-stimuli probability influences response bias in the sustained attention to response task: a signal detection theory perspective.

The sustained attention to response task (SART) is a popular measure in the psychology and neuroscience of attention. The underlying psychological cause for errors, in particular errors of commission, in the SART is actively disputed. Some researchers have suggested task-disengagement due to mind-wandering or mindlessness, and others have proposed strategic choices. In this study we explored an alternative perspective based on Signal Detection Theory, in which the high rate of commission errors in the SART reflects simply a shift in response bias (criterion) due to the high prevalence of Go-stimuli. We randomly assigned 406 participants to one of ten Go-stimuli prevalence rates (50%, 64%, 74%, 78%, 82%, 86%, 90%, 94%, 98% and 100%). As Go-stimuli prevalence increased reaction times to both Go and No-Go stimuli decreased, omission errors decreased and commission errors increased. These all were predicted from a hypothesized bias shift, but the findings were not compatible with some alternative theories of SART performance. These findings may have implications for similar tasks.

Does ROC asymmetry reverse when detecting new stimuli? Reinvestigating whether the retrievability of mnemonic information is task-dependent.

Recently, it has been suggested that the mnemonic information that underlies recognition decisions changes when participants are asked to indicate whether a test stimulus is new rather than old (Brainerd et al., 2021, Journal of Experimental Psychology: Learning Memory, and Cognition, advance online publication). However, some observations that have been interpreted as evidence for this assertion need not be due to mnemonic changes, but may instead be the result of conservative response strategies if the possibility of asymmetric receiver operating characteristics (ROCs) is taken into account. Conversely, recent findings in support of asymmetric ROCs rely on the assumption that the mnemonic information accessed by the decision-maker does not depend on whether an old or a new item is considered to be the target Kellen et al. (2021, Psychological Review 128[6], 1022-1050). Here, we aim to clarify whether there is such a difference in accessibility of mnemonic information by applying signal detection theory. To this end, we used two versions of a simultaneous detection and identification task in which we presented participants with two test stimuli at a time. In one version, the old item was the target; in the other, the new item was the target. This allowed us to assess differences in mnemonic information retrieved in the two tasks while taking possible ROC asymmetry into account. Results clearly indicate that there is indeed a difference in the accessibility of mnemonic information as postulated by (Brainerd et al., 2021, Journal of Experimental Psychology: Learning Memory, and Cognition, advance online publication).

fullROC: An R package for generating and analyzing eyewitness-lineup ROC curves.

A police lineup is a procedure in which a suspect is surrounded by known-innocent persons (fillers) and presented to the witness for an identification attempt. The purpose of a lineup is to test the investigator's hypothesis that the suspect is the culprit, and the investigator uses the witness' identification decision and the associated confidence level to inform this hypothesis. Whereas suspect identifications provide evidence of guilt, filler identifications and rejections provide evidence of innocence. Despite the capacity of lineups to provide exculpatory information, past research has focused, almost exclusively, on inculpatory behaviors. We recently developed a method for incorporating all lineup outcomes in a single receiver operator characteristic (ROC) curve. The area under the full lineup ROC curve reflects the total capacity of a lineup procedure to discriminate guilty suspects from innocent suspects. Here, we introduce a Comprehensive R Archive Network (CRAN) package, fullROC, to support eyewitness researchers in using the full ROC approach to analyze lineup data. The fullROC package provides functions for adjusting identification rates, generating full ROC curves for lineup data, computing the area under the ROC curves (AUC), and statistically comparing the AUCs of different lineups. Using both simulated and empirical data, we illustrate the functionality of the fullROC CRAN package. In brief, the fullROC package provides a useful tool for eyewitness researchers to analyze lineup data using the full ROC method, which incorporates both the inculpatory and exculpatory information of eyewitness behaviors.

Does scent attractiveness reveal women's ovulatory timing? Evidence from signal detection analyses and endocrine predictors of odour attractiveness.

Odour cues associated with shifts in ovarian hormones indicate ovulatory timing in females of many nonhuman species. Although prior evidence supports women's body odours smelling more attractive on days when conception is possible, that research has left ambiguous how diagnostic of ovulatory timing odour cues are, as well as whether shifts in odour attractiveness are correlated with shifts in ovarian hormones. Here, 46 women each provided six overnight scent and corresponding day saliva samples spaced five days apart, and completed luteinizing hormone tests to determine ovulatory timing. Scent samples collected near ovulation were rated more attractive, on average, relative to samples from the same women collected on other days. Importantly, however, signal detection analyses showed that rater discrimination of fertile window timing from odour attractiveness ratings was very poor. Within-women shifts in salivary oestradiol and progesterone were not significantly associated with within-women shifts in odour attractiveness. Between-women, mean oestradiol was positively associated with mean odour attractiveness. Our findings suggest that raters cannot reliably detect women's ovulatory timing from their scent attractiveness. The between-women effect of oestradiol raises the possibility that women's scents provide information about overall cycle fecundity, though further research is necessary to rigorously investigate this possibility.

