Models Of Semantic Processing Research Articles

Accumulating evidence for myriad alternatives: Modeling the generation of free association.

The associative manner by which thoughts follow one another has intrigued scholars for decades. The process by which an association is generated in response to a cue can be explained by classic models of semantic processing through distinct computational mechanisms. Distributed attractor networks implement rich-get-richer dynamics and assume that stronger associations can be reached with fewer steps. Conversely, spreading activation models assume that a cue distributes its activation, in parallel, to all associations at a constant rate. Despite these models' huge influence, their intractability together with the unconstrained nature of free association have restricted their few previous uses to qualitative predictions. To test these computational mechanisms quantitatively, we conceptualize free association as the product of internal evidence accumulation and generate predictions concerning the speed and strength of people's associations. To this end, we first develop a novel approach to mapping the personalized space of words from which an individual chooses an association to a given cue. We then use state-of-the-art evidence accumulation models to demonstrate the function of rich-get-richer dynamics on the one hand and of stochasticity in the rate of spreading activation on the other hand, in preventing an exceedingly slow resolution of the competition among myriad potential associations. Furthermore, whereas our results uniformly indicate that stronger associations require less evidence, only in combination with rich-get-richer dynamics does this explain why weak associations are slow yet prevalent. We discuss implications for models of semantic processing and evidence accumulation and offer recommendations for practical applications and individual-differences research. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Latent Semantic Structure of the WMS-III Verbal Paired-Associates.

To investigate the factor structure of the verbal paired-associates (VPA) subtest in the WMS-III using a theoretically driven model of semantic processing previously found to be well-fitting for the WMS-IV version of the test. Archival data were used from 267 heterogeneous neurosciences patients and 223 seizure disorder patients who completed the WMS-III as part of a standard neuropsychological evaluation. Confirmatory factor analysis was used to test theoretically driven models for VPA based on principles of semantic processing. Four nested models of different complexities were examined and compared for goodness-of-fit using chi-squared difference testing. Measurement invariance testing was conducted across heterogeneous neuroscience and seizure disorder samples to test generality of the factor model. After removing items with limited variability (very easy or very hard; 12 of 40 items), a four-factor model was found to be best-fitting in the present patient samples. The four factors were "recreational", "functional", "material", and "symbolic", each representing semantic knowledge associated with the function of the target word referent. This model subsequently met the criteria for the strict measurement invariance, showing good overall fit when factor loadings, thresholds, and residuals were held to equality across samples. The results of this study provide further evidence that "arbitrary" associations between word pairs in VPA items have an underlying semantic structure, challenging the idea that unrelated hard-pairs are semantic-free. These results suggest that a semantic-structure model may be implemented as an alternative scoring in future editions of the WMS to facilitate interpretation.

Feedback Relevance Spaces: Interactional Constraints on Processing Contexts in Dynamic Syntax

Feedback such as backchannels and clarification requests often occurs subsententially, demonstrating the incremental nature of grounding in dialogue. However, although such feedback can occur at any point within an utterance, it typically does not do so, tending to occur at Feedback Relevance Spaces (FRSs). We present a corpus study of acknowledgements and clarification requests in British English, and describe how our low-level, semantic processing model in Dynamic Syntax accounts for this feedback. The model trivially accounts for the 85% of cases where feedback occurs at FRSs, but we also describe how it can be integrated or interpreted at non-FRSs using the predictive, incremental and interactive nature of the formalism. This model shows how feedback serves to continually realign processing contexts and thus manage the characteristic divergence and convergence that is key to moving dialogue forward.

Mathematical model of the process of text information semantic processing

A formalized description of the process of unstructured text information complete linguistic analysis is considered. The results of the development of a mathematical model of semantic processing of unstructured texts based on data arrays and rules of complete linguistic analysis are presented. The data on the implementation of the developed scientific provisions are given.

A novel co-occurrence-based approach to predict pure associative and semantic priming.

