Electrophysiological correlates of cognitive control and performance monitoring in risk propensity: An event-related potential study

Investigating the cognitive control processes and error detection mechanisms involved in risk-taking behaviors is essential for understanding risk propensity. This study investigated the relationship between risk propensity and cognitive control processes using an event-related potentials (ERP) approach. The study employed a Cued Go/Nogo paradigm to elicit ERP components related to cognitive control processes, including contingent negative variation (CNV), P300, error-related negativity (ERN), and error positivity (Pe). Healthy participants were categorized into high-risk and low-risk groups based on their performance in the Balloon Analogue Risk Task (BART). The results revealed risk-taking behavior influenced CNV amplitudes, indicating heightened response preparation and inhibition for the high-risk group. In contrast, the P300 component showed no group differences but revealed enhanced amplitudes in Nogo trials, particularly in high-risk group. Furthermore, despite the lack of difference in the Pe component, the high-risk group exhibited smaller ERN amplitudes compared to the low-risk group, suggesting reduced sensitivity to error detection. These findings imply that risk-taking behaviors may be associated with a hypoactive avoidance system rather than impaired response inhibition. Understanding the neural mechanisms underlying risk propensity and cognitive control processes can contribute to the development of interventions aimed at reducing risky behaviors and promoting better decision-making.

Error-related cardiac deceleration: Functional interplay between error-related brain activity and autonomic nervous system in performance monitoring

Coordinated interactions between the central and autonomic nervous systems are crucial for survival due to the inherent propensity for human behavior to make errors. In our ever-changing environment, when individuals make mistakes, these errors can have life-threatening consequences. In response to errors, specific reactions occur in both brain activity and heart rate to detect and correct errors. Specifically, there are two brain-related indicators of error detection and awareness known as error-related negativity and error positivity. Conversely, error-related cardiac deceleration denotes a momentary slowing of heart rate following an error, signaling an autonomic response. However, what is the connection between the brain and the heart during error processing? In this review, we discuss the functional and neuroanatomical connections between the brain and heart markers of error processing, exploring the experimental conditions in which they covary. Given the current limitations of available data, future research will continue to investigate the neurobiological factors governing the brain-heart interaction, aiming to utilize them as combined markers for assessing cognitive control in healthy and pathological conditions.

Self-supervised multi-modal training from uncurated images and reports enables monitoring AI in radiology

The escalating demand for artificial intelligence (AI) systems that can monitor and supervise human errors and abnormalities in healthcare presents unique challenges. Recent advances in vision-language models reveal the challenges of monitoring AI by understanding both visual and textual concepts and their semantic correspondences. However, there has been limited success in the application of vision-language models in the medical domain. Current vision-language models and learning strategies for photographic images and captions call for a web-scale data corpus of image and text pairs which is not often feasible in the medical domain. To address this, we present a model named medical cross-attention vision-language model (Medical X-VL), which leverages key components to be tailored for the medical domain. The model is based on the following components: self-supervised unimodal models in medical domain and a fusion encoder to bridge them, momentum distillation, sentencewise contrastive learning for medical reports, and sentence similarity-adjusted hard negative mining. We experimentally demonstrated that our model enables various zero-shot tasks for monitoring AI, ranging from the zero-shot classification to zero-shot error correction. Our model outperformed current state-of-the-art models in two medical image datasets, suggesting a novel clinical application of our monitoring AI model to alleviate human errors. Our method demonstrates a more specialized capacity for fine-grained understanding, which presents a distinct advantage particularly applicable to the medical domain.

Thought Experiments as an Error Detection and Correction Tool

The ability to recognize and correct errors in one's explanatory understanding is critically important for learning. However, little is known about the mechanisms that determine when and under what circumstances errors are detected and how they are corrected. The present study investigated thought experiments as a potential tool that can reveal errors and trigger belief revision in the service of error correction. Across two experiments, 1149 participants engaged in reasoning about force and motion (a domain with well-documented misconceptions) in a pre-training-training-post-training design. The two experiments manipulated the type of mental model manipulated in the thought experiments (i.e., whether participants reasoned about forces acting on their own bodies vs. on external objects), as well as the level of relational and argumentative reasoning about the outcomes of the thought experiments. The results showed that: (i) thought experiments can serve as a tool to elicit inconsistencies in one's representations; (ii) the level of relational and argumentative reasoning determines the level of belief revision in the service of error correction; and (iii) the type of mental model manipulated in a thought experiment determines its outcome and its potential to initiate belief revision. Thought experiments can serve as a valuable teaching and learning tool, and they can help us better understand the nature of error detection and correction systems.

The DetectDeviatingCells algorithm was a useful addition to the toolkit for cellwise error detection in observational data

OBJECTIVES

We evaluated the error detection performance of the DetectDeviatingCells (DDC) algorithm which flags data anomalies at observation (casewise) and variable (cellwise) level in continuous variables. We compared its performance to other approaches in a simulated dataset.