The paired A-Not A design within signal detection theory: Description, differentiation, power analysis and application.

Signal detection theory gives a framework for determining how well participants can discriminate between two types of stimuli. This article first examines similarities and differences of forced-choice and A-Not A designs (also known as the yes-no or one-interval). Then it focuses on the latter, in which participants have to classify stimuli, presented to them one at a time, as belonging to one of two possible response categories. The A-Not A task can be, on a first level, replicated or non-replicated, and the sub-design for each can be, on a second level, either a monadic, a mixed, or a paired design. These combinations are explained, and the present article then focuses on the both the non-replicated and replicated paired A-Not A task. Data structure, descriptive statistics, inference statistics, and effect sizes are explained in general and based on example data (Düvel et al., 2020). Documents for the data analysis are given in an extensive online supplement. Furthermore, the important question of statistical power and required sample size is addressed, and several means for the calculation are explained. The authors suggest a standardized procedure for planning, conducting, and evaluating a study employing an A-Not A design.

Predicting the Partition of Behavioral Variability in Speed Perception with Naturalistic Stimuli.

A core goal of visual neuroscience is to predict human perceptual performance from natural signals. Performance in any natural task can be limited by at least three sources of uncertainty: stimulus variability, internal noise, and suboptimal computations. Determining the relative importance of these factors has been a focus of interest for decades but requires methods for predicting the fundamental limits imposed by stimulus variability on sensory-perceptual precision. Most successes have been limited to simple stimuli and simple tasks. But perception science ultimately aims to understand how vision works with natural stimuli. Successes in this domain have proven elusive. Here, we develop a model of humans based on an image-computable (images in, estimates out) Bayesian ideal observer. Given biological constraints, the ideal optimally uses the statistics relating local intensity patterns in moving images to speed, specifying the fundamental limits imposed by natural stimuli. Next, we propose a theoretical link between two key decision-theoretic quantities that suggests how to experimentally disentangle the impacts of internal noise and deterministic suboptimal computations. In several interlocking discrimination experiments with three male observers, we confirm this link and determine the quantitative impact of each candidate performance-limiting factor. Human performance is near-exclusively limited by natural stimulus variability and internal noise, and humans use near-optimal computations to estimate speed from naturalistic image movies. The findings indicate that the partition of behavioral variability can be predicted from a principled analysis of natural images and scenes. The approach should be extendable to studies of neural variability with natural signals.SIGNIFICANCE STATEMENT Accurate estimation of speed is critical for determining motion in the environment, but humans cannot perform this task without error. Different objects moving at the same speed cast different images on the eyes. This stimulus variability imposes fundamental external limits on the human ability to estimate speed. Predicting these limits has proven difficult. Here, by analyzing natural signals, we predict the quantitative impact of natural stimulus variability on human performance given biological constraints. With integrated experiments, we compare its impact to well-studied performance-limiting factors internal to the visual system. The results suggest that the deterministic computations humans perform are near optimal, and that behavioral responses to natural stimuli can be studied with the rigor and interpretability defining work with simpler stimuli.

Coping with Danger and Deception: Lessons from Signal Detection Theory.

AbstractSignal detection theory (SDT) has been used to model optimal stimulus discrimination for more than four decades in evolutionary ecology. A popular standard model that maximizes payoff per encounter was recently criticized for being too simplistic, leading to erroneous predictions. We review a number of SDT models that have received less attention but have explicitly taken repeated encounters into account, focusing on prey choice, mate search, aggressive mimicry, and the aiding of kin. We show how these models can be seen as variants of a second standard model that can be analyzed in a unified framework. In contrast to the simpler model, in this second model a higher probability of an undesirable or dangerous event occurring may either decrease or increase the receiver's acceptance rates. In each instance, the latter outcome requires undesirable events to be undesirable in a relative rather than an absolute sense. Increasing the abundance of desirable signalers or the payoff from accepting them may also either raise or reduce acceptance rates. Our synthesis highlights fundamental similarities among models previously studied on a case-by-case basis and challenges some long-held beliefs. For example, some classic predictions of Batesian mimicry can be reversed when model prey are protected by low profitability rather than harmful defense.