The theoretical "difficulty in separating association strength from [semantic] feature overlap" has resulted in inconsistent findings of either the presence or absence of "pure" associative priming in recent literature (Hutchison, 2003, Psychonomic Bulletin & Review, 10(4), p. 787). The present study used co-occurrence statistics of words in sentences to provide a full factorial manipulation of direct association (strong/no) and the number of common associates (many/no) of the prime and target words. These common associates were proposed to serve as semantic features for a recent interactive activation model of semantic processing (i.e., the associative read-out model; Hofmann & Jacobs, 2014). With stimulus onset asynchrony (SOA) as an additional factor, our findings indicate that associative and semantic priming are indeed dissociable. Moreover, the effect of direct association was strongest at a long SOA (1,000 ms), while many common associates facilitated lexical decisions primarily at a short SOA (200 ms). This response pattern is consistent with previous performance-based accounts and suggests that associative and semantic priming can be evoked by computationally determined direct and common associations.

A Tri-network Model of Human Semantic Processing.

Humans process the meaning of the world via both verbal and nonverbal modalities. It has been established that widely distributed cortical regions are involved in semantic processing, yet the global wiring pattern of this brain system has not been considered in the current neurocognitive semantic models. We review evidence from the brain-network perspective, which shows that the semantic system is topologically segregated into three brain modules. Revisiting previous region-based evidence in light of these new network findings, we postulate that these three modules support multimodal experiential representation, language-supported representation, and semantic control. A tri-network neurocognitive model of semantic processing is proposed, which generates new hypotheses regarding the network basis of different types of semantic processes.

Process-Oriented Requirements Engineering: User-Centric LORS Framework

In recent years, the process orientation requirements engineering field has received significant interest. However, dealing with ordinary users within an enterprise for developing as-is business process is very complex because this requires skills, responsibility, knowledge, and expertise of business processes. This research answers the following questions: 1) how to systematically gather information regarding as-is business process requirements in an informal environment and by non-expert users? and 2) how can an enterprise refine the identified business process with a semantic process model? The primary purpose of this research is to develop a supporting framework that is suitable for the definition of an as-is business process to be deployed within the enterprise environment. Hence, the focus is on gathering requirements to define the as-is business process. This framework concentrates on three significant aspects of this process: development, refinement, and serialization the semantics of the process model. To accomplish this objective, the LORS framework has been proposed, which consists of four phases (List, Order, Refinement, and Serialization). The framework presents a new unique technique to identify the business process, refine the process, and generate the model semantics. This study assumes that a simple and complete framework will help non-expert users define a high-quality as-is process, such that enhance and facilitate the matching process with existing reference models. We present a case study, evaluate the case study relative to specified criteria, and research the limitations and implications discovered from our research. This research concludes that the LORS framework is simple, flexible, visible, interactive, dynamic, and effective.

Hemispheric lateralization of semantic feature distinctiveness

Recent models of semantic memory propose that the semantic representation of concepts is based, in part, on a network of features. In this view, a feature that is distinctive for an object (a zebra has stripes) is processed differently from a feature that is shared across many objects (a zebra has four legs). The goal of this paper is to determine whether there are hemispheric differences in such processing. In a feature verification task, participants responded ‘yes’ or ‘no’ following concepts which were presented to a single visual field (left or right) paired with a shared or distinctive feature. Both hemispheres showed faster reaction times to shared features than to distinctive features, although right hemisphere responses were significantly slower overall and particularly in the processing of distinctive features. These findings support models of semantic processing in which the dominant left hemisphere more efficiently performs highly discriminating ‘fine’ encoding, in contrast to the right hemisphere which performs less discriminating ‘coarse’ encoding.

