Distinct mechanisms underlying cross-modal semantic conflict and response conflict processing.

Interference from task-irrelevant stimuli can occur during the semantic and response processing stages. Previous studies have shown both common and distinct mechanisms underlying semantic conflict processing and response conflict processing in the visual domain. However, it remains unclear whether common and/or distinct mechanisms are involved in semantic conflict processing and response conflict processing in the cross-modal domain. Therefore, the present electroencephalography study adopted an audiovisual 2-1 mapping Stroop task to investigate whether common and/or distinct mechanisms underlie semantic conflict and response conflict. Behaviorally, significant cross-modal semantic conflict and significant cross-modal response conflict were observed. Electroencephalography results revealed that the frontal N2 amplitude and theta power increased only in the semantic conflict condition, while the parietal N450 amplitude increased only in the response conflict condition. These findings indicated that distinct neural mechanisms were involved in cross-modal semantic conflict and response conflict processing, supporting the domain-specific cognitive control mechanisms from a cross-modal multistage conflict processing perspective.

Distinct and common mechanisms of cross-model semantic conflict and response conflict in an auditory relevant task.

The mechanisms of semantic conflict and response conflict in the Stroop task have mainly been investigated in the visual modality. However, the understanding of these mechanisms in cross-modal modalities remains limited. In this electroencephalography (EEG) study, an audiovisual 2-1 mapping Stroop task was utilized to investigate whether distinct and/or common neural mechanisms underlie cross-modal semantic conflict and response conflict. The response time data showed significant effects on both cross-modal semantic and response conflicts. Interestingly, the magnitude of semantic conflict was found to be smaller in the fast response time bins than in the slow response time bins, whereas no such difference was observed for response conflict. The EEG data demonstrated that cross-modal semantic conflict specifically increased the N450 amplitude. However, cross-modal response conflict specifically enhanced theta band power and theta phase synchronization between the medial frontal cortex (MFC) and lateral prefrontal electrodes as well as between the MFC and motor electrodes. In addition, both cross-modal semantic conflict and response conflict led to a decrease in P3 amplitude. Taken together, these findings provide cross-modal evidence for domain-specific mechanism in conflict detection and suggest both domain-specific and domain-general mechanisms exist in conflict resolution.

Biology System Description Language (BiSDL): a modeling language for the design of multicellular synthetic biological systems.

BACKGROUND: The Biology System Description Language (BiSDL) is an accessible, easy-to-use computational language for multicellular synthetic biology. It allows synthetic biologists to represent spatiality and multi-level cellular dynamics inherent to multicellular designs, filling a gap in the state of the art. Developed for designing and simulating spatial, multicellular synthetic biological systems, BiSDL integrates high-level conceptual design with detailed low-level modeling, fostering collaboration in the Design-Build-Test-Learn cycle. BiSDL descriptions directly compile into Nets-Within-Nets (NWNs) models, offering a unique approach to spatial and hierarchical modeling in biological systems. RESULTS: BiSDL's effectiveness is showcased through three case studies on complex multicellular systems: a bacterial consortium, a synthetic morphogen system and a conjugative plasmid transfer process. These studies highlight the BiSDL proficiency in representing spatial interactions and multi-level cellular dynamics. The language facilitates the compilation of conceptual designs into detailed, simulatable models, leveraging the NWNs formalism. This enables intuitive modeling of complex biological systems, making advanced computational tools more accessible to a broader range of researchers. CONCLUSIONS: BiSDL represents a significant step forward in computational languages for synthetic biology, providing a sophisticated yet user-friendly tool for designing and simulating complex biological systems with an emphasis on spatiality and cellular dynamics. Its introduction has the potential to transform research and development in synthetic biology, allowing for deeper insights and novel applications in understanding and manipulating multicellular systems.

County-level Racial/Ethnic Residential Segregation and Physical Activity Behavior among US Adults.

