A Joint Investigation of Semantic Facilitation and Semantic Interference in Continuous Naming

ERIC Educational Resources Information Center

Scaltritti, Michele; Peressotti, Francesca; Navarrete, Eduardo

2017-01-01

When speakers name multiple semantically related items, opposing effects can be found. Semantic facilitation is found when naming 2 semantically related items in a row. In contrast, semantic interference is found when speakers name semantically related items separated by 1 or more intervening unrelated items. This latter form of interference is…

Auditing the Assignments of Top-Level Semantic Types in the UMLS Semantic Network to UMLS Concepts

PubMed Central

He, Zhe; Perl, Yehoshua; Elhanan, Gai; Chen, Yan; Geller, James; Bian, Jiang

2018-01-01

The Unified Medical Language System (UMLS) is an important terminological system. By the policy of its curators, each concept of the UMLS should be assigned the most specific Semantic Types (STs) in the UMLS Semantic Network (SN). Hence, the Semantic Types of most UMLS concepts are assigned at or near the bottom (leaves) of the UMLS Semantic Network. While most ST assignments are correct, some errors do occur. Therefore, Quality Assurance efforts of UMLS curators for ST assignments should concentrate on automatically detected sets of UMLS concepts with higher error rates than random sets. In this paper, we investigate the assignments of top-level semantic types in the UMLS semantic network to concepts, identify potential erroneous assignments, define four categories of errors, and thus provide assistance to curators of the UMLS to avoid these assignments errors. Human experts analyzed samples of concepts assigned 10 of the top-level semantic types and categorized the erroneous ST assignments into these four logical categories. Two thirds of the concepts assigned these 10 top-level semantic types are erroneous. Our results demonstrate that reviewing top-level semantic type assignments to concepts provides an effective way for UMLS quality assurance, comparing to reviewing a random selection of semantic type assignments. PMID:29375930

Auditing the Assignments of Top-Level Semantic Types in the UMLS Semantic Network to UMLS Concepts.

PubMed

He, Zhe; Perl, Yehoshua; Elhanan, Gai; Chen, Yan; Geller, James; Bian, Jiang

2017-11-01

The Unified Medical Language System (UMLS) is an important terminological system. By the policy of its curators, each concept of the UMLS should be assigned the most specific Semantic Types (STs) in the UMLS Semantic Network (SN). Hence, the Semantic Types of most UMLS concepts are assigned at or near the bottom (leaves) of the UMLS Semantic Network. While most ST assignments are correct, some errors do occur. Therefore, Quality Assurance efforts of UMLS curators for ST assignments should concentrate on automatically detected sets of UMLS concepts with higher error rates than random sets. In this paper, we investigate the assignments of top-level semantic types in the UMLS semantic network to concepts, identify potential erroneous assignments, define four categories of errors, and thus provide assistance to curators of the UMLS to avoid these assignments errors. Human experts analyzed samples of concepts assigned 10 of the top-level semantic types and categorized the erroneous ST assignments into these four logical categories. Two thirds of the concepts assigned these 10 top-level semantic types are erroneous. Our results demonstrate that reviewing top-level semantic type assignments to concepts provides an effective way for UMLS quality assurance, comparing to reviewing a random selection of semantic type assignments.

SemantGeo: Powering Ecological and Environment Data Discovery and Search with Standards-Based Geospatial Reasoning

NASA Astrophysics Data System (ADS)

Seyed, P.; Ashby, B.; Khan, I.; Patton, E. W.; McGuinness, D. L.

2013-12-01

Recent efforts to create and leverage standards for geospatial data specification and inference include the GeoSPARQL standard, Geospatial OWL ontologies (e.g., GAZ, Geonames), and RDF triple stores that support GeoSPARQL (e.g., AllegroGraph, Parliament) that use RDF instance data for geospatial features of interest. However, there remains a gap on how best to fuse software engineering best practices and GeoSPARQL within semantic web applications to enable flexible search driven by geospatial reasoning. In this abstract we introduce the SemantGeo module for the SemantEco framework that helps fill this gap, enabling scientists find data using geospatial semantics and reasoning. SemantGeo provides multiple types of geospatial reasoning for SemantEco modules. The server side implementation uses the Parliament SPARQL Endpoint accessed via a Tomcat servlet. SemantGeo uses the Google Maps API for user-specified polygon construction and JsTree for providing containment and categorical hierarchies for search. SemantGeo uses GeoSPARQL for spatial reasoning alone and in concert with RDFS/OWL reasoning capabilities to determine, e.g., what geofeatures are within, partially overlap with, or within a certain distance from, a given polygon. We also leverage qualitative relationships defined by the Gazetteer ontology that are composites of spatial relationships as well as administrative designations or geophysical phenomena. We provide multiple mechanisms for exploring data, such as polygon (map-based) and named-feature (hierarchy-based) selection, that enable flexible search constraints using boolean combination of selections. JsTree-based hierarchical search facets present named features and include a 'part of' hierarchy (e.g., measurement-site-01, Lake George, Adirondack Region, NY State) and type hierarchies (e.g., nodes in the hierarchy for WaterBody, Park, MeasurementSite), depending on the ';axis of choice' option selected. Using GeoSPARQL and aforementioned ontology, these hierarchies are constrained based on polygon selection, where the corresponding polygons of the contained features are visually rendered to assist exploration. Once measurement sites are plotted based on initial search, subsequent searches using JsTree selections can extend the previous based on nearby waterbodies in some semantic relationship of interest. For example, ';tributary of' captures water bodies that flow into the current one, and extending the original search to include tributaries of the observed water body is useful to environmental scientists for isolating the source of characteristic levels, including pollutants. Ultimately any SemantEco module can leverage SemantGeo's underlying APIs, leveraged in a deployment of SemantEco that combines EPA and USGS water quality data, and one customized for searching data available from the Darrin Freshwater Institute. Future work will address generating RDF geometry data from shape files, aligning RDF data sources to better leverage qualitative and spatial relationships, and validating newly generated RDF data adhering to the GeoSPARQL standard.

Motor knowledge is one dimension for concept organization: further evidence from a Chinese semantic dementia case.

PubMed

Lin, Nan; Guo, Qihao; Han, Zaizhu; Bi, Yanchao

2011-11-01

Neuropsychological and neuroimaging studies have indicated that motor knowledge is one potential dimension along which concepts are organized. Here we present further direct evidence for the effects of motor knowledge in accounting for categorical patterns across object domains (living vs. nonliving) and grammatical domains (nouns vs. verbs), as well as the integrity of other modality-specific knowledge (e.g., visual). We present a Chinese case, XRK, who suffered from semantic dementia with left temporal lobe atrophy. In naming and comprehension tasks, he performed better at nonliving items than at living items, and better at verbs than at nouns. Critically, multiple regression method revealed that these two categorical effects could be both accounted for by the charade rating, a continuous measurement of the significance of motor knowledge for a concept or a semantic feature. Furthermore, charade rating also predicted his performances on the generation frequency of semantic features of various modalities. These findings consolidate the significance of motor knowledge in conceptual organization and further highlights the interactions between different types of semantic knowledge. Copyright © 2010 Elsevier Inc. All rights reserved.

A Story of a Crashed Plane in US-Mexican border

NASA Astrophysics Data System (ADS)

Bermudez, Luis; Hobona, Gobe; Vretanos, Peter; Peterson, Perry

2013-04-01

A plane has crashed on the US-Mexican border. The search and rescue command center planner needs to find information about the crash site, a mountain, nearby mountains for the establishment of a communications tower, as well as ranches for setting up a local incident center. Events like this one occur all over the world and exchanging information seamlessly is key to save lives and prevent further disasters. This abstract describes an interoperability testbed that applied this scenario using technologies based on Open Geospatial Consortium (OGC) standards. The OGC, which has about 500 members, serves as a global forum for the collaboration of developers and users of spatial data products and services, and to advance the development of international standards for geospatial interoperability. The OGC Interoperability Program conducts international interoperability testbeds, such as the OGC Web Services Phase 9 (OWS-9), that encourages rapid development, testing, validation, demonstration and adoption of open, consensus based standards and best practices. The Cross-Community Interoperability (CCI) thread in OWS-9 advanced the Web Feature Service for Gazetteers (WFS-G) by providing a Single Point of Entry Global Gazetteer (SPEGG), where a user can submit a single query and access global geographic names data across multiple Federal names databases. Currently users must make two queries with differing input parameters against two separate databases to obtain authoritative cross border geographic names data. The gazetteers in this scenario included: GNIS and GNS. GNIS or Geographic Names Information System is managed by USGS. It was first developed in 1964 and contains information about domestic and Antarctic names. GNS or GeoNET Names Server provides the Geographic Names Data Base (GNDB) and it is managed by National Geospatial Intelligence Agency (NGA). GNS has been in service since 1994, and serves names for areas outside the United States and its dependent areas, as well as names for undersea features. The following challenges were advanced: Cascaded WFS-G servers (allowing to query multiple WFSs with a "parent" WFS), implemented query names filters (e.g. fuzzy search, text search), implemented dealing with multilingualism and diacritics, implemented advanced spatial constraints (e.g. search by radial search and nearest neighbor) and semantically mediated feature types (e.g. mountain vs. hill). To enable semantic mediation, a series of semantic mappings were defined between the NGA GNS, USGS GNIS and the Alexandria Digital Library (ADL) Gazetteer. The mappings were encoded in the Web Ontology Language (OWL) to enable them to be used by semantic web technologies. The semantic mappings were then published for ingestion into a semantic mediator that used the mappings to associate location types from one gazetteer with location types in another. The semantic mediator was then able to transform requests on the fly, providing a single point of entry WFS-G to multiple gazetteers. The presentation will provide a live presentation of the work performed, highlight main developments, and discuss future development.

The semantics of pain in Greco-Roman antiquity.

PubMed

Wilson, Nicole

2013-01-01

The semantics of pain are an important and interesting aspect of any language. Ancient Greek and Latin had multiple words for pain, which makes scrutinizing different meanings problematic. The ancient physician Galen approached this issue through the use of adjectives to describe the qualities for pain, instead of the words for pain themselves. The medical texts of Celsus and Caelius Aurelianus reveal that Latin also vested particular significance in qualifiers to distinguish between different types of pain. This article looks at the qualifying terms used for pain in the ancient Greek and Latin languages to reveal a sophisticated Greco-Roman vocabulary for pain.

Multiple Regions of a Cortical Network Commonly Encode the Meaning of Words in Multiple Grammatical Positions of Read Sentences.

PubMed

Anderson, Andrew James; Lalor, Edmund C; Lin, Feng; Binder, Jeffrey R; Fernandino, Leonardo; Humphries, Colin J; Conant, Lisa L; Raizada, Rajeev D S; Grimm, Scott; Wang, Xixi

2018-05-16

Deciphering how sentence meaning is represented in the brain remains a major challenge to science. Semantically related neural activity has recently been shown to arise concurrently in distributed brain regions as successive words in a sentence are read. However, what semantic content is represented by different regions, what is common across them, and how this relates to words in different grammatical positions of sentences is weakly understood. To address these questions, we apply a semantic model of word meaning to interpret brain activation patterns elicited in sentence reading. The model is based on human ratings of 65 sensory/motor/emotional and cognitive features of experience with words (and their referents). Through a process of mapping functional Magnetic Resonance Imaging activation back into model space we test: which brain regions semantically encode content words in different grammatical positions (e.g., subject/verb/object); and what semantic features are encoded by different regions. In left temporal, inferior parietal, and inferior/superior frontal regions we detect the semantic encoding of words in all grammatical positions tested and reveal multiple common components of semantic representation. This suggests that sentence comprehension involves a common core representation of multiple words' meaning being encoded in a network of regions distributed across the brain.

CUILESS2016: a clinical corpus applying compositional normalization of text mentions.

PubMed

Osborne, John D; Neu, Matthew B; Danila, Maria I; Solorio, Thamar; Bethard, Steven J

2018-01-10

Traditionally text mention normalization corpora have normalized concepts to single ontology identifiers ("pre-coordinated concepts"). Less frequently, normalization corpora have used concepts with multiple identifiers ("post-coordinated concepts") but the additional identifiers have been restricted to a defined set of relationships to the core concept. This approach limits the ability of the normalization process to express semantic meaning. We generated a freely available corpus using post-coordinated concepts without a defined set of relationships that we term "compositional concepts" to evaluate their use in clinical text. We annotated 5397 disorder mentions from the ShARe corpus to SNOMED CT that were previously normalized as "CUI-less" in the "SemEval-2015 Task 14" shared task because they lacked a pre-coordinated mapping. Unlike the previous normalization method, we do not restrict concept mappings to a particular set of the Unified Medical Language System (UMLS) semantic types and allow normalization to occur to multiple UMLS Concept Unique Identifiers (CUIs). We computed annotator agreement and assessed semantic coverage with this method. We generated the largest clinical text normalization corpus to date with mappings to multiple identifiers and made it freely available. All but 8 of the 5397 disorder mentions were normalized using this methodology. Annotator agreement ranged from 52.4% using the strictest metric (exact matching) to 78.2% using a hierarchical agreement that measures the overlap of shared ancestral nodes. Our results provide evidence that compositional concepts can increase semantic coverage in clinical text. To our knowledge we provide the first freely available corpus of compositional concept annotation in clinical text.

Analyzing polysemous concepts from a clinical perspective: Application to auditing concept categorization in the UMLS

PubMed Central

Mougin, Fleur; Bodenreider, Olivier; Burgun, Anita

2015-01-01

Objectives Polysemy is a frequent issue in biomedical terminologies. In the Unified Medical Language System (UMLS), polysemous terms are either represented as several independent concepts, or clustered into a single, multiply-categorized concept. The objective of this study is to analyze polysemous concepts in the UMLS through their categorization and hierarchical relations for auditing purposes. Methods We used the association of a concept with multiple Semantic Groups (SGs) as a surrogate for polysemy. We first extracted multi-SG (MSG) concepts from the UMLS Metathesaurus and characterized them in terms of the combinations of SGs with which they are associated. We then clustered MSG concepts in order to identify major types of polysemy. We also analyzed the inheritance of SGs in MSG concepts. Finally, we manually reviewed the categorization of the MSG concepts for auditing purposes. Results The 1208 MSG concepts in the Metathesaurus are associated with 30 distinct pairs of SGs. We created 75 semantically homogeneous clusters of MSG concepts, and 276 MSG concepts could not be clustered for lack of hierarchical relations. The clusters were characterized by the most frequent pairs of semantic types of their constituent MSG concepts. MSG concepts exhibit limited semantic compatibility with their parent and child concepts. A large majority of MSG concepts (92%) are adequately categorized. Examples of miscategorized concepts are presented. Conclusion This work is a systematic analysis and manual review of all concepts categorized by multiple SGs in the UMLS. The correctly-categorized MSG concepts do reflect polysemy in the UMLS Metathesaurus. The analysis of inheritance of SGs proved useful for auditing concept categorization in the UMLS. PMID:19303057

Multiple Semantic Matching on Augmented N-partite Graph for Object Co-segmentation.

PubMed

Wang, Chuan; Zhang, Hua; Yang, Liang; Cao, Xiaochun; Xiong, Hongkai

2017-09-08

Recent methods for object co-segmentation focus on discovering single co-occurring relation of candidate regions representing the foreground of multiple images. However, region extraction based only on low and middle level information often occupies a large area of background without the help of semantic context. In addition, seeking single matching solution very likely leads to discover local parts of common objects. To cope with these deficiencies, we present a new object cosegmentation framework, which takes advantages of semantic information and globally explores multiple co-occurring matching cliques based on an N-partite graph structure. To this end, we first propose to incorporate candidate generation with semantic context. Based on the regions extracted from semantic segmentation of each image, we design a merging mechanism to hierarchically generate candidates with high semantic responses. Secondly, all candidates are taken into consideration to globally formulate multiple maximum weighted matching cliques, which complements the discovery of part of the common objects induced by a single clique. To facilitate the discovery of multiple matching cliques, an N-partite graph, which inherently excludes intralinks between candidates from the same image, is constructed to separate multiple cliques without additional constraints. Further, we augment the graph with an additional virtual node in each part to handle irrelevant matches when the similarity between two candidates is too small. Finally, with the explored multiple cliques, we statistically compute pixel-wise co-occurrence map for each image. Experimental results on two benchmark datasets, i.e., iCoseg and MSRC datasets, achieve desirable performance and demonstrate the effectiveness of our proposed framework.

The effects of shared information on semantic calculations in the gene ontology.

PubMed

Bible, Paul W; Sun, Hong-Wei; Morasso, Maria I; Loganantharaj, Rasiah; Wei, Lai

2017-01-01

The structured vocabulary that describes gene function, the gene ontology (GO), serves as a powerful tool in biological research. One application of GO in computational biology calculates semantic similarity between two concepts to make inferences about the functional similarity of genes. A class of term similarity algorithms explicitly calculates the shared information (SI) between concepts then substitutes this calculation into traditional term similarity measures such as Resnik, Lin, and Jiang-Conrath. Alternative SI approaches, when combined with ontology choice and term similarity type, lead to many gene-to-gene similarity measures. No thorough investigation has been made into the behavior, complexity, and performance of semantic methods derived from distinct SI approaches. We apply bootstrapping to compare the generalized performance of 57 gene-to-gene semantic measures across six benchmarks. Considering the number of measures, we additionally evaluate whether these methods can be leveraged through ensemble machine learning to improve prediction performance. Results showed that the choice of ontology type most strongly influenced performance across all evaluations. Combining measures into an ensemble classifier reduces cross-validation error beyond any individual measure for protein interaction prediction. This improvement resulted from information gained through the combination of ontology types as ensemble methods within each GO type offered no improvement. These results demonstrate that multiple SI measures can be leveraged for machine learning tasks such as automated gene function prediction by incorporating methods from across the ontologies. To facilitate future research in this area, we developed the GO Graph Tool Kit (GGTK), an open source C++ library with Python interface (github.com/paulbible/ggtk).

Overlap in the functional neural systems involved in semantic and episodic memory retrieval.

PubMed

Rajah, M N; McIntosh, A R

2005-03-01

Neuroimaging and neuropsychological data suggest that episodic and semantic memory may be mediated by distinct neural systems. However, an alternative perspective is that episodic and semantic memory represent different modes of processing within a single declarative memory system. To examine whether the multiple or the unitary system view better represents the data we conducted a network analysis using multivariate partial least squares (PLS ) activation analysis followed by covariance structural equation modeling (SEM) of positron emission tomography data obtained while healthy adults performed episodic and semantic verbal retrieval tasks. It is argued that if performance of episodic and semantic retrieval tasks are mediated by different memory systems, then there should differences in both regional activations and interregional correlations related to each type of retrieval task, respectively. The PLS results identified brain regions that were differentially active during episodic retrieval versus semantic retrieval. Regions that showed maximal differences in regional activity between episodic retrieval tasks were used to construct separate functional models for episodic and semantic retrieval. Omnibus tests of these functional models failed to find a significant difference across tasks for both functional models. The pattern of path coefficients for the episodic retrieval model were not different across tasks, nor were the path coefficients for the semantic retrieval model. The SEM results suggest that the same memory network/system was engaged across tasks, given the similarities in path coefficients. Therefore, activation differences between episodic and semantic retrieval may ref lect variation along a continuum of processing during task performance within the context of a single memory system.

Quality evaluation of value sets from cancer study common data elements using the UMLS semantic groups

PubMed Central

Solbrig, Harold R; Chute, Christopher G

2012-01-01

Objective The objective of this study is to develop an approach to evaluate the quality of terminological annotations on the value set (ie, enumerated value domain) components of the common data elements (CDEs) in the context of clinical research using both unified medical language system (UMLS) semantic types and groups. Materials and methods The CDEs of the National Cancer Institute (NCI) Cancer Data Standards Repository, the NCI Thesaurus (NCIt) concepts and the UMLS semantic network were integrated using a semantic web-based framework for a SPARQL-enabled evaluation. First, the set of CDE-permissible values with corresponding meanings in external controlled terminologies were isolated. The corresponding value meanings were then evaluated against their NCI- or UMLS-generated semantic network mapping to determine whether all of the meanings fell within the same semantic group. Results Of the enumerated CDEs in the Cancer Data Standards Repository, 3093 (26.2%) had elements drawn from more than one UMLS semantic group. A random sample (n=100) of this set of elements indicated that 17% of them were likely to have been misclassified. Discussion The use of existing semantic web tools can support a high-throughput mechanism for evaluating the quality of large CDE collections. This study demonstrates that the involvement of multiple semantic groups in an enumerated value domain of a CDE is an effective anchor to trigger an auditing point for quality evaluation activities. Conclusion This approach produces a useful quality assurance mechanism for a clinical study CDE repository. PMID:22511016

Acquisition of Multiple Questions in English, Russian, and Malayalam

ERIC Educational Resources Information Center

Grebenyova, Lydia

2011-01-01

This article presents the results of four studies exploring the acquisition of the language-specific syntactic and semantic properties of multiple interrogatives in English, Russian, and Malayalam, languages that behave differently with respect to the syntax and semantics of multiple interrogatives. A corpus analysis investigated the frequency of…

Concept Representation Reflects Multimodal Abstraction: A Framework for Embodied Semantics

PubMed Central

Fernandino, Leonardo; Binder, Jeffrey R.; Desai, Rutvik H.; Pendl, Suzanne L.; Humphries, Colin J.; Gross, William L.; Conant, Lisa L.; Seidenberg, Mark S.

2016-01-01

Recent research indicates that sensory and motor cortical areas play a significant role in the neural representation of concepts. However, little is known about the overall architecture of this representational system, including the role played by higher level areas that integrate different types of sensory and motor information. The present study addressed this issue by investigating the simultaneous contributions of multiple sensory-motor modalities to semantic word processing. With a multivariate fMRI design, we examined activation associated with 5 sensory-motor attributes—color, shape, visual motion, sound, and manipulation—for 900 words. Regions responsive to each attribute were identified using independent ratings of the attributes' relevance to the meaning of each word. The results indicate that these aspects of conceptual knowledge are encoded in multimodal and higher level unimodal areas involved in processing the corresponding types of information during perception and action, in agreement with embodied theories of semantics. They also reveal a hierarchical system of abstracted sensory-motor representations incorporating a major division between object interaction and object perception processes. PMID:25750259

Overcoming an obstacle in expanding a UMLS semantic type extent.

PubMed

Chen, Yan; Gu, Huanying; Perl, Yehoshua; Geller, James

2012-02-01

This paper strives to overcome a major problem encountered by a previous expansion methodology for discovering concepts highly likely to be missing a specific semantic type assignment in the UMLS. This methodology is the basis for an algorithm that presents the discovered concepts to a human auditor for review and possible correction. We analyzed the problem of the previous expansion methodology and discovered that it was due to an obstacle constituted by one or more concepts assigned the UMLS Semantic Network semantic type Classification. A new methodology was designed that bypasses such an obstacle without a combinatorial explosion in the number of concepts presented to the human auditor for review. The new expansion methodology with obstacle avoidance was tested with the semantic type Experimental Model of Disease and found over 500 concepts missed by the previous methodology that are in need of this semantic type assignment. Furthermore, other semantic types suffering from the same major problem were discovered, indicating that the methodology is of more general applicability. The algorithmic discovery of concepts that are likely missing a semantic type assignment is possible even in the face of obstacles, without an explosion in the number of processed concepts. Copyright © 2011 Elsevier Inc. All rights reserved.