Detecting potential weaknesses in business processes

Purpose – Automating the task of identifying process weaknesses using process models is promising, as many organizations have to manage a large amount of process models. The purpose of this paper is to introduce a pattern-based approach for automatically detecting potential process weaknesses in semantic process models, thus supporting the task of business process improvement. Design/methodology/approach – Based on design research, combined with a case study, the authors explore the design, application and evaluation of a pattern-based process weakness detection approach within the setting of a real-life case study in a German bank. Findings – Business process weakness detection can be automated to a remarkable extent using pattern matching and a semantic business process modeling language. A case study provided evidence that such an approach highly supports business process analysts. Research limitations/implications – The presented approach is limited by the fact that not every potential process weakness detected by pattern matching is really a weakness but just gives the impression to be one. Hence, after detecting a weakness, analysts still have to decide on its authenticity. Practical implications – Applying weakness patterns to semantic process models via pattern matching allows organizations to automatically and efficiently identify process improvement potentials. Hence, this research helps to avoid time- and resource-consuming manual analysis of process model landscapes. Originality/value – The approach is not restricted to a single modeling language. Furthermore, by applying the pattern matching approach to a semantic modeling language, the authors avoid ambiguous search results. A case study proves the usefulness of the approach.

Dissociating the semantic function of two neighbouring subregions in the left lateral anterior temporal lobe

We used fMRI in 35 healthy participants to investigate how two neighbouring subregions in the lateral anterior temporal lobe (LATL) contribute to semantic matching and object naming. Four different levels of processing were considered: (A) recognition of the object concepts; (B) search for semantic associations related to object stimuli; (C) retrieval of semantic concepts of interest; and (D) retrieval of stimulus specific concepts as required for naming. During semantic association matching on picture stimuli or heard object names, we found that activation in both subregions was higher when the objects were semantically related (mug–kettle) than unrelated (car–teapot). This is consistent with both LATL subregions playing a role in (C), the successful retrieval of amodal semantic concepts. In addition, one subregion was more activated for object naming than matching semantically related objects, consistent with (D), the retrieval of a specific concept for naming. We discuss the implications of these novel findings for cognitive models of semantic processing and left anterior temporal lobe function.

Auditory semantic processing in dichotic listening: Effects of competing speech, ear of presentation, and sentential bias on N400s to spoken words in context

The effects of ear of presentation and competing speech on N400s to spoken words in context were examined in a dichotic sentence priming paradigm. Auditory sentence contexts with a strong or weak semantic bias were presented in isolation to the right or left ear, or with a competing signal presented in the other ear at a SNR of −12dB. Target words were congruent or incongruent with the sentence meaning. Competing speech attenuated N400s to both congruent and incongruent targets, suggesting that the demand imposed by a competing signal disrupts the engagement of semantic comprehension processes. Bias strength affected N400 amplitudes differentially depending upon ear of presentation: weak contexts presented to the le/RH produced a more negative N400 response to targets than strong contexts, whereas no significant effect of bias strength was observed for sentences presented to the re/LH. The results are consistent with a model of semantic processing in which the RH relies on integrative processing strategies in the interpretation of sentence-level meaning.

BPMO-Based OWL Representation of Business Processes

Semantic process modeling approaches are used in modelling, making use of the process ontology, which is the preferred BPMO. In the process of semantically modeling, using ontology to describe the business process is an important step. Therefore, the text proposed for BPMO-based OWL representation of business process, lays the foundation for resolving issues, such as semantic annotation, machine-understandable, and reasoning on business process. We will put forward the construction and representation of our business process knowledge; examine the workshop business process activities; according to business rules, describe business processes on the basis of the BPMO; represent BPMO-based process on the basis of ontology modeling language OWL; model the process on the foundation of softeware BPMO Modeller. Workshop product packaging as an example, we will verify business processes based on BPMO methods.

Semantic Process Modeling – Design and Implementation of an Ontology-based Representation of Business Processes

An extension of process modeling languages is designed which allows representing the semantics of model element labels which are formulated in natural language by using concepts of a formal ontology. This combination of semiformal models with formal ontologies will be characterized as semantic process modeling. The approach is exemplarily applied to the languages EPC (Event-driven Process Chain), BPMN (Business Process Modeling Notation) and OWL (Web Ontology Language) and is generalized by means of an information model. The proposed formalization of the semantics of individual model elements in conjunction with the usage of inference engines allows the improvement of query functionalities in modeling tools and enables new possibilities of model validation. The integration of the approach in the IT-based work environments of modelers is demonstrated by a system architecture and a prototypical implementation. Evidently, advantages in the areas of modeling, model management, IT-business alignment, and compliance can be achieved by the application of modeling tools augmented with semantic technologies.