The relationship between racial/ethnic residential segregation and physical activity (PA) remains unclear with both positive and negative associations between segregation and PA recently reported. We aimed to examine the relationship between county-level residential segregation and total daily PA and domain-specific PA and whether these associations varied by gender. Participants (N = 2625, mean age [SD] = 45.2 [15.4]) were recruited from the AmeriSpeak panel who completed up to two Activities Completed over Time in 24 Hours (ACT24) previous day recalls in 2019. PA outcomes were created for the following: (1) light PA (LPA), (2) moderate-to-vigorous PA (MVPA), (3) total active time, and (4) domain-specific PA, including leisure, work, household, transport, personal, and other activities. County-level residential segregation based on isolation. Weighted generalized linear models were used to examine the relationship between county-level segregation and each PA outcome, controlling for age, gender, race/ethnicity, income, employment, body mass index, county-level poverty, and census region. Overall, results showed no association between county-level residential segregation and LPA, MVPA, total active time, and domain-specific PA among NH Black and Hispanic populations. Among NH Black females, greater residential segregation was associated with more total hours/day of activity (ß = 3.54, 95% CI [0.23, 6.85]). Only NH Black females living in segregated neighborhoods had more total active time. Additionally, it is important to acknowledge that these relationships may vary among NH Black and Hispanic populations. Future studies should examine the interaction between segregation and a broader range of individual, contextual, and environmental factors in relation to PA and domain-specific PA.

Disentangling Stereotypes towards Older Age Groups: Evidence from Factorial Survey Experiments in China and the USA.

INTRODUCTION: Older adults are usually perceived as warmer but less competent than younger adults. This study examined how these stereotypes are related to domain-specific attributes and how individuals' values may moderate the association. METHODS: We recruited 560 Chinese participants (mean age [SD]: 23.14 ± 7.08 years old, ranging from 18 to 60 years old) and 479 American participants (mean age [SD]: 31.37 ± 7.19 years old, ranging from 18 to 57 years old). Participants rated perceived warmth and competence of older adults based on vignettes with varying descriptions of specific domains (i.e., three relational domains: number of friends, family relationship quality, and engagement in neighbourhood activities; and three individualistic domains: income, depression, and memory) and personal attributes (i.e., gender, age, and independence). RESULTS: Firstly, the results showed that relational domains predict warmth, whereas individualistic domains predict competence in both samples from China and the USA. Secondly, in both samples, people with higher communal values attributed more relevance to relational domains on judgement of warmth. Lastly, only in the US sample did people with higher agentic values attribute more relevance to individualistic domains on judgement of competence. DISCUSSION/CONCLUSION: The study revealed that personal values, when determined relatively, contribute to stereotypes of older adults in the two independent samples.

Associations between domains of sedentary behavior, well-being, and quality of life - a cross-sectional study.

The importance of reducing sedentary behavior (SB) in the prevention of mortality and chronic and mental diseases is scientifically well grounded, but SB can be accumulated in diverse domains of life, such as leisure-time SB, transport between home/work/school when sitting (transport-related SB), or in occupational settings such as working or studying (occupational SB), and the associations for each domain of SB with well-being measures and quality of life are still underexplored from a positive perspective. Through a cross-sectional investigation, we collected data from 584 participants who completed a questionnaire throughout November 2021 and with Spearman correlation test, analysed the associations between SB in three different domains with psychological well-being, satisfaction with life, and quality of life. Our results indicated that after adjustment for physical activity, sex, body mass index, smoking history, chronic disease status, financial perception, quality/duration of sleep and university group, in younger adults (18 to 24 years old), leisure-time SB was negatively related to psychological well-being (rho = -0.255; p = 0.008), and in adults (25 to 64 years old), occupational SB was negatively related to satisfaction with life (rho = -0.257; p < .001) and the mental component of quality of life (rho = -0.163; p = 0.027). Our findings highlight the idea that not all SB is built the same and that future strategies to reduce SB from people's lives must target specific domains of SB according to the age group when aiming to improve well-being and quality of life.

Evaluating and Enhancing Large Language Models' Performance in Domain-Specific Medicine: Development and Usability Study With DocOA.

BACKGROUND: The efficacy of large language models (LLMs) in domain-specific medicine, particularly for managing complex diseases such as osteoarthritis (OA), remains largely unexplored. OBJECTIVE: This study focused on evaluating and enhancing the clinical capabilities and explainability of LLMs in specific domains, using OA management as a case study. METHODS: A domain-specific benchmark framework was developed to evaluate LLMs across a spectrum from domain-specific knowledge to clinical applications in real-world clinical scenarios. DocOA, a specialized LLM designed for OA management integrating retrieval-augmented generation and instructional prompts, was developed. It can identify the clinical evidence upon which its answers are based through retrieval-augmented generation, thereby demonstrating the explainability of those answers. The study compared the performance of GPT-3.5, GPT-4, and a specialized assistant, DocOA, using objective and human evaluations. RESULTS: Results showed that general LLMs such as GPT-3.5 and GPT-4 were less effective in the specialized domain of OA management, particularly in providing personalized treatment recommendations. However, DocOA showed significant improvements. CONCLUSIONS: This study introduces a novel benchmark framework that assesses the domain-specific abilities of LLMs in multiple aspects, highlights the limitations of generalized LLMs in clinical contexts, and demonstrates the potential of tailored approaches for developing domain-specific medical LLMs.

Youth Athletes' Self-Esteem: The Impact of Integrated Psychological Skills Training.

PURPOSE: Study on the effect of psychological skills training on self-esteem (SE) in young athletes. METHOD: 10 swimmers and 35 volleyball players, split into an intervention group (25) and a control group (18). The intervention entailed a 3-week psychological skills training program covering arousal management, breathing, relaxation, mental imagery, and self-talk. Multilevel growth curve analyses evaluated SE changes. RESULTS: The intervention group showed significant improvements in multiple SE dimensions-physical self-worth, fitness, athletic competence, strength, and body attractiveness but not general SE. CONCLUSIONS: This study provides initial evidence of a multimodal psychological skills training's effectiveness in enhancing young athletes' domain-specific SE. It highlights the role of domain-specific SE in young athletes' well-being. Future research should examine psychological and physiological correlations and assess the long-term SE development in adolescent athletes.

Post-stroke fatigue severity is associated with executive dysfunction in chronic stroke.

Following stroke, fatigue is highly prevalent and managing fatigue is consistently rated a key unmet need by stroke survivors and professionals. Domain-specific cognitive impairments have been associated with greater fatigue severity in earlier stages of stroke recovery, but it is unclear whether these associations hold in chronic (>2 years) stroke. The present cross-sectional observational study evaluates the relationship between domain-specific cognitive functioning and the severity of self-reported fatigue among chronic stroke survivors. Participants (N = 105; mean age = 72.92, 41.90% female; mean years post-stroke = 4.57) were assessed in domains of attention (Hearts Cancellation test), language (Boston Naming Test), episodic memory (Logical Memory Test), working memory (Digit Span Backwards task), and executive functioning (set-shifting: Trail Making Test, Part B), as part of the OX-CHRONIC study, a longitudinal stroke cohort. Fatigue was assessed using the Fatigue Severity Scale. In a multiple linear regression analysis inclusive of above cognitive domains, only poorer executive functioning was associated with increased fatigue severity. This provides insight into the cognitive impairment profile of post-stroke fatigue long-term after stroke, with executive functioning deficits as the key hallmark.

Environmental Constraints for Intelligent Internet of Deep-Sea/Underwater Things Relying on Enterprise Architecture Approach.

Through the use of Underwater Smart Sensor Networks (USSNs), Marine Observatories (MOs) provide continuous ocean monitoring. Deployed sensors may not perform as intended due to the heterogeneity of USSN devices' hardware and software when combined with the Internet. Hence, USSNs are regarded as complex distributed systems. As such, USSN designers will encounter challenges throughout the design phase related to time, complexity, sharing diverse domain experiences (viewpoints), and ensuring optimal performance for the deployed USSNs. Accordingly, during the USSN development and deployment phases, a few Underwater Environmental Constraints (UECs) should be taken into account. These constraints may include the salinity level and the operational depth of every physical component (sensor, server, etc.) that will be utilized throughout the duration of the USSN information systems' development and implementation. To this end, in this article we present how we integrated an Artificial Intelligence (AI) Database, an extended ArchiMO meta-model, and a design tool into our previously proposed Enterprise Architecture Framework. This addition proposes adding new Underwater Environmental Constraints (UECs) to the AI Database, which is accessed by USSN designers when they define models, with the goal of simplifying the USSN design activity. This serves as the basis for generating a new version of our ArchiMO design tool that includes the UECs. To illustrate our proposal, we use the newly generated ArchiMO to create a model in the MO domain. Furthermore, we use our self-developed domain-specific model compiler to produce the relevant simulation code. Throughout the design phase, our approach contributes to the handling and controling of the uncertainties and variances of the provided quality of service that may occur during the performance of the USSNs, as well as reducing the design activity's complexity and time. It provides a way to share the different viewpoints of the designers in the domain of USSNs.

Cultural Dimensions Moderate the Association between Loneliness and Mental Health during Adolescence and Younger Adulthood: A Systematic Review and Meta-Analysis.

Cultural factors, such as country or continent, influence the relationship between loneliness and mental health. However, less is known about how cultural dimensions moderate this relationship during adolescence and younger adulthood, even if these dimensions manifest as country or continent differences. This study aims to examine the potential influence of Hofstede's cultural dimensions on this relationship using a three-level meta-analysis approach. A total of 292 studies with 291,946 participants aged 10 to 24 were included in this study. The results indicate that cultural dimensions, such as individualism vs. collectivism, indulgence vs. restraint, power distance, and long-term vs. short-term orientation, moderated the associations between loneliness and social anxiety, stress, Internet overuse, and negative affect. The association between loneliness and mental health was not moderated by cultural dimensions, such as masculinity and uncertainty avoidance. These findings suggest that culture's influence on the association between loneliness and mental health is based on a domain-specific mechanism.

General versus domain-specific grit in the work context.

Researchers have questioned whether grit should be conceptualized and measured as a global (i.e., domain-general) or domain-specific construct. Although evidence is beginning to appear that grit in educational and sport contexts may be measured as domain-specific, it has not yet been explored in the organizational context. The objective of this research was to study the psychometric properties of grit as domain-specific for subsequently analyzing if such domain-specific grit (labor grit) improves the predictive validity of different organizational results. A sample of 326 active workers was used (Myears = 37.52; SD = 9.85). Their grit levels in the general domain and specific domain were evaluated, as well as their main personality traits and other organizational results such as work engagement and work performance. The grit instrument as domain-specific showed excellent reliability (ω = 0.92), and the unidimensionality of the instrument was confirmed. The results point to the fact that giving an organizational connotation to the grit items does not improve the predictability of the results. However, labor grit adds incremental validity over personality traits and work engagement to predict task and contextual performance (Δr2 = 0.13), but not to predict counterproductive behavior.

Individual consistency in the learning abilities of honey bees: cognitive specialization within sensory and reinforcement modalities.

The question of whether individuals perform consistently across a variety of cognitive tasks is relevant for studies of comparative cognition. The honey bee (Apis mellifera) is an appropriate model to study cognitive consistency as its learning can be studied in multiple elemental and non-elemental learning tasks. We took advantage of this possibility and studied if the ability of honey bees to learn a simple discrimination correlates with their ability to solve two tasks of higher complexity, reversal learning and negative patterning. We performed four experiments in which we varied the sensory modality of the stimuli (visual or olfactory) and the type (Pavlovian or operant) and complexity (elemental or non-elemental) of conditioning to examine if stable correlated performances could be observed across experiments. Across all experiments, an individual's proficiency to learn the simple discrimination task was positively and significantly correlated with performance in both reversal learning and negative patterning, while the performances in reversal learning and negative patterning were positively, yet not significantly correlated. These results suggest that correlated performances across learning paradigms represent a distinct cognitive characteristic of bees. Further research is necessary to examine if individual cognitive consistency can be found in other insect species as a common characteristic of insect brains.

Trends in insufficient physical activity among adults in China 2010-18: a population-based study.