Overcoming an Obstacle in Expanding a UMLS Semantic Type Extent

PubMed Central

Chen, Yan; Gu, Huanying; Perl, Yehoshua; Geller, James

2011-01-01

This paper strives to overcome a major problem encountered by a previous expansion methodology for discovering concepts highly likely to be missing a specific semantic type assignment in the UMLS. This methodology is the basis for an algorithm that presents the discovered concepts to a human auditor for review and possible correction. We analyzed the problem of the previous expansion methodology and discovered that it was due to an obstacle constituted by one or more concepts assigned the UMLS Semantic Network semantic type Classification. A new methodology was designed that bypasses such an obstacle without a combinatorial explosion in the number of concepts presented to the human auditor for review. The new expansion methodology with obstacle avoidance was tested with the semantic type Experimental Model of Disease and found over 500 concepts missed by the previous methodology that are in need of this semantic type assignment. Furthermore, other semantic types suffering from the same major problem were discovered, indicating that the methodology is of more general applicability. The algorithmic discovery of concepts that are likely missing a semantic type assignment is possible even in the face of obstacles, without an explosion in the number of processed concepts. PMID:21925287

Early Parallel Activation of Semantics and Phonology in Picture Naming: Evidence from a Multiple Linear Regression MEG Study

PubMed Central

Miozzo, Michele; Pulvermüller, Friedemann; Hauk, Olaf

2015-01-01

The time course of brain activation during word production has become an area of increasingly intense investigation in cognitive neuroscience. The predominant view has been that semantic and phonological processes are activated sequentially, at about 150 and 200–400 ms after picture onset. Although evidence from prior studies has been interpreted as supporting this view, these studies were arguably not ideally suited to detect early brain activation of semantic and phonological processes. We here used a multiple linear regression approach to magnetoencephalography (MEG) analysis of picture naming in order to investigate early effects of variables specifically related to visual, semantic, and phonological processing. This was combined with distributed minimum-norm source estimation and region-of-interest analysis. Brain activation associated with visual image complexity appeared in occipital cortex at about 100 ms after picture presentation onset. At about 150 ms, semantic variables became physiologically manifest in left frontotemporal regions. In the same latency range, we found an effect of phonological variables in the left middle temporal gyrus. Our results demonstrate that multiple linear regression analysis is sensitive to early effects of multiple psycholinguistic variables in picture naming. Crucially, our results suggest that access to phonological information might begin in parallel with semantic processing around 150 ms after picture onset. PMID:25005037

Quality Assurance of UMLS Semantic Type Assignments Using SNOMED CT Hierarchies.

PubMed

Gu, H; Chen, Y; He, Z; Halper, M; Chen, L

2016-01-01

The Unified Medical Language System (UMLS) is one of the largest biomedical terminological systems, with over 2.5 million concepts in its Metathesaurus repository. The UMLS's Semantic Network (SN) with its collection of 133 high-level semantic types serves as an abstraction layer on top of the Metathesaurus. In particular, the SN elaborates an aspect of the Metathesaurus's concepts via the assignment of one or more types to each concept. Due to the scope and complexity of the Metathesaurus, errors are all but inevitable in this semantic-type assignment process. To develop a semi-automated methodology to help assure the quality of semantic-type assignments within the UMLS. The methodology uses a cross-validation strategy involving SNOMED CT's hierarchies in combination with UMLS semantic types. Semantically uniform, disjoint concept groups are generated programmatically by partitioning the collection of all concepts in the same SNOMED CT hierarchy according to their respective semantic-type assignments in the UMLS. Domain experts are then called upon to review the concepts in any group having a small number of concepts. It is our hypothesis that a semantic-type assignment combination applicable only to a very small number of concepts in a SNOMED CT hierarchy is an indicator of potential problems. The methodology was applied to the UMLS 2013AA release along with the SNOMED CT from January 2013. An overall error rate of 33% was found for concepts proposed by the quality-assurance methodology. Supporting our hypothesis, that number was four times higher than the error rate found in control samples. The results show that the quality-assurance methodology can aid in effective and efficient identification of UMLS semantic-type assignment errors.

Distributed smoothed tree kernel for protein-protein interaction extraction from the biomedical literature

PubMed Central

Murugesan, Gurusamy; Abdulkadhar, Sabenabanu; Natarajan, Jeyakumar

2017-01-01

Automatic extraction of protein-protein interaction (PPI) pairs from biomedical literature is a widely examined task in biological information extraction. Currently, many kernel based approaches such as linear kernel, tree kernel, graph kernel and combination of multiple kernels has achieved promising results in PPI task. However, most of these kernel methods fail to capture the semantic relation information between two entities. In this paper, we present a special type of tree kernel for PPI extraction which exploits both syntactic (structural) and semantic vectors information known as Distributed Smoothed Tree kernel (DSTK). DSTK comprises of distributed trees with syntactic information along with distributional semantic vectors representing semantic information of the sentences or phrases. To generate robust machine learning model composition of feature based kernel and DSTK were combined using ensemble support vector machine (SVM). Five different corpora (AIMed, BioInfer, HPRD50, IEPA, and LLL) were used for evaluating the performance of our system. Experimental results show that our system achieves better f-score with five different corpora compared to other state-of-the-art systems. PMID:29099838

Distributed smoothed tree kernel for protein-protein interaction extraction from the biomedical literature.

PubMed

Murugesan, Gurusamy; Abdulkadhar, Sabenabanu; Natarajan, Jeyakumar

2017-01-01

Automatic extraction of protein-protein interaction (PPI) pairs from biomedical literature is a widely examined task in biological information extraction. Currently, many kernel based approaches such as linear kernel, tree kernel, graph kernel and combination of multiple kernels has achieved promising results in PPI task. However, most of these kernel methods fail to capture the semantic relation information between two entities. In this paper, we present a special type of tree kernel for PPI extraction which exploits both syntactic (structural) and semantic vectors information known as Distributed Smoothed Tree kernel (DSTK). DSTK comprises of distributed trees with syntactic information along with distributional semantic vectors representing semantic information of the sentences or phrases. To generate robust machine learning model composition of feature based kernel and DSTK were combined using ensemble support vector machine (SVM). Five different corpora (AIMed, BioInfer, HPRD50, IEPA, and LLL) were used for evaluating the performance of our system. Experimental results show that our system achieves better f-score with five different corpora compared to other state-of-the-art systems.

Semantic Asymmetries Are Modulated by Phonological Asymmetries: Evidence from the Disambiguation of Homophonic versus Heterophonic Homographs

ERIC Educational Resources Information Center

Peleg, Orna; Eviatar, Zohar

2009-01-01

The present study investigated cerebral asymmetries in accessing multiple meanings of two types of homographs: homophonic homographs (e.g., "bank") and heterophonic homographs (e.g., "tear"). Participants read homographs preceded by either a biasing or a non-biasing sentential context and performed a lexical decision on lateralized targets…

Verbal and non-verbal semantic impairment: From fluent primary progressive aphasia to semantic dementia

PubMed Central

Senaha, Mirna Lie Hosogi; Caramelli, Paulo; Porto, Claudia Sellitto; Nitrini, Ricardo

2007-01-01

Selective disturbances of semantic memory have attracted the interest of many investigators and the question of the existence of single or multiple semantic systems remains a very controversial theme in the literature. Objectives To discuss the question of multiple semantic systems based on a longitudinal study of a patient who presented semantic dementia from fluent primary progressive aphasia. Methods A 66 year-old woman with selective impairment of semantic memory was examined on two occasions, undergoing neuropsychological and language evaluations, the results of which were compared to those of three paired control individuals. Results In the first evaluation, physical examination was normal and the score on the Mini-Mental State Examination was 26. Language evaluation revealed fluent speech, anomia, disturbance in word comprehension, preservation of the syntactic and phonological aspects of the language, besides surface dyslexia and dysgraphia. Autobiographical and episodic memories were relatively preserved. In semantic memory tests, the following dissociation was found: disturbance of verbal semantic memory with preservation of non-verbal semantic memory. Magnetic resonance of the brain revealed marked atrophy of the left anterior temporal lobe. After 14 months, the difficulties in verbal semantic memory had become more severe and the semantic disturbance, limited initially to the linguistic sphere, had worsened to involve non-verbal domains. Conclusions Given the dissociation found in the first examination, we believe there is sufficient clinical evidence to refute the existence of a unitary semantic system. PMID:29213389

Evaluation of the Clinical LOINC (Logical Observation Identifiers, Names, and Codes) Semantic Structure as a Terminology Model for Standardized Assessment Measures

PubMed Central

Bakken, Suzanne; Cimino, James J.; Haskell, Robert; Kukafka, Rita; Matsumoto, Cindi; Chan, Garrett K.; Huff, Stanley M.

2000-01-01

Objective: The purpose of this study was to test the adequacy of the Clinical LOINC (Logical Observation Identifiers, Names, and Codes) semantic structure as a terminology model for standardized assessment measures. Methods: After extension of the definitions, 1,096 items from 35 standardized assessment instruments were dissected into the elements of the Clinical LOINC semantic structure. An additional coder dissected at least one randomly selected item from each instrument. When multiple scale types occurred in a single instrument, a second coder dissected one randomly selected item representative of each scale type. Results: The results support the adequacy of the Clinical LOINC semantic structure as a terminology model for standardized assessments. Using the revised definitions, the coders were able to dissect into the elements of Clinical LOINC all the standardized assessment items in the sample instruments. Percentage agreement for each element was as follows: component, 100 percent; property, 87.8 percent; timing, 82.9 percent; system/sample, 100 percent; scale, 92.6 percent; and method, 97.6 percent. Discussion: This evaluation was an initial step toward the representation of standardized assessment items in a manner that facilitates data sharing and re-use. Further clarification of the definitions, especially those related to time and property, is required to improve inter-rater reliability and to harmonize the representations with similar items already in LOINC. PMID:11062226

Generation of open biomedical datasets through ontology-driven transformation and integration processes.

PubMed

Carmen Legaz-García, María Del; Miñarro-Giménez, José Antonio; Menárguez-Tortosa, Marcos; Fernández-Breis, Jesualdo Tomás

2016-06-03

Biomedical research usually requires combining large volumes of data from multiple heterogeneous sources, which makes difficult the integrated exploitation of such data. The Semantic Web paradigm offers a natural technological space for data integration and exploitation by generating content readable by machines. Linked Open Data is a Semantic Web initiative that promotes the publication and sharing of data in machine readable semantic formats. We present an approach for the transformation and integration of heterogeneous biomedical data with the objective of generating open biomedical datasets in Semantic Web formats. The transformation of the data is based on the mappings between the entities of the data schema and the ontological infrastructure that provides the meaning to the content. Our approach permits different types of mappings and includes the possibility of defining complex transformation patterns. Once the mappings are defined, they can be automatically applied to datasets to generate logically consistent content and the mappings can be reused in further transformation processes. The results of our research are (1) a common transformation and integration process for heterogeneous biomedical data; (2) the application of Linked Open Data principles to generate interoperable, open, biomedical datasets; (3) a software tool, called SWIT, that implements the approach. In this paper we also describe how we have applied SWIT in different biomedical scenarios and some lessons learned. We have presented an approach that is able to generate open biomedical repositories in Semantic Web formats. SWIT is able to apply the Linked Open Data principles in the generation of the datasets, so allowing for linking their content to external repositories and creating linked open datasets. SWIT datasets may contain data from multiple sources and schemas, thus becoming integrated datasets.

Knowledge Representation Issues in Semantic Graphs for Relationship Detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barthelemy, M; Chow, E; Eliassi-Rad, T

2005-02-02

An important task for Homeland Security is the prediction of threat vulnerabilities, such as through the detection of relationships between seemingly disjoint entities. A structure used for this task is a ''semantic graph'', also known as a ''relational data graph'' or an ''attributed relational graph''. These graphs encode relationships as typed links between a pair of typed nodes. Indeed, semantic graphs are very similar to semantic networks used in AI. The node and link types are related through an ontology graph (also known as a schema). Furthermore, each node has a set of attributes associated with it (e.g., ''age'' maymore » be an attribute of a node of type ''person''). Unfortunately, the selection of types and attributes for both nodes and links depends on human expertise and is somewhat subjective and even arbitrary. This subjectiveness introduces biases into any algorithm that operates on semantic graphs. Here, we raise some knowledge representation issues for semantic graphs and provide some possible solutions using recently developed ideas in the field of complex networks. In particular, we use the concept of transitivity to evaluate the relevance of individual links in the semantic graph for detecting relationships. We also propose new statistical measures for semantic graphs and illustrate these semantic measures on graphs constructed from movies and terrorism data.« less

Multiple Meanings Are Not Necessarily a Disadvantage in Semantic Processing: Evidence from Homophone Effects in Semantic Categorisation

ERIC Educational Resources Information Center

Siakaluk, Paul D.; Pexman, Penny M.; Sears, Christopher R.; Owen, William J.

2007-01-01

The ambiguity disadvantage (slower processing of ambiguous words relative to unambiguous words) has been taken as evidence for a distributed semantic representational system like that embodied in parallel distributed processing (PDP) models. In the present study, we investigated whether semantic ambiguity slows meaning activation, as PDP models…

Extending Automatic Parallelization to Optimize High-Level Abstractions for Multicore

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liao, C; Quinlan, D J; Willcock, J J

2008-12-12

Automatic introduction of OpenMP for sequential applications has attracted significant attention recently because of the proliferation of multicore processors and the simplicity of using OpenMP to express parallelism for shared-memory systems. However, most previous research has only focused on C and Fortran applications operating on primitive data types. C++ applications using high-level abstractions, such as STL containers and complex user-defined types, are largely ignored due to the lack of research compilers that are readily able to recognize high-level object-oriented abstractions and leverage their associated semantics. In this paper, we automatically parallelize C++ applications using ROSE, a multiple-language source-to-source compiler infrastructuremore » which preserves the high-level abstractions and gives us access to their semantics. Several representative parallelization candidate kernels are used to explore semantic-aware parallelization strategies for high-level abstractions, combined with extended compiler analyses. Those kernels include an array-base computation loop, a loop with task-level parallelism, and a domain-specific tree traversal. Our work extends the applicability of automatic parallelization to modern applications using high-level abstractions and exposes more opportunities to take advantage of multicore processors.« less

Content Integration across Multiple Documents Reduces Memory for Sources

ERIC Educational Resources Information Center

Braasch, Jason L. G.; McCabe, Rebecca M.; Daniel, Frances

2016-01-01

The current experiments systematically examined semantic content integration as a mechanism for explaining source inattention and forgetting when reading-to-remember multiple texts. For all 3 experiments, degree of semantic overlap was manipulated amongst messages provided by various information sources. In Experiment 1, readers' source…

Facilitation and interference in naming: A consequence of the same learning process?

PubMed

Hughes, Julie W; Schnur, Tatiana T

2017-08-01

Our success with naming depends on what we have named previously, a phenomenon thought to reflect learning processes. Repeatedly producing the same name facilitates language production (i.e., repetition priming), whereas producing semantically related names hinders subsequent performance (i.e., semantic interference). Semantic interference is found whether naming categorically related items once (continuous naming) or multiple times (blocked cyclic naming). A computational model suggests that the same learning mechanism responsible for facilitation in repetition creates semantic interference in categorical naming (Oppenheim, Dell, & Schwartz, 2010). Accordingly, we tested the predictions that variability in semantic interference is correlated across categorical naming tasks and is caused by learning, as measured by two repetition priming tasks (picture-picture repetition priming, Exp. 1; definition-picture repetition priming, Exp. 2, e.g., Wheeldon & Monsell, 1992). In Experiment 1 (77 subjects) semantic interference and repetition priming effects were robust, but the results revealed no relationship between semantic interference effects across contexts. Critically, learning (picture-picture repetition priming) did not predict semantic interference effects in either task. We replicated these results in Experiment 2 (81 subjects), finding no relationship between semantic interference effects across tasks or between semantic interference effects and learning (definition-picture repetition priming). We conclude that the changes underlying facilitatory and interfering effects inherent to lexical access are the result of distinct learning processes where multiple mechanisms contribute to semantic interference in naming. Copyright © 2017 Elsevier B.V. All rights reserved.

Integrating semantic information into multiple kernels for protein-protein interaction extraction from biomedical literatures.

PubMed

Li, Lishuang; Zhang, Panpan; Zheng, Tianfu; Zhang, Hongying; Jiang, Zhenchao; Huang, Degen

2014-01-01

Protein-Protein Interaction (PPI) extraction is an important task in the biomedical information extraction. Presently, many machine learning methods for PPI extraction have achieved promising results. However, the performance is still not satisfactory. One reason is that the semantic resources were basically ignored. In this paper, we propose a multiple-kernel learning-based approach to extract PPIs, combining the feature-based kernel, tree kernel and semantic kernel. Particularly, we extend the shortest path-enclosed tree kernel (SPT) by a dynamic extended strategy to retrieve the richer syntactic information. Our semantic kernel calculates the protein-protein pair similarity and the context similarity based on two semantic resources: WordNet and Medical Subject Heading (MeSH). We evaluate our method with Support Vector Machine (SVM) and achieve an F-score of 69.40% and an AUC of 92.00%, which show that our method outperforms most of the state-of-the-art systems by integrating semantic information.

Architecture for WSN Nodes Integration in Context Aware Systems Using Semantic Messages

NASA Astrophysics Data System (ADS)

Larizgoitia, Iker; Muguira, Leire; Vazquez, Juan Ignacio

Wireless sensor networks (WSN) are becoming extremely popular in the development of context aware systems. Traditionally WSN have been focused on capturing data, which was later analyzed and interpreted in a server with more computational power. In this kind of scenario the problem of representing the sensor information needs to be addressed. Every node in the network might have different sensors attached; therefore their correspondent packet structures will be different. The server has to be aware of the meaning of every single structure and data in order to be able to interpret them. Multiple sensors, multiple nodes, multiple packet structures (and not following a standard format) is neither scalable nor interoperable. Context aware systems have solved this problem with the use of semantic technologies. They provide a common framework to achieve a standard definition of any domain. Nevertheless, these representations are computationally expensive, so a WSN cannot afford them. The work presented in this paper tries to bridge the gap between the sensor information and its semantic representation, by defining a simple architecture that enables the definition of this information natively in a semantic way, achieving the integration of the semantic information in the network packets. This will have several benefits, the most important being the possibility of promoting every WSN node to a real semantic information source.

Type-specific proactive interference in patients with semantic and phonological STM deficits.

PubMed

Harris, Lara; Olson, Andrew; Humphreys, Glyn

2014-01-01

Prior neuropsychological evidence suggests that semantic and phonological components of short-term memory (STM) are functionally and neurologically distinct. The current paper examines proactive interference (PI) from semantic and phonological information in two STM-impaired patients, DS (semantic STM deficit) and AK (phonological STM deficit). In Experiment 1 probe recognition tasks with open and closed sets of stimuli were used. Phonological PI was assessed using nonword items, and semantic and phonological PI was assessed using words. In Experiment 2 phonological and semantic PI was elicited by an item recognition probe test with stimuli that bore phonological and semantic relations to the probes. The data suggested heightened phonological PI for the semantic STM patient, and exaggerated effects of semantic PI in the phonological STM case. The findings are consistent with an account of extremely rapid decay of activated type-specific representations in cases of severely impaired phonological and semantic STM.

How Different Types of Conceptual Relations Modulate Brain Activation during Semantic Priming

ERIC Educational Resources Information Center

Sachs, Olga; Weis, Susanne; Zellagui, Nadia; Sass, Katharina; Huber, Walter; Zvyagintsev, Mikhail; Mathiak, Klaus; Kircher, Tilo

2011-01-01

Semantic priming, a well-established technique to study conceptual representation, has thus far produced variable fMRI results, both regarding the type of priming effects and their correlation with brain activation. The aims of the current study were (a) to investigate two types of semantic relations--categorical versus associative--under…

The association of personal semantic memory to identity representations: insight into higher-order networks of autobiographical contents.

PubMed

Grilli, Matthew D

2017-11-01

Identity representations are higher-order knowledge structures that organise autobiographical memories on the basis of personality and role-based themes of one's self-concept. In two experiments, the extent to which different types of personal semantic content are reflected in these higher-order networks of memories was investigated. Healthy, young adult participants generated identity representations that varied in remoteness of formation and verbally reflected on these themes in an open-ended narrative task. The narrative responses were scored for retrieval of episodic, experience-near personal semantic and experience-far (i.e., abstract) personal semantic contents. Results revealed that to reflect on remotely formed identity representations, experience-far personal semantic contents were retrieved more than experience-near personal semantic contents. In contrast, to reflect on recently formed identity representations, experience-near personal semantic contents were retrieved more than experience-far personal semantic contents. Although episodic memory contents were retrieved less than both personal semantic content types to reflect on remotely formed identity representations, this content type was retrieved at a similar frequency as experience-far personal semantic content to reflect on recently formed identity representations. These findings indicate that the association of personal semantic content to identity representations is robust and related to time since acquisition of these knowledge structures.

Cognitive modeling as an interface between brain and behavior: Measuring the semantic decline in mild cognitive impairment.

PubMed

Johns, Brendan T; Taler, Vanessa; Pisoni, David B; Farlow, Martin R; Hake, Ann Marie; Kareken, David A; Unverzagt, Frederick W; Jones, Michael N

2018-06-01

Mild cognitive impairment (MCI) is characterised by subjective and objective memory impairment in the absence of dementia. MCI is a strong predictor for the development of Alzheimer's disease, and may represent an early stage in the disease course in many cases. A standard task used in the diagnosis of MCI is verbal fluency, where participants produce as many items from a specific category (e.g., animals) as possible. Verbal fluency performance is typically analysed by counting the number of items produced. However, analysis of the semantic path of the items produced can provide valuable additional information. We introduce a cognitive model that uses multiple types of lexical information in conjunction with a standard memory search process. The model used a semantic representation derived from a standard semantic space model in conjunction with a memory searching mechanism derived from the Luce choice rule (Luce, 1977). The model was able to detect differences in the memory searching process of patients who were developing MCI, suggesting that the formal analysis of verbal fluency data is a promising avenue to examine the underlying changes occurring in the development of cognitive impairment. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Language-Mediated Visual Orienting Behavior in Low and High Literates

PubMed Central

Huettig, Falk; Singh, Niharika; Mishra, Ramesh Kumar

2011-01-01

The influence of formal literacy on spoken language-mediated visual orienting was investigated by using a simple look and listen task which resembles every day behavior. In Experiment 1, high and low literates listened to spoken sentences containing a target word (e.g., “magar,” crocodile) while at the same time looking at a visual display of four objects (a phonological competitor of the target word, e.g., “matar,” peas; a semantic competitor, e.g., “kachuwa,” turtle, and two unrelated distractors). In Experiment 2 the semantic competitor was replaced with another unrelated distractor. Both groups of participants shifted their eye gaze to the semantic competitors (Experiment 1). In both experiments high literates shifted their eye gaze toward phonological competitors as soon as phonological information became available and moved their eyes away as soon as the acoustic information mismatched. Low literates in contrast only used phonological information when semantic matches between spoken word and visual referent were not present (Experiment 2) but in contrast to high literates these phonologically mediated shifts in eye gaze were not closely time-locked to the speech input. These data provide further evidence that in high literates language-mediated shifts in overt attention are co-determined by the type of information in the visual environment, the timing of cascaded processing in the word- and object-recognition systems, and the temporal unfolding of the spoken language. Our findings indicate that low literates exhibit a similar cognitive behavior but instead of participating in a tug-of-war among multiple types of cognitive representations, word–object mapping is achieved primarily at the semantic level. If forced, for instance by a situation in which semantic matches are not present (Experiment 2), low literates may on occasion have to rely on phonological information but do so in a much less proficient manner than their highly literate counterparts. PMID:22059083

A remember-know analysis of the semantic serial position function.

PubMed

Kelley, Matthew R; Neath, Ian; Surprenant, Aimée M

2014-01-01

Did the serial position functions observed in certain semantic memory tasks (e.g., remembering the order of books or films) arise because they really tapped episodic memory? To address this issue, participants were asked to make "remember-know" judgments as they reconstructed the release order of the 7 Harry Potter books and 2 sets of movies. For both classes of stimuli, the "remember" and "know" serial position functions were indistinguishable, and all showed the characteristic U-shape with marked primacy and recency effects. These results are inconsistent with a multiple memory systems view, which predicts recency effects only for "remember" responses and no recency effects for "know" responses. However, the data were consistent with a general memory principle account: the relative distinctiveness principle. According to this view, performance on both episodic and semantic memory tasks arises from the same type of processing: Items that are more separated from their close neighbors in psychological space at the time of recall will be better remembered.

A Semantic Analysis Method for Scientific and Engineering Code

NASA Technical Reports Server (NTRS)

Stewart, Mark E. M.