Optimal templates for signal extraction by noisy ideal detectors and human observers.

The optimal template for signal detection in white additive noise is the signal itself: the ideal observer matches each stimulus against this template and selects the stimulus associated with largest match. In the noisy ideal observer, internal noise is added to the decision variable returned by the template. While the ideal observer represents an unrealistic approximation to the human visual process, the noisy ideal observer may be applicable under certain experimental conditions. For template values constrained to lie within a specified range, theory predicts that the template associated with a noisy ideal observer should be a clipped image of the signal, a result which we demonstrate analytically using variational calculus. It is currently unknown whether the human process conforms to theory. We report a targeted analysis of the theoretical prediction for an experimental protocol that maximizes template-matching on the part of human participants. We find indicative evidence to support the theoretical expectation when internal noise is compared across participants, but not within each participant. Our results indicate that implicit knowledge about internal variability in different individuals is reflected by their detection templates; no implicit knowledge is retained for internal-noise fluctuations experienced by a given participant during data collection. The results also indicate that template encoding is constrained by the dynamic range of weight specification, rather than the range of output values transduced by the template-matching process.

A Cortico-Collicular Amplification Mechanism for Gap Detection.

Auditory cortex (AC) is necessary for the detection of brief gaps in ongoing sounds, but not for the detection of longer gaps or other stimuli such as tones or noise. It remains unclear why this is so, and what is special about brief gaps in particular. Here, we used both optogenetic suppression and conventional lesions to show that the cortical dependence of brief gap detection hinges specifically on gap termination. We then identified a cortico-collicular gap detection circuit that amplifies cortical gap termination responses before projecting to inferior colliculus (IC) to impact behavior. We found that gaps evoked off-responses and on-responses in cortical neurons, which temporally overlapped for brief gaps, but not long gaps. This overlap specifically enhanced cortical responses to brief gaps, whereas IC neurons preferred longer gaps. Optogenetic suppression of AC reduced collicular responses specifically to brief gaps, indicating that under normal conditions, the enhanced cortical representation of brief gaps amplifies collicular gap responses. Together these mechanisms explain how and why AC contributes to the behavioral detection of brief gaps, which are critical cues for speech perception, perceptual grouping, and auditory scene analysis.

Aging and working memory modulate the ability to benefit from visible speech and iconic gestures during speech-in-noise comprehension.

When comprehending speech-in-noise (SiN), younger and older adults benefit from seeing the speaker's mouth, i.e. visible speech. Younger adults additionally benefit from manual iconic co-speech gestures. Here, we investigate to what extent younger and older adults benefit from perceiving both visual articulators while comprehending SiN, and whether this is modulated by working memory and inhibitory control. Twenty-eight younger and 28 older adults performed a word recognition task in three visual contexts: mouth blurred (speech-only), visible speech, or visible speech + iconic gesture. The speech signal was either clear or embedded in multitalker babble. Additionally, there were two visual-only conditions (visible speech, visible speech + gesture). Accuracy levels for both age groups were higher when both visual articulators were present compared to either one or none. However, older adults received a significantly smaller benefit than younger adults, although they performed equally well in speech-only and visual-only word recognition. Individual differences in verbal working memory and inhibitory control partly accounted for age-related performance differences. To conclude, perceiving iconic gestures in addition to visible speech improves younger and older adults' comprehension of SiN. Yet, the ability to benefit from this additional visual information is modulated by age and verbal working memory. Future research will have to show whether these findings extend beyond the single word level.

Visual attention in spatial cueing and visual search.

To characterize internal processes of an observer conducting perceptual tasks, we developed an observer model that combines the perceptual template model (PTM), the attention mechanisms in the PTM framework (Lu & Dosher, 1998), and uncertainty of signal detection theory (Green & Swets, 1966). The model was evaluated with a visual search experiment conducted in a range of external noise, signal contrast, and target-distractor similarity conditions. In each trial, eight Gabor patches were shown in each of two brief intervals, with one target at a different orientation from the distractors in one of the presentations. Subjects were precued to a subset of the stimuli (1, 2, 4, or 8) and asked to report (a) which interval contained the target and (b) where the target was. Individual roles of uncertainty and of attention in visual search were investigated by comparing models with and without an attention component. The results showed that decision uncertainty alone was sufficient to account for the set-size effect, even in conditions with high target-distractor similarity. Our theoretical model and empirical results provide a coherent picture regarding how visual information is selected and processed during feature search.