STUDY DESIGN AND SETTING

We simulated height and weight data for hypothetical individuals aged 2-20 years. We changed a proportion of height values according to predetermined error patterns. We applied the DDC algorithm and other error-detection approaches (descriptive statistics, plots, fixed-threshold rules, classic, and robust Mahalanobis distance) and we compared error detection performance with sensitivity, specificity, likelihood ratios, predictive values, and receiver operating characteristic (ROC) curves.

RESULTS

At our chosen thresholds error detection specificity was excellent across all scenarios for all methods and sensitivity was higher for multivariable and robust methods. The DDC algorithm performance was similar to other robust multivariable methods. Analysis of ROC curves suggested that all methods had comparable performance for gross errors (e.g., wrong measurement unit), but the DDC algorithm outperformed the others for more complex error patterns (e.g., transcription errors that are still plausible, although extreme).

CONCLUSIONS

The DDC algorithm has the potential to improve error detection processes for observational data.

Developing an evidence-based approach to quality control

Effective Quality Control remains one of the pillars of Clinical Biochemistry. An understanding of the possible analytical errors that may occur, how to detect them efficiently and how to prevent them from causing patient harm are critical components of a Quality System. For some time, there have been questions about the theoretical basis of the models used to describe and detect analytical error. The current theory recognises two types of error, systematic and random and a system based on sampling the analytical process using a synthetic material to detect these errors. However, there are at least two other errors that are present. One is related to the QC material and the other, irregular errors. In this Opinion Piece, some of the underlying assumptions of Quality Control systems are described and analysed.

Treatment verification in high dose rate brachytherapy using a realistic 3D printed head phantom and an imaging panel

PURPOSE

Even though High Dose Rate (HDR) brachytherapy has good treatment outcomes in different treatment sites, treatment verification is far from widely implemented because of a lack of easily available solutions. Previously it has been shown that an imaging panel (IP) near the patient can be used to determine treatment parameters such as the dwell time and source positions in a single material pelvic phantom. In this study we will use a heterogeneous head phantom to test this IP approach, and simulate common treatment errors to assess the sensitivity and specificity of the error-detecting capabilities of the IP.

METHODS AND MATERIALS

A heterogeneous head-phantom consisting of soft tissue and bone equivalent materials was 3D-printed to simulate a base of tongue treatment. An High Dose Rate treatment plan with 3 different catheters was used to simulate a treatment delivery, using dwell times ranging from 0.3 s to 4 s and inter-dwell distances of 2 mm. The IP was used to measure dwell times, positions and detect simulated errors. Measured dwell times and positions were used to calculate the delivered dose.

RESULTS

Dwell times could be determined within 0.1 s. Source positions were measured with submillimeter accuracy in the plane of the IP, and average distance accuracy of 1.7 mm in three dimensions. All simulated treatment errors (catheter swap, catheter shift, afterloader errors) were detected. Dose calculations show slightly different distributions with the measured dwell positions and dwell times (gamma pass rate for 1 mm/1% of 96.5%).

CONCLUSIONS

Using an IP, it was possible to verify the treatment in a realistic heterogeneous phantom and detect certain treatment errors.

Error detection using EPID-based 3D in vivo dose verification for lung stereotactic body radiotherapy

PURPOSE

To investigate the error detectability limitations of an EPID-based 3D in vivo dosimetry verification system for lung stereotactic body radiation therapy (SBRT).

METHODS

Thirty errors were intentionally introduced, consisting of dynamic and constant machine errors, to simulate the possible errors that may occur during delivery. The dynamic errors included errors in the output, gantry angle and MLC positions related to gantry inertial and gravitational effects, while the constant errors included errors in the collimator angle, jaw positions, central leaf positions, setup shift and thickness to simulate patient weight loss. These error plans were delivered to a CIRS phantom using the SBRT technique for lung cancer. Following irradiation of these error plans, the dose distribution was reconstructed using iViewDose™ and compared with the no error plan.

RESULTS

All errors caused by the central leaf positions, dynamic MLC errors, Jaw inwards movements, setup shifts and patient anatomical changes were successfully detected. However, dynamic gantry angle and collimator angle errors were not detected in the lung case due to the rotation-symmetric target shape. The results showed that the γ_mean and γ_passrate indicators can detect 13 (81.3%) and 14 (87.5%) of the 16 errors respectively without including the gantry angle error, collimator angle error and output error.

CONCLUSIONS

In summary, iViewDose™ is an appropriate approach for detecting most types of clinical errors for lung SBRT. However, the phantom results also showed some detectability limitations of the system in terms of dynamic gantry angle and constant collimator angle errors.

Error assessment and correction for extrusion-based bioprinting using computer vision method

299Bioprinting offers a new approach to addressing the organ shortage crisis. Despite recent technological advances, insufficient printing resolution continues to be one of the reasons that impede the development of bioprinting. Normally, machine axes movement cannot be reliably used to predict material placement, and the printing path tends to deviate from the predetermined designed reference trajectory in varying degrees. Therefore, a computer vision-based method was proposed in this study to correct trajectory deviation and improve printing accuracy. The image algorithm calculated the deviation between the printed trajectory and the reference trajectory to generate an error vector. Furthermore, the axes trajectory was modified according to the normal vector approach in the second printing to compensate for the deviation error. The highest correction efficiency that could be achieved was 91%. More significantly, we discovered that the correction results, for the first time, were in a normal distribution instead of a random distribution.