1998-01-01

This paper develops a procedure to statically analyze aspects of the meaning or semantics of scientific and engineering code. The analysis involves adding semantic declarations to a user's code and parsing this semantic knowledge with the original code using multiple expert parsers. These semantic parsers are designed to recognize formulae in different disciplines including physical and mathematical formulae and geometrical position in a numerical scheme. In practice, a user would submit code with semantic declarations of primitive variables to the analysis procedure, and its semantic parsers would automatically recognize and document some static, semantic concepts and locate some program semantic errors. A prototype implementation of this analysis procedure is demonstrated. Further, the relationship between the fundamental algebraic manipulations of equations and the parsing of expressions is explained. This ability to locate some semantic errors and document semantic concepts in scientific and engineering code should reduce the time, risk, and effort of developing and using these codes.

Verbal Fluency, Semantics, Context and Symptom Complexes in Schizophrenia

ERIC Educational Resources Information Center

Vogel, Adam P.; Chenery, Helen J.; Dart, Catriona M.; Doan, Binh; Tan, Mildred; Copland, David A.

2009-01-01

Lexical-semantic access and retrieval was examined in 15 adults diagnosed with schizophrenia and matched controls. This study extends the literature through the inclusion of multiple examinations of lexical-semantic production within the same patient group and through correlating performance on these tasks with various positive and negative…

Effects of Morphology and Semantic Transparency on Typing Latencies in English Compound and Pseudocompound Words

ERIC Educational Resources Information Center

Gagné, Christina L.; Spalding, Thomas L.

2016-01-01

We used a typing task to measure the written production of compounds, pseudocompounds, and monomorphemic words on a letter-by-letter basis to determine whether written production (as measured by interletter typing speed) was affected by morphemic structure and semantic transparency of the constituents. Semantic transparency was analyzed using a…

An Experiment in Scientific Code Semantic Analysis

NASA Technical Reports Server (NTRS)

Stewart, Mark E. M.

1998-01-01

This paper concerns a procedure that analyzes aspects of the meaning or semantics of scientific and engineering code. This procedure involves taking a user's existing code, adding semantic declarations for some primitive variables, and parsing this annotated code using multiple, distributed expert parsers. These semantic parser are designed to recognize formulae in different disciplines including physical and mathematical formulae and geometrical position in a numerical scheme. The parsers will automatically recognize and document some static, semantic concepts and locate some program semantic errors. Results are shown for a subroutine test case and a collection of combustion code routines. This ability to locate some semantic errors and document semantic concepts in scientific and engineering code should reduce the time, risk, and effort of developing and using these codes.

Evaluation of a UMLS Auditing Process of Semantic Type Assignments

PubMed Central

Gu, Huanying; Hripcsak, George; Chen, Yan; Morrey, C. Paul; Elhanan, Gai; Cimino, James J.; Geller, James; Perl, Yehoshua

2007-01-01

The UMLS is a terminological system that integrates many source terminologies. Each concept in the UMLS is assigned one or more semantic types from the Semantic Network, an upper level ontology for biomedicine. Due to the complexity of the UMLS, errors exist in the semantic type assignments. Finding assignment errors may unearth modeling errors. Even with sophisticated tools, discovering assignment errors requires manual review. In this paper we describe the evaluation of an auditing project of UMLS semantic type assignments. We studied the performance of the auditors who reviewed potential errors. We found that four auditors, interacting according to a multi-step protocol, identified a high rate of errors (one or more errors in 81% of concepts studied) and that results were sufficiently reliable (0.67 to 0.70) for the two most common types of errors. However, reliability was low for each individual auditor, suggesting that review of potential errors is resource-intensive. PMID:18693845

Semantic-based surveillance video retrieval.

PubMed

Hu, Weiming; Xie, Dan; Fu, Zhouyu; Zeng, Wenrong; Maybank, Steve

2007-04-01

Visual surveillance produces large amounts of video data. Effective indexing and retrieval from surveillance video databases are very important. Although there are many ways to represent the content of video clips in current video retrieval algorithms, there still exists a semantic gap between users and retrieval systems. Visual surveillance systems supply a platform for investigating semantic-based video retrieval. In this paper, a semantic-based video retrieval framework for visual surveillance is proposed. A cluster-based tracking algorithm is developed to acquire motion trajectories. The trajectories are then clustered hierarchically using the spatial and temporal information, to learn activity models. A hierarchical structure of semantic indexing and retrieval of object activities, where each individual activity automatically inherits all the semantic descriptions of the activity model to which it belongs, is proposed for accessing video clips and individual objects at the semantic level. The proposed retrieval framework supports various queries including queries by keywords, multiple object queries, and queries by sketch. For multiple object queries, succession and simultaneity restrictions, together with depth and breadth first orders, are considered. For sketch-based queries, a method for matching trajectories drawn by users to spatial trajectories is proposed. The effectiveness and efficiency of our framework are tested in a crowded traffic scene.

Semantics-Based Interoperability Framework for the Geosciences

NASA Astrophysics Data System (ADS)

Sinha, A.; Malik, Z.; Raskin, R.; Barnes, C.; Fox, P.; McGuinness, D.; Lin, K.

2008-12-01

Interoperability between heterogeneous data, tools and services is required to transform data to knowledge. To meet geoscience-oriented societal challenges such as forcing of climate change induced by volcanic eruptions, we suggest the need to develop semantic interoperability for data, services, and processes. Because such scientific endeavors require integration of multiple data bases associated with global enterprises, implicit semantic-based integration is impossible. Instead, explicit semantics are needed to facilitate interoperability and integration. Although different types of integration models are available (syntactic or semantic) we suggest that semantic interoperability is likely to be the most successful pathway. Clearly, the geoscience community would benefit from utilization of existing XML-based data models, such as GeoSciML, WaterML, etc to rapidly advance semantic interoperability and integration. We recognize that such integration will require a "meanings-based search, reasoning and information brokering", which will be facilitated through inter-ontology relationships (ontologies defined for each discipline). We suggest that Markup languages (MLs) and ontologies can be seen as "data integration facilitators", working at different abstraction levels. Therefore, we propose to use an ontology-based data registration and discovery approach to compliment mark-up languages through semantic data enrichment. Ontologies allow the use of formal and descriptive logic statements which permits expressive query capabilities for data integration through reasoning. We have developed domain ontologies (EPONT) to capture the concept behind data. EPONT ontologies are associated with existing ontologies such as SUMO, DOLCE and SWEET. Although significant efforts have gone into developing data (object) ontologies, we advance the idea of developing semantic frameworks for additional ontologies that deal with processes and services. This evolutionary step will facilitate the integrative capabilities of scientists as we examine the relationships between data and external factors such as processes that may influence our understanding of "why" certain events happen. We emphasize the need to go from analysis of data to concepts related to scientific principles of thermodynamics, kinetics, heat flow, mass transfer, etc. Towards meeting these objectives, we report on a pair of related service engines: DIA (Discovery, integration and analysis), and SEDRE (Semantically-Enabled Data Registration Engine) that utilize ontologies for semantic interoperability and integration.

Actively learning human gaze shifting paths for semantics-aware photo cropping.

PubMed

Zhang, Luming; Gao, Yue; Ji, Rongrong; Xia, Yingjie; Dai, Qionghai; Li, Xuelong

2014-05-01

Photo cropping is a widely used tool in printing industry, photography, and cinematography. Conventional cropping models suffer from the following three challenges. First, the deemphasized role of semantic contents that are many times more important than low-level features in photo aesthetics. Second, the absence of a sequential ordering in the existing models. In contrast, humans look at semantically important regions sequentially when viewing a photo. Third, the difficulty of leveraging inputs from multiple users. Experience from multiple users is particularly critical in cropping as photo assessment is quite a subjective task. To address these challenges, this paper proposes semantics-aware photo cropping, which crops a photo by simulating the process of humans sequentially perceiving semantically important regions of a photo. We first project the local features (graphlets in this paper) onto the semantic space, which is constructed based on the category information of the training photos. An efficient learning algorithm is then derived to sequentially select semantically representative graphlets of a photo, and the selecting process can be interpreted by a path, which simulates humans actively perceiving semantics in a photo. Furthermore, we learn a prior distribution of such active graphlet paths from training photos that are marked as aesthetically pleasing by multiple users. The learned priors enforce the corresponding active graphlet path of a test photo to be maximally similar to those from the training photos. Experimental results show that: 1) the active graphlet path accurately predicts human gaze shifting, and thus is more indicative for photo aesthetics than conventional saliency maps and 2) the cropped photos produced by our approach outperform its competitors in both qualitative and quantitative comparisons.

A Methodology for the Development of RESTful Semantic Web Services for Gene Expression Analysis

PubMed Central

Guardia, Gabriela D. A.; Pires, Luís Ferreira; Vêncio, Ricardo Z. N.; Malmegrim, Kelen C. R.; de Farias, Cléver R. G.

2015-01-01

Gene expression studies are generally performed through multi-step analysis processes, which require the integrated use of a number of analysis tools. In order to facilitate tool/data integration, an increasing number of analysis tools have been developed as or adapted to semantic web services. In recent years, some approaches have been defined for the development and semantic annotation of web services created from legacy software tools, but these approaches still present many limitations. In addition, to the best of our knowledge, no suitable approach has been defined for the functional genomics domain. Therefore, this paper aims at defining an integrated methodology for the implementation of RESTful semantic web services created from gene expression analysis tools and the semantic annotation of such services. We have applied our methodology to the development of a number of services to support the analysis of different types of gene expression data, including microarray and RNASeq. All developed services are publicly available in the Gene Expression Analysis Services (GEAS) Repository at http://dcm.ffclrp.usp.br/lssb/geas. Additionally, we have used a number of the developed services to create different integrated analysis scenarios to reproduce parts of two gene expression studies documented in the literature. The first study involves the analysis of one-color microarray data obtained from multiple sclerosis patients and healthy donors. The second study comprises the analysis of RNA-Seq data obtained from melanoma cells to investigate the role of the remodeller BRG1 in the proliferation and morphology of these cells. Our methodology provides concrete guidelines and technical details in order to facilitate the systematic development of semantic web services. Moreover, it encourages the development and reuse of these services for the creation of semantically integrated solutions for gene expression analysis. PMID:26207740

A Methodology for the Development of RESTful Semantic Web Services for Gene Expression Analysis.

PubMed

Guardia, Gabriela D A; Pires, Luís Ferreira; Vêncio, Ricardo Z N; Malmegrim, Kelen C R; de Farias, Cléver R G

2015-01-01

Gene expression studies are generally performed through multi-step analysis processes, which require the integrated use of a number of analysis tools. In order to facilitate tool/data integration, an increasing number of analysis tools have been developed as or adapted to semantic web services. In recent years, some approaches have been defined for the development and semantic annotation of web services created from legacy software tools, but these approaches still present many limitations. In addition, to the best of our knowledge, no suitable approach has been defined for the functional genomics domain. Therefore, this paper aims at defining an integrated methodology for the implementation of RESTful semantic web services created from gene expression analysis tools and the semantic annotation of such services. We have applied our methodology to the development of a number of services to support the analysis of different types of gene expression data, including microarray and RNASeq. All developed services are publicly available in the Gene Expression Analysis Services (GEAS) Repository at http://dcm.ffclrp.usp.br/lssb/geas. Additionally, we have used a number of the developed services to create different integrated analysis scenarios to reproduce parts of two gene expression studies documented in the literature. The first study involves the analysis of one-color microarray data obtained from multiple sclerosis patients and healthy donors. The second study comprises the analysis of RNA-Seq data obtained from melanoma cells to investigate the role of the remodeller BRG1 in the proliferation and morphology of these cells. Our methodology provides concrete guidelines and technical details in order to facilitate the systematic development of semantic web services. Moreover, it encourages the development and reuse of these services for the creation of semantically integrated solutions for gene expression analysis.

Multiple priming of lexically ambiguous and unambiguous targets in the cerebral hemispheres: the coarse coding hypothesis revisited

PubMed Central

Kandhadai, Padmapriya; Federmeier, Kara D.

2009-01-01

The coarse coding hypothesis (Jung-Beeman 2005) postulates that the cerebral hemispheres differ in their breadth of semantic activation, with the left hemisphere (LH) activating a narrow, focused semantic field and the right (RH) weakly activating a broader semantic field. In support of coarse coding, studies (e.g., Faust and Lavidor 2003) investigating priming for multiple senses of a lexically ambiguous word have reported a RH benefit. However, studies of mediated priming (Livesay and Burgess 2003; Richards and Chiarello 1995) have failed to find a RH advantage for processing distantly-linked, unambiguous words. To address this debate, the present study made use of a multiple priming paradigm (Balota and Paul, 1996) in which two primes either converged onto the single meaning of an unambiguous, lexically-associated target (LION-STRIPES-TIGER) or diverged onto different meanings of an ambiguous target (KIDNEY-PIANO-ORGAN). In two experiments, participants either made lexical decisions to targets (Experiment 1) or made a semantic relatedness judgment between primes and targets (Experiment 2). In both tasks, for both ambiguous and unambiguous triplets we found equivalent priming strengths and patterns across the two visual fields, counter to the predictions of the coarse coding hypothesis. Priming patterns further suggested that both hemispheres made use of lexical level representations in the lexical decision task and semantic representations in the semantic judgment task. PMID:17459344

Neural Dynamics Associated with Semantic and Episodic Memory for Faces: Evidence from Multiple Frequency Bands

ERIC Educational Resources Information Center

Zion-Golumbic, Elana; Kutas, Marta; Bentin, Shlomo

2010-01-01

Prior semantic knowledge facilitates episodic recognition memory for faces. To examine the neural manifestation of the interplay between semantic and episodic memory, we investigated neuroelectric dynamics during the creation (study) and the retrieval (test) of episodic memories for famous and nonfamous faces. Episodic memory effects were evident…

Acceptability of Dative Argument Structure in Spanish: Assessing Semantic and Usage-Based Factors

ERIC Educational Resources Information Center

Reali, Florencia

2017-01-01

Multiple constraints, including semantic, lexical, and usage-based factors, have been shown to influence dative alternation across different languages. This work explores whether fine-grained statistics and semantic properties of the verb affect the acceptability of dative constructions in Spanish. First, a corpus analysis reveals that verbs of…

Development of a One-Stop Data Search and Discovery Engine using Ontologies for Semantic Mappings (HydroSeek)

NASA Astrophysics Data System (ADS)

Piasecki, M.; Beran, B.

2007-12-01

Search engines have changed the way we see the Internet. The ability to find the information by just typing in keywords was a big contribution to the overall web experience. While the conventional search engine methodology worked well for textual documents, locating scientific data remains a problem since they are stored in databases not readily accessible by search engine bots. Considering different temporal, spatial and thematic coverage of different databases, especially for interdisciplinary research it is typically necessary to work with multiple data sources. These sources can be federal agencies which generally offer national coverage or regional sources which cover a smaller area with higher detail. However for a given geographic area of interest there often exists more than one database with relevant data. Thus being able to query multiple databases simultaneously is a desirable feature that would be tremendously useful for scientists. Development of such a search engine requires dealing with various heterogeneity issues. In scientific databases, systems often impose controlled vocabularies which ensure that they are generally homogeneous within themselves but are semantically heterogeneous when moving between different databases. This defines the boundaries of possible semantic related problems making it easier to solve than with the conventional search engines that deal with free text. We have developed a search engine that enables querying multiple data sources simultaneously and returns data in a standardized output despite the aforementioned heterogeneity issues between the underlying systems. This application relies mainly on metadata catalogs or indexing databases, ontologies and webservices with virtual globe and AJAX technologies for the graphical user interface. Users can trigger a search of dozens of different parameters over hundreds of thousands of stations from multiple agencies by providing a keyword, a spatial extent, i.e. a bounding box, and a temporal bracket. As part of this development we have also added an environment that allows users to do some of the semantic tagging, i.e. the linkage of a variable name (which can be anything they desire) to defined concepts in the ontology structure which in turn provides the backbone of the search engine.

FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation.

PubMed

Bolleman, Jerven T; Mungall, Christopher J; Strozzi, Francesco; Baran, Joachim; Dumontier, Michel; Bonnal, Raoul J P; Buels, Robert; Hoehndorf, Robert; Fujisawa, Takatomo; Katayama, Toshiaki; Cock, Peter J A

2016-06-13

Nucleotide and protein sequence feature annotations are essential to understand biology on the genomic, transcriptomic, and proteomic level. Using Semantic Web technologies to query biological annotations, there was no standard that described this potentially complex location information as subject-predicate-object triples. We have developed an ontology, the Feature Annotation Location Description Ontology (FALDO), to describe the positions of annotated features on linear and circular sequences. FALDO can be used to describe nucleotide features in sequence records, protein annotations, and glycan binding sites, among other features in coordinate systems of the aforementioned "omics" areas. Using the same data format to represent sequence positions that are independent of file formats allows us to integrate sequence data from multiple sources and data types. The genome browser JBrowse is used to demonstrate accessing multiple SPARQL endpoints to display genomic feature annotations, as well as protein annotations from UniProt mapped to genomic locations. Our ontology allows users to uniformly describe - and potentially merge - sequence annotations from multiple sources. Data sources using FALDO can prospectively be retrieved using federalised SPARQL queries against public SPARQL endpoints and/or local private triple stores.

FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation

DOE PAGES

Bolleman, Jerven T.; Mungall, Christopher J.; Strozzi, Francesco; ...

2016-06-13

Nucleotide and protein sequence feature annotations are essential to understand biology on the genomic, transcriptomic, and proteomic level. Using Semantic Web technologies to query biological annotations, there was no standard that described this potentially complex location information as subject-predicate-object triples. In this paper, we have developed an ontology, the Feature Annotation Location Description Ontology (FALDO), to describe the positions of annotated features on linear and circular sequences. FALDO can be used to describe nucleotide features in sequence records, protein annotations, and glycan binding sites, among other features in coordinate systems of the aforementioned “omics” areas. Using the same data formatmore » to represent sequence positions that are independent of file formats allows us to integrate sequence data from multiple sources and data types. The genome browser JBrowse is used to demonstrate accessing multiple SPARQL endpoints to display genomic feature annotations, as well as protein annotations from UniProt mapped to genomic locations. Our ontology allows users to uniformly describe – and potentially merge – sequence annotations from multiple sources. Finally, data sources using FALDO can prospectively be retrieved using federalised SPARQL queries against public SPARQL endpoints and/or local private triple stores.« less

FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bolleman, Jerven T.; Mungall, Christopher J.; Strozzi, Francesco

Nucleotide and protein sequence feature annotations are essential to understand biology on the genomic, transcriptomic, and proteomic level. Using Semantic Web technologies to query biological annotations, there was no standard that described this potentially complex location information as subject-predicate-object triples. In this paper, we have developed an ontology, the Feature Annotation Location Description Ontology (FALDO), to describe the positions of annotated features on linear and circular sequences. FALDO can be used to describe nucleotide features in sequence records, protein annotations, and glycan binding sites, among other features in coordinate systems of the aforementioned “omics” areas. Using the same data formatmore » to represent sequence positions that are independent of file formats allows us to integrate sequence data from multiple sources and data types. The genome browser JBrowse is used to demonstrate accessing multiple SPARQL endpoints to display genomic feature annotations, as well as protein annotations from UniProt mapped to genomic locations. Our ontology allows users to uniformly describe – and potentially merge – sequence annotations from multiple sources. Finally, data sources using FALDO can prospectively be retrieved using federalised SPARQL queries against public SPARQL endpoints and/or local private triple stores.« less

Progress in The Semantic Analysis of Scientific Code

NASA Technical Reports Server (NTRS)

Stewart, Mark

2000-01-01

This paper concerns a procedure that analyzes aspects of the meaning or semantics of scientific and engineering code. This procedure involves taking a user's existing code, adding semantic declarations for some primitive variables, and parsing this annotated code using multiple, independent expert parsers. These semantic parsers encode domain knowledge and recognize formulae in different disciplines including physics, numerical methods, mathematics, and geometry. The parsers will automatically recognize and document some static, semantic concepts and help locate some program semantic errors. These techniques may apply to a wider range of scientific codes. If so, the techniques could reduce the time, risk, and effort required to develop and modify scientific codes.

Sculpting the UMLS Refined Semantic Network.

PubMed

He, Zhe; Morrey, C Paul; Perl, Yehoshua; Elhanan, Gai; Chen, Ling; Chen, Yan; Geller, James

2014-01-01

The Refined Semantic Network (RSN) for the UMLS was previously introduced to complement the UMLS Semantic Network (SN). The RSN partitions the UMLS Metathesaurus (META) into disjoint groups of concepts. Each such group is semantically uniform. However, the RSN was initially an order of magnitude larger than the SN, which is undesirable since to be useful, a semantic network should be compact. Most semantic types in the RSN represent combinations of semantic types in the UMLS SN. Such a "combination semantic type" is called Intersection Semantic Type (IST). Many ISTs are assigned to very few concepts. Moreover, when reviewing those concepts, many semantic type assignment inconsistencies were found. After correcting those inconsistencies many ISTs, among them some that contradicted UMLS rules, disappeared, which made the RSN smaller. The authors performed a longitudinal study with the goal of reducing the size of the RSN to become compact. This goal was achieved by correcting inconsistencies and errors in the IST assignments in the UMLS, which additionally helped identify and correct ambiguities, inconsistencies, and errors in source terminologies widely used in the realm of public health. In this paper, we discuss the process and steps employed in this longitudinal study and the intermediate results for different stages. The sculpting process includes removing redundant semantic type assignments, expanding semantic type assignments, and removing illegitimate ISTs by auditing ISTs of small extents. However, the emphasis of this paper is not on the auditing methodologies employed during the process, since they were introduced in earlier publications, but on the strategy of employing them in order to transform the RSN into a compact network. For this paper we also performed a comprehensive audit of 168 "small ISTs" in the 2013AA version of the UMLS to finalize the longitudinal study. Over the years it was found that the editors of the UMLS introduced some new inconsistencies that resulted in the reintroduction of unwarranted ISTs that had already been eliminated as a result of their previous corrections. Because of that, the transformation of the RSN into a compact network covering all necessary categories for the UMLS was slowed down. The corrections suggested by an audit of the 2013AA version of the UMLS achieve a compact RSN of equal magnitude as the UMLS SN. The number of ISTs has been reduced to 336. We also demonstrate how auditing the semantic type assignments of UMLS concepts can expose other modeling errors in the UMLS source terminologies, e.g., SNOMED CT, LOINC, and RxNORM that are important for health informatics. Such errors would otherwise stay hidden. It is hoped that the UMLS curators will implement all required corrections and use the RSN along with the SN when maintaining and extending the UMLS. When used correctly, the RSN will support the prevention of the accidental introduction of inconsistent semantic type assignments into the UMLS. Furthermore, this way the RSN will support the exposure of other hidden errors and inconsistencies in health informatics terminologies, which are sources of the UMLS. Notably, the development of the RSN materializes the deeper, more refined Semantic Network for the UMLS that its designers envisioned originally but had not implemented.

AlzPharm: integration of neurodegeneration data using RDF.

PubMed

Lam, Hugo Y K; Marenco, Luis; Clark, Tim; Gao, Yong; Kinoshita, June; Shepherd, Gordon; Miller, Perry; Wu, Elizabeth; Wong, Gwendolyn T; Liu, Nian; Crasto, Chiquito; Morse, Thomas; Stephens, Susie; Cheung, Kei-Hoi

2007-05-09

Neuroscientists often need to access a wide range of data sets distributed over the Internet. These data sets, however, are typically neither integrated nor interoperable, resulting in a barrier to answering complex neuroscience research questions. Domain ontologies can enable the querying heterogeneous data sets, but they are not sufficient for neuroscience since the data of interest commonly span multiple research domains. To this end, e-Neuroscience seeks to provide an integrated platform for neuroscientists to discover new knowledge through seamless integration of the very diverse types of neuroscience data. Here we present a Semantic Web approach to building this e-Neuroscience framework by using the Resource Description Framework (RDF) and its vocabulary description language, RDF Schema (RDFS), as a standard data model to facilitate both representation and integration of the data. We have constructed a pilot ontology for BrainPharm (a subset of SenseLab) using RDFS and then converted a subset of the BrainPharm data into RDF according to the ontological structure. We have also integrated the converted BrainPharm data with existing RDF hypothesis and publication data from a pilot version of SWAN (Semantic Web Applications in Neuromedicine). Our implementation uses the RDF Data Model in Oracle Database 10g release 2 for data integration, query, and inference, while our Web interface allows users to query the data and retrieve the results in a convenient fashion. Accessing and integrating biomedical data which cuts across multiple disciplines will be increasingly indispensable and beneficial to neuroscience researchers. The Semantic Web approach we undertook has demonstrated a promising way to semantically integrate data sets created independently. It also shows how advanced queries and inferences can be performed over the integrated data, which are hard to achieve using traditional data integration approaches. Our pilot results suggest that our Semantic Web approach is suitable for realizing e-Neuroscience and generic enough to be applied in other biomedical fields.