History of aphasia

Background: A prominent model of semantic processing in modern cognitive psychology proposes that semantic memory originates in everyday life experience with concrete objects such as plants, animals, and tools (Martin & Chao, 2001). When the meaning of a concrete content word is being acquired, the learner is confronted with stimuli of various modalities related to the word's meaning. This comes to be stored as sensory knowledge about the object. It is further postulated that there is a conceptual domain remote from the mechanisms of perception, which is often referred to as functional knowledge or verbal semantics. There is a large body of neuropsychological literature trying to establish how much sensory and functional semantics is needed to access a name, and whether the relative contribution of these types of knowledge is the same for all categories of objects. Another controversial issue is whether naming requires access to semantic knowledge, or whether object names can be accessed directly from vision without the intervention of semantics, as is generally accepted for written word naming. Some support for this assumption seems to come from cases of so‐called non‐optic aphasia, a condition in which patients can name from visual presentation only but not from any other modality of presentation such as auditory, verbal, tactile, etc. In optic aphasia, a condition far better established, naming is possible from all modalities except vision. Aims: The aim of this paper is to draw attention to the first case description of non‐optic or negative optic aphasia described by Wolff (1897, 1904). Methods & Procedures: The case describes the results of a re‐examination of Voit, who was seen by several neurologists in the course of a decade in classical aphasiology. The patient demonstrated anomia in oral but not in written naming of objects in view. Wolff's examination involves extensive testing of semantic processing in several modalities, especially with respect to the status of functional and sensory semantic features Outcomes & Results: The re‐examination of patient Voit by Wolff in 1897 with new procedures revealed a specific impairment in processing sensory knowledge, while functional knowledge of objects was relatively preserved. This led to a naming impairment in all modalities of presentation except the visual one. Using more refined tasks, Wolff also demonstrated receptive impairments, in contrast to previous researchers who had concluded that the impairment was restricted to oral production. Conclusions: Although Wolff's (1904) case of negative optic aphasia has been almost completely forgotten (but see Bartels & Wallesch, 1996), it is astonishingly modern in its conceptual approach and in the central questions it addresses on the mechanisms involved in the process of naming and on the structure of the semantic system. As is usual in classical cases, the methodology may appear less stringent than in most contemporary work, but the approach was brilliant.

Dynamics of activation of semantically similar concepts during spoken word recognition.

Semantic similarity effects provide critical insight into the organization of semantic knowledge and the nature of semantic processing. In the present study, we examined the dynamics of semantic similarity effects by using the visual world eyetracking paradigm. Four objects were shown on a computer monitor, and participants were instructed to click on a named object, during which time their gaze position was recorded. The likelihood of fixating competitor objects was predicted by the degree of semantic similarity to the target concept. We found reliable, graded competition that depended on degree of target-competitor similarity, even for distantly related items for which priming has not been found in previous priming studies. Time course measures revealed a consistently earlier fixation peak for near semantic neighbors relative to targets. Computational investigations with an attractor dynamical model, a spreading activation model, and a decision model revealed that a combination of excitatory and inhibitory mechanisms is required to obtain such peak timing, providing new constraints on models of semantic processing.

The effect of frequency of shared features on judgments of semantic similarity

Insight into the structure of conceptual knowledge can be gleaned by examining how statistical regularities in the semantic structure of concepts affect semantic processing. Two similarity judgment experiments revealed that pairs of concepts sharing relatively rare features were judged to be more similar than concepts sharing an equal number of relatively frequent features. Simulations confirmed that these results are consistent with a recurrent connectionist network model of semantic processing in which units corresponding to rare features are activated more quickly and accurately than units corresponding to frequent features. These results support the hypothesis that rare features play a privileged role in the processing of word meanings.

The role of inferior frontal gyrus and inferior parietal lobule in semantic processing of Chinese characters

Functional magnetic resonance imaging was used to explore the neural correlates of semantic judgments to Chinese characters. Adult participants were asked to indicate if character pairs were related in meaning that were arranged in a continuous variable according to association strength. This parametric manipulation allowed for a more precise determination of the role of the left inferior parietal lobule in processing meaning, which has not been reported in previous Chinese studies. Consistent with previous findings in English, participants showed activation in left inferior frontal gyrus (BA 47, 45) and left posterior middle temporal gyrus (BA 21). Characters with stronger semantic association elicited greater activation in left inferior parietal lobule (BA 39), suggesting stronger integration of highly related semantic features. By contrast, characters with weaker semantic association elicited greater activation in both an anterior ventral region (BA 47) and a mid-ventral region of left inferior frontal gyrus (BA 45), suggesting a controlled retrieval process and a selection process. Our findings of association strength are discussed in a proposed neuro-anatomical model of semantic processing.

A cortical network for semantics: (de)constructing the N400

Measuring event-related potentials (ERPs) has been fundamental to our understanding of how language is encoded in the brain. One particular ERP response, the N400 response, has been especially influential as an index of lexical and semantic processing. However, there remains a lack of consensus on the interpretation of this component. Resolving this issue has important consequences for neural models of language comprehension. Here we show that evidence bearing on where the N400 response is generated provides key insights into what it reflects. A neuroanatomical model of semantic processing is used as a guide to interpret the pattern of activated regions in functional MRI, magnetoencephalography and intracranial recordings that are associated with contextual semantic manipulations that lead to N400 effects.

Semantic Memory Disorders in Alzheimers Disease: Clues from Semantic Priming Effects

Semantic memory deficits are a common landmark in Alzheimer's disease, but the nature of these impairments remains to be clarified. The tests used to explore this memory system are not specific and involve cognitive processes often disturbed in Alzheimer's disease. A complementary way to investigate semantic memory in neuropsychology is by using the semantic priming paradigm. Here, semantic priming refers specifically to the modification of a stimulus processing behind the presentation of a related stimulus; it is a short-lived phenomenon considered an implicit measure of semantic memory integrity. However, semantic priming studies have yielded contradictory results in Alzheimer's disease, with authors reporting normal priming, less-than-normal priming, or increased priming effects (hyperpriming). The aim of this paper is to review the literature investigating semantic priming in Alzheimer's disease, and to discuss the contradictory results in the context of current models of semantic processing. For a clear comprehension of the semantic priming patterns in this pathology, we will precise the methodology used and the characteristics of the Alzheimer's disease patients examined. Besides, the surprising hyperpriming phenomenon - often observed in Alzheimer's disease at the early stage of dementia--will also be explained in detail. These results from semantic priming represent invaluable clues to widen our knowledge and conceptions about deterioration of the semantic memory in Alzheimer's disease.

Hemispheric asymmetries in the split-fovea model of semantic processing

We report a series of neural network models of semantic processing of single English words in the left and the right hemispheres of the brain. We implement the foveal splitting of the visual field and assess the influence of this splitting on a mapping from orthography to semantic representations in single word reading. The models were trained on English four-letter words, presented according to their frequency in all positions encountered during normal reading. The architecture of the model interacted with the training set to produce processing asymmetries comparable to those found in behavioral studies. First, the cueing effects of dominant and subordinate meanings of ambiguous words were different for words presented to the left or to the right of the input layer. Second, priming effects of groups of related words were stronger in the left input than the right input of the model. These effects were caused by coarser-coding in the right half compared with the left half of the model, an emergent effect of the split model interacting with informational asymmetries in the left and right parts of words in the lexicon of English. Some or all of the behavioral data for reading single words in English may have a similar origin.