Propagation, detection and correction of errors using the sequence database network

Nucleotide and protein sequences stored in public databases are the cornerstone of many bioinformatics analyses. The records containing these sequences are prone to a wide range of errors, including incorrect functional annotation, sequence contamination and taxonomic misclassification. One source of information that can help to detect errors are the strong interdependency between records. Novel sequences in one database draw their annotations from existing records, may generate new records in multiple other locations and will have varying degrees of similarity with existing records across a range of attributes. A network perspective of these relationships between sequence records, within and across databases, offers new opportunities to detect-or even correct-erroneous entries and more broadly to make inferences about record quality. Here, we describe this novel perspective of sequence database records as a rich network, which we call the sequence database network, and illustrate the opportunities this perspective offers for quantification of database quality and detection of spurious entries. We provide an overview of the relevant databases and describe how the interdependencies between sequence records across these databases can be exploited by network analyses. We review the process of sequence annotation and provide a classification of sources of error, highlighting propagation as a major source. We illustrate the value of a network perspective through three case studies that use network analysis to detect errors, and explore the quality and quantity of critical relationships that would inform such network analyses. This systematic description of a network perspective of sequence database records provides a novel direction to combat the proliferation of errors within these critical bioinformatics resources.

EXPRESS: Examining the Difference in Error Detection when Listening to Native and Non-Native Speakers

As communication with non-native speakers becomes increasingly common, it is important to understand how foreign-accented speech might influence language processing. Non-native speech can require the listener to process errors such as grammatical violations or unexpected word choices. The present study examines how listeners process different types of errors across native and non-native speakers. Using a self-paced listening task measuring reaction times to target words, 30 participants listened to sentences that contained either no error, a grammatical error (e.g.," Do you wanting anything?"), or a contextual formal/informal word-choice error (e.g. "Do you require anything?" in an informal context). Participants responded more slowly while processing grammatical and word-choice errors compared to control sentences, especially when listening to non-native speech. This suggests that errors spoken by non-native speakers take longer to process, both in the case of grammatical errors as well as when contextually inappropriate words are used.

The influence of error detection and error significance on neural and behavioral correlates of error processing in a complex choice task

Error detection and error significance form essential mechanisms that influence error processing and action adaptation. Error detection often is assessed by an immediate self-evaluation of accuracy. Our study used cognitive neuroscience methods to elucidate whether self-evaluation itself influences error processing by increasing error significance in the context of a complex response selection process. In a novel eight-alternative response task, our participants responded to eight symbol stimuli with eight different response keys and a specific stimulus-response assignment. In the first part of the experiment, the participants merely performed the task. In the second part, they also evaluated their response accuracy on each trial. We replicated variations in early and later stages of error processing and action adaptation as a function of error detection. The additional self-evaluation enhanced error processing on later stages, probably reflecting error evidence accumulation, whereas earlier error monitoring processes were not amplified. Implementing multivariate pattern analysis revealed that self-evaluation influenced brain activity patterns preceding and following the response onset, independent of response accuracy. The classifier successfully differentiated between responses from the self- and the no-self-evaluation condition several hundred milliseconds before response onset. Subsequent exploratory analyses indicated that both self-evaluation and the time on task contributed to these differences in brain activity patterns. This suggests that in addition to its effect on error processing, self-evaluation in a complex choice task seems to have an influence on early and general processing mechanisms (e.g., the quality of attention and stimulus encoding), which is amplified by the time on task.

Perspective on reducing errors in research

Efforts to ensure research integrity has mostly focused on research misconduct. However, the complexity of research operations and processes makes research work also prone to unintentional errors. To safeguard against errors and their consequences, strategies for error reduction, detection, and mitigation can be applied to research work. Nurturing a scientific culture that encourages error disclosure and rectification is essential to reduce the negative consequences of errors. Creating repositories where errors can be reported can enable learning from errors and creation of more robust research processes.

Neural correlates of metacognition across the adult lifespan

Metacognitive accuracy describes the degree of overlap between the subjective perception of one's decision accuracy (i.e. confidence) and objectively observed performance. With older age, the need for accurate metacognitive evaluation increases; however, error detection rates typically decrease. We investigated the effect of ageing on metacognitive accuracy using event-related potentials (ERPs) reflecting error detection and confidence: the error/correct negativity (N_e/c) and the error/correct positivity (P_e/c). Sixty-five healthy adults (20 to 76 years) completed a complex Flanker task and provided confidence ratings. We found that metacognitive accuracy declined with age beyond the expected decline in task performance, while the adaptive adjustment of behaviour was well preserved. P_e amplitudes following errors varied by confidence rating, but they did not mirror the reduction in metacognitive accuracy. N_e amplitudes decreased with age for low confidence errors. The results suggest that age-related difficulties in metacognitive evaluation could be related to an impaired integration of decision accuracy and confidence information processing. Ultimately, training the metacognitive evaluation of fundamental decisions in older adults might constitute a promising endeavour.

Adaptive rescheduling of error monitoring in multitasking

The concurrent execution of temporally overlapping tasks leads to considerable interference between the subtasks. This also impairs control processes associated with the detection of performance errors. In the present study, we investigated how the human brain adapts to this interference between task representations in such multitasking scenarios. In Experiment 1, participants worked on a dual-tasking paradigm with partially overlapping execution of two tasks (T1 and T2), while we recorded error-related scalp potentials. The error positivity (Pe), a correlate of higher-level error evaluation, was reduced after T1 errors but occurred after a correct T2-response instead. MVPA-based and regression-based single-trial analysis revealed that the immediate Pe and deferred Pe are negatively correlated, suggesting a trial-wise trade-off between immediate and postponed error processing. Experiment 2 confirmed this finding and additionally showed that this result is not due to credit-assignment errors in which a T1 error is falsely attributed to T2. For the first time reporting a Pe that is temporally detached from its eliciting error event by a considerable amount of time, this study illustrates how reliable error detection in dual-tasking is maintained by a mechanism that adaptively schedules error processing, thus demonstrating a remarkable flexibility of the human brain when adapting to multitasking situations.

Improving dose delivery accuracy with EPID in vivo dosimetry: results from a multicenter study

PURPOSE

To investigate critical aspects and effectiveness of in vivo dosimetry (IVD) tests obtained by an electronic portal imaging device (EPID) in a multicenter and multisystem context.

MATERIALS AND METHODS

Eight centers with three commercial systems-SoftDiso (SD, Best Medical Italy, Chianciano, Italy), Dosimetry Check (DC, Math Resolution, LCC), and PerFRACTION (PF, Sun Nuclear Corporation, SNC, Melbourne, FL)-collected IVD results for a total of 2002 patients and 32,276 tests. Data are summarized for IVD software, radiotherapy technique, and anatomical site. Every center reported the number of patients and tests analyzed, and the percentage of tests outside of the tolerance level (OTL%). OTL% was categorized as being due to incorrect patient setup, incorrect use of immobilization devices, incorrect dose computation, anatomical variations, and unknown causes.

RESULTS

The three systems use different approaches and customized alert indices, based on local protocols. For Volumetric Modulated Arc Therapy (VMAT) treatments OTL% mean values were up to 8.9% for SD, 18.0% for DC, and 16.0% for PF. Errors due to "anatomical variations" for head and neck were up to 9.0% for SD and DC and 8.0% for PF systems, while for abdomen and pelvis/prostate treatments were up to 9%, 17.0%, and 9.0% for SD, DC, and PF, respectively. The comparison among techniques gave 3% for Stereotactic Body Radiation Therapy, 7.0% (range 4.7-8.9%) for VMAT, 10.4% (range 7.0-12.2%) for Intensity Modulated Radiation Therapy, and 13.2% (range 8.8-21.0%) for 3D Conformal Radiation Therapy.

CONCLUSION

The results obtained with different IVD software and among centers were consistent and showed an acceptable homogeneity. EPID IVD was effective in intercepting important errors.

Visual awareness judgments are sensitive to accuracy feedback in stimulus discrimination tasks

In this study we tested the hypothesis that perceptual awareness judgments are sensitive to accuracy feedback about the previous action. We used a perceptual discrimination task in which participants reported their stimulus awareness. We created two conditions: No-feedback and Feedback (discrimination accuracy feedback was provided at the end of each trial). The results showed that visual awareness judgments are related to the accuracy of current and previous responses. Participants reported lower stimulus awareness for incorrectly versus correctly discriminated stimuli in both conditions; they also reported lower stimulus awareness in trials preceded by incorrect discrimination responses, compared to trials preceded by correct discrimination responses. This difference was significantly stronger in the Feedback condition, in which we also observed post-error slowing for PAS ratings. We discuss the relation between visual awareness and the effects of performance monitoring and interpret the results in the context of current theories of consciousness.

Inhibiting errors while they are produced: Direct evidence for error monitoring and inhibitory control in children

The maturation of processes involved in performance monitoring, crucial for adaptive behavior, is a core aspect of developmental changes. Monitoring processes are often studied through the analysis of error processing. Previous developmental studies generally focused on post-error slowing and error-related EEG activities. Instead, the present study aims at collecting indicators of error monitoring processes occurring within trials that is, before the erroneous response is produced. Electromyographic (EMG) activity and force produced during responding were registered in 6 to 14-year-olds performing a choice-response task. As already reported in adults, force produced was weaker, EMG bursts were smaller, and motor times (interval between EMG onsets and responses) were longer during errors compared to correct responses. In contrast, the rising part of EMG burst, reflecting the initial motor command, was the same for both response outcomes. This suggests that error inhibition was applied online after the response was triggered but before the actual key was pressed. This error correction was already present in children as young as 6 years old. The effects of reduced EMG and force amplitudes remained stable across childhood. However, the prolonged motor times in young children suggests that they need more time to implement motor inhibition than their older peers.

Are errors detected before they occur? Early error sensations revealed by metacognitive judgments on the timing of error awareness

Errors in choice tasks are not only detected fast and reliably, participants often report that they knew that an error occurred already before a response was produced. These early error sensations stand in contrast with evidence suggesting that the earliest neural correlates of error awareness emerge around 300 ms after erroneous responses. The present study aimed to investigate whether anecdotal evidence for early error sensations can be corroborated in a controlled study in which participants provide metacognitive judgments on the subjective timing of error awareness. In Experiment 1, participants had to report whether they became aware of their errors before or after the response. In Experiment 2, wemeasured confidence in these metacognitive judgments. Our data show that participants report early error sensations with high confidence in the majority of error trials across paradigms and experiments. These results provide first evidence for early error sensations, informing theories of error awareness.

Error processing and mindfulness meditation in female students

Mindfulness seems to have an impact on error processing in simple response tasks, as former studies reported both an effect of mindfulness meditation on, as well as relationships to trait mindfulness with behavioral and neural correlates of error processing. However, the results of these studies showed no consistent pattern. To dismantle some of these findings, this study investigated the impact in female students of a four-week, smartphone-based mindfulness training program (N = 22) in comparison with an active control group that did progressive muscle relaxation (PMR; N = 20). In addition to behavioral data, two error-related components of the event-related potential were measured with electroencephalogram while performing a combination of a modified Simon task and an error detection paradigm, namely error-related negativity and error positivity. Mindfulness meditation did not have a differential effect on error components in comparison to PMR. For both, we found a reduction of stress symptoms, an increase in mindfulness and an increase in error positivity.

Deficits in arithmetic error detection in infants with prenatal alcohol exposure: An ERP study

Prenatal alcohol exposure (PAE) is associated with a range of physical, cognitive, and behavioral problems, particularly in arithmetic. We report ERP data collected from 32 infants (mean age = 6.8 mo; SD = 0.6; range = 6.1–8.1; 16 typically developing [TD]; 16 prenatally alcohol-exposed) during a task designed to assess error detection. Evidence of error monitoring at this early age suggests that precursors of the onset of executive control can already be detected in infancy. As predicted, the ERPs of the TD infants, time-locked to the presentation of the solution to simple arithmetic equations, showed greater negative activity for the incorrect solution condition at middle-frontal scalp areas. Spectral analysis indicated specificity to the 6–7 Hz frequency range. By contrast, the alcohol-exposed infants did not show the increased middle-frontal negativity seen in the TD group nor the increased power in the 6–7 Hz frequency, suggesting a marked developmental delay in error detection and/or early impairment in information processing of small quantities. Overall, our research demonstrates that (a) the brain network involved in error detection can be identified and highly specified in TD young infants, and (b) this effect is replicable and can be utilized for studying developmental psychopathology at very early ages.

Using cantor sets for error detection

Error detection is a fundamental need in most computer networks and communication systems in order to combat the effect of noise. Error detection techniques have also been incorporated with lossless data compression algorithms for transmission across communication networks. In this paper, we propose to incorporate a novel error detection scheme into a Shannon optimal lossless data compression algorithm known as Generalized Luröth Series (GLS) coding. GLS-coding is a generalization of the popular Arithmetic Coding which is an integral part of the JPEG2000 standard for still image compression. GLS-coding encodes the input message as a symbolic sequence on an appropriate 1D chaotic map Generalized Luröth Series (GLS) and the compressed file is obtained as the initial value by iterating backwards on the map. However, in the presence of noise, even small errors in the compressed file leads to catastrophic decoding errors owing to sensitive dependence on initial values, the hallmark of deterministic chaos. In this paper, we first show that repetition codes, the oldest and the most basic error correction and detection codes in literature, actually lie on a Cantor set with a fractal dimension of 1 n , which is also the rate of the code. Inspired by this, we incorporate error detection capability to GLS-coding by ensuring that the compressed file (initial value on the chaotic map) lies on a Cantor set. Even a 1-bit error in the initial value will throw it outside the Cantor set, which can be detected while decoding. The rate of the code can be adjusted by the fractal dimension of the Cantor set, thereby controlling the error detection performance.

Religious fundamentalism is associated with hyperactive performance monitoring: ERP evidence from correct and erroneous responses

The aim of the current study was to examine whether action monitoring is associated with religious fundamentalism. Participants performed a stop-signal task that required response inhibition to a simple auditory tone. The level of their religious fundamentalism was measured on a scale. Analysis with mixed-effects linear models revealed significantly larger error-related negativity, correct-related negativity, and post-error positivity components in individuals scoring higher on religious fundamentalism, pointing to their increased engagement in response monitoring. However, it was not accompanied by improved behavioral performance. The electrophysiological results of our study suggest that individuals high in religious fundamentalism engage more in monitoring for conflict between outcomes of their actions and standards of correct behavior. Our findings also point to a possible association between a fundamentalist mindset and higher levels of negative affect, uncertainty, anxiety, and distress, as measured by response-related brain activity.

A statistical framework for detecting mislabeled and contaminated samples using shallow-depth sequence data

BACKGROUND

Researchers typically sequence a given individual multiple times, either re-sequencing the same DNA sample (technical replication) or sequencing different DNA samples collected on the same individual (biological replication) or both. Before merging the data from these replicate sequence runs, it is important to verify that no errors, such as DNA contamination or mix-ups, occurred during the data collection pipeline. Methods to detect such errors exist but are often ad hoc, cannot handle missing data and several require phased data. Because they require some combination of genotype calling, imputation, and haplotype phasing, these methods are unsuitable for error detection in low- to moderate-depth sequence data where such tasks are difficult to perform accurately. Additionally, because most existing methods employ a pairwise-comparison approach for error detection rather than joint analysis of the putative replicates, results may be difficult to interpret.

RESULTS

We introduce a new method for error detection suitable for shallow-, moderate-, and high-depth sequence data. Using Bayes Theorem, we calculate the posterior probability distribution over the set of relations describing the putative replicates and infer which of the samples originated from an identical genotypic source.

CONCLUSIONS

Our method addresses key limitations of existing approaches and produced highly accurate results in simulation experiments. Our method is implemented as an R package called BIGRED (Bayes Inferred Genotype Replicate Error Detector), which is freely available for download: https://github.com/ac2278/BIGRED .

Don't worry, be active: how to facilitate the detection of errors in immersive virtual environments

The current research aims to study the link between the type of vision experienced in a collaborative immersive virtual environment (active vs. multiple passive), the type of error one looks for during a cooperative multi-user exploration of a design project (affordance vs. perceptual violations), and the type of setting in which multi-user perform (field in Experiment 1 vs. laboratory in Experiment 2). The relevance of this link is backed by the lack of conclusive evidence on an active vs. passive vision advantage in cooperative search tasks within software based on immersive virtual reality (IVR). Using a yoking paradigm based on the mixed usage of simultaneous active and multiple passive viewings, we found that the likelihood of error detection in a complex 3D environment was characterized by an active vs. multi-passive viewing advantage depending on: (1) the degree of knowledge dependence of the type of error the passive/active observers were looking for (low for perceptual violations, vs. high for affordance violations), as the advantage tended to manifest itself irrespectively from the setting for affordance, but not for perceptual violations; and (2) the degree of social desirability possibly induced by the setting in which the task was performed, as the advantage occurred irrespectively from the type of error in the laboratory (Experiment 2) but not in the field (Experiment 1) setting. Results are relevant to future development of cooperative software based on IVR used for supporting the design review. A multi-user design review experience in which designers, engineers and end-users all cooperate actively within the IVR wearing their own head mounted display, seems more suitable for the detection of relevant errors than standard systems characterized by a mixed usage of active and passive viewing.

The relationship between naturalistic sleep variation and error monitoring in young adults: An event-related potential (ERP) study

Sleep deprivation studies have highlighted the importance of adequate sleep for optimal daytime functioning. However, there is limited research exploring whether variations in natural sleep patterns produce similar difficulties to those seen in sleep deprivation studies. The aim of the current study was to explore whether naturalistic reductions in sleep duration and/or sleep quality were associated with behavioural and electrophysiological measures of cognitive control. Sixty undergraduate students were asked to wear an actigraph for 7 consecutive nights before completing a hybrid Flanker-Go/NoGo task whilst continuous EEG data were recorded. Participants were assigned to high or low sleep quality and short or long sleep duration groups using the National Sleep Foundation guidelines. Results indicated that individuals who, on average, slept <7 h each night showed inefficiencies in error-monitoring, as reflected by a reduction in amplitude of the error-related negativity (ERN) in comparison to those with longer sleep duration. These findings suggest that natural variations in sleep quantity are associated with atypical error detection.

Testing the bottleneck account for post-error slowing beyond the post-error response

The bottleneck account for post-error slowing assumes that cognitive resources are depleted after errors and thus the processing of subsequent events is delayed. To test this, we used a novel speeded-choice task and recorded behavioral measures and ERP (event-related potential) components on five trials following either an erroneous or correct response. We found that participants were slower and less accurate immediately after making an error and that this reduction of performance decayed on the following trials. Moreover, post-correct versus post-error differences in both the visual N1 and the P3 component were found. However, the difference in the P3 component rapidly diminished over time, whereas the differences in the N1 component were still evident in the fourth trial following the erroneous response. The results lay further support to the bottleneck account for post-error slowing and show a combination of early attentional and higher-order processing changes that occur after erroneous responses.

Thalamic Cortical Error-Related Responses in Adult Social Drinkers: Sex Differences and Problem Alcohol Use

BACKGROUND

Error-related brain activities are altered in individuals with substance use disorders. Here we examined error-related activities in relation to problem drinking in nondependent alcohol drinkers. In particular, we investigated sex differences and whether altered error responses are related to post-error behavioral control.

METHODS

A sample of 145 nondependent drinkers (77 women) performed the stop-signal task during functional magnetic resonance imaging. Imaging data were processed and modeled using statistical parametric mapping. Independent sample t test and linear regression were employed to examine sex differences in error response and relationship between error response and problem drinking.

RESULTS

Compared with men, women showed greater error-related (stop error > go success) activations in the bilateral thalamus, right middle/superior temporal cortex, and bilateral dorsal anterior cingulate cortex. In whole-brain linear regression of error responses against the Alcohol Use Disorders Identification Test score, a wide swath of cortical and subcortical regions, including the thalamus, showed decreased activation in association with problem drinking in women but not in men. However, men and women were not different in the extent of post-error slowing and decreased thalamic error response in association with problem drinking was not related to the extent of post-error slowing in women.

CONCLUSIONS

The results suggest sex differences in error-related activations with heavier drinking associated with reduced error activations in women but not in men. These differences in cerebral activations may reflect higher physiological arousal in response to errors and greater vulnerability of saliency-related arousal response to problem drinking in female as compared with male social drinkers.

Quality of the Reviews Submitted by Attendees of a Workshop on Peer Review

OBJECTIVE

The objective of the study was to study the methodological quality and error detection of the review by the participants of a peer review workshop.

METHODS

All participants of the workshop were invited to peer review a randomized controlled trial. The manuscript was E-mailed to them after introducing eight deliberate errors to it. Specific instructions and a deadline were provided. All the reviews were analyzed using review quality instrument (RQI). Furthermore, the rate and the type of errors identified were recorded.

RESULTS

Of 25 participants, 16 (64%) returned the reviews. The mean total score on RQI was 4.12 (standard deviation 0.70, 95% confidence interval 3.74-4.50); the items which most reviewers did not discuss where the importance of research question and originality of the paper. The number of errors correctly identified varied from 0 to 6 (median 3), the most common being a wrong conclusion (87.5%), randomization procedure (50%), written informed consent (50%), ethics committee approval (42.8%), and masking (31.2%). Only 5 (31.2%) gave an overall recommendation on whether the manuscript should be accepted or not.

CONCLUSIONS

Major errors were readily identified by the reviewers; however, the need for training was felt in some areas in which the review quality was modest.

Evidence for aversive withdrawal response to own errors

Recent model suggests that error detection gives rise to defensive motivation prompting protective behavior. Models of active avoidance behavior predict it should grow larger with threat imminence and avoidance. We hypothesized that in a task requiring left or right key strikes, error detection would drive an avoidance reflex manifested by rapid withdrawal of an erring finger growing larger with threat imminence and avoidance. In experiment 1, three groups differing by error-related threat imminence and avoidance performed a flanker task requiring left or right force sensitive-key strikes. As predicted, errors were followed by rapid force release growing faster with threat imminence and opportunity to evade threat. In experiment 2, we established a link between error key release time (KRT) and the subjective sense of inner-threat. In a simultaneous, multiple regression analysis of three error-related compensatory mechanisms (error KRT, flanker effect, error correction RT), only error KRT was significantly associated with increased compulsive checking tendencies. We propose that error response withdrawal reflects an error-withdrawal reflex.

Assay Stability, the missing component of the Error Budget

Gaining a better understanding of Quality Control (QC) processes is a key requirement to improving performance and reducing patient risk. Detecting analytical error is dependent on a QC strategy that reliably detects a critical shift in a result away from the true value. Recently the concept of Six Sigma has been used by diagnostic laboratories to assess the performance of assays and to assist in the selection of QC rules. The sigma metric is one measure of an assay's ability to perform within specification. However an additional dimension to managing an assay is its stability in bias over time. The concept of long term stability is the same as measured QC drift (SE_drift) which is the effect of numerous calibrations, changes in reagent lots and other conditions i.e. a long term effect. This implies that the standard error budget is wrong because it is modelled on short term QC and misses this SE_drift stability component. We show that SE_drift provides a measure of Assay Stability that should be included in Quality Planning and that by including an allowance for this drift, determining target imprecision appropriate for matched QC algorithms that provide high error detection is as simple as dividing the Allowable Performance Specification by 4, 5 or 6.

The timing of spontaneous detection and repair of naming errors in aphasia

This study examined the timing of spontaneous self-monitoring in the naming responses of people with aphasia. Twelve people with aphasia completed a 615-item naming test twice, in separate sessions. Naming attempts were scored for accuracy and error type, and verbalizations indicating detection were coded as negation (e.g., "no, not that") or repair attempts (i.e., a changed naming attempt). Focusing on phonological and semantic errors, we measured the timing of the errors and of the utterances that provided evidence of detection. The effects of error type and detection response type on error-to-detection latencies were analyzed using mixed-effects regression modeling. We first asked whether phonological errors and semantic errors differed in the timing of the detection process or repair planning. Results suggested that the two error types primarily differed with respect to repair planning. Specifically, repair attempts for phonological errors were initiated more quickly than repair attempts for semantic errors. We next asked whether this difference between the error types could be attributed to the tendency for phonological errors to have a high degree of phonological similarity with the subsequent repair attempts, thereby speeding the programming of the repairs. Results showed that greater phonological similarity between the error and the repair was associated with faster repair times for both error types, providing evidence of error-to-repair priming in spontaneous self-monitoring. When controlling for phonological overlap, significant effects of error type and repair accuracy on repair times were also found. These effects indicated that correct repairs of phonological errors were initiated particularly quickly, whereas repairs of semantic errors were initiated relatively slowly, regardless of their accuracy. We discuss the implications of these findings for theoretical accounts of self-monitoring and the role of speech error repair in learning.

Does perceptual or motor experience influence the perception of global and joint-specific kinematic changes in complex movement patterns?

The perception and identification of technical errors during skill execution is a critical component in coaching, because it provides the foundation for skill analysis, instruction, and feedback provision. In this study, we examined the influences of perceptual and motor experience on the perception of kinematic change in a technical evaluation task that is common in coaching. A total of 21 expert coaches, stratified by playing ("motor") expertise, as well as ten novice coaches and ten current players, observed video and point-light displays of a service action and recorded written judgments on whether the serve had changed from one video clip to the next. Three kinematic variables were manipulated: maximum knee flexion, maximum trunk rotation, and ball toss position at zenith. Coaching experience provided no additional benefit when perceiving global (holistic) changes in the service action, and limited if any benefit when perceiving specific changes in the observed kinematics. A significant expertise effect showed that expert coaches have increased sensitivity when detecting smaller changes in knee flexion. Changes in trunk rotation appeared difficult to perceive for all groups, whereas changes in lateral ball toss position were easily perceived. Motor experience did not influence the perception of global kinematics and provided no benefit above perceptual experience alone when perceiving specific kinematic changes. Collectively, the findings demonstrate that experienced coaches have the capacity to detect relatively small changes in kinematics; however, the ability to detect changes does not appear to be influenced by the extent of their own expertise in producing the movement pattern being evaluated.

Quality control for the in-clinic veterinary laboratory and pre-analytic considerations for specialized diagnostic testing

This review, aimed primarily at general practitioners, focuses on quality assurance/quality control principles for all three phases of clinical pathology testing: preanalytic, analytic, and postanalytic. Specific emphasis is placed on the preanalytic phase of diagnostic modalities for identifying neoplastic cells, specifically flow cytometry, PCR for antigen receptor rearrangement, and immunocytochemistry. Recommendations for establishing an in-clinic quality assurance system are provided.

The cost of errors: Perceived error detection in dual-task conditions

Detecting that an error has been made can be crucial for the implementation of appropriate behavioral adjustments. Brain imaging studies indicate that error detection is not limited to response errors and that similar mechanisms are engaged even when behavioral control is not needed. The current study examines whether perceived error detection - the detection of erroneous stimuli that violate our expectations - requires central resources. In two experiments - using a dual-task design - we show that perceived error detection in the first task creates a bottleneck in information processing and delays the response selection of the second task. The results suggest that the requirement for central cognitive resources is a general feature of error detection because it is present even when the demand for behavioral control is low.

Cortical processes associated with continuous balance control as revealed by EEG spectral power

Balance is a crucial component in numerous every day activities such as locomotion. Previous research has reported distinct changes in cortical theta activity during transient balance instability. However, there remains little understanding of the neural mechanisms underlying continuous balance control. This study aimed to investigate cortical theta activity during varying difficulties of continuous balance tasks, as well as examining the relationship between theta activity and balance performance. 37 subjects completed nine balance tasks with different levels of surface stability and base of support. Throughout the balancing task, electroencephalogram (EEG) was recorded from 32 scalp locations. ICA-based artifact rejection was applied and spectral power was analyzed in the theta frequency band. Theta power increased in the frontal, central, and parietal regions of the cortex when balance tasks became more challenging. In addition, fronto-central and centro-parietal theta power correlated with balance performance. This study demonstrates the involvement of the cerebral cortex in maintaining upright posture during continuous balance tasks. Specifically, the results emphasize the important role of frontal and parietal theta oscillations in balance control.

Possible role of an error detection mechanism in brain processing of deception: PET-fMRI study

To investigate brain maintenance of deliberate deception the positron emission tomography and the event related functional MRI studies were performed. We used an experimental paradigm that presupposed free choices between equally beneficial deceptive or honest actions. Experimental task simulated the "Cheat" card game which aims to defeat an opponent by sequential deceptive and honest claims. Results of both the PET and the fMRI studies revealed that execution of both deliberately deceptive and honest claims is associated with fronto-parietal brain network comprised of inferior and middle frontal gyri, precentral gyrus (BA 6), caudate nucleus, and inferior parietal lobule. Direct comparison between those claims, balanced in terms of decision making and action outcome (gain and losses), revealed activation of areas specifically associated with deception execution: precentral gyrus (BA 6), caudate nuclei, thalamus and inferior parietal lobule (BA 39/40). The obtained experimental data were discussed in relation to a possible role of an error detection system in processing deliberate deception.