AlzPharm: integration of neurodegeneration data using RDF

PubMed Central

Lam, Hugo YK; Marenco, Luis; Clark, Tim; Gao, Yong; Kinoshita, June; Shepherd, Gordon; Miller, Perry; Wu, Elizabeth; Wong, Gwendolyn T; Liu, Nian; Crasto, Chiquito; Morse, Thomas; Stephens, Susie; Cheung, Kei-Hoi

2007-01-01

Background Neuroscientists often need to access a wide range of data sets distributed over the Internet. These data sets, however, are typically neither integrated nor interoperable, resulting in a barrier to answering complex neuroscience research questions. Domain ontologies can enable the querying heterogeneous data sets, but they are not sufficient for neuroscience since the data of interest commonly span multiple research domains. To this end, e-Neuroscience seeks to provide an integrated platform for neuroscientists to discover new knowledge through seamless integration of the very diverse types of neuroscience data. Here we present a Semantic Web approach to building this e-Neuroscience framework by using the Resource Description Framework (RDF) and its vocabulary description language, RDF Schema (RDFS), as a standard data model to facilitate both representation and integration of the data. Results We have constructed a pilot ontology for BrainPharm (a subset of SenseLab) using RDFS and then converted a subset of the BrainPharm data into RDF according to the ontological structure. We have also integrated the converted BrainPharm data with existing RDF hypothesis and publication data from a pilot version of SWAN (Semantic Web Applications in Neuromedicine). Our implementation uses the RDF Data Model in Oracle Database 10g release 2 for data integration, query, and inference, while our Web interface allows users to query the data and retrieve the results in a convenient fashion. Conclusion Accessing and integrating biomedical data which cuts across multiple disciplines will be increasingly indispensable and beneficial to neuroscience researchers. The Semantic Web approach we undertook has demonstrated a promising way to semantically integrate data sets created independently. It also shows how advanced queries and inferences can be performed over the integrated data, which are hard to achieve using traditional data integration approaches. Our pilot results suggest that our Semantic Web approach is suitable for realizing e-Neuroscience and generic enough to be applied in other biomedical fields. PMID:17493287

Semantic Priming Effects in Normal versus Poor Readers

ERIC Educational Resources Information Center

Assink, Egbert M. H.; Van Bergen, Floor; Van Teeseling, Heleen; Knuijt, Paul P. N. A.

2004-01-01

The authors studied sensitivity to semantic priming, as distinct from semantic judgment, in poor readers. Association strength (high vs. low semantic association) was manipulated factorially with semantic association type (categoric vs. thematic association). Participants were 11-year-old poor readers (n = 15) who were matched with a group of…

MediaNet: a multimedia information network for knowledge representation

NASA Astrophysics Data System (ADS)

Benitez, Ana B.; Smith, John R.; Chang, Shih-Fu

2000-10-01

In this paper, we present MediaNet, which is a knowledge representation framework that uses multimedia content for representing semantic and perceptual information. The main components of MediaNet include conceptual entities, which correspond to real world objects, and relationships among concepts. MediaNet allows the concepts and relationships to be defined or exemplified by multimedia content such as images, video, audio, graphics, and text. MediaNet models the traditional relationship types such as generalization and aggregation but adds additional functionality by modeling perceptual relationships based on feature similarity. For example, MediaNet allows a concept such as car to be defined as a type of a transportation vehicle, but which is further defined and illustrated through example images, videos and sounds of cars. In constructing the MediaNet framework, we have built on the basic principles of semiotics and semantic networks in addition to utilizing the audio-visual content description framework being developed as part of the MPEG-7 multimedia content description standard. By integrating both conceptual and perceptual representations of knowledge, MediaNet has potential to impact a broad range of applications that deal with multimedia content at the semantic and perceptual levels. In particular, we have found that MediaNet can improve the performance of multimedia retrieval applications by using query expansion, refinement and translation across multiple content modalities. In this paper, we report on experiments that use MediaNet in searching for images. We construct the MediaNet knowledge base using both WordNet and an image network built from multiple example images and extracted color and texture descriptors. Initial experimental results demonstrate improved retrieval effectiveness using MediaNet in a content-based retrieval system.

Category specific dysnomia after thalamic infarction: a case-control study.

PubMed

Levin, Netta; Ben-Hur, Tamir; Biran, Iftah; Wertman, Eli

2005-01-01

Category specific naming impairment was described mainly after cortical lesions. It is thought to result from a lesion in a specific network, reflecting the organization of our semantic knowledge. The deficit usually involves multiple semantic categories whose profile of naming deficit generally obeys the animate/inanimate dichotomy. Thalamic lesions cause general semantic naming deficit, and only rarely a category specific semantic deficit for very limited and highly specific categories. We performed a case-control study on a 56-year-old right-handed man who presented with language impairment following a left anterior thalamic infarction. His naming ability and semantic knowledge were evaluated in the visual, tactile and auditory modalities for stimuli from 11 different categories, and compared to that of five controls. In naming to visual stimuli the patient performed poorly (error rate>50%) in four categories: vegetables, toys, animals and body parts (average 70.31+/-15%). In each category there was a different dominating error type. He performed better in the other seven categories (tools, clothes, transportation, fruits, electric, furniture, kitchen utensils), averaging 14.28+/-9% errors. Further analysis revealed a dichotomy between naming in animate and inanimate categories in the visual and tactile modalities but not in response to auditory stimuli. Thus, a unique category specific profile of response and naming errors to visual and tactile, but not auditory stimuli was found after a left anterior thalamic infarction. This might reflect the role of the thalamus not only as a relay station but further as a central integrator of different stages of perceptual and semantic processing.

Semantic memory retrieval circuit: role of pre-SMA, caudate, and thalamus.

PubMed

Hart, John; Maguire, Mandy J; Motes, Michael; Mudar, Raksha Anand; Chiang, Hsueh-Sheng; Womack, Kyle B; Kraut, Michael A

2013-07-01

We propose that pre-supplementary motor area (pre-SMA)-thalamic interactions govern processes fundamental to semantic retrieval of an integrated object memory. At the onset of semantic retrieval, pre-SMA initiates electrical interactions between multiple cortical regions associated with semantic memory subsystems encodings as indexed by an increase in theta-band EEG power. This starts between 100-150 ms after stimulus presentation and is sustained throughout the task. We posit that this activity represents initiation of the object memory search, which continues in searching for an object memory. When the correct memory is retrieved, there is a high beta-band EEG power increase, which reflects communication between pre-SMA and thalamus, designates the end of the search process and resultant in object retrieval from multiple semantic memory subsystems. This high beta signal is also detected in cortical regions. This circuit is modulated by the caudate nuclei to facilitate correct and suppress incorrect target memories. Copyright © 2012 Elsevier Inc. All rights reserved.

A Collection of Features for Semantic Graphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eliassi-Rad, T; Fodor, I K; Gallagher, B

2007-05-02

Semantic graphs are commonly used to represent data from one or more data sources. Such graphs extend traditional graphs by imposing types on both nodes and links. This type information defines permissible links among specified nodes and can be represented as a graph commonly referred to as an ontology or schema graph. Figure 1 depicts an ontology graph for data from National Association of Securities Dealers. Each node type and link type may also have a list of attributes. To capture the increased complexity of semantic graphs, concepts derived for standard graphs have to be extended. This document explains brieflymore » features commonly used to characterize graphs, and their extensions to semantic graphs. This document is divided into two sections. Section 2 contains the feature descriptions for static graphs. Section 3 extends the features for semantic graphs that vary over time.« less

Semantic knowledge fractionations: verbal propositions vs. perceptual input? Evidence from a child with Klinefelter syndrome.

PubMed

Robinson, Sally J; Temple, Christine M

2013-04-01

This paper addresses the relative independence of different types of lexical- and factually-based semantic knowledge in JM, a 9-year-old boy with Klinefelter syndrome (KS). JM was matched to typically developing (TD) controls on the basis of chronological age. Lexical-semantic knowledge was investigated for common noun (CN) and mathematical vocabulary items (MV). Factually-based semantic knowledge was investigated for general and number facts. For CN items, JM's lexical stores were of a normal size but the volume of correct 'sensory feature' semantic knowledge he generated within verbal item descriptions was significantly reduced. He was also significantly impaired at naming item descriptions and pictures, particularly for fruit and vegetables. There was also weak object decision for fruit and vegetables. In contrast, for MV items, JM's lexical stores were elevated, with no significant difference in the amount and type of correct semantic knowledge generated within verbal item descriptions and normal naming. JM's fact retrieval accuracy was normal for all types of factual knowledge. JM's performance indicated a dissociation between the representation of CN and MV vocabulary items during development. JM's preserved semantic knowledge of facts in the face of impaired semantic knowledge of vocabulary also suggests that factually-based semantic knowledge representation is not dependent on normal lexical-semantic knowledge during development. These findings are discussed in relation to the emergence of distinct semantic knowledge representations during development, due to differing degrees of dependency upon the acquisition and representation of semantic knowledge from verbal propositions and perceptual input.

When Meaning Is Not Enough: Distributional and Semantic Cues to Word Categorization in Child Directed Speech.

PubMed

Feijoo, Sara; Muñoz, Carmen; Amadó, Anna; Serrat, Elisabet

2017-01-01

One of the most important tasks in first language development is assigning words to their grammatical category. The Semantic Bootstrapping Hypothesis postulates that, in order to accomplish this task, children are guided by a neat correspondence between semantic and grammatical categories, since nouns typically refer to objects and verbs to actions. It is this correspondence that guides children's initial word categorization. Other approaches, on the other hand, suggest that children might make use of distributional cues and word contexts to accomplish the word categorization task. According to such approaches, the Semantic Bootstrapping assumption offers an important limitation, as it might not be true that all the nouns that children hear refer to specific objects or people. In order to explore that, we carried out two studies based on analyses of children's linguistic input. We analyzed child-directed speech addressed to four children under the age of 2;6, taken from the CHILDES database. The corpora were selected from the Manchester corpus. The corpora from the four selected children contained a total of 10,681 word types and 364,196 word tokens. In our first study, discriminant analyses were performed using semantic cues alone. The results show that many of the nouns found in parents' speech do not relate to specific objects and that semantic information alone might not be sufficient for successful word categorization. Given that there must be an additional source of information which, alongside with semantics, might assist young learners in word categorization, our second study explores the availability of both distributional and semantic cues in child-directed speech. Our results confirm that this combination might yield better results for word categorization. These results are in line with theories that suggest the need for an integration of multiple cues from different sources in language development.

Integrating Semantic Information in Metadata Descriptions for a Geoscience-wide Resource Inventory.

NASA Astrophysics Data System (ADS)

Zaslavsky, I.; Richard, S. M.; Gupta, A.; Valentine, D.; Whitenack, T.; Ozyurt, I. B.; Grethe, J. S.; Schachne, A.

2016-12-01

Integrating semantic information into legacy metadata catalogs is a challenging issue and so far has been mostly done on a limited scale. We present experience of CINERGI (Community Inventory of Earthcube Resources for Geoscience Interoperability), an NSF Earthcube Building Block project, in creating a large cross-disciplinary catalog of geoscience information resources to enable cross-domain discovery. The project developed a pipeline for automatically augmenting resource metadata, in particular generating keywords that describe metadata documents harvested from multiple geoscience information repositories or contributed by geoscientists through various channels including surveys and domain resource inventories. The pipeline examines available metadata descriptions using text parsing, vocabulary management and semantic annotation and graph navigation services of GeoSciGraph. GeoSciGraph, in turn, relies on a large cross-domain ontology of geoscience terms, which bridges several independently developed ontologies or taxonomies including SWEET, ENVO, YAGO, GeoSciML, GCMD, SWO, and CHEBI. The ontology content enables automatic extraction of keywords reflecting science domains, equipment used, geospatial features, measured properties, methods, processes, etc. We specifically focus on issues of cross-domain geoscience ontology creation, resolving several types of semantic conflicts among component ontologies or vocabularies, and constructing and managing facets for improved data discovery and navigation. The ontology and keyword generation rules are iteratively improved as pipeline results are presented to data managers for selective manual curation via a CINERGI Annotator user interface. We present lessons learned from applying CINERGI metadata augmentation pipeline to a number of federal agency and academic data registries, in the context of several use cases that require data discovery and integration across multiple earth science data catalogs of varying quality and completeness. The inventory is accessible at http://cinergi.sdsc.edu, and the CINERGI project web page is http://earthcube.org/group/cinergi

From Data to Semantic Information

NASA Astrophysics Data System (ADS)

Floridi, Luciano

2003-06-01

There is no consensus yet on the definition of semantic information. This paper contributes to the current debate by criticising and revising the Standard Definition of semantic Information (SDI) as meaningful data, in favour of the Dretske-Grice approach: meaningful and well-formed data constitute semantic information only if they also qualify as contingently truthful. After a brief introduction, SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information. SDI is incorrect because truth-values do not supervene on semantic information, and misinformation (that is, false semantic information) is not a type of semantic information, but pseudo-information, that is not semantic information at all. This is shown by arguing that none of the reasons for interpreting misinformation as a type of semantic information is convincing, whilst there are compelling reasons to treat it as pseudo-information. As a consequence, SDI is revised to include a necessary truth-condition. The last section summarises the main results of the paper and indicates the important implications of the revised definition for the analysis of the deflationary theories of truth, the standard definition of knowledge and the classic, quantitative theory of semantic information.

The Role of Semantics in Translation Recognition: Effects of Number of Translations, Dominance of Translations and Semantic Relatedness of Multiple Translations

ERIC Educational Resources Information Center

Laxen, Jannika; Lavaur, Jean-Marc

2010-01-01

This study aims to examine the influence of multiple translations of a word on bilingual processing in three translation recognition experiments during which French-English bilinguals had to decide whether two words were translations of each other or not. In the first experiment, words with only one translation were recognized as translations…

The Fluctuating Development of Cross-Linguistic Semantic Awareness: A Longitudinal Multiple-Case Study

ERIC Educational Resources Information Center

Zheng, Yongyan

2014-01-01

Second language (L2) learners' awareness of first language-second language (L1-L2) semantic differences plays a critical role in L2 vocabulary learning. This study investigates the long-term development of eight university-level Chinese English as a foreign language learners' cross-linguistic semantic awareness over the course of 10 months. A…

Linked Registries: Connecting Rare Diseases Patient Registries through a Semantic Web Layer

PubMed Central

González-Castro, Lorena; Carta, Claudio; van der Horst, Eelke; Lopes, Pedro; Kaliyaperumal, Rajaram; Thompson, Mark; Thompson, Rachel; Queralt-Rosinach, Núria; Lopez, Estrella; Wood, Libby; Robertson, Agata; Lamanna, Claudia; Gilling, Mette; Orth, Michael; Merino-Martinez, Roxana; Taruscio, Domenica; Lochmüller, Hanns

2017-01-01

Patient registries are an essential tool to increase current knowledge regarding rare diseases. Understanding these data is a vital step to improve patient treatments and to create the most adequate tools for personalized medicine. However, the growing number of disease-specific patient registries brings also new technical challenges. Usually, these systems are developed as closed data silos, with independent formats and models, lacking comprehensive mechanisms to enable data sharing. To tackle these challenges, we developed a Semantic Web based solution that allows connecting distributed and heterogeneous registries, enabling the federation of knowledge between multiple independent environments. This semantic layer creates a holistic view over a set of anonymised registries, supporting semantic data representation, integrated access, and querying. The implemented system gave us the opportunity to answer challenging questions across disperse rare disease patient registries. The interconnection between those registries using Semantic Web technologies benefits our final solution in a way that we can query single or multiple instances according to our needs. The outcome is a unique semantic layer, connecting miscellaneous registries and delivering a lightweight holistic perspective over the wealth of knowledge stemming from linked rare disease patient registries. PMID:29214177

Linked Registries: Connecting Rare Diseases Patient Registries through a Semantic Web Layer.

PubMed

Sernadela, Pedro; González-Castro, Lorena; Carta, Claudio; van der Horst, Eelke; Lopes, Pedro; Kaliyaperumal, Rajaram; Thompson, Mark; Thompson, Rachel; Queralt-Rosinach, Núria; Lopez, Estrella; Wood, Libby; Robertson, Agata; Lamanna, Claudia; Gilling, Mette; Orth, Michael; Merino-Martinez, Roxana; Posada, Manuel; Taruscio, Domenica; Lochmüller, Hanns; Robinson, Peter; Roos, Marco; Oliveira, José Luís

2017-01-01

Patient registries are an essential tool to increase current knowledge regarding rare diseases. Understanding these data is a vital step to improve patient treatments and to create the most adequate tools for personalized medicine. However, the growing number of disease-specific patient registries brings also new technical challenges. Usually, these systems are developed as closed data silos, with independent formats and models, lacking comprehensive mechanisms to enable data sharing. To tackle these challenges, we developed a Semantic Web based solution that allows connecting distributed and heterogeneous registries, enabling the federation of knowledge between multiple independent environments. This semantic layer creates a holistic view over a set of anonymised registries, supporting semantic data representation, integrated access, and querying. The implemented system gave us the opportunity to answer challenging questions across disperse rare disease patient registries. The interconnection between those registries using Semantic Web technologies benefits our final solution in a way that we can query single or multiple instances according to our needs. The outcome is a unique semantic layer, connecting miscellaneous registries and delivering a lightweight holistic perspective over the wealth of knowledge stemming from linked rare disease patient registries.

Semantic layers for illustrative volume rendering.

PubMed

Rautek, Peter; Bruckner, Stefan; Gröller, Eduard

2007-01-01

Direct volume rendering techniques map volumetric attributes (e.g., density, gradient magnitude, etc.) to visual styles. Commonly this mapping is specified by a transfer function. The specification of transfer functions is a complex task and requires expert knowledge about the underlying rendering technique. In the case of multiple volumetric attributes and multiple visual styles the specification of the multi-dimensional transfer function becomes more challenging and non-intuitive. We present a novel methodology for the specification of a mapping from several volumetric attributes to multiple illustrative visual styles. We introduce semantic layers that allow a domain expert to specify the mapping in the natural language of the domain. A semantic layer defines the mapping of volumetric attributes to one visual style. Volumetric attributes and visual styles are represented as fuzzy sets. The mapping is specified by rules that are evaluated with fuzzy logic arithmetics. The user specifies the fuzzy sets and the rules without special knowledge about the underlying rendering technique. Semantic layers allow for a linguistic specification of the mapping from attributes to visual styles replacing the traditional transfer function specification.

Tracking real-time neural activation of conceptual knowledge using single-trial event-related potentials.

PubMed

Amsel, Ben D

2011-04-01

Empirically derived semantic feature norms categorized into different types of knowledge (e.g., visual, functional, auditory) can be summed to create number-of-feature counts per knowledge type. Initial evidence suggests several such knowledge types may be recruited during language comprehension. The present study provides a more detailed understanding of the timecourse and intensity of influence of several such knowledge types on real-time neural activity. A linear mixed-effects model was applied to single trial event-related potentials for 207 visually presented concrete words measured on total number of features (semantic richness), imageability, and number of visual motion, color, visual form, smell, taste, sound, and function features. Significant influences of multiple feature types occurred before 200ms, suggesting parallel neural computation of word form and conceptual knowledge during language comprehension. Function and visual motion features most prominently influenced neural activity, underscoring the importance of action-related knowledge in computing word meaning. The dynamic time courses and topographies of these effects are most consistent with a flexible conceptual system wherein temporally dynamic recruitment of representations in modal and supramodal cortex are a crucial element of the constellation of processes constituting word meaning computation in the brain. Copyright © 2011 Elsevier Ltd. All rights reserved.

EEG source reconstruction evidence for the noun-verb neural dissociation along semantic dimensions.

PubMed

Zhao, Bin; Dang, Jianwu; Zhang, Gaoyan

2017-09-17

One of the long-standing issues in neurolinguistic research is about the neural basis of word representation, concerning whether grammatical classification or semantic difference causes the neural dissociation of brain activity patterns when processing different word categories, especially nouns and verbs. To disentangle this puzzle, four orthogonalized word categories in Chinese: unambiguous nouns (UN), unambiguous verbs (UV), ambiguous words with noun-biased semantics (AN), and ambiguous words with verb-biased semantics (AV) were adopted in an auditory task for recording electroencephalographic (EEG) signals from 128 electrodes on the scalps of twenty-two subjects. With the advanced current density reconstruction (CDR) algorithm and the constraint of standardized low-resolution electromagnetic tomography, the spatiotemporal brain dynamics of word processing were explored with the results that in multiple time periods including P1 (60-90ms), N1 (100-140ms), P200 (150-250ms) and N400 (350-450ms), noun-verb dissociation over the parietal-occipital and frontal-central cortices appeared not only between the UN-UV grammatical classes but also between the grammatically identical but semantically different AN-AV pairs. The apparent semantic dissociation within one grammatical class strongly suggests that the semantic difference rather than grammatical classification could be interpreted as the origin of the noun-verb neural dissociation. Our results also revealed that semantic dissociation occurs from an early stage and repeats in multiple phases, thus supporting a functionally hierarchical word processing mechanism. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

Syntax does not necessarily precede semantics in sentence processing: ERP evidence from Chinese.

PubMed

Zhang, Yaxu; Li, Ping; Piao, Qiuhong; Liu, Youyi; Huang, Yongjing; Shu, Hua

2013-07-01

Two event-related potential experiments were conducted to examine whether the processing of syntactic category or syntactic subcategorization frame always needs to temporally precede semantic processing during the reading of Chinese sentences of object-subject-verb construction. The sentences contained (a) no anomalies, (b) semantic only anomalies, (c) syntactic category plus semantic anomalies, or (d) transitivity plus semantic anomalies. In both experiments, all three types of anomalies elicited a broad negativity between 300 and 500 ms. This negativity included an N400 effect, given its distribution. Moreover, syntactic category plus semantic anomalies elicited a P600 response, whereas the other two types of anomalies did not. The finding of N400 effects suggests that semantic integration can be attempted even when the processing of syntactic category or syntactic subcategorization frame is unsuccessful. Thus, syntactic processing is not a necessary prerequisite for the initiation of semantic integration in Chinese. Copyright © 2013 Elsevier Inc. All rights reserved.

