Phonetic categorization in phonological lexical neighborhoods: Facilitatory and inhibitory effects.

Phonetic processing, whereby the bottom-up speech signal is translated into higher-level phonological representations such as phonemes, has been demonstrated to be influenced by phonological lexical neighborhoods. Previous studies show facilitatory effects of lexicality and phonological neighborhood density on phonetic categorization. However, given the evidence for lexical competition in spoken word recognition, we hypothesize that there are concurrent facilitatory and inhibitory effects of phonological lexical neighborhoods on phonetic processing. In Experiments 1 and 2, participants categorized the onset phoneme in word-nonword and nonword-word acoustic continua. The results show that the target word of the continuum exhibits facilitatory lexical influences whereas rhyme neighbors inhibit phonetic categorization. The results support the hypothesis that sublexical phonetic processing is affected by multiple facilitatory and inhibitory lexical forces in the processing stream.

A proposed framework for defining the relationship between complexity, project categorization, and project risk management: Case study of a medical company in Morocco.

Recent financial crises have highlighted the utmost importance of implementing risk management practices, as exemplified by the profound repercussions of the COVID-19 pandemic. Moreover, we witnessed the rise of various initiatives within the medical sector, specifically in the fields of biomedicine, hospitals, and pharmaceuticals, across Africa, with a notable emphasis on Morocco. The government in Morocco has implemented measures to foster investment and encourage participation from companies and stakeholders. Taking into account an indeterminate and volatile future, it becomes imperative for organizations to establish robust risk management strategies to navigate successfully through these uncertainties. This research paper concentrates on the convergence of complexity, project categorization, and risks. We propose a novel approach to the implementation of the Risk Management Process, utilizing the Enterprise Risk Management framework. By establishing Risk Management rules within the context of a "complex" project, we observed enhanced performance and improved risk management through the holistic consideration of interdependencies rather than treating them as separate entities. Additionally, to substantiate this interdependency, we conducted a comparative analysis of the project's risk and complexity between 2020 and 2022.

A library for innovative category exemplars (ALICE) database: Streamlining research with printable 3D novel objects.

This paper introduces A Library for Innovative Category Exemplars (ALICE) database, a resource that enhances research efficiency in cognitive and developmental studies by providing printable 3D objects representing 30 novel categories. Our research consists of three experiments to validate the novelty and complexity of the objects in ALICE. Experiment 1 assessed the novelty of objects through adult participants' subjective familiarity ratings and agreement on object naming and descriptions. The results confirm the general novelty of the objects. Experiment 2 employed multidimensional scaling (MDS) to analyze perceived similarities between objects, revealing a three-dimensional structure based solely on shape, indicative of their complexity. Experiment 3 used two clustering techniques to categorize objects: k-means clustering for creating nonoverlapping global categories, and hierarchical clustering for allowing global categories that overlap and have a hierarchical structure. Through stability tests, we verified the robustness of each clustering method and observed a moderate to good consensus between them, affirming the strength of our dual approach in effectively and accurately delineating meaningful object categories. By offering easy access to customizable novel stimuli, ALICE provides a practical solution to the challenges of creating novel physical objects for experimental purposes.

Neural Basis of Categorical Representations of Animal Body Silhouettes.

Neural activities differentiating bodies versus non-body stimuli have been identified in the occipitotemporal cortex of both humans and nonhuman primates. However, the neural mechanisms of coding the similarity of different individuals' bodies of the same species to support their categorical representations remain unclear. Using electroencephalography (EEG) and magnetoencephalography (MEG), we investigated the temporal and spatial characteristics of neural processes shared by different individual body silhouettes of the same species by quantifying the repetition suppression of neural responses to human and animal (chimpanzee, dog, and bird) body silhouettes showing different postures. Our EEG results revealed significant repetition suppression of the amplitudes of early frontal/central activity at 180-220 ms (P2) and late occipitoparietal activity at 220-320 ms (P270) in response to animal (but not human) body silhouettes of the same species. Our MEG results further localized the repetition suppression effect related to animal body silhouettes in the left supramarginal gyrus and left frontal cortex at 200-440 ms after stimulus onset. Our findings suggest two neural processes that are involved in spontaneous categorical representations of animal body silhouettes as a cognitive basis of human-animal interactions.

Evaluating Large Language Models for Automated Reporting and Data Systems Categorization: Cross-Sectional Study.

BACKGROUND: Large language models show promise for improving radiology workflows, but their performance on structured radiological tasks such as Reporting and Data Systems (RADS) categorization remains unexplored. OBJECTIVE: This study aims to evaluate 3 large language model chatbots-Claude-2, GPT-3.5, and GPT-4-on assigning RADS categories to radiology reports and assess the impact of different prompting strategies. METHODS: This cross-sectional study compared 3 chatbots using 30 radiology reports (10 per RADS criteria), using a 3-level prompting strategy: zero-shot, few-shot, and guideline PDF-informed prompts. The cases were grounded in Liver Imaging Reporting & Data System (LI-RADS) version 2018, Lung CT (computed tomography) Screening Reporting & Data System (Lung-RADS) version 2022, and Ovarian-Adnexal Reporting & Data System (O-RADS) magnetic resonance imaging, meticulously prepared by board-certified radiologists. Each report underwent 6 assessments. Two blinded reviewers assessed the chatbots' response at patient-level RADS categorization and overall ratings. The agreement across repetitions was assessed using Fleiss κ. RESULTS: Claude-2 achieved the highest accuracy in overall ratings with few-shot prompts and guideline PDFs (prompt-2), attaining 57% (17/30) average accuracy over 6 runs and 50% (15/30) accuracy with k-pass voting. Without prompt engineering, all chatbots performed poorly. The introduction of a structured exemplar prompt (prompt-1) increased the accuracy of overall ratings for all chatbots. Providing prompt-2 further improved Claude-2's performance, an enhancement not replicated by GPT-4. The interrun agreement was substantial for Claude-2 (k=0.66 for overall rating and k=0.69 for RADS categorization), fair for GPT-4 (k=0.39 for both), and fair for GPT-3.5 (k=0.21 for overall rating and k=0.39 for RADS categorization). All chatbots showed significantly higher accuracy with LI-RADS version 2018 than with Lung-RADS version 2022 and O-RADS (P<.05); with prompt-2, Claude-2 achieved the highest overall rating accuracy of 75% (45/60) in LI-RADS version 2018. CONCLUSIONS: When equipped with structured prompts and guideline PDFs, Claude-2 demonstrated potential in assigning RADS categories to radiology cases according to established criteria such as LI-RADS version 2018. However, the current generation of chatbots lags in accurately categorizing cases based on more recent RADS criteria.

Processing of visual hapaxes in picture naming task: An event-related potential study.

Object recognition and visual categorization are typically swift and seemingly effortless tasks that involve numerous underlying processes. In our investigation, we utilized a picture naming task to explore the processing of rarely encountered objects (visual hapaxes) in comparison to common objects. Our aim was to determine the stage at which these rare objects are classified as unnamable. Contrary to our expectations and in contrast to some prior research on event-related potentials (ERPs) with novel and atypical objects, no differences between conditions were observed in the late time windows corresponding to the P300 or N400 components. However, distinctive patterns between hapaxes and common objects surfaced in three early time windows, corresponding to the posterior N1 and P2 waves, as well as a widespread N2 wave. According to the ERP data, the differentiation between hapaxes and common objects occurs within the first 380 ms of the processing line, involving only limited and indirect top-down influence.

Feedback and observational learning differ in effectiveness during category learning in early school aged children and adults.

When learning new categories, do children benefit from the same types of training as adults? We compared the effects of feedback-based training with observational training in young adults (ages 18-25) and early school aged children (ages 6-7) across two different multimodal category learning tasks: conjunctive rule based and information integration. We used multimodal stimuli that varied across a visual feature (rotation speed of the "planet" stimulus) and an auditory feature (pitch frequency of a pure tone stimulus). We found an interaction between age and training type for the rule-based category task, such that adults performed better in feedback training than in observational training, whereas training type had no significant effect on children's category learning performance. Overall adults performed better than children in learning both the rule based and information integration category structures. In information integration category learning, feedback versus observational training did not have a significant effect on either adults' or children's category learning. Computational modelling revealed that children defaulted to univariate rules in both tasks. The finding that children do not benefit from feedback training and can learn successfully via observational learning has implications for the design of educational interventions appropriate for children.

Automating population dose survey processing-An Australian feasibility study.

BACKGROUND: A comprehensive collection of data on doses in adult computed tomography procedures in Australia has not been undertaken for some time. This is largely due to the effort involved in collecting the data required for calculating the population dose. This data collection effort can be greatly reduced, and the coverage increased, if the process can be automated without major changes to the workflow of the imaging facilities providing the data. Success would provide a tool to determine a truly national assessment of the dose incurred through diagnostic imaging in Australia. PURPOSE: The aims of this study were to develop an automated tool to categorize electronic records of imaging procedures into a standardized set of broad procedure types, to validate the tool by applying it to data collected from nine facilities, and to assess the feasibility of applying the automated tool to compute population dose and determine the data manipulations required. METHODS: A rule-based classifier was implemented capitalizing on semantic and clinical rules. The keyword list was initially built from 609 unique study descriptions. It was then refined using an additional 414 unique study descriptions. The classifier was then tested on an additional 1198 unique study descriptions. Input from a radiologist provided the ground truth for the refinement of the classifier. RESULTS: From a sample of 238 139 studies containing 2794 unique study descriptions, the classifier correctly classified 2789 study types with only five misclassifications, demonstrating the feasibility of automating the process and the need for data pre-processing. Dose statistics for 21 categories were compiled using the 238 139 studies. CONCLUSION: The classifier achieved excellent classification results using the testing data supplied by the facilities. However, since all data supplied were from public facilities, the performance of the classifier may be biased. The performance of the classifier is yet to be tested on a more representative mix of private and public facilities.

Advancements in Asymmetric Supercapacitors: From Historical Milestones to Challenges and Future Directions.

Numerous challenges, like the uninterrupted supply of electricity, stable and reliable power, and energy storage during non-operational hours, arise across various industries due to the absence of advanced energy storage technologies. With the continual technological advancements in portable electronics, green energy, and transportation, there are inherent limitations in their innovative production. Thus, ongoing research is focused on pursuing sustainable energy storage technologies. An emerging solution lies in the development of asymmetric supercapacitors (ASCs), which offer the potential to extend their operational voltage limit beyond the thermodynamic breakdown voltage range of electrolytes. This is achieved by employing two distinct electrode materials, presenting an effective solution to the energy storage limitations faced by ASCs. The current review concentrates on the progression of working materials to develop authentic pseudocapacitive energy storage systems (ESS). Also, evaluates their ability to exceed energy storage constraints. It provides insights into fundamental energy storage mechanisms, performance evaluation methodologies, and recent advancements in electrode material strategies. The review approaches developing high-performance electrode materials and achieving efficient ASC types. It delves into critical aspects for enhancing the energy density of ASCs, presenting debates and prospects, thereby offering a comprehensive understanding and design principles for next-generation ASCs in diverse applications.

Pre-frontal cortex guides dimension-reducing transformations in the occipito-ventral pathway for categorization behaviors.

To interpret our surroundings, the brain uses a visual categorization process. Current theories and models suggest that this process comprises a hierarchy of different computations that transforms complex, high-dimensional inputs into lower-dimensional representations (i.e., manifolds) in support of multiple categorization behaviors. Here, we tested this hypothesis by analyzing these transformations reflected in dynamic MEG source activity while individual participants actively categorized the same stimuli according to different tasks: face expression, face gender, pedestrian gender, and vehicle type. Results reveal three transformation stages guided by the pre-frontal cortex. At stage 1 (high-dimensional, 50-120 ms), occipital sources represent both task-relevant and task-irrelevant stimulus features; task-relevant features advance into higher ventral/dorsal regions, whereas task-irrelevant features halt at the occipital-temporal junction. At stage 2 (121-150 ms), stimulus feature representations reduce to lower-dimensional manifolds, which then transform into the task-relevant features underlying categorization behavior over stage 3 (161-350 ms). Our findings shed light on how the brain's network mechanisms transform high-dimensional inputs into specific feature manifolds that support multiple categorization behaviors.

The link between non-human primate vocalizations and cognition is not constrained by maturation alone: Evidence from healthy preterm infants.

To acquire language, infants must not only identify the signals of their language(s), but also discover how these signals are connected to meaning. By 3 months of age, infants' native language, non-native languages, and vocalizations of non-human primates support infants' formation of object categories-a building block of cognition. But by 6 months, only the native language exerts this cognitive advantage. Prior work with preterm infants indicates that maturation constrains this developing link between the native language and cognition. Here, we assess whether maturation exerts similar constraints on the influence of non-human primate vocalizations on infant categorization. Cross-sectional growth curve analyses of new data from preterm infants and extant data from fullterm infants indicate that developmental tuning of this signal's influence on categorization is best predicted by infants' chronological age, and not gestational status. This evidence, together with prior work, suggests that as infants tune the initially broad set of signals that support early cognition, they are guided by two independent processes: maturation constrains the expression of a link between their native language and cognition, while the influence of non-linguistic signals are guided by other factors, such as postnatal age and experience.

The Development of Global-Level Categorization: Frequency Tagging EEG Responses.

Adults and infants form abstract categories of visual objects, but little is known about the development of global categorization. This study aims to characterize the development of very fast global categorization (living and non-living objects) and to determine whether and how low-level stimulus characteristics contribute to this response. Frequency tagging was used to characterize the development of global-level categorization in N = 69 infants (4, 7, 11 months), N = 22 children (5-6 years old), and N = 20 young adults. Images were presented in an oddball paradigm, with a category change at every fifth position (AAAABAAAABA…). Strong and significant high-level categorization was observed in all age groups, with reduced responses for phase-scrambled control sequences (R2 = 0.34-0.73). No differences between the categorization of living and non-living targets were observed. These data demonstrate high-level visual categorization as living and non-living from four months to adulthood, providing converging evidence that humans are highly sensitive to broad categorical information from infancy onward.

Evolution of natural disaster terminologies, with a case study of the covid-19 pandemic.

Disaster, catastrophe, and cataclysm are some English terminologies that describe the severity of adverse events. Civilians, reporters, and professionals often use these terminologies to communicate and report any event's severity. This linguistic method is the most practical way to rapidly reach all levels of local/regional/national, and international stakeholders during disasters. Therefore, disaster terminologies play a significant role in disaster management. However, attaining the actual magnitude of a disaster's severity cannot be comprehended simply by using these terminologies because they are used interchangeably. Unfortunately, there is no consistent method to differentiate disaster terminologies from one another. Additionally, no globally accepted standard technique exists to communicate the severity level when disasters strike; one observer's 'disaster' can be another's 'catastrophe'. Hence, a nation's ability to manage extreme events is difficult when there are no agreed terminologies among emergency management systems. A standard severity classification system is required to understand, communicate, report, and educate stakeholders. This paper presents perceptions of people about disaster terminologies in different geographical regions, rankings and differences in disaster lexical and lexicon. It explores how people perceive major events (e.g., the Covid-19 pandemic), and proposes a ranking of disaster terminologies to create a severity classification system suitable for global use.

Categorization of second language accents by bilingual and multilingual listeners.

This study examines how listeners categorize second language (L2) accents and how their linguistic background affects this categorization. Ninety-eight adult bilingual and multilingual Greek listeners categorized accents in a familiar (British English)-unfamiliar (Australian English) L2 accent condition. Data were collected through an online survey and analysed using binomial mixed-effects models and signal detection analysis. The results demonstrated that both bilinguals and multilinguals exhibited low performance in the task, potentially due to their decreased familiarity with the Australian English accent and the fact that the two accents are phonetically similar. However, despite both groups' low performance, multilinguals outperformed bilinguals in accent categorization accuracy. This advantage could be attributed to a combination of cognitive and social dynamics. Results expand upon prior research, indicating that exposure to accent variation enhances listeners' abilities to categorize non-native accents. The study provides important theoretical implications for the perception of accents and practical insights into foreign language learning and multilingual communication.

Toward the Emergence of Intelligent Control: Episodic Generalization and Optimization.

Human cognition is unique in its ability to perform a wide range of tasks and to learn new tasks quickly. Both abilities have long been associated with the acquisition of knowledge that can generalize across tasks and the flexible use of that knowledge to execute goal-directed behavior. We investigate how this emerges in a neural network by describing and testing the Episodic Generalization and Optimization (EGO) framework. The framework consists of an episodic memory module, which rapidly learns relationships between stimuli; a semantic pathway, which more slowly learns how stimuli map to responses; and a recurrent context module, which maintains a representation of task-relevant context information, integrates this over time, and uses it both to recall context-relevant memories (in episodic memory) and to bias processing in favor of context-relevant features and responses (in the semantic pathway). We use the framework to address empirical phenomena across reinforcement learning, event segmentation, and category learning, showing in simulations that the same set of underlying mechanisms accounts for human performance in all three domains. The results demonstrate how the components of the EGO framework can efficiently learn knowledge that can be flexibly generalized across tasks, furthering our understanding of how humans can quickly learn how to perform a wide range of tasks-a capability that is fundamental to human intelligence.

Indirect Fistula: A New Terminology for Cerebrospinal Fluid Fistula With Different 'Apparent Origin' and 'Real Origin'.

Fistulas are abnormal communications between body cavities. They can occur between the CNS and the extracranial space, presenting clinically as CSF leaks. Due to the variety of features, multiple classifications have been implemented to better study this pathology. A systematic review was conducted using the Scopus, Medline, and Web of Science databases. Observational studies such as cohort studies, case reports, case series, cross-sectional studies, systematic reviews, and publications that assess the classification of CSF leaks were included. The systematic review identified 29 publications that met the required criteria for inclusion. Although the primary focus of most of these publications was not on classification, they briefly mentioned it. The included publications describe classifications according to etiology, exiting flow pressure, anatomic site, and some new classification proposals. Of the 29 included studies, 11 referred to the appearance of CSF rhinorrhea or otorrhea with no relationship between the cause or site of origin and the site of the CSF leak. However, none of these publications names this situation. These results clearly indicate that a term for this circumstance needs to be established; none of the previously listed publications provide a name for this condition. This systematic review aims to demonstrate the necessity of implementing a new term to describe CSF leaks where the 'apparent origin' does not correspond to the 'real origin.' The results show no existing term that considers such cases; therefore, we propose the term 'Indirect Fistula' to designate these cases.

Religious labels and food preferences, but not country of origin, support opposing face aftereffects.

Face templates can be experimentally manipulated, and category-contingent aftereffects suggest discrete templates across social groups. We tested whether 1) explicit religious labels, 2) food preferences, and 3) country of origin would support religion-contingent aftereffects across Christians and Muslims face sets. While viewing face images, ninety-three participants heard audio that stated either 1) a character's religious identity, 2) preferred food, or 3) country of origin. Participants viewed contracted Christian faces and expanded Muslim faces during the training phase. To measure adaptation, before and after the training phases, participants selected the face out of a pair of expanded and contracted Christian or Muslim faces that they found more attractive. Contingent aftereffects were found in the religious explicit (t(30) = 2.49, p = 0.02, Cohen's d = 0.58) and food conditions (t(30) = -3.77, p < 0.01, Cohen's d = -0.82), but not the country condition (t(30) = 1.64, p = 0.11, Cohen's d = 0.31). This suggests that religious labels and food preferences create socially meaningful groups, but country of origin does not. This is evidence of an impact of social categorization on visual processing.

Unveiling the neural dynamics of conscious perception in rapid object recognition.

Our brain excels at recognizing objects, even when they flash by in a rapid sequence. However, the neural processes determining whether a target image in a rapid sequence can be recognized or not remains elusive. We used electroencephalography (EEG) to investigate the temporal dynamics of brain processes that shape perceptual outcomes in these challenging viewing conditions. Using naturalistic images and advanced multivariate pattern analysis (MVPA) techniques, we probed the brain dynamics governing conscious object recognition. Our results show that although initially similar, the processes for when an object can or cannot be recognized diverge around 180 ms post-appearance, coinciding with feedback neural processes. Decoding analyses indicate that gist perception (partial conscious perception) can occur at ∼120 ms through feedforward mechanisms. In contrast, object identification (full conscious perception of the image) is resolved at ∼190 ms after target onset, suggesting involvement of recurrent processing. These findings underscore the importance of recurrent neural connections in object recognition and awareness in rapid visual presentations.

Not Everybody Has an Inner Voice: Behavioral Consequences of Anendophasia.

It is commonly assumed that inner speech-the experience of thought as occurring in a natural language-is a human universal. Recent evidence, however, suggests that the experience of inner speech in adults varies from near constant to nonexistent. We propose a name for a lack of the experience of inner speech-anendophasia-and report four studies examining some of its behavioral consequences. We found that adults who reported low levels of inner speech (N = 46) had lower performance on a verbal working memory task and more difficulty performing rhyme judgments compared with adults who reported high levels of inner speech (N = 47). Task-switching performance-previously linked to endogenous verbal cueing-and categorical effects on perceptual judgments were unrelated to differences in inner speech.

The Effects of Linear Order in Category Learning: Some Replications of Ramscar et al. (2010) and Their Implications for Replicating Training Studies.

Ramscar, Yarlett, Dye, Denny, and Thorpe (2010) showed how, consistent with the predictions of error-driven learning models, the order in which stimuli are presented in training can affect category learning. Specifically, learners exposed to artificial language input where objects preceded their labels learned the discriminating features of categories better than learners exposed to input where labels preceded objects. We sought to replicate this finding in two online experiments employing the same tests used originally: A four pictures test (match a label to one of four pictures) and a four labels test (match a picture to one of four labels). In our study, only findings from the four pictures test were consistent with the original result. Additionally, the effect sizes observed were smaller, and participants over-generalized high-frequency category labels more than in the original study. We suggest that although Ramscar, Yarlett, Dye, Denny, and Thorpe (2010) feature-label order predictions were derived from error-driven learning, they failed to consider that this mechanism also predicts that performance in any training paradigm must inevitably be influenced by participant prior experience. We consider our findings in light of these factors, and discuss implications for the generalizability and replication of training studies.