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Objectives: The underlying mechanisms of burning mouth syndrome (BMS) remain unclear leading to challenges and unsatisfactory management. Current treatments focus primarily on symptom relief, with few consistently achieving a 50% reduction in pain. This review aims to explore animal models of BMS to gain a better understanding of the underlying mechanisms and to discuss potential and existing knowledge gaps. Methods: A comprehensive review of PubMed®, Google Scholar, and Scopus was performed to assess advances and significant gaps of existing rodent models that mimic BMS‐related symptoms. Results: Rodent models of BMS involve reproduction of dry‐tongue, chorda tympani transection, or overexpression of artemin protein. Existing preclinical models tend to highlight one specific etiopathogenesis and often overlook sex‐ and hormone‐specific factors. Conclusion: Combining aspects from various BMS models could prove beneficial in developing comprehensive experimental designs and outcomes encompassing the multifaceted nature of BMS. [ABSTRACT FROM AUTHOR]

We investigate conditions in which novices make some reference errors when programming. We asked students from introductory programming courses to perform a simple code-writing task that required constructing references to objects and their attributes. By experimentally manipulating the nature of the attributes in the tasks, from identifying attributes (e.g., "title" or "label") to descriptive attributes (e.g., "calories" or "texture"), the study revealed the relative frequencies with which students mistakenly omit the name of an identifying attribute while attempting to reference its value. We explain how these reference-point shifts are consistent with the use of metonymy, a form of figurative expression in human communication. Our analysis also reveals how the presentation of examples can affect the construction of the reference in the student's solution. We discuss plausible accounts of the reference-point errors and how they may inform a model of reference construction. We suggest that reference-point errors may be the result of well-practiced habits of communication rather than misconceptions of the task or what the computer can do.

Objectives: To assess the effectiveness of topical interventions in the management of burning mouth syndrome (BMS), based on the core outcome domains recommended by the Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT). Methods: A systematic literature review of RCTs on topical interventions for the management of BMS, published in PubMed, Web of Science, PsycInfo, Cochrane Database/Central, and Google Scholar through May 2021 was performed. Results: Eight RCTs (n = 358 study participants) were included in this study. Due to underreporting of IMMPACT domains, publication bias, high degree of heterogeneity between studies, meta‐analysis was not undertaken. Based on changes in visual analogue pain scores (ΔVAS), the most reported outcome, the effectiveness of the topical interventions was demonstrated; however, it is low level of evidence. Conclusions: High levels of variability (interventions, outcomes, outcome measurement tools, and intervention effects evaluated), heterogeneity, publication bias, and underreporting of IMMPACT domains were observed across the RCTs. This systematic review highlights the need for application of standardized outcome measures to future RCTs. At the present time, there is lack of moderate‐strong evidence on short‐ and long‐term outcomes to support or refute the use of any particular topical intervention in managing BMS. Future RCTs with standardized outcome measures are needed. [ABSTRACT FROM AUTHOR]

This paper presents ongoing work that demonstrates how a discrete rule-based model may appropriately manifest graded performance and investigates the source contributing to graded performance of a particular rule-based model called SCA. Previous results have demonstrated that SCA produces appropriate graded performance as a function of learning experience, instance typicality, and other similarity-dependent properties. However, the source of its graded behavior has been somewhat obscured by the presence of continuous components in some aspects of the model. Fully symbolic altemates are presented here and the qualitative predictions from previous work is replicated, thereby suggesting that explicit gradient representations are not necessary for producing graded behavior In addition to replicating previous results, the results presented here clarify a peculiar character of the model, namely, that the model's typicality differences disappear after extended learning.

This paper describes a model that learns to pronounce English words. Learning occurs in two modules: 1) a rule-based module that constructs pronunciations by phonetic analysis of the letter string, and 2) a whole-word module that leams to associate subsets of letters to the pronunciation, without phonetic analysis. In a simulation on a corpus of over 300 words the model produced pronunciation latencies consistent with the effects of word frequency and orthographic regularity observed in human data. Imphcations of the model for theories of visual word processing and reading instruction are discussed.

This paper addresses category typicality in the context of a category naming task. In contrast to the predominant effort with gradient models, a symbolic search framework is taken. Within this framework, the SC A (Symbolic Concept Acquisition) model demonstrates varying response times as a function of an instance's intra-category typicality. Here its coverage is expanded to inter-category typicality. A functionally motivated extension for SC A is advanced that pursues search backtracking under ambiguous cases. I explain how the backtracking extension accounts for inter-category typicality effects, and support it with some empirical evidence. I discuss how the effect generalizes to a larger class of symbolic search models.

When learning to program, students often mistakenly refer to an element that is structurally related to the element that they intend to reference. For example, they may indicate the attribute of an object when their intention is to reference the whole object. This paper examines these reference-point errors through the context of metonymy. Metonymy is a rhetorical device where the speaker states a referent that is structurally related to the intended referent. For example, the following sentence states an office bureau but actually refers to a person working at the bureau: "The tourist asked the travel bureau for directions to the museum." Drawing upon previous studies, I discuss how student reference errors may be consistent with the use of metonymy. In particular, I hypothesize that students are more likely to reference an identifying element even when a structurally related element is intended. I then present two experiments, which produce results consistent with this analysis. In both experiments, students are more likely to produce reference-point errors that involve identifying attributes than descriptive attributes. Given these results, I explore the possibility that students are relying on habits of communication rather than the mechanistic principles needed for successful programming. Finally I discuss teaching interventions using live examples and how metonymy may be presented to non-computing students as pedagogy for computational thinking.

How does working within a unified theory of cognition - an architecture - provide useful constraint when modeling large timescale tasks, where performance Is primarily determined by knowledge, rather than the architecture's basic mechanisms? W e present a methodology for extracting the constraint that comes from the architecture, by deriving a set of architectural entailments which as for certain model properties over others. The methodology allows us to fzictor the effect that various architectural properties have on a model. We demonstrate the methodology with a case study: a model of learning procedures from natural language instructions, Instructo-Soar, within the Soar architecture.

A cognitive model for learning associations between words and objects is presented. We first list basic constraints to which the model must adhere. The constraints arise from two sources. First they stem from observed psychological phenomena including typicality effects, extension errors observed from children and belief-dependent behavior. Secondly they arise from our choice to integrate the model in a unified theory of cognition. In presenting the constraints to the model's construction, w e motivate our design decisions while describing our algorithm that takes a symbolic, production-based approach. The model's adherence to the constraints is further supported by some empirical results.

The International Classification of Disease defines burning mouth syndrome (BMS) as a chronic intraoral burning sensation, with no identifiable local or systemic cause. Since current management is often unsatisfactory, the aim of this report is to describe a new treatment modality (i.e., low-dose naltrexone [LDN]). A 62-year-old woman presented with the complaint of burning on the tongue of 3 years' duration. Existing comorbidities were fibromyalgia, irritable bowel syndrome, headache, and interstitial cystitis. Her reported pain intensity ranged from 2/10 (morning) to 8/10 (evening) on a numeric rating scale. With the diagnosis of BMS and hyposalivation, and in light of her current clonazepam use and fibromyalgia, a dry mouth protocol and LDN (3 mg) were prescribed. After 1 month, her pain intensity decreased by 50%, with no pain upon awakening. After 2 months, the widespread pain associated with her chronic morbidities also reduced by 50%, and her headache disappeared. After adjusting LDN dose to 4.5 mg, the patient was stable at 6 months, with 50% reduction of widespread pain and 2/10 BMS pain, and no reported side effects. These preliminary results suggest that LDN may be a feasible and effective treatment for BMS, especially in patients' refractory to traditional treatment. [ABSTRACT FROM AUTHOR]