Sculpting the UMLS Refined Semantic Network

PubMed Central

Morrey, C. Paul; Perl, Yehoshua; Elhanan, Gai; Chen, Ling; Chen, Yan; Geller, James

2014-01-01

Background The Refined Semantic Network (RSN) for the UMLS was previously introduced to complement the UMLS Semantic Network (SN). The RSN partitions the UMLS Metathesaurus (META) into disjoint groups of concepts. Each such group is semantically uniform. However, the RSN was initially an order of magnitude larger than the SN, which is undesirable since to be useful, a semantic network should be compact. Most semantic types in the RSN represent combinations of semantic types in the UMLS SN. Such a “combination semantic type” is called Intersection Semantic Type (IST). Many ISTs are assigned to very few concepts. Moreover, when reviewing those concepts, many semantic type assignment inconsistencies were found. After correcting those inconsistencies many ISTs, among them some that contradicted UMLS rules, disappeared, which made the RSN smaller. Objective The authors performed a longitudinal study with the goal of reducing the size of the RSN to become compact. This goal was achieved by correcting inconsistencies and errors in the IST assignments in the UMLS, which additionally helped identify and correct ambiguities, inconsistencies, and errors in source terminologies widely used in the realm of public health. Methods In this paper, we discuss the process and steps employed in this longitudinal study and the intermediate results for different stages. The sculpting process includes removing redundant semantic type assignments, expanding semantic type assignments, and removing illegitimate ISTs by auditing ISTs of small extents. However, the emphasis of this paper is not on the auditing methodologies employed during the process, since they were introduced in earlier publications, but on the strategy of employing them in order to transform the RSN into a compact network. For this paper we also performed a comprehensive audit of 168 “small ISTs” in the 2013AA version of the UMLS to finalize the longitudinal study. Results Over the years it was found that the editors of the UMLS introduced some new inconsistencies that resulted in the reintroduction of unwarranted ISTs that had already been eliminated as a result of their previous corrections. Because of that, the transformation of the RSN into a compact network covering all necessary categories for the UMLS was slowed down. The corrections suggested by an audit of the 2013AA version of the UMLS achieve a compact RSN of equal magnitude as the UMLS SN. The number of ISTs has been reduced to 336. We also demonstrate how auditing the semantic type assignments of UMLS concepts can expose other modeling errors in the UMLS source terminologies, e.g., SNOMED CT, LOINC, and RxNORM that are important for health informatics. Such errors would otherwise stay hidden. Conclusions It is hoped that the UMLS curators will implement all required corrections and use the RSN along with the SN when maintaining and extending the UMLS. When used correctly, the RSN will support the prevention of the accidental introduction of inconsistent semantic type assignments into the UMLS. Furthermore, this way the RSN will support the exposure of other hidden errors and inconsistencies in health informatics terminologies, which are sources of the UMLS. Notably, the development of the RSN materializes the deeper, more refined Semantic Network for the UMLS that its designers envisioned originally but had not implemented. PMID:25422719

Knowledge of the human body: a distinct semantic domain.

PubMed

Coslett, H Branch; Saffran, Eleanor M; Schwoebel, John

2002-08-13

Patients with selective deficits in the naming and comprehension of animals, plants, and artifacts have been reported. These descriptions of specific semantic category deficits have contributed substantially to the understanding of the architecture of semantic representations. This study sought to further understanding of the organization of the semantic system by demonstrating that another semantic category, knowledge of the human body, may be selectively preserved. The performance of a patient with semantic dementia was compared with the performance of healthy controls on a variety of tasks assessing distinct types of body representations, including the body schema, body image, and body structural description. Despite substantial deficits on tasks involving language and knowledge of the world generally, the patient performed normally on all tests of body knowledge except body part naming; even in this naming task, however, her performance with body parts was significantly better than on artifacts. The demonstration that body knowledge may be preserved despite substantial semantic deficits involving other types of semantic information argues that body knowledge is a distinct and dissociable semantic category. These data are interpreted as support for a model of semantics that proposes that knowledge is distributed across different cortical regions reflecting the manner in which the information was acquired.

Improvements to the Ontology-based Metadata Portal for Unified Semantics (OlyMPUS)

NASA Astrophysics Data System (ADS)

Linsinbigler, M. A.; Gleason, J. L.; Huffer, E.

2016-12-01

The Ontology-based Metadata Portal for Unified Semantics (OlyMPUS), funded by the NASA Earth Science Technology Office Advanced Information Systems Technology program, is an end-to-end system designed to support Earth Science data consumers and data providers, enabling the latter to register data sets and provision them with the semantically rich metadata that drives the Ontology-Driven Interactive Search Environment for Earth Sciences (ODISEES). OlyMPUS complements the ODISEES' data discovery system with an intelligent tool to enable data producers to auto-generate semantically enhanced metadata and upload it to the metadata repository that drives ODISEES. Like ODISEES, the OlyMPUS metadata provisioning tool leverages robust semantics, a NoSQL database and query engine, an automated reasoning engine that performs first- and second-order deductive inferencing, and uses a controlled vocabulary to support data interoperability and automated analytics. The ODISEES data discovery portal leverages this metadata to provide a seamless data discovery and access experience for data consumers who are interested in comparing and contrasting the multiple Earth science data products available across NASA data centers. Olympus will support scientists' services and tools for performing complex analyses and identifying correlations and non-obvious relationships across all types of Earth System phenomena using the full spectrum of NASA Earth Science data available. By providing an intelligent discovery portal that supplies users - both human users and machines - with detailed information about data products, their contents and their structure, ODISEES will reduce the level of effort required to identify and prepare large volumes of data for analysis. This poster will explain how OlyMPUS leverages deductive reasoning and other technologies to create an integrated environment for generating and exploiting semantically rich metadata.

Semantic and visual determinants of face recognition in a prosopagnosic patient.

PubMed

Dixon, M J; Bub, D N; Arguin, M

1998-05-01

Prosopagnosia is the neuropathological inability to recognize familiar people by their faces. It can occur in isolation or can coincide with recognition deficits for other nonface objects. Often, patients whose prosopagnosia is accompanied by object recognition difficulties have more trouble identifying certain categories of objects relative to others. In previous research, we demonstrated that objects that shared multiple visual features and were semantically close posed severe recognition difficulties for a patient with temporal lobe damage. We now demonstrate that this patient's face recognition is constrained by these same parameters. The prosopagnosic patient ELM had difficulties pairing faces to names when the faces shared visual features and the names were semantically related (e.g., Tonya Harding, Nancy Kerrigan, and Josee Chouinard -three ice skaters). He made tenfold fewer errors when the exact same faces were associated with semantically unrelated people (e.g., singer Celine Dion, actress Betty Grable, and First Lady Hillary Clinton). We conclude that prosopagnosia and co-occurring category-specific recognition problems both stem from difficulties disambiguating the stored representations of objects that share multiple visual features and refer to semantically close identities or concepts.

Language Networks Associated with Computerized Semantic Indices

PubMed Central

Pakhomov, Serguei V. S.; Jones, David T.; Knopman, David S.

2014-01-01

Tests of generative semantic verbal fluency are widely used to study organization and representation of concepts in the human brain. Previous studies demonstrated that clustering and switching behavior during verbal fluency tasks is supported by multiple brain mechanisms associated with semantic memory and executive control. Previous work relied on manual assessments of semantic relatedness between words and grouping of words into semantic clusters. We investigated a computational linguistic approach to measuring the strength of semantic relatedness between words based on latent semantic analysis of word co-occurrences in a subset of a large online encyclopedia. We computed semantic clustering indices and compared them to brain network connectivity measures obtained with task-free fMRI in a sample consisting of healthy participants and those differentially affected by cognitive impairment. We found that semantic clustering indices were associated with brain network connectivity in distinct areas including fronto-temporal, fronto-parietal and fusiform gyrus regions. This study shows that computerized semantic indices complement traditional assessments of verbal fluency to provide a more complete account of the relationship between brain and verbal behavior involved organization and retrieval of lexical information from memory. PMID:25315785

Construction of a virtual EPR and automated contextual linkage to multiple sources of support information on the Oxford Clinical Intranet.

PubMed

Kay, J D; Nurse, D

1999-01-01

We have used internet-standard tools to provide access for clinicians to the components of the electronic patient record held on multiple remote disparate systems. Through the same interface we have provided access to multiple knowledgebases, some written locally and others published elsewhere. We have developed linkage between these two types of information which removes the need for the user to drill down into each knowledgebase to search for relevant information. This approach may help in the implementation of evidence-based practice. The major problems appear to be semantic rather than technological. The intranet was developed at low cost and is now in routine use. This approach appears to be transferable across systems and organisations.

Distinct Effects of Lexical and Semantic Competition during Picture Naming in Younger Adults, Older Adults, and People with Aphasia

PubMed Central

Britt, Allison E.; Ferrara, Casey; Mirman, Daniel

2016-01-01

Producing a word requires selecting among a set of similar alternatives. When many semantically related items become activated, the difficulty of the selection process is increased. Experiment 1 tested naming of items with either multiple synonymous labels (“Alternate Names,” e.g., gift/present) or closely semantically related but non-equivalent responses (“Near Semantic Neighbors,” e.g., jam/jelly). Picture naming was fastest and most accurate for pictures with only one label (“High Name Agreement”), slower and less accurate in the Alternate Names condition, and slowest and least accurate in the Near Semantic Neighbors condition. These results suggest that selection mechanisms in picture naming operate at two distinct levels of processing: selecting between similar but non-equivalent names requires two selection processes (semantic and lexical), whereas selecting among equivalent names only requires one selection at the lexical level. Experiment 2 examined how these selection mechanisms are affected by normal aging and found that older adults had significantly more difficulty in the Near Semantic Neighbors condition, but not in the Alternate Names condition. This suggests that aging affects semantic processing and selection more strongly than it affects lexical selection. Experiment 3 examined the role of the left inferior frontal gyrus (LIFG) in these selection processes by testing individuals with aphasia secondary to stroke lesions that either affected the LIFG or spared it. Surprisingly, there was no interaction between condition and lesion group: the presence of LIFG damage was not associated with substantively worse naming performance for pictures with multiple acceptable labels. These results are not consistent with a simple view of LIFG as the locus of lexical selection and suggest a more nuanced view of the neural basis of lexical and semantic selection. PMID:27458393

SIDD: A Semantically Integrated Database towards a Global View of Human Disease

PubMed Central

Cheng, Liang; Wang, Guohua; Li, Jie; Zhang, Tianjiao; Xu, Peigang; Wang, Yadong

2013-01-01

Background A number of databases have been developed to collect disease-related molecular, phenotypic and environmental features (DR-MPEs), such as genes, non-coding RNAs, genetic variations, drugs, phenotypes and environmental factors. However, each of current databases focused on only one or two DR-MPEs. There is an urgent demand to develop an integrated database, which can establish semantic associations among disease-related databases and link them to provide a global view of human disease at the biological level. This database, once developed, will facilitate researchers to query various DR-MPEs through disease, and investigate disease mechanisms from different types of data. Methodology To establish an integrated disease-associated database, disease vocabularies used in different databases are mapped to Disease Ontology (DO) through semantic match. 4,284 and 4,186 disease terms from Medical Subject Headings (MeSH) and Online Mendelian Inheritance in Man (OMIM) respectively are mapped to DO. Then, the relationships between DR-MPEs and diseases are extracted and merged from different source databases for reducing the data redundancy. Conclusions A semantically integrated disease-associated database (SIDD) is developed, which integrates 18 disease-associated databases, for researchers to browse multiple types of DR-MPEs in a view. A web interface allows easy navigation for querying information through browsing a disease ontology tree or searching a disease term. Furthermore, a network visualization tool using Cytoscape Web plugin has been implemented in SIDD. It enhances the SIDD usage when viewing the relationships between diseases and DR-MPEs. The current version of SIDD (Jul 2013) documents 4,465,131 entries relating to 139,365 DR-MPEs, and to 3,824 human diseases. The database can be freely accessed from: http://mlg.hit.edu.cn/SIDD. PMID:24146757

A common type system for clinical natural language processing

PubMed Central

2013-01-01

Background One challenge in reusing clinical data stored in electronic medical records is that these data are heterogenous. Clinical Natural Language Processing (NLP) plays an important role in transforming information in clinical text to a standard representation that is comparable and interoperable. Information may be processed and shared when a type system specifies the allowable data structures. Therefore, we aim to define a common type system for clinical NLP that enables interoperability between structured and unstructured data generated in different clinical settings. Results We describe a common type system for clinical NLP that has an end target of deep semantics based on Clinical Element Models (CEMs), thus interoperating with structured data and accommodating diverse NLP approaches. The type system has been implemented in UIMA (Unstructured Information Management Architecture) and is fully functional in a popular open-source clinical NLP system, cTAKES (clinical Text Analysis and Knowledge Extraction System) versions 2.0 and later. Conclusions We have created a type system that targets deep semantics, thereby allowing for NLP systems to encapsulate knowledge from text and share it alongside heterogenous clinical data sources. Rather than surface semantics that are typically the end product of NLP algorithms, CEM-based semantics explicitly build in deep clinical semantics as the point of interoperability with more structured data types. PMID:23286462

A common type system for clinical natural language processing.

PubMed

Wu, Stephen T; Kaggal, Vinod C; Dligach, Dmitriy; Masanz, James J; Chen, Pei; Becker, Lee; Chapman, Wendy W; Savova, Guergana K; Liu, Hongfang; Chute, Christopher G

2013-01-03

One challenge in reusing clinical data stored in electronic medical records is that these data are heterogenous. Clinical Natural Language Processing (NLP) plays an important role in transforming information in clinical text to a standard representation that is comparable and interoperable. Information may be processed and shared when a type system specifies the allowable data structures. Therefore, we aim to define a common type system for clinical NLP that enables interoperability between structured and unstructured data generated in different clinical settings. We describe a common type system for clinical NLP that has an end target of deep semantics based on Clinical Element Models (CEMs), thus interoperating with structured data and accommodating diverse NLP approaches. The type system has been implemented in UIMA (Unstructured Information Management Architecture) and is fully functional in a popular open-source clinical NLP system, cTAKES (clinical Text Analysis and Knowledge Extraction System) versions 2.0 and later. We have created a type system that targets deep semantics, thereby allowing for NLP systems to encapsulate knowledge from text and share it alongside heterogenous clinical data sources. Rather than surface semantics that are typically the end product of NLP algorithms, CEM-based semantics explicitly build in deep clinical semantics as the point of interoperability with more structured data types.

OlyMPUS - The Ontology-based Metadata Portal for Unified Semantics

NASA Astrophysics Data System (ADS)

Huffer, E.; Gleason, J. L.

2015-12-01

The Ontology-based Metadata Portal for Unified Semantics (OlyMPUS), funded by the NASA Earth Science Technology Office Advanced Information Systems Technology program, is an end-to-end system designed to support data consumers and data providers, enabling the latter to register their data sets and provision them with the semantically rich metadata that drives the Ontology-Driven Interactive Search Environment for Earth Sciences (ODISEES). OlyMPUS leverages the semantics and reasoning capabilities of ODISEES to provide data producers with a semi-automated interface for producing the semantically rich metadata needed to support ODISEES' data discovery and access services. It integrates the ODISEES metadata search system with multiple NASA data delivery tools to enable data consumers to create customized data sets for download to their computers, or for NASA Advanced Supercomputing (NAS) facility registered users, directly to NAS storage resources for access by applications running on NAS supercomputers. A core function of NASA's Earth Science Division is research and analysis that uses the full spectrum of data products available in NASA archives. Scientists need to perform complex analyses that identify correlations and non-obvious relationships across all types of Earth System phenomena. Comprehensive analytics are hindered, however, by the fact that many Earth science data products are disparate and hard to synthesize. Variations in how data are collected, processed, gridded, and stored, create challenges for data interoperability and synthesis, which are exacerbated by the sheer volume of available data. Robust, semantically rich metadata can support tools for data discovery and facilitate machine-to-machine transactions with services such as data subsetting, regridding, and reformatting. Such capabilities are critical to enabling the research activities integral to NASA's strategic plans. However, as metadata requirements increase and competing standards emerge, metadata provisioning becomes increasingly burdensome to data producers. The OlyMPUS system helps data providers produce semantically rich metadata, making their data more accessible to data consumers, and helps data consumers quickly discover and download the right data for their research.

Phonological and Semantic Cues to Learning from Word-Types

PubMed Central

Richtsmeier, Peter

2017-01-01

Word-types represent the primary form of data for many models of phonological learning, and they often predict performance in psycholinguistic tasks. Word-types are often tacitly defined as phonologically unique words. Yet, an explicit test of this definition is lacking, and natural language patterning suggests that word meaning could also act as a cue to word-type status. This possibility was tested in a statistical phonotactic learning experiment in which phonological and semantic properties of word-types varied. During familiarization, the learning targets—word-medial consonant sequences—were instantiated either by four related word-types or by just one word-type (the experimental frequency factor). The expectation was that more word-types would lead participants to generalize the target sequences. Regarding semantic cues, related word-types were either associated with different referents or all with a single referent. Regarding phonological cues, related word-types differed from each other by one, two, or more phonemes. At test, participants rated novel wordforms for their similarity to the familiarization words. When participants heard four related word-types, they gave higher ratings to test words with the same consonant sequences, irrespective of the phonological and semantic manipulations. The results support the existing phonological definition of word-types. PMID:29187914

Distributed semantic networks and CLIPS

NASA Technical Reports Server (NTRS)

Snyder, James; Rodriguez, Tony

1991-01-01

Semantic networks of frames are commonly used as a method of reasoning in many problems. In most of these applications the semantic network exists as a single entity in a single process environment. Advances in workstation hardware provide support for more sophisticated applications involving multiple processes, interacting in a distributed environment. In these applications the semantic network may well be distributed over several concurrently executing tasks. This paper describes the design and implementation of a frame based, distributed semantic network in which frames are accessed both through C Language Integrated Production System (CLIPS) expert systems and procedural C++ language programs. The application area is a knowledge based, cooperative decision making model utilizing both rule based and procedural experts.

Phonetic Pause Unites Phonology and Semantics against Morphology and Syntax

ERIC Educational Resources Information Center

Sakarna, Ahmad Khalaf; Mobaideen, Adnan

2012-01-01

The present study investigates the phonological effect triggered by the different types of phonetic pause used in Quran on morphology, syntax, and semantics. It argues that Quranic pause provides interesting evidence about the close relation between phonology and semantics, from one side, and semantics, morphology, and syntax, from the other…

Separate Brain Circuits Support Integrative and Semantic Priming in the Human Language System.

PubMed

Feng, Gangyi; Chen, Qi; Zhu, Zude; Wang, Suiping

2016-07-01

Semantic priming is a crucial phenomenon to study the organization of semantic memory. A novel type of priming effect, integrative priming, has been identified behaviorally, whereby a prime word facilitates recognition of a target word when the 2 concepts can be combined to form a unitary representation. We used both functional and anatomical imaging approaches to investigate the neural substrates supporting such integrative priming, and compare them with those in semantic priming. Similar behavioral priming effects for both semantic (Bread-Cake) and integrative conditions (Cherry-Cake) were observed when compared with an unrelated condition. However, a clearly dissociated brain response was observed between these 2 types of priming. The semantic-priming effect was localized to the posterior superior temporal and middle temporal gyrus. In contrast, the integrative-priming effect localized to the left anterior inferior frontal gyrus and left anterior temporal cortices. Furthermore, fiber tractography showed that the integrative-priming regions were connected via uncinate fasciculus fiber bundle forming an integrative circuit, whereas the semantic-priming regions connected to the posterior frontal cortex via separated pathways. The results point to dissociable neural pathways underlying the 2 distinct types of priming, illuminating the neural circuitry organization of semantic representation and integration. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The role of medial temporal lobe in retrieving spatial and nonspatial relations from episodic and semantic memory.

PubMed

Ryan, Lee; Lin, Chun-Yu; Ketcham, Katie; Nadel, Lynn

2010-01-01

This study examined the involvement of medial temporal lobe, especially the hippocampus, in processing spatial and nonspatial relations using episodic and semantic versions of a relational judgment task. Participants studied object arrays and were tested on different types of relations between pairs of objects. Three prevalent views of hippocampal function were considered. Cognitive map theory (O'Keefe and Nadel (1978) The Hippocampus as a Cognitive Map. USA: Oxford University Press) emphasizes hippocampal involvement in spatial relational tasks. Multiple trace theory (Nadel and Moscovitch (1997) Memory consolidation, retrograde amnesia and the hippocampal complex Curr Opin Neurobiol 7:217-227) emphasizes hippocampal involvement in episodic tasks. Eichenbaum and Cohen's ((2001) From Conditioning to Conscious Recollection: Memory Systems of the Brain. USA: Oxford University Press) relational theory predicts equivalent hippocampal involvement in all relational tasks within both semantic and episodic memory. The fMRI results provided partial support for all three theories, though none of them fit the data perfectly. We observed hippocampal activation during all relational tasks, with increased activation for spatial compared to nonspatial relations, and for episodic compared to semantic relations. The placement of activation along the anterior-posterior axis of the hippocampus also differentiated the conditions. We suggest a view of hippocampal function in memory that incorporates aspects of all three theories. Copyright 2009 Wiley-Liss, Inc.

Multivariate Pattern Analysis Reveals Category-Related Organization of Semantic Representations in Anterior Temporal Cortex.

PubMed

Malone, Patrick S; Glezer, Laurie S; Kim, Judy; Jiang, Xiong; Riesenhuber, Maximilian

2016-09-28

The neural substrates of semantic representation have been the subject of much controversy. The study of semantic representations is complicated by difficulty in disentangling perceptual and semantic influences on neural activity, as well as in identifying stimulus-driven, "bottom-up" semantic selectivity unconfounded by top-down task-related modulations. To address these challenges, we trained human subjects to associate pseudowords (TPWs) with various animal and tool categories. To decode semantic representations of these TPWs, we used multivariate pattern classification of fMRI data acquired while subjects performed a semantic oddball detection task. Crucially, the classifier was trained and tested on disjoint sets of TPWs, so that the classifier had to use the semantic information from the training set to correctly classify the test set. Animal and tool TPWs were successfully decoded based on fMRI activity in spatially distinct subregions of the left medial anterior temporal lobe (LATL). In addition, tools (but not animals) were successfully decoded from activity in the left inferior parietal lobule. The tool-selective LATL subregion showed greater functional connectivity with left inferior parietal lobule and ventral premotor cortex, indicating that each LATL subregion exhibits distinct patterns of connectivity. Our findings demonstrate category-selective organization of semantic representations in LATL into spatially distinct subregions, continuing the lateral-medial segregation of activation in posterior temporal cortex previously observed in response to images of animals and tools, respectively. Together, our results provide evidence for segregation of processing hierarchies for different classes of objects and the existence of multiple, category-specific semantic networks in the brain. The location and specificity of semantic representations in the brain are still widely debated. We trained human participants to associate specific pseudowords with various animal and tool categories, and used multivariate pattern classification of fMRI data to decode the semantic representations of the trained pseudowords. We found that: (1) animal and tool information was organized in category-selective subregions of medial left anterior temporal lobe (LATL); (2) tools, but not animals, were encoded in left inferior parietal lobe; and (3) LATL subregions exhibited distinct patterns of functional connectivity with category-related regions across cortex. Our findings suggest that semantic knowledge in LATL is organized in category-related subregions, providing evidence for the existence of multiple, category-specific semantic representations in the brain. Copyright © 2016 the authors 0270-6474/16/3610089-08$15.00/0.

What is it that lingers? Garden-path (mis)interpretations in younger and older adults.

PubMed

Malyutina, Svetlana; den Ouden, Dirk-Bart

2016-01-01

Previous research has shown that comprehenders do not always conduct a full (re)analysis of temporarily ambiguous "garden-path" sentences. The present study used a sentence-picture matching task to investigate what kind of representations are formed when full reanalysis is not performed: Do comprehenders "blend" two incompatible representations as a result of shallow syntactic processing or do they erroneously maintain the initial incorrect parsing without incorporating new information, and does this vary with age? Twenty-five younger and 15 older adults performed a multiple-choice sentence-picture matching task with stimuli including early-closure garden-path sentences. The results suggest that the type of erroneous representation is affected by linguistic variables, such as sentence structure, verb type, and semantic plausibility, as well as by age. Older adults' response patterns indicate an increased reliance on inferencing based on lexical and semantic cues, with a lower bar for accepting an initial parse and with a weaker drive to reanalyse a syntactic representation. Among younger adults, there was a tendency to blend two representations into a single interpretation, even if this was not licensed by the syntax.

BDVC (Bimodal Database of Violent Content): A database of violent audio and video

NASA Astrophysics Data System (ADS)

Rivera Martínez, Jose Luis; Mijes Cruz, Mario Humberto; Rodríguez Vázqu, Manuel Antonio; Rodríguez Espejo, Luis; Montoya Obeso, Abraham; García Vázquez, Mireya Saraí; Ramírez Acosta, Alejandro Álvaro

2017-09-01

Nowadays there is a trend towards the use of unimodal databases for multimedia content description, organization and retrieval applications of a single type of content like text, voice and images, instead bimodal databases allow to associate semantically two different types of content like audio-video, image-text, among others. The generation of a bimodal database of audio-video implies the creation of a connection between the multimedia content through the semantic relation that associates the actions of both types of information. This paper describes in detail the used characteristics and methodology for the creation of the bimodal database of violent content; the semantic relationship is stablished by the proposed concepts that describe the audiovisual information. The use of bimodal databases in applications related to the audiovisual content processing allows an increase in the semantic performance only and only if these applications process both type of content. This bimodal database counts with 580 audiovisual annotated segments, with a duration of 28 minutes, divided in 41 classes. Bimodal databases are a tool in the generation of applications for the semantic web.