BACKGROUND: The global prevalence of insufficient physical activity (PA) was reported to be 27.5% in 2016, and there were stable levels of insufficient PA worldwide between 2001 and 2016. The global target of a 10% reduction in insufficient PA by 2025 will not be met if the trends remain. The relevant data for trends in China were still scarce. This study aimed to determine nationwide temporal trends in insufficient PA among adults in China from 2010 to 2018. METHODS: 645 903 adults aged 18 years or older were randomly selected from four nationally representative cross-sectional surveys of the China Chronic Disease and Risk Factor Surveillance conducted in 2010, 2013, 2015, and 2018. PA was measured using the Global Physical Activity Questionnaire. Temporal changes in insufficient PA prevalence and participation of domain-specific moderate- to vigorous-intensity PA (MVPA) were analyzed using logistic regression. RESULTS: From 2010 to 2018, the age-adjusted prevalence of insufficient PA in China increased from 17.9% (95% confidence interval 16.3% to 19.5%) in 2010 to 22.3% (20.9% to 23.8%) in 2018 (P for trend < 0.001). By age group, with a significant increase in insufficient PA in adults aged 18-34 years (P for trend < 0.001), which rose more rapidly than in adults aged ≥ 35 years (P for interaction < 0.001). Insufficient PA has increased significantly among adults engaged in agriculture-related work, non-manual work, and other manual work (all P for trend < 0.05). And among the occupational groups, those engaged in agriculture-related work had the fastest increase (P for interaction = 0.01). The percentage of adults participating in work-related MVPA decreased from 79.6% (77.8% to 81.5%) to 66.8% (64.9% to 68.7%) along with a decrease in time spent on work-related MVPA, while percentages of adults participating in recreation-related MVPA increased from 14.2% (12.5% to 15.9%) to 17.2% (16.0% to 18.4%) (all P for trend < 0.05). CONCLUSIONS: Among Chinese adults, an increasing trend was found in insufficient PA from 2010 to 2018, with more than one-fifth of adults failing to achieve the recommendation of adequate PA. More targeted PA promotion strategies should be developed to improve population health.

Domain-specific physical activity, sedentary behavior, subjective health, and health-related quality of life among older adults.

PURPOSE: This study aims to investigate the association between domain-specific physical activity (PA), sedentary behavior, subjective health perception, and health-related quality of life (HR-QoL) in Korean adults aged ≥ 65 years. METHODS: This cross-sectional study analyzed 6,004 older adults from the Korean National Health and Nutrition Examination Survey 2017-2020. PA and sedentary behavior were measured using a global PA questionnaire, and HR-QoL was assessed using the EuroQol-5 Dimension (EQ-5D, three-level version). Multiple logistic regression was used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) after adjusting for confounding parameters. RESULTS: Older adults who were physically active at work showed a negative association with subjectively good health and HR-QoL, whereas those physically active in transport or leisure time showed a positive association with subjectively good health and HR-QoL. Older adults highly engaged in sedentary behavior showed a worse perception of health and HR-QoL. Compared to high sedentary behavior and physical activity during leisure time or transport, the EQ-5D index was higher than that of their counterparts. CONCLUSION: Both domain-specific PA and sedentary behavior were significantly associated with older adults' perception of health and HR-QoL. Interventions are needed to improve HR-QoL by reducing sedentary behavior and encouraging physical activity in transportation or leisure time among adults aged 65 years and above.

A self-supervised language model selection strategy for biomedical question answering.

Large neural-based Pre-trained Language Models (PLM) have recently gained much attention due to their noteworthy performance in many downstream Information Retrieval (IR) and Natural Language Processing (NLP) tasks. PLMs can be categorized as either general-purpose, which are trained on resources such as large-scale Web corpora, and domain-specific which are trained on in-domain or mixed-domain corpora. While domain-specific PLMs have shown promising performance on domain-specific tasks, they are significantly more computationally expensive compared to general-purpose PLMs as they have to be either retrained or trained from scratch. The objective of our work in this paper is to explore whether it would be possible to leverage general-purpose PLMs to show competitive performance to domain-specific PLMs without the need for expensive retraining of the PLMs for domain-specific tasks. By focusing specifically on the recent BioASQ Biomedical Question Answering task, we show how different general-purpose PLMs show synergistic behaviour in terms of performance, which can lead to overall notable performance improvement when used in tandem with each other. More concretely, given a set of general-purpose PLMs, we propose a self-supervised method for training a classifier that systematically selects the PLM that is most likely to answer the question correctly on a per-input basis. We show that through such a selection strategy, the performance of general-purpose PLMs can become competitive with domain-specific PLMs while remaining computationally light since there is no need to retrain the large language model itself. We run experiments on the BioASQ dataset, which is a large-scale biomedical question-answering benchmark. We show that utilizing our proposed selection strategy can show statistically significant performance improvements on general-purpose language models with an average of 16.7% when using only lighter models such as DistilBERT and DistilRoBERTa, as well as 14.2% improvement when using relatively larger models such as BERT and RoBERTa and so, their performance become competitive with domain-specific large language models such as PubMedBERT.

Environmental susceptibility for all: A data-driven approach suggests individual differences in domain-general and domain-specific patterns of environmental susceptibility.

How we are influenced by our environment is a fundamental question in developmental science. Theories and empirical research have claimed that some individuals are susceptible to environmental influences and others are much less susceptible. The present study addressed four questions: (1) Is environmental susceptibility a continuous or categorical construct? (2) Is environmental susceptibility unidimensional (i.e., domain general) or multidimensional (i.e., domain specific)? (3) Are there genetic contributions to individual differences in environmental susceptibility? (4) What are the temperamental characteristics of different environmental susceptibility patterns? We used child- and mother-report data from a sample of 11-year-old twins (N = 1,507) and applied a novel data-driven approach to assess an environmental susceptibility space, based on simultaneous associations between multiple environmental exposures (18 measures relating to parenting, parent, peer, and twin relationships) and developmental outcomes (10 measures relating to empathy, prosocial behavior, aggression, and self-esteem). The results suggest that the environmental susceptibility space we assessed is better conceptualized as continuous and multidimensional. Different children showed susceptibility to different contexts and variation in domain-general versus domain-specific patterns. A comparison of distances between monozygotic and dizygotic twins within the space demonstrated genetic contributions. Finally, susceptibility patterns could not be differentiated based on a specific temperament trait, but rather related to temperament profiles.

Relative Contributions of g and Basic Domain-Specific Mathematics Skills to Complex Mathematics Competencies.

Meta-analytic structural equation modeling was used to estimate the relative contributions of general cognitive ability or g (defined by executive functions, short-term memory, and intelligence) and basic domain-specific mathematical abilities to performance in more complex mathematics domains. The domain-specific abilities included mathematics fluency (e.g., speed of retrieving basic facts), computational skills (i.e., accuracy at solving multi-step arithmetic, algebra, or geometry problems), and word problems (i.e., mathematics problems presented in narrative form). The core analysis included 448 independent samples and 431,344 participants and revealed that g predicted performance in all three mathematics domains. Mathematics fluency contributed to the prediction of computational skills, and both mathematics fluency and computational skills predicted word problem performance, controlling g. The relative contribution of g was consistently larger than basic domain-specific abilities, although the latter may be underestimated. The patterns were similar across younger and older individuals, individuals with and without a disability (e.g., learning disability), concurrent and longitudinal assessments, and family socioeconomic status, and have implications for fostering mathematical development.

Global and domain-specific self-esteem from middle childhood to early adolescence: Co-developmental trajectories and directional relations.

OBJECTIVE: The study used both person-centered (i.e., parallel process latent class growth modeling) and variable-centered (i.e., random intercept cross-lagged panel modeling) approaches to examine developmental changes in global and domain-specific self-esteem from middle childhood to early adolescence. METHOD: A total of 715 Chinese youth participated (54.3% boys; 45.7% girls; Mage = 9.96; SD = 0.51) in a 6-wave longitudinal study with 6-month intervals. RESULTS: Parallel process latent class growth modeling identified three co-developmental trajectories of global and domain-specific self-esteem: Congruent high increasing and then flattening global and domain-specific self-esteem, congruent moderate domain-specific self-esteem with convex global self-esteem, and congruent low with concave appearance and global self-esteem. Results from random intercept cross-lagged panel modeling found reciprocal within-person associations between academic self-esteem and global self-esteem; global self-esteem significantly predicted social self-esteem, while physical appearance self-esteem significantly predicted global self-esteem. CONCLUSION: Evidence was provided for top-down and bottom-up effects of self-esteem among Chinese youth. The findings provided new insight into the development of self-esteem in youth.

An expert advantage in detecting unfamiliar visual signals in noise.

Diagnostic radiologists are experts in discriminating and classifying medical images for clinically significant anomalies. Does their perceptual expertise confer an advantage in unfamiliar visual tasks? Here, this issue was investigated by comparing the performance of 10 radiologists and 2 groups of novices on the ability to detect novel visual signals: band-limited textures in noise. Observers performed a yes/no detection task in which texture spatial frequency and external noise levels were varied. The task was performed on two consecutive days. Contrast thresholds and response bias were measured. Contrast thresholds of radiologists were superior to the control groups in all stimulus conditions on both days. Performance improved by an equivalent amount for all groups across days. Response bias differed consistently across stimulus conditions and days but not across groups. The difference in thresholds between the radiologists and control groups suggests that experience in diagnostic medical imaging produces perceptual skills that that transfer beyond the trained domain.