Imageability and semantic association in the representation and processing of event verbs.

PubMed

Xu, Xu; Kang, Chunyan; Guo, Taomei

2016-05-01

This study examined the relative salience of imageability (the degree to which a word evokes mental imagery) versus semantic association (the density of semantic network in which a word is embedded) in the representation and processing of four types of event verbs: sensory, cognitive, speech, and motor verbs. ERP responses were recorded, while 34 university students performed on a lexical decision task. Analysis focused primarily on amplitude differences across verb conditions within the N400 time window where activities are considered representing meaning activation. Variation in N400 amplitude across four types of verbs was found significantly associated with the level of imageability, but not the level of semantic association. The findings suggest imageability as a more salient factor relative to semantic association in the processing of these verbs. The role of semantic association and the representation of speech verbs are also discussed.

Salient object detection method based on multiple semantic features

NASA Astrophysics Data System (ADS)

Wang, Chunyang; Yu, Chunyan; Song, Meiping; Wang, Yulei

2018-04-01

The existing salient object detection model can only detect the approximate location of salient object, or highlight the background, to resolve the above problem, a salient object detection method was proposed based on image semantic features. First of all, three novel salient features were presented in this paper, including object edge density feature (EF), object semantic feature based on the convex hull (CF) and object lightness contrast feature (LF). Secondly, the multiple salient features were trained with random detection windows. Thirdly, Naive Bayesian model was used for combine these features for salient detection. The results on public datasets showed that our method performed well, the location of salient object can be fixed and the salient object can be accurately detected and marked by the specific window.

Landscape features, standards, and semantics in U.S. national topographic mapping databases

USGS Publications Warehouse

Varanka, Dalia

2009-01-01

The objective of this paper is to examine the contrast between local, field-surveyed topographical representation and feature representation in digital, centralized databases and to clarify their ontological implications. The semantics of these two approaches are contrasted by examining the categorization of features by subject domains inherent to national topographic mapping. When comparing five USGS topographic mapping domain and feature lists, results indicate that multiple semantic meanings and ontology rules were applied to the initial digital database, but were lost as databases became more centralized at national scales, and common semantics were replaced by technological terms.

A journey to Semantic Web query federation in the life sciences.

PubMed

Cheung, Kei-Hoi; Frost, H Robert; Marshall, M Scott; Prud'hommeaux, Eric; Samwald, Matthias; Zhao, Jun; Paschke, Adrian

2009-10-01

As interest in adopting the Semantic Web in the biomedical domain continues to grow, Semantic Web technology has been evolving and maturing. A variety of technological approaches including triplestore technologies, SPARQL endpoints, Linked Data, and Vocabulary of Interlinked Datasets have emerged in recent years. In addition to the data warehouse construction, these technological approaches can be used to support dynamic query federation. As a community effort, the BioRDF task force, within the Semantic Web for Health Care and Life Sciences Interest Group, is exploring how these emerging approaches can be utilized to execute distributed queries across different neuroscience data sources. We have created two health care and life science knowledge bases. We have explored a variety of Semantic Web approaches to describe, map, and dynamically query multiple datasets. We have demonstrated several federation approaches that integrate diverse types of information about neurons and receptors that play an important role in basic, clinical, and translational neuroscience research. Particularly, we have created a prototype receptor explorer which uses OWL mappings to provide an integrated list of receptors and executes individual queries against different SPARQL endpoints. We have also employed the AIDA Toolkit, which is directed at groups of knowledge workers who cooperatively search, annotate, interpret, and enrich large collections of heterogeneous documents from diverse locations. We have explored a tool called "FeDeRate", which enables a global SPARQL query to be decomposed into subqueries against the remote databases offering either SPARQL or SQL query interfaces. Finally, we have explored how to use the vocabulary of interlinked Datasets (voiD) to create metadata for describing datasets exposed as Linked Data URIs or SPARQL endpoints. We have demonstrated the use of a set of novel and state-of-the-art Semantic Web technologies in support of a neuroscience query federation scenario. We have identified both the strengths and weaknesses of these technologies. While Semantic Web offers a global data model including the use of Uniform Resource Identifiers (URI's), the proliferation of semantically-equivalent URI's hinders large scale data integration. Our work helps direct research and tool development, which will be of benefit to this community.

A journey to Semantic Web query federation in the life sciences

PubMed Central

Cheung, Kei-Hoi; Frost, H Robert; Marshall, M Scott; Prud'hommeaux, Eric; Samwald, Matthias; Zhao, Jun; Paschke, Adrian

2009-01-01

Background As interest in adopting the Semantic Web in the biomedical domain continues to grow, Semantic Web technology has been evolving and maturing. A variety of technological approaches including triplestore technologies, SPARQL endpoints, Linked Data, and Vocabulary of Interlinked Datasets have emerged in recent years. In addition to the data warehouse construction, these technological approaches can be used to support dynamic query federation. As a community effort, the BioRDF task force, within the Semantic Web for Health Care and Life Sciences Interest Group, is exploring how these emerging approaches can be utilized to execute distributed queries across different neuroscience data sources. Methods and results We have created two health care and life science knowledge bases. We have explored a variety of Semantic Web approaches to describe, map, and dynamically query multiple datasets. We have demonstrated several federation approaches that integrate diverse types of information about neurons and receptors that play an important role in basic, clinical, and translational neuroscience research. Particularly, we have created a prototype receptor explorer which uses OWL mappings to provide an integrated list of receptors and executes individual queries against different SPARQL endpoints. We have also employed the AIDA Toolkit, which is directed at groups of knowledge workers who cooperatively search, annotate, interpret, and enrich large collections of heterogeneous documents from diverse locations. We have explored a tool called "FeDeRate", which enables a global SPARQL query to be decomposed into subqueries against the remote databases offering either SPARQL or SQL query interfaces. Finally, we have explored how to use the vocabulary of interlinked Datasets (voiD) to create metadata for describing datasets exposed as Linked Data URIs or SPARQL endpoints. Conclusion We have demonstrated the use of a set of novel and state-of-the-art Semantic Web technologies in support of a neuroscience query federation scenario. We have identified both the strengths and weaknesses of these technologies. While Semantic Web offers a global data model including the use of Uniform Resource Identifiers (URI's), the proliferation of semantically-equivalent URI's hinders large scale data integration. Our work helps direct research and tool development, which will be of benefit to this community. PMID:19796394

A hybrid approach to software repository retrieval: Blending faceted classification and type signatures

NASA Technical Reports Server (NTRS)

Eichmann, David A.

1992-01-01

We present a user interface for software reuse repository that relies both on the informal semantics of faceted classification and the formal semantics of type signatures for abstract data types. The result is an interface providing both structural and qualitative feedback to a software reuser.

Language networks associated with computerized semantic indices.

PubMed

Pakhomov, Serguei V S; Jones, David T; Knopman, David S

2015-01-01

Tests of generative semantic verbal fluency are widely used to study organization and representation of concepts in the human brain. Previous studies demonstrated that clustering and switching behavior during verbal fluency tasks is supported by multiple brain mechanisms associated with semantic memory and executive control. Previous work relied on manual assessments of semantic relatedness between words and grouping of words into semantic clusters. We investigated a computational linguistic approach to measuring the strength of semantic relatedness between words based on latent semantic analysis of word co-occurrences in a subset of a large online encyclopedia. We computed semantic clustering indices and compared them to brain network connectivity measures obtained with task-free fMRI in a sample consisting of healthy participants and those differentially affected by cognitive impairment. We found that semantic clustering indices were associated with brain network connectivity in distinct areas including fronto-temporal, fronto-parietal and fusiform gyrus regions. This study shows that computerized semantic indices complement traditional assessments of verbal fluency to provide a more complete account of the relationship between brain and verbal behavior involved organization and retrieval of lexical information from memory. Copyright © 2014 Elsevier Inc. All rights reserved.

The loss of episodic memories in retrograde amnesia: single-case and group studies.

PubMed

Kopelman, M D; Kapur, N

2001-09-29

Retrograde amnesia in neurological disorders is a perplexing and fascinating research topic. The severity of retrograde amnesia is not well correlated with that of anterograde amnesia, and there can be disproportionate impairments of either. Within retrograde amnesia, there are various dissociations which have been claimed-for example, between the more autobiographical (episodic) and more semantic components of memory. However, the associations of different types of retrograde amnesia are also important, and clarification of these issues is confounded by the fact that retrograde amnesia seems to be particularly vulnerable to psychogenic factors. Large frontal and temporal lobe lesions have been postulated as critical in producing retrograde amnesia. Theories of retrograde amnesia have encompassed storage versus access disruption, physiological processes of 'consolidation', the progressive transformation of episodic memories into a more 'semantic' form, and multiple-trace theory. Single-case investigations, group studies and various forms of neuroimaging can all contribute to the resolution of these controversies.

SLEEC: Semantics-Rich Libraries for Effective Exascale Computation. Final Technical Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Milind, Kulkarni

SLEEC (Semantics-rich Libraries for Effective Exascale Computation) was a project funded by the Department of Energy X-Stack Program, award number DE-SC0008629. The initial project period was September 2012–August 2015. The project was renewed for an additional year, expiring August 2016. Finally, the project received a no-cost extension, leading to a final expiry date of August 2017. Modern applications, especially those intended to run at exascale, are not written from scratch. Instead, they are built by stitching together various carefully-written, hand-tuned libraries. Correctly composing these libraries is difficult, but traditional compilers are unable to effectively analyze and transform across abstraction layers.more » Domain specific compilers integrate semantic knowledge into compilers, allowing them to transform applications that use particular domain-specific languages, or domain libraries. But they do not help when new domains are developed, or applications span multiple domains. SLEEC aims to fix these problems. To do so, we are building generic compiler and runtime infrastructures that are semantics-aware but not domain-specific. By performing optimizations related to the semantics of a domain library, the same infrastructure can be made generic and apply across multiple domains.« less

Auditory attention strategy depends on target linguistic properties and spatial configurationa)

PubMed Central

McCloy, Daniel R.; Lee, Adrian K. C.

2015-01-01

Whether crossing a busy intersection or attending a large dinner party, listeners sometimes need to attend to multiple spatially distributed sound sources or streams concurrently. How they achieve this is not clear—some studies suggest that listeners cannot truly simultaneously attend to separate streams, but instead combine attention switching with short-term memory to achieve something resembling divided attention. This paper presents two oddball detection experiments designed to investigate whether directing attention to phonetic versus semantic properties of the attended speech impacts listeners' ability to divide their auditory attention across spatial locations. Each experiment uses four spatially distinct streams of monosyllabic words, variation in cue type (providing phonetic or semantic information), and requiring attention to one or two locations. A rapid button-press response paradigm is employed to minimize the role of short-term memory in performing the task. Results show that differences in the spatial configuration of attended and unattended streams interact with linguistic properties of the speech streams to impact performance. Additionally, listeners may leverage phonetic information to make oddball detection judgments even when oddballs are semantically defined. Both of these effects appear to be mediated by the overall complexity of the acoustic scene. PMID:26233011

Relations between Semantic and Cognitive Development in the One-Word Stage: The Specificity Hypothesis.

ERIC Educational Resources Information Center

Gopnik, Alison; Meltzoff, Andrew N.

1986-01-01

Compares two types of semantic development (the acquisition of disappearance words and success-failure words) to performance on two types of cognitive tasks (object-permanence and means-ends tasks) among infants. (HOD)

Measuring effectiveness of semantic cues in degraded English sentences in non-native listeners.

PubMed

Shi, Lu-Feng

2014-01-01

This study employed Boothroyd and Nittrouer's k (1988) to directly quantify effectiveness in native versus non-native listeners' use of semantic cues. Listeners were presented speech-perception-in-noise sentences processed at three levels of concurrent multi-talker babble and reverberation. For each condition, 50 sentences with multiple semantic cues and 50 with minimum semantic cues were randomly presented. Listeners verbally reported and wrote down the target words. The metric, k, was derived from percent-correct scores for sentences with and without semantics. Ten native and 33 non-native listeners participated. The presence of semantics increased recognition benefit by over 250% for natives, but access to semantics remained limited for non-native listeners (90-135%). The k was comparable across conditions for native listeners, but level-dependent for non-natives. The k for non-natives was significantly different from 1 in all conditions, suggesting semantic cues, though reduced in importance in difficult conditions, were helpful for non-natives. Non-natives as a group were not as effective in using semantics to facilitate English sentence recognition as natives. Poor listening conditions were particularly adverse to the use of semantics in non-natives, who may rely on clear acoustic-phonetic cues before benefitting from semantic cues when recognizing connected speech.

The Syntax and Semantics of ERICA. Technical Report No. 185, Psychology and Education Series.

ERIC Educational Resources Information Center

Smith, Robert Lawrence, Jr.

This report is a detailed empirical examination of Suppes' ideas about the syntax and semantics of natural language, and an attempt at supporting the proposal that model-theoretic semantics of the type first proposed by Tarski is a useful tool for understanding the semantics of natural language. Child speech was selected as the best place to find…

Semantic Processing in Native and Second Language: Evidence from Hemispheric Differences in Fine and Coarse Semantic Coding

ERIC Educational Resources Information Center

Faust, Miriam; Ben-Artzi, Elisheva; Vardi, Nili

2012-01-01

Previous studies suggest that whereas the left hemisphere (LH) is involved in fine semantic processing, the right hemisphere (RH) is uniquely engaged in coarse semantic coding including the comprehension of distinct types of language such as figurative language, lexical ambiguity and verbal humor (e.g., and ). The present study examined the…

Constructing a Geology Ontology Using a Relational Database

NASA Astrophysics Data System (ADS)

Hou, W.; Yang, L.; Yin, S.; Ye, J.; Clarke, K.

2013-12-01

In geology community, the creation of a common geology ontology has become a useful means to solve problems of data integration, knowledge transformation and the interoperation of multi-source, heterogeneous and multiple scale geological data. Currently, human-computer interaction methods and relational database-based methods are the primary ontology construction methods. Some human-computer interaction methods such as the Geo-rule based method, the ontology life cycle method and the module design method have been proposed for applied geological ontologies. Essentially, the relational database-based method is a reverse engineering of abstracted semantic information from an existing database. The key is to construct rules for the transformation of database entities into the ontology. Relative to the human-computer interaction method, relational database-based methods can use existing resources and the stated semantic relationships among geological entities. However, two problems challenge the development and application. One is the transformation of multiple inheritances and nested relationships and their representation in an ontology. The other is that most of these methods do not measure the semantic retention of the transformation process. In this study, we focused on constructing a rule set to convert the semantics in a geological database into a geological ontology. According to the relational schema of a geological database, a conversion approach is presented to convert a geological spatial database to an OWL-based geological ontology, which is based on identifying semantics such as entities, relationships, inheritance relationships, nested relationships and cluster relationships. The semantic integrity of the transformation was verified using an inverse mapping process. In a geological ontology, an inheritance and union operations between superclass and subclass were used to present the nested relationship in a geochronology and the multiple inheritances relationship. Based on a Quaternary database of downtown of Foshan city, Guangdong Province, in Southern China, a geological ontology was constructed using the proposed method. To measure the maintenance of semantics in the conversation process and the results, an inverse mapping from the ontology to a relational database was tested based on a proposed conversation rule. The comparison of schema and entities and the reduction of tables between the inverse database and the original database illustrated that the proposed method retains the semantic information well during the conversation process. An application for abstracting sandstone information showed that semantic relationships among concepts in the geological database were successfully reorganized in the constructed ontology. Key words: geological ontology; geological spatial database; multiple inheritance; OWL Acknowledgement: This research is jointly funded by the Specialized Research Fund for the Doctoral Program of Higher Education of China (RFDP) (20100171120001), NSFC (41102207) and the Fundamental Research Funds for the Central Universities (12lgpy19).

Effects of semantic context on access to words of low imageability in deep-phonological dysphasia: a treatment case study.

PubMed

McCarthy, Laura Mary; Kalinyak-Fliszar, Michelene; Kohen, Francine; Martin, Nadine

2017-01-01

Deep dysphasia is a relatively rare subcategory of aphasia, characterised by word repetition impairment and a profound auditory-verbal short-term memory (STM) limitation. Repetition of words is better than nonwords (lexicality effect) and better for high-image than low-image words (imageability effect). Another related language impairment profile is phonological dysphasia, which includes all of the characteristics of deep dysphasia except for the occurrence of semantic errors in single word repetition. The overlap in symptoms of deep and phonological dysphasia has led to the hypothesis that they share the same root cause, impaired maintenance of activated representation of words, but that they differ in severity of that impairment, with deep dysphasia being more severe. We report a single-subject multiple baseline, multiple probe treatment study of a person who presented with a pattern of repetition that was consistent with the continuum of deep-phonological dysphasia: imageability and lexicality effects in repetition of single and multiple words and semantic errors in repetition of multiple-word utterances. The aim of this treatment study was to improve access to and repetition of low-imageability words by embedding them in modifier-noun phrases that enhanced their imageability. The treatment involved repetition of abstract noun pairs. We created modifier-abstract noun phrases that increased the semantic and syntactic cohesiveness of the words in the pair. For example, the phrases "long distance" and "social exclusion" were developed to improve repetition of the abstract pair "distance-exclusion". The goal of this manipulation was to increase the probability of accessing lexical and semantic representations of abstract words in repetition by enriching their semantic -syntactic context. We predicted that this increase in accessibility would be maintained when the words were repeated as pairs, but without the contextual phrase. Treatment outcomes indicated that increasing the semantic and syntactic cohesiveness of low-imageability and low-frequency words later improved this participant's ability to repeat those words when presented in isolation. This treatment approach to improving access to abstract word pairs for repetition was successful for our participant with phonological dysphasia. The approach exemplifies the potential value in manipulating linguistic characteristics of stimuli in ways that improve access between phonological and lexical-semantic levels of representation. Additionally, this study demonstrates how principles of a cognitive model of word processing can be used to guide treatment of word processing impairments in aphasia.

Effects of Embedded Processing Tasks on Learning Outcomes.

ERIC Educational Resources Information Center

Hobbs, D. J.

1987-01-01

Describes a British study with undergraduate accountancy students which compared the quantitative and qualitative effects of three types of embedded tasks or questions--relational-semantic, transpose-semantic, and non-semantic--on learning outcomes. Variables investigated included mathematical background, recall, and comprehension. Relevance of…

Semi-Supervised Learning to Identify UMLS Semantic Relations.

PubMed

Luo, Yuan; Uzuner, Ozlem

2014-01-01

The UMLS Semantic Network is constructed by experts and requires periodic expert review to update. We propose and implement a semi-supervised approach for automatically identifying UMLS semantic relations from narrative text in PubMed. Our method analyzes biomedical narrative text to collect semantic entity pairs, and extracts multiple semantic, syntactic and orthographic features for the collected pairs. We experiment with seeded k-means clustering with various distance metrics. We create and annotate a ground truth corpus according to the top two levels of the UMLS semantic relation hierarchy. We evaluate our system on this corpus and characterize the learning curves of different clustering configuration. Using KL divergence consistently performs the best on the held-out test data. With full seeding, we obtain macro-averaged F-measures above 70% for clustering the top level UMLS relations (2-way), and above 50% for clustering the second level relations (7-way).

Orchestrating Distributed Resource Ensembles for Petascale Science

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baldin, Ilya; Mandal, Anirban; Ruth, Paul

2014-04-24

Distributed, data-intensive computational science applications of interest to DOE scientific com- munities move large amounts of data for experiment data management, distributed analysis steps, remote visualization, and accessing scientific instruments. These applications need to orchestrate ensembles of resources from multiple resource pools and interconnect them with high-capacity multi- layered networks across multiple domains. It is highly desirable that mechanisms are designed that provide this type of resource provisioning capability to a broad class of applications. It is also important to have coherent monitoring capabilities for such complex distributed environments. In this project, we addressed these problems by designing an abstractmore » API, enabled by novel semantic resource descriptions, for provisioning complex and heterogeneous resources from multiple providers using their native provisioning mechanisms and control planes: computational, storage, and multi-layered high-speed network domains. We used an extensible resource representation based on semantic web technologies to afford maximum flexibility to applications in specifying their needs. We evaluated the effectiveness of provisioning using representative data-intensive ap- plications. We also developed mechanisms for providing feedback about resource performance to the application, to enable closed-loop feedback control and dynamic adjustments to resource allo- cations (elasticity). This was enabled through development of a novel persistent query framework that consumes disparate sources of monitoring data, including perfSONAR, and provides scalable distribution of asynchronous notifications.« less

Semantic and Inferencing Abilities in Children with Communication Disorders

ERIC Educational Resources Information Center

Botting, Nicola; Adams, Catherine

2005-01-01

Background: Semantic and inferencing abilities have not been fully examined in children with communication difficulties. Aims: To investigate the inferential and semantic abilities of children with communication difficulties using newly designed tasks. Methods & Procedures: Children with different types of communication disorder were compared with…

An Experiment in Scientific Program Understanding

NASA Technical Reports Server (NTRS)

Stewart, Mark E. M.; Owen, Karl (Technical Monitor)

2000-01-01

This paper concerns a procedure that analyzes aspects of the meaning or semantics of scientific and engineering code. This procedure involves taking a user's existing code, adding semantic declarations for some primitive variables, and parsing this annotated code using multiple, independent expert parsers. These semantic parsers encode domain knowledge and recognize formulae in different disciplines including physics, numerical methods, mathematics, and geometry. The parsers will automatically recognize and document some static, semantic concepts and help locate some program semantic errors. Results are shown for three intensively studied codes and seven blind test cases; all test cases are state of the art scientific codes. These techniques may apply to a wider range of scientific codes. If so, the techniques could reduce the time, risk, and effort required to develop and modify scientific codes.

False memories and lexical decision: even twelve primes do not cause long-term semantic priming.

PubMed

Zeelenberg, René; Pecher, Diane

2002-03-01

Semantic priming effects are usually obtained only if the prime is presented shortly before the target stimulus. Recent evidence obtained with the so-called false memory paradigm suggests, however, that in both explicit and implicit memory tasks semantic relations between words can result in long-lasting effects when multiple 'primes' are presented. The aim of the present study was to investigate whether these effects would generalize to lexical decision. In four experiments we showed that even as many as 12 primes do not cause long-term semantic priming. In all experiments, however, a repetition priming effect was obtained. The present results are consistent with a number of other results showing that semantic information plays a minimal role in long-term priming in visual word recognition.

Re-thinking typologies of multiple murders: the missing category of serial-mass murder and its theoretical and practical implications.

PubMed

Edelstein, Arnon

2014-01-01

The concept of multiple murders (mm) is as old as humanity itself but it has only become prevalent in academic thought within the last three decades. Over this period scholars have introduced two main attitudes regarding multiple murders. Some argue that multiple murders are, theoretically and empirically, one concept that includes different sub-types: mass murder, spree murder, and serial murder. Other scholars claim that those "sub categories", are a whole different phenomenon, which are worthy and needed a separate examination and discussion because its uniqueness. To my opinion, this argument is more a semantic one than a fundamental one, as long as we consider each type of these murders as a unique phenomenon, with its own and unique characteristics. In addition both parties agree that the concept of multiple murders is differentiated into the same three main sub-categories. My argument is that a fourth sub-category of mm exists which goes unrecognized by most scholars. This sub-category, named "serial-mass murder," will help to differentiate the sub-categories more accurately and will more clearly define each of the remaining sub-categories.

Discovery in a World of Mashups

NASA Astrophysics Data System (ADS)

King, T. A.; Ritschel, B.; Hourcle, J. A.; Moon, I. S.

2014-12-01

When the first digital information was stored electronically, discovery of what existed was through file names and the organization of the file system. With the advent of networks, digital information was shared on a wider scale, but discovery remained based on file and folder names. With a growing number of information sources, named based discovery quickly became ineffective. The keyword based search engine was one of the first types of a mashup in the world of Web 1.0. Embedded links from one document to another with prescribed relationships between files and the world of Web 2.0 was formed. Search engines like Google used the links to improve search results and a worldwide mashup was formed. While a vast improvement, the need for semantic (meaning rich) discovery was clear, especially for the discovery of scientific data. In response, every science discipline defined schemas to describe their type of data. Some core schemas where shared, but most schemas are custom tailored even though they share many common concepts. As with the networking of information sources, science increasingly relies on data from multiple disciplines. So there is a need to bring together multiple sources of semantically rich information. We explore how harvesting, conceptual mapping, facet based search engines, search term promotion, and style sheets can be combined to create the next generation of mashups in the emerging world of Web 3.0. We use NASA's Planetary Data System and NASA's Heliophysics Data Environment to illustrate how to create a multi-discipline mash-up.

Adventures in Semantic Publishing: Exemplar Semantic Enhancements of a Research Article

PubMed Central

Shotton, David; Portwin, Katie; Klyne, Graham; Miles, Alistair

2009-01-01

Scientific innovation depends on finding, integrating, and re-using the products of previous research. Here we explore how recent developments in Web technology, particularly those related to the publication of data and metadata, might assist that process by providing semantic enhancements to journal articles within the mainstream process of scholarly journal publishing. We exemplify this by describing semantic enhancements we have made to a recent biomedical research article taken from PLoS Neglected Tropical Diseases, providing enrichment to its content and increased access to datasets within it. These semantic enhancements include provision of live DOIs and hyperlinks; semantic markup of textual terms, with links to relevant third-party information resources; interactive figures; a re-orderable reference list; a document summary containing a study summary, a tag cloud, and a citation analysis; and two novel types of semantic enrichment: the first, a Supporting Claims Tooltip to permit “Citations in Context”, and the second, Tag Trees that bring together semantically related terms. In addition, we have published downloadable spreadsheets containing data from within tables and figures, have enriched these with provenance information, and have demonstrated various types of data fusion (mashups) with results from other research articles and with Google Maps. We have also published machine-readable RDF metadata both about the article and about the references it cites, for which we developed a Citation Typing Ontology, CiTO (http://purl.org/net/cito/). The enhanced article, which is available at http://dx.doi.org/10.1371/journal.pntd.0000228.x001, presents a compelling existence proof of the possibilities of semantic publication. We hope the showcase of examples and ideas it contains, described in this paper, will excite the imaginations of researchers and publishers, stimulating them to explore the possibilities of semantic publishing for their own research articles, and thereby break down present barriers to the discovery and re-use of information within traditional modes of scholarly communication. PMID:19381256

Lexical factors and cerebral regions influencing verbal fluency performance in MCI.

PubMed

Clark, D G; Wadley, V G; Kapur, P; DeRamus, T P; Singletary, B; Nicholas, A P; Blanton, P D; Lokken, K; Deshpande, H; Marson, D; Deutsch, G

2014-02-01

To evaluate assumptions regarding semantic (noun), verb, and letter fluency in mild cognitive impairment (MCI) and Alzheimer disease (AD) using novel techniques for measuring word similarity in fluency lists and a region of interest (ROI) analysis of gray matter correlates. Fifty-eight individuals with normal cognition (NC, n=25), MCI (n=23), or AD (n=10) underwent neuropsychological tests, including 10 verbal fluency tasks (three letter tasks [F, A, S], six noun categories [animals, water creatures, fruits and vegetables, tools, vehicles, boats], and verbs). All pairs of words generated by each participant on each task were compared in terms of semantic (meaning), orthographic (spelling), and phonemic (pronunciation) similarity. We used mixed-effects logistic regression to determine which lexical factors were predictive of word adjacency within the lists. Associations between each fluency raw score and gray matter volumes in sixteen ROIs were identified by means of multiple linear regression. We evaluated causal models for both types of analyses to specify the contributions of diagnosis and various mediator variables to the outcomes of word adjacency and fluency raw score. Semantic similarity between words emerged as the strongest predictor of word adjacency for all fluency tasks, including the letter fluency tasks. Semantic similarity mediated the effect of cognitive impairment on word adjacency only for three fluency tasks employing a biological cue. Orthographic similarity was predictive of word adjacency for the A and S tasks, while phonemic similarity was predictive only for the S task and one semantic task (vehicles). The ROI analysis revealed different patterns of correlations among the various fluency tasks, with the most common associations in the right lower temporal and bilateral dorsal frontal regions. Following correction with gray matter volumes from the opposite hemisphere, significant associations persisted for animals, vehicles, and a composite nouns score in the left inferior frontal gyrus, but for letter A, letter S, and a composite FAS score in the right inferior frontal gyrus. These regressions also revealed a lateralized association of the left subcortical nuclei with all letter fluency scores and fruits and vegetables fluency, and an association of the right lower temporal ROI with letter A, FAS, and verb fluency. Gray matter volume in several bihemispheric ROIs (left dorsal frontal, right lower temporal, right occipital, and bilateral mesial temporal) mediated the relationship between cognitive impairment and fluency for fruits and vegetables. Gray matter volume in the right lower temporal ROI mediated the relationship between cognitive impairment and five fluency raw scores (animals, fruits and vegetables, tools, verbs, and the composite nouns score). Semantic memory exerts the strongest influence on word adjacency in letter fluency as well as semantic verbal fluency tasks. Orthography is a stronger influence than pronunciation. All types of fluency task raw scores (letter, noun, and verb) correlate with cerebral regions known to support verbal or nonverbal semantic memory. The findings emphasize the contribution of right hemisphere regions to fluency task performance, particularly for verb and letter fluency. The relationship between diagnosis and semantic fluency performance is mediated by semantic similarity of words and by gray matter volume in the right lower temporal region. Published by Elsevier Ltd.

The Role of Semantic Diversity in Word Recognition across Aging and Bilingualism

PubMed Central

Johns, Brendan T.; Sheppard, Christine L.; Jones, Michael N.; Taler, Vanessa

2016-01-01

Frequency effects are pervasive in studies of language, with higher frequency words being recognized faster than lower frequency words. However, the exact nature of frequency effects has recently been questioned, with some studies finding that contextual information provides a better fit to lexical decision and naming data than word frequency (Adelman et al., 2006). Recent work has cemented the importance of these results by demonstrating that a measure of the semantic diversity of the contexts that a word occurs in provides a powerful measure to account for variability in word recognition latency (Johns et al., 2012, 2015; Jones et al., 2012). The goal of the current study is to extend this measure to examine bilingualism and aging, where multiple theories use frequency of occurrence of linguistic constructs as central to accounting for empirical results (Gollan et al., 2008; Ramscar et al., 2014). A lexical decision experiment was conducted with four groups of subjects: younger and older monolinguals and bilinguals. Consistent with past results, a semantic diversity variable accounted for the greatest amount of variance in the latency data. In addition, the pattern of fits of semantic diversity across multiple corpora suggests that bilinguals and older adults are more sensitive to semantic diversity information than younger monolinguals. PMID:27458392

The effects of rehearsal on the functional neuroanatomy of episodic autobiographical and semantic remembering: an fMRI study

PubMed Central

Svoboda, Eva; Levine, Brian

2009-01-01

This study examined the effects of rehearsal on the neural substrates supporting episodic autobiographical and semantic memory. Stimuli were collected prospectively using audio recordings, thereby bringing under experimental control ecologically-valid, naturalistic autobiographical stimuli. Participants documented both autobiographical and semantic stimuli over a period of 6 to 8 months, followed by a rehearsal manipulation during the three days preceding scanning. During fMRI scanning participants were exposed to recordings that they were hearing for the first, second or eighth time. Rehearsal increased the rated vividness with which information was remembered, particularly for autobiographical events. Neuroimaging findings revealed rehearsal-related suppression of activation in regions supporting episodic autobiographical and semantic memory. Episodic autobiographical and semantic memory produced distinctly different patterns of regional activation that held even after eight repetitions. Region of interest analyses further indicated a functional anatomical dissociation in response to rehearsal and memory conditions. These findings revealed that the hippocampus was specifically engaged by episodic autobiographical memory, whereas both memory conditions engaged the parahippocampal cortex. Our data suggest that when retrieval cues are potent enough to engage a vivid episodic recollection, the episodic/semantic dissociation within medial temporal lobe structures endure even with multiple stimulus repetitions. These findings support the Multiple Trace Theory (MTT) which predicts that the hippocampus is engaged in the retrieval of rich episodic recollection regardless of repeated reactivation such as that occurring with the passage of time. PMID:19279244

The effects of rehearsal on the functional neuroanatomy of episodic autobiographical and semantic remembering: a functional magnetic resonance imaging study.

PubMed

Svoboda, Eva; Levine, Brian

2009-03-11

This study examined the effects of rehearsal on the neural substrates supporting episodic autobiographical and semantic memory. Stimuli were collected prospectively using audio recordings, thereby bringing under experimental control ecologically valid, naturalistic autobiographical stimuli. Participants documented both autobiographical and semantic stimuli over a period of 6-8 months, followed by a rehearsal manipulation during the 3 d preceding scanning. During functional magnetic resonance imaging scanning, participants were exposed to recordings that they were hearing for the first, second, or eighth time. Rehearsal increased the rated vividness with which information was remembered, particularly for autobiographical events. Neuroimaging findings revealed rehearsal-related suppression of activation in regions supporting episodic autobiographical and semantic memory. Episodic autobiographical and semantic memory produced distinctly different patterns of regional activation that held even after eight repetitions. Region of interest analyses further indicated a functional anatomical dissociation in response to rehearsal and memory conditions. These findings revealed that the hippocampus was specifically engaged by episodic autobiographical memory, whereas both memory conditions engaged the parahippocampal cortex. Our data suggest that, when retrieval cues are potent enough to engage a vivid episodic recollection, the episodic/semantic dissociation within medial temporal lobe structures endure even with multiple stimulus repetitions. These findings support the multiple trace theory, which predicts that the hippocampus is engaged in the retrieval of rich episodic recollection regardless of repeated reactivation such as that occurring with the passage of time.

Semantic and Thematic List Learning of Second Language Vocabulary

ERIC Educational Resources Information Center

Gholami, Javad; Khezrlou, Sima

2014-01-01

This article overviews research on second language vocabulary instruction with a specific focus on semantic and thematic vocabulary-clustering types. The theoretical benefits associated with both the semantic and thematic approaches, as well as the potential problems associated with them, are discussed. The conclusion drawn is that reinforcing the…

The Influence of Semantic Property and Grammatical Class on Semantic Selection

ERIC Educational Resources Information Center

Yang, Fan-pei Gloria; Khodaparast, Navid; Bradley, Kailyn; Fang, Min-Chieh; Bernstein, Ari; Krawczyk, Daniel C.

2013-01-01

Research to-date has not successfully demonstrated consistent neural distinctions for different types of ambiguity or explored the effect of grammatical class on semantic selection. We conducted a relatedness judgment task using event-related functional magnetic resonance imaging (fMRI) to further explore these topics. Participants judged…

The Grammar of Mental Predicates in Japanese.

ERIC Educational Resources Information Center

Onishi, Masayuki

1997-01-01

Examines Japanese equivalents of the six mental predicates defined as semantic universals in Natural Semantic Metalanguage theory, with special attention to syntax and semantics of complementation types. It is shown that each primitive predicate has a specific set of syntactic frames for expressing primitive meaning and that extended meanings that…

SoyBase Simple Semantic Web Architecture and Protocol (SSWAP) Services

USDA-ARS?s Scientific Manuscript database

Semantic web technologies offer the potential to link internet resources and data by shared concepts without having to rely on absolute lexical matches. Thus two web sites or web resources which are concerned with similar data types could be identified based on similar semantics. In the biological...

Modelling the Effects of Semantic Ambiguity in Word Recognition

ERIC Educational Resources Information Center

Rodd, Jennifer M.; Gaskell, M. Gareth; Marslen-Wilson, William D.

2004-01-01

Most words in English are ambiguous between different interpretations; words can mean different things in different contexts. We investigate the implications of different types of semantic ambiguity for connectionist models of word recognition. We present a model in which there is competition to activate distributed semantic representations. The…

Integrating a Hypernymic Proposition Interpreter into a Semantic Processor for Biomedical Texts

PubMed Central

Fiszman, Marcelo; Rindflesch, Thomas C.; Kilicoglu, Halil

2003-01-01

Semantic processing provides the potential for producing high quality results in natural language processing (NLP) applications in the biomedical domain. In this paper, we address a specific semantic phenomenon, the hypernymic proposition, and concentrate on integrating the interpretation of such predications into a more general semantic processor in order to improve overall accuracy. A preliminary evaluation assesses the contribution of hypernymic propositions in providing more specific semantic predications and thus improving effectiveness in retrieving treatment propositions in MEDLINE abstracts. Finally, we discuss the generalization of this methodology to additional semantic propositions as well as other types of biomedical texts. PMID:14728170

Solving Multiple Isolated, Interleaved, and Blended Tasks through Modular Neuroevolution.

PubMed

Schrum, Jacob; Miikkulainen, Risto

2016-01-01

Many challenging sequential decision-making problems require agents to master multiple tasks. For instance, game agents may need to gather resources, attack opponents, and defend against attacks. Learning algorithms can thus benefit from having separate policies for these tasks, and from knowing when each one is appropriate. How well this approach works depends on how tightly coupled the tasks are. Three cases are identified: Isolated tasks have distinct semantics and do not interact, interleaved tasks have distinct semantics but do interact, and blended tasks have regions where semantics from multiple tasks overlap. Learning across multiple tasks is studied in this article with Modular Multiobjective NEAT, a neuroevolution framework applied to three variants of the challenging Ms. Pac-Man video game. In the standard blended version of the game, a surprising, highly effective machine-discovered task division surpasses human-specified divisions, achieving the best scores to date in this game. In isolated and interleaved versions of the game, human-specified task divisions are also successful, though the best scores are surprisingly still achieved by machine discovery. Modular neuroevolution is thus shown to be capable of finding useful, unexpected task divisions better than those apparent to a human designer.

Rapid Parallel Semantic Processing of Numbers without Awareness

ERIC Educational Resources Information Center

Van Opstal, Filip; de Lange, Floris P.; Dehaene, Stanislas

2011-01-01

In this study, we investigate whether multiple digits can be processed at a semantic level without awareness, either serially or in parallel. In two experiments, we presented participants with two successive sets of four simultaneous Arabic digits. The first set was masked and served as a subliminal prime for the second, visible target set.…

Effects of Semantic Ambiguity Detection Training on Reading Comprehension Achievement of English Learners with Learning Difficulties

ERIC Educational Resources Information Center

Jozwik, Sara L.; Douglas, Karen H.

2016-01-01

This study examined how explicit instruction in semantic ambiguity detection affected the reading comprehension and metalinguistic awareness of five English learners (ELs) with learning difficulties (e.g., attention deficit/hyperactivity disorder, specific learning disability). A multiple probe across participants design (Gast & Ledford, 2010)…

The Language Environment and Syntactic Word-Class Acquisition.

ERIC Educational Resources Information Center

Zavrel, Jakub; Veenstra, Jorn

A study analyzed the distribution of words in a three-million-word corpus of text from the "Wall Street Journal," in order to test a theory of the acquisition of word categories. The theory, an alternative to the semantic bootstrapping hypothesis, proposes that the child exploits multiple sources of cues (distributional, semantic, or…

Personal semantic memory: insights from neuropsychological research on amnesia.

PubMed

Grilli, Matthew D; Verfaellie, Mieke

2014-08-01

This paper provides insight into the cognitive and neural mechanisms of personal semantic memory, knowledge that is specific and unique to individuals, by reviewing neuropsychological research on stable amnesia secondary to medial temporal lobe damage. The results reveal that personal semantic memory does not depend on a unitary set of cognitive and neural mechanisms. Findings show that autobiographical fact knowledge reflects an experience-near type of personal semantic memory that relies on the medial temporal lobe for retrieval, albeit less so than personal episodic memory. Additional evidence demonstrates that new autobiographical fact learning likely relies on the medial temporal lobe, but the extent to which remains unclear. Other findings show that retrieval of personal traits/roles and new learning of personal traits/roles and thoughts/beliefs are independent of the medial temporal lobe and thus may represent highly conceptual types of personal semantic memory that are stored in the neocortex. Published by Elsevier Ltd.

A Tri-network Model of Human Semantic Processing

PubMed Central

Xu, Yangwen; He, Yong; Bi, Yanchao

2017-01-01

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. PMID:28955266

The role of the right hemisphere in semantic control: A case-series comparison of right and left hemisphere stroke

PubMed Central

Thompson, Hannah E.; Henshall, Lauren; Jefferies, Elizabeth

2016-01-01

Semantic control processes guide conceptual retrieval so that we are able to focus on non-dominant associations and features when these are required for the task or context, yet the neural basis of semantic control is not fully understood. Neuroimaging studies have emphasised the role of left inferior frontal gyrus (IFG) in controlled retrieval, while neuropsychological investigations of semantic control deficits have almost exclusively focussed on patients with left-sided damage (e.g., patients with semantic aphasia, SA). Nevertheless, activation in fMRI during demanding semantic tasks typically extends to right IFG. To investigate the role of the right hemisphere (RH) in semantic control, we compared nine RH stroke patients with 21 left-hemisphere SA patients, 11 mild SA cases and 12 healthy, aged-matched controls on semantic and executive tasks, plus experimental tasks that manipulated semantic control in paradigms particularly sensitive to RH damage. RH patients had executive deficits to parallel SA patients but they performed well on standard semantic tests. Nevertheless, multimodal semantic control deficits were found in experimental tasks involving facial emotions and the ‘summation’ of meaning across multiple items. On these tasks, RH patients showed effects similar to those in SA cases – multimodal deficits that were sensitive to distractor strength and cues and miscues, plus increasingly poor performance in cyclical matching tasks which repeatedly probed the same set of concepts. Thus, despite striking differences in single-item comprehension, evidence presented here suggests semantic control is bilateral, and disruption of this component of semantic cognition can be seen following damage to either hemisphere. PMID:26945505

SciFlo: Semantically-Enabled Grid Workflow for Collaborative Science

NASA Astrophysics Data System (ADS)

Yunck, T.; Wilson, B. D.; Raskin, R.; Manipon, G.

2005-12-01

SciFlo is a system for Scientific Knowledge Creation on the Grid using a Semantically-Enabled Dataflow Execution Environment. SciFlo leverages Simple Object Access Protocol (SOAP) Web Services and the Grid Computing standards (WS-* standards and the Globus Alliance toolkits), and enables scientists to do multi-instrument Earth Science by assembling reusable SOAP Services, native executables, local command-line scripts, and python codes into a distributed computing flow (a graph of operators). SciFlo's XML dataflow documents can be a mixture of concrete operators (fully bound operations) and abstract template operators (late binding via semantic lookup). All data objects and operators can be both simply typed (simple and complex types in XML schema) and semantically typed using controlled vocabularies (linked to OWL ontologies such as SWEET). By exploiting ontology-enhanced search and inference, one can discover (and automatically invoke) Web Services and operators that have been semantically labeled as performing the desired transformation, and adapt a particular invocation to the proper interface (number, types, and meaning of inputs and outputs). The SciFlo client & server engines optimize the execution of such distributed data flows and allow the user to transparently find and use datasets and operators without worrying about the actual location of the Grid resources. The scientist injects a distributed computation into the Grid by simply filling out an HTML form or directly authoring the underlying XML dataflow document, and results are returned directly to the scientist's desktop. A Visual Programming tool is also being developed, but it is not required. Once an analysis has been specified for a granule or day of data, it can be easily repeated with different control parameters and over months or years of data. SciFlo uses and preserves semantics, and also generates and infers new semantic annotations. Specifically, the SciFlo engine uses semantic metadata to understand (infer) what it is doing and potentially improve the data flow; preserves semantics by saving links to the semantics of (metadata describing) the input datasets, related datasets, and the data transformations (algorithms) used to generate downstream products; generates new metadata by allowing the user to add semantic annotations to the generated data products (or simply accept automatically generated provenance annotations); and infers new semantic metadata by understanding and applying logic to the semantics of the data and the transformations performed. Much ontology development still needs to be done but, nevertheless, SciFlo documents provide a substrate for using and preserving more semantics as ontologies develop. We will give a live demonstration of the growing SciFlo network using an example dataflow in which atmospheric temperature and water vapor profiles from three Earth Observing System (EOS) instruments are retrieved using SOAP (geo-location query & data access) services, co-registered, and visually & statistically compared on demand (see http://sciflo.jpl.nasa.gov for more information).

Selective Audiovisual Semantic Integration Enabled by Feature-Selective Attention.

PubMed

Li, Yuanqing; Long, Jinyi; Huang, Biao; Yu, Tianyou; Wu, Wei; Li, Peijun; Fang, Fang; Sun, Pei

2016-01-13

An audiovisual object may contain multiple semantic features, such as the gender and emotional features of the speaker. Feature-selective attention and audiovisual semantic integration are two brain functions involved in the recognition of audiovisual objects. Humans often selectively attend to one or several features while ignoring the other features of an audiovisual object. Meanwhile, the human brain integrates semantic information from the visual and auditory modalities. However, how these two brain functions correlate with each other remains to be elucidated. In this functional magnetic resonance imaging (fMRI) study, we explored the neural mechanism by which feature-selective attention modulates audiovisual semantic integration. During the fMRI experiment, the subjects were presented with visual-only, auditory-only, or audiovisual dynamical facial stimuli and performed several feature-selective attention tasks. Our results revealed that a distribution of areas, including heteromodal areas and brain areas encoding attended features, may be involved in audiovisual semantic integration. Through feature-selective attention, the human brain may selectively integrate audiovisual semantic information from attended features by enhancing functional connectivity and thus regulating information flows from heteromodal areas to brain areas encoding the attended features.

Semantic deficits in Spanish-English bilingual children with language impairment.

PubMed

Sheng, Li; Peña, Elizabeth D; Bedore, Lisa M; Fiestas, Christine E

2012-02-01

To examine the nature and extent of semantic deficits in bilingual children with language impairment (LI). Thirty-seven Spanish-English bilingual children with LI (ranging from age 7;0 [years;months] to 9;10) and 37 typically developing (TD) age-matched peers generated 3 associations to 12 pairs of translation equivalents in English and Spanish. Responses were coded as paradigmatic (e.g., dinner-lunch, cena-desayuno [dinner-breakfast]), syntagmatic (e.g., delicious-pizza, delicioso-frijoles [delicious-beans]), and errors (e.g., wearing-where, vestirse-mal [to get dressed-bad]). A semantic depth score was derived in each language and conceptually by combining children's performance in both languages. The LI group achieved significantly lower semantic depth scores than the TD group after controlling for group differences in vocabulary size. Children showed higher conceptual scores than single-language scores. Both groups showed decreases in semantic depth scores across multiple elicitations. Analyses of individual performances indicated that semantic deficits (1 SD below the TD mean semantic depth score) were manifested in 65% of the children with LI and in 14% of the TD children. School-age bilingual children with and without LI demonstrated spreading activation of semantic networks. Consistent with the literature on monolingual children with LI, sparsely linked semantic networks characterize a considerable proportion of bilingual children with LI.

The Local Geometry of Multiattribute Tradeoff Preferences

PubMed Central

McGeachie, Michael; Doyle, Jon

2011-01-01

Existing representations for multiattribute ceteris paribus preference statements have provided useful treatments and clear semantics for qualitative comparisons, but have not provided similarly clear representations or semantics for comparisons involving quantitative tradeoffs. We use directional derivatives and other concepts from elementary differential geometry to interpret conditional multiattribute ceteris paribus preference comparisons that state bounds on quantitative tradeoff ratios. This semantics extends the familiar economic notion of marginal rate of substitution to multiple continuous or discrete attributes. The same geometric concepts also provide means for interpreting statements about the relative importance of different attributes. PMID:21528018

Semantic Categorization and Reading Skill across Dutch Primary Grades: Development Yes, Relationship No

ERIC Educational Resources Information Center

Gijsel, Martine A. R.; Ormel, Ellen A.; Hermans, Daan; Verhoeven, L.; Bosman, Anna M. T.

2011-01-01

In the present study, the development of semantic categorization and its relationship with reading was investigated across Dutch primary grade students. Three Exemplar-level tasks (Experiment 1) and two Superordinate-level tasks (Experiment 2) with different types of distracters (phonological, semantic and perceptual) were administered to assess…

Practical Experiences for the Development of Educational Systems in the Semantic Web

ERIC Educational Resources Information Center

Sánchez Vera, Ma. del Mar; Tomás Fernández Breis, Jesualdo; Serrano Sánchez, José Luis; Prendes Espinosa, Ma. Paz

2013-01-01

Semantic Web technologies have been applied in educational settings for different purposes in recent years, with the type of application being mainly defined by the way in which knowledge is represented and exploited. The basic technology for knowledge representation in Semantic Web settings is the ontology, which represents a common, shareable…

Cross-language parafoveal semantic processing: Evidence from Korean-Chinese bilinguals.

PubMed

Wang, Aiping; Yeon, Junmo; Zhou, Wei; Shu, Hua; Yan, Ming

2016-02-01

In the present study, we aimed at testing cross-language cognate and semantic preview effects. We tested how native Korean readers who learned Chinese as a second language make use of the parafoveal information during the reading of Chinese sentences. There were 3 types of Korean preview words: cognate translations of the Chinese target words, semantically related noncognate words, and unrelated words. Together with a highly significant cognate preview effect, more critically, we also observed reliable facilitation in processing of the target word from the semantically related previews in all fixation measures. Results from the present study provide first evidence for semantic processing from parafoveally presented Korean words and for cross-language parafoveal semantic processing.

Children and adolescents' performance on a medium-length/nonsemantic word-list test.

PubMed

Flores-Lázaro, Julio César; Salgado Soruco, María Alejandra; Stepanov, Igor I

2017-01-01

Word-list learning tasks are among the most important and frequently used tests for declarative memory evaluation. For example, the California Verbal Learning Test-Children's Version (CVLT-C) and Rey Auditory Verbal Learning Test provide important information about different cognitive-neuropsychological processes. However, the impact of test length (i.e., number of words) and semantic organization (i.e., type of words) on children's and adolescents' memory performance remains to be clarified, especially during this developmental stage. To explore whether a medium-length non-semantically organized test can produce the typical curvilinear performance that semantically organized tests produce, reflecting executive control, we studied and compared the cognitive performance of normal children and adolescents by utilizing mathematical modeling. The model is based on the first-order system transfer function and has been successfully applied to learning curves for the CVLT-C (15 words, semantically organized paradigm). Results indicate that learning nine semantically unrelated words produces typical curvilinear (executive function) performance in children and younger adolescents and that performance could be effectively analyzed with the mathematical model. This indicates that the exponential increase (curvilinear performance) of correctly learned words does not solely depend on semantic and/or length features. This type of test controls semantic and length effects and may represent complementary tools for executive function evaluation in clinical populations in which semantic and/or length processing are affected.

Syntactic, Semantic and Pragmatic Correlates of the Acquisition of Exhaustivity in "Wh"-Questions: A Study of Polish Monolingual Children

ERIC Educational Resources Information Center

Forys-Nogala, Malgorzata; Haman, Ewa; Katsos, Napoleon; Krajewski, Grzegorz; Schulz, Petra

2017-01-01

This study investigates relationships between acquisition of exhaustivity in single and multiple "wh"-questions, mastery of semantic and pragmatic aspects of quantifier comprehension, and general skills in receptive grammar. The participants of the study were 25 Polish monolingual typically developing children aged 4;02-6;02, who were…

A semantic medical multimedia retrieval approach using ontology information hiding.

PubMed

Guo, Kehua; Zhang, Shigeng

2013-01-01

Searching useful information from unstructured medical multimedia data has been a difficult problem in information retrieval. This paper reports an effective semantic medical multimedia retrieval approach which can reflect the users' query intent. Firstly, semantic annotations will be given to the multimedia documents in the medical multimedia database. Secondly, the ontology that represented semantic information will be hidden in the head of the multimedia documents. The main innovations of this approach are cross-type retrieval support and semantic information preservation. Experimental results indicate a good precision and efficiency of our approach for medical multimedia retrieval in comparison with some traditional approaches.

Automatic Semantic Facilitation in Anterior Temporal Cortex Revealed through Multimodal Neuroimaging

PubMed Central

Gramfort, Alexandre; Hämäläinen, Matti S.; Kuperberg, Gina R.

2013-01-01

A core property of human semantic processing is the rapid, facilitatory influence of prior input on extracting the meaning of what comes next, even under conditions of minimal awareness. Previous work has shown a number of neurophysiological indices of this facilitation, but the mapping between time course and localization—critical for separating automatic semantic facilitation from other mechanisms—has thus far been unclear. In the current study, we used a multimodal imaging approach to isolate early, bottom-up effects of context on semantic memory, acquiring a combination of electroencephalography (EEG), magnetoencephalography (MEG), and functional magnetic resonance imaging (fMRI) measurements in the same individuals with a masked semantic priming paradigm. Across techniques, the results provide a strikingly convergent picture of early automatic semantic facilitation. Event-related potentials demonstrated early sensitivity to semantic association between 300 and 500 ms; MEG localized the differential neural response within this time window to the left anterior temporal cortex, and fMRI localized the effect more precisely to the left anterior superior temporal gyrus, a region previously implicated in semantic associative processing. However, fMRI diverged from early EEG/MEG measures in revealing semantic enhancement effects within frontal and parietal regions, perhaps reflecting downstream attempts to consciously access the semantic features of the masked prime. Together, these results provide strong evidence that automatic associative semantic facilitation is realized as reduced activity within the left anterior superior temporal cortex between 300 and 500 ms after a word is presented, and emphasize the importance of multimodal neuroimaging approaches in distinguishing the contributions of multiple regions to semantic processing. PMID:24155321

When fruits lose to animals: Disorganized search of semantic memory in Parkinson's disease.

PubMed

Tagini, Sofia; Seyed-Allaei, Shima; Scarpina, Federica; Toraldo, Alessio; Mauro, Alessandro; Cherubini, Paolo; Reverberi, Carlo

2018-04-16

The semantic fluency task is widely used in both clinical and research settings to assess both the integrity of the semantic store and the effectiveness of the search through it. Our aim was to investigate whether nondemented Parkinson's disease (PD) patients show an impairment in the strategic exploration of the semantic store and whether the tested semantic category has an impact on multiple measures of performance. We compared 74 nondemented PD patients with 254 healthy subjects in a semantic fluency test using relatively small (fruits) and large (animals) semantic categories. Number of words produced, number of explored semantic subcategories, and degree of order in the produced sequences were computed as dependent variables. PD patients produced fewer words than healthy subjects did, regardless of the category. Number of subcategories was also lower in PD patients than in healthy subjects, without a significant difference between categories. Critically, PD patients' sequences were less semantically organized than were those of controls, but this effect appeared in only the smaller category (fruits), thus pointing to a lack of strategy in exploring the semantic store. Our results show that the semantic fluency deficit in PD patients has a strategic component, even though that may not be the only cause of the impaired performance. Furthermore, our evidence suggests that the semantic category used in the test influences performance, hence providing an explanation for the failure by previous studies, which often used large categories such as animals, to detect strategy deficits in PD. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Expressing Intervals in Automated Service Negotiation

NASA Astrophysics Data System (ADS)

Clark, Kassidy P.; Warnier, Martijn; van Splunter, Sander; Brazier, Frances M. T.

During automated negotiation of services between autonomous agents, utility functions are used to evaluate the terms of negotiation. These terms often include intervals of values which are prone to misinterpretation. It is often unclear if an interval embodies a continuum of real numbers or a subset of natural numbers. Furthermore, it is often unclear if an agent is expected to choose only one value, multiple values, a sub-interval or even multiple sub-intervals. Additional semantics are needed to clarify these issues. Normally, these semantics are stored in a domain ontology. However, ontologies are typically domain specific and static in nature. For dynamic environments, in which autonomous agents negotiate resources whose attributes and relationships change rapidly, semantics should be made explicit in the service negotiation. This paper identifies issues that are prone to misinterpretation and proposes a notation for expressing intervals. This notation is illustrated using an example in WS-Agreement.

Lexical access changes in patients with multiple sclerosis: a two-year follow-up study.

PubMed

Sepulcre, Jorge; Peraita, Herminia; Goni, Joaquin; Arrondo, Gonzalo; Martincorena, Inigo; Duque, Beatriz; Velez de Mendizabal, Nieves; Masdeu, Joseph C; Villoslada, Pablo

2011-02-01

The aim of the study was to analyze lexical access strategies in patients with multiple sclerosis (MS) and their changes over time. We studied lexical access strategies during semantic and phonemic verbal fluency tests and also confrontation naming in a 2-year prospective cohort of 45 MS patients and 20 healthy controls. At baseline, switching lexical access strategy (both in semantic and in phonemic verbal fluency tests) and confrontation naming were significantly impaired in MS patients compared with controls. After 2 years follow-up, switching score decreased, and cluster size increased over time in semantic verbal fluency tasks, suggesting a failure in the retrieval of lexical information rather than an impairment of the lexical pool. In conclusion, these findings underline the significant presence of lexical access problems in patients with MS and could point out their key role in the alterations of high-level communications abilities in MS.

Semantic and phonological information in sentence recall: converging psycholinguistic and neuropsychological evidence.

PubMed

Schweppe, Judith; Rummer, Ralf; Bormann, Tobias; Martin, Randi C

2011-12-01

We present one experiment and a neuropsychological case study to investigate to what extent phonological and semantic representations contribute to short-term sentence recall. We modified Potter and Lombardi's (1990) intrusion paradigm, in which retention of a list interferes with sentence recall such that on the list a semantically related lure is presented, which is expected to intrude into sentence recall. In our version, lure words are either semantically related to target words in the sentence or semantically plus phonologically related. With healthy participants, intrusions are more frequent when lure and target overlap phonologically in addition to semantically than when they solely overlap semantically. When this paradigm is applied to a patient with a phonological short-term memory impairment, both lure types induce the same amount of intrusions. These findings indicate that usually phonological information is retained in sentence recall in addition to semantic information.

Integrated Japanese Dependency Analysis Using a Dialog Context

NASA Astrophysics Data System (ADS)

Ikegaya, Yuki; Noguchi, Yasuhiro; Kogure, Satoru; Itoh, Toshihiko; Konishi, Tatsuhiro; Kondo, Makoto; Asoh, Hideki; Takagi, Akira; Itoh, Yukihiro

This paper describes how to perform syntactic parsing and semantic analysis in a dialog system. The paper especially deals with how to disambiguate potentially ambiguous sentences using the contextual information. Although syntactic parsing and semantic analysis are often studied independently of each other, correct parsing of a sentence often requires the semantic information on the input and/or the contextual information prior to the input. Accordingly, we merge syntactic parsing with semantic analysis, which enables syntactic parsing taking advantage of the semantic content of an input and its context. One of the biggest problems of semantic analysis is how to interpret dependency structures. We employ a framework for semantic representations that circumvents the problem. Within the framework, the meaning of any predicate is converted into a semantic representation which only permits a single type of predicate: an identifying predicate "aru". The semantic representations are expressed as sets of "attribute-value" pairs, and those semantic representations are stored in the context information. Our system disambiguates syntactic/semantic ambiguities of inputs referring to the attribute-value pairs in the context information. We have experimentally confirmed the effectiveness of our approach; specifically, the experiment confirmed high accuracy of parsing and correctness of generated semantic representations.

Enhancing acronym/abbreviation knowledge bases with semantic information.

PubMed

Torii, Manabu; Liu, Hongfang

2007-10-11

In the biomedical domain, a terminology knowledge base that associates acronyms/abbreviations (denoted as SFs) with the definitions (denoted as LFs) is highly needed. For the construction such terminology knowledge base, we investigate the feasibility to build a system automatically assigning semantic categories to LFs extracted from text. Given a collection of pairs (SF,LF) derived from text, we i) assess the coverage of LFs and pairs (SF,LF) in the UMLS and justify the need of a semantic category assignment system; and ii) automatically derive name phrases annotated with semantic category and construct a system using machine learning. Utilizing ADAM, an existing collection of (SF,LF) pairs extracted from MEDLINE, our system achieved an f-measure of 87% when assigning eight UMLS-based semantic groups to LFs. The system has been incorporated into a web interface which integrates SF knowledge from multiple SF knowledge bases. Web site: http://gauss.dbb.georgetown.edu/liblab/SFThesurus.

The role of the right hemisphere in semantic control: A case-series comparison of right and left hemisphere stroke.

PubMed

Thompson, Hannah E; Henshall, Lauren; Jefferies, Elizabeth

2016-05-01

Semantic control processes guide conceptual retrieval so that we are able to focus on non-dominant associations and features when these are required for the task or context, yet the neural basis of semantic control is not fully understood. Neuroimaging studies have emphasised the role of left inferior frontal gyrus (IFG) in controlled retrieval, while neuropsychological investigations of semantic control deficits have almost exclusively focussed on patients with left-sided damage (e.g., patients with semantic aphasia, SA). Nevertheless, activation in fMRI during demanding semantic tasks typically extends to right IFG. To investigate the role of the right hemisphere (RH) in semantic control, we compared nine RH stroke patients with 21 left-hemisphere SA patients, 11 mild SA cases and 12 healthy, aged-matched controls on semantic and executive tasks, plus experimental tasks that manipulated semantic control in paradigms particularly sensitive to RH damage. RH patients had executive deficits to parallel SA patients but they performed well on standard semantic tests. Nevertheless, multimodal semantic control deficits were found in experimental tasks involving facial emotions and the 'summation' of meaning across multiple items. On these tasks, RH patients showed effects similar to those in SA cases - multimodal deficits that were sensitive to distractor strength and cues and miscues, plus increasingly poor performance in cyclical matching tasks which repeatedly probed the same set of concepts. Thus, despite striking differences in single-item comprehension, evidence presented here suggests semantic control is bilateral, and disruption of this component of semantic cognition can be seen following damage to either hemisphere. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Semantic and visual memory codes in learning disabled readers.

PubMed

Swanson, H L

1984-02-01

Two experiments investigated whether learning disabled readers' impaired recall is due to multiple coding deficiencies. In Experiment 1, learning disabled and skilled readers viewed nonsense pictures without names or with either relevant or irrelevant names with respect to the distinctive characteristics of the picture. Both types of names improved recall of nondisabled readers, while learning disabled readers exhibited better recall for unnamed pictures. No significant difference in recall was found between name training (relevant, irrelevant) conditions within reading groups. In Experiment 2, both reading groups participated in recall training for complex visual forms labeled with unrelated words, hierarchically related words, or without labels. A subsequent reproduction transfer task showed a facilitation in performance in skilled readers due to labeling, with learning disabled readers exhibiting better reproduction for unnamed pictures. Measures of output organization (clustering) indicated that recall is related to the development of superordinate categories. The results suggest that learning disabled children's reading difficulties are due to an inability to activate a semantic representation that interconnects visual and verbal codes.

Selective impairment of masked priming in dual-task performance.

PubMed

Fischer, Rico; Kiesel, Andrea; Kunde, Wilfried; Schubert, Torsten

2011-03-01

This study investigated the impact of divided attention on masked priming. In a dual-task setting, two tasks had to be carried out in close temporal succession: a tone discrimination task and a masked priming task. The order of the tasks was varied between experiments, and attention was always allocated to the first task-that is, the first task was prioritized. The priming task was the second (nonprioritized) task in Experiment 1 and the first (prioritized) task in Experiment 2. In both experiments, "novel" prime stimuli associated with semantic processing were essentially ineffective. However, there was intact priming by another type of prime stimuli associated with response priming. Experiment 3 showed that all these prime stimuli can reveal significant priming effects during a task-switching paradigm in which both tasks were performed consecutively. We conclude that dual-task specific interference processes (e.g., the simultaneous coordination of multiple stimulus-response rules) selectively impair priming that is assumed to rely on semantic processing.

Concomitant use of the matrix strategy and the mand-model procedure in teaching graphic symbol combinations.

PubMed

Nigam, Ravi; Schlosser, Ralf W; Lloyd, Lyle L

2006-09-01

Matrix strategies employing parts of speech arranged in systematic language matrices and milieu language teaching strategies have been successfully used to teach word combining skills to children who have cognitive disabilities and some functional speech. The present study investigated the acquisition and generalized production of two-term semantic relationships in a new population using new types of symbols. Three children with cognitive disabilities and little or no functional speech were taught to combine graphic symbols. The matrix strategy and the mand-model procedure were used concomitantly as intervention procedures. A multiple probe design across sets of action-object combinations with generalization probes of untrained combinations was used to teach the production of graphic symbol combinations. Results indicated that two of the three children learned the early syntactic-semantic rule of combining action-object symbols and demonstrated generalization to untrained action-object combinations and generalization across trainers. The results and future directions for research are discussed.

Action semantics: A unifying conceptual framework for the selective use of multimodal and modality-specific object knowledge

NASA Astrophysics Data System (ADS)

van Elk, Michiel; van Schie, Hein; Bekkering, Harold

2014-06-01

Our capacity to use tools and objects is often considered one of the hallmarks of the human species. Many objects greatly extend our bodily capabilities to act in the physical world, such as when using a hammer or a saw. In addition, humans have the remarkable capability to use objects in a flexible fashion and to combine multiple objects in complex actions. We prepare coffee, cook dinner and drive our car. In this review we propose that humans have developed declarative and procedural knowledge, i.e. action semantics that enables us to use objects in a meaningful way. A state-of-the-art review of research on object use is provided, involving behavioral, developmental, neuropsychological and neuroimaging studies. We show that research in each of these domains is characterized by similar discussions regarding (1) the role of object affordances, (2) the relation between goals and means in object use and (3) the functional and neural organization of action semantics. We propose a novel conceptual framework of action semantics to address these issues and to integrate the previous findings. We argue that action semantics entails both multimodal object representations and modality-specific sub-systems, involving manipulation knowledge, functional knowledge and representations of the sensory and proprioceptive consequences of object use. Furthermore, we argue that action semantics are hierarchically organized and selectively activated and used depending on the action intention of the actor and the current task context. Our framework presents an integrative account of multiple findings and perspectives on object use that may guide future studies in this interdisciplinary domain.

A new semantic vigilance task: vigilance decrement, workload, and sensitivity to dual-task costs.

PubMed

Epling, Samantha L; Russell, Paul N; Helton, William S

2016-01-01

Cognitive resource theory is a common explanation for both the performance decline in vigilance tasks, known as the vigilance decrement, and the limited ability to perform multiple tasks simultaneously. The limited supply of cognitive resources may be utilized faster than they are replenished resulting in a performance decrement, or may need to be allocated among multiple tasks with some performance cost. Researchers have proposed both domain-specific, for example spatial versus verbal processing resources, and domain general cognitive resources. One challenge in testing the domain specificity of cognitive resources in vigilance is the current lack of difficult semantic vigilance tasks which reliably produce a decrement. In the present research, we investigated whether the vigilance decrement was found in a new abbreviated semantic discrimination vigilance task, and whether there was a performance decrement in said vigilance task when paired with a word recall task, as opposed to performed individually. As hypothesized, a vigilance decrement in the semantic vigilance task was found in both the single-task and dual-task conditions, along with reduced vigilance performance in the dual-task condition and reduced word recall in the dual-task condition. This is consistent with cognitive resource theory. The abbreviated semantic vigilance task will be a useful tool for researchers interested in determining the specificity of cognitive resources utilized in vigilance tasks.

The Interaction between Semantic Representation and Episodic Memory.

PubMed

Fang, Jing; Rüther, Naima; Bellebaum, Christian; Wiskott, Laurenz; Cheng, Sen

2018-02-01

The experimental evidence on the interrelation between episodic memory and semantic memory is inconclusive. Are they independent systems, different aspects of a single system, or separate but strongly interacting systems? Here, we propose a computational role for the interaction between the semantic and episodic systems that might help resolve this debate. We hypothesize that episodic memories are represented as sequences of activation patterns. These patterns are the output of a semantic representational network that compresses the high-dimensional sensory input. We show quantitatively that the accuracy of episodic memory crucially depends on the quality of the semantic representation. We compare two types of semantic representations: appropriate representations, which means that the representation is used to store input sequences that are of the same type as those that it was trained on, and inappropriate representations, which means that stored inputs differ from the training data. Retrieval accuracy is higher for appropriate representations because the encoded sequences are less divergent than those encoded with inappropriate representations. Consistent with our model prediction, we found that human subjects remember some aspects of episodes significantly more accurately if they had previously been familiarized with the objects occurring in the episode, as compared to episodes involving unfamiliar objects. We thus conclude that the interaction with the semantic system plays an important role for episodic memory.

Structure Discovery in Large Semantic Graphs Using Extant Ontological Scaling and Descriptive Statistics

DOE Office of Scientific and Technical Information (OSTI.GOV)

al-Saffar, Sinan; Joslyn, Cliff A.; Chappell, Alan R.

As semantic datasets grow to be very large and divergent, there is a need to identify and exploit their inherent semantic structure for discovery and optimization. Towards that end, we present here a novel methodology to identify the semantic structures inherent in an arbitrary semantic graph dataset. We first present the concept of an extant ontology as a statistical description of the semantic relations present amongst the typed entities modeled in the graph. This serves as a model of the underlying semantic structure to aid in discovery and visualization. We then describe a method of ontological scaling in which themore » ontology is employed as a hierarchical scaling filter to infer different resolution levels at which the graph structures are to be viewed or analyzed. We illustrate these methods on three large and publicly available semantic datasets containing more than one billion edges each. Keywords-Semantic Web; Visualization; Ontology; Multi-resolution Data Mining;« less

Knowledge-Base Semantic Gap Analysis for the Vulnerability Detection

NASA Astrophysics Data System (ADS)

Wu, Raymond; Seki, Keisuke; Sakamoto, Ryusuke; Hisada, Masayuki

Web security became an alert in internet computing. To cope with ever-rising security complexity, semantic analysis is proposed to fill-in the gap that the current approaches fail to commit. Conventional methods limit their focus to the physical source codes instead of the abstraction of semantics. It bypasses new types of vulnerability and causes tremendous business loss.

The Semantics of Complementation in English: A Cognitive Semantic Account of Two English Complement Constructions

ERIC Educational Resources Information Center

Smith, Michael B.

2009-01-01

Studies on complementation in English and other languages have traditionally focused on syntactic issues, most notably on the constituent structures of different complement types. As a result, they have neglected the role of meaning in the choice of different complements. This paper investigates the semantics of complementation within the…

Linking consistency with object/thread semantics - An approach to robust computation

NASA Technical Reports Server (NTRS)

Chen, Raymond C.; Dasgupta, Partha

1989-01-01

This paper presents an object/thread based paradigm that links data consistency with object/thread semantics. The paradigm can be used to achieve a wide range of consistency semantics from strict atomic transactions to standard process semantics. The paradigm supports three types of data consistency. Object programmers indicate the type of consistency desired on a per-operation basis and the system performs automatic concurrency control and recovery management to ensure that those consistency requirements are met. This allows programmers to customize consistency and recovery on a per-application basis without having to supply complicated, custom recovery management schemes. The paradigm allows robust and nonrobust computation to operate concurrently on the same data in a well defined manner. The operating system needs to support only one vehicle of computation - the thread.

Developing a Domain Ontology: the Case of Water Cycle and Hydrology

NASA Astrophysics Data System (ADS)

Gupta, H.; Pozzi, W.; Piasecki, M.; Imam, B.; Houser, P.; Raskin, R.; Ramachandran, R.; Martinez Baquero, G.

2008-12-01

A semantic web ontology enables semantic data integration and semantic smart searching. Several organizations have attempted to implement smart registration and integration or searching using ontologies. These are the NOESIS (NSF project: LEAD) and HydroSeek (NSF project: CUAHS HIS) data discovery engines and the NSF project GEON. All three applications use ontologies to discover data from multiple sources and projects. The NASA WaterNet project was established to identify creative, innovative ways to bridge NASA research results to real world applications, linking decision support needs to available data, observations, and modeling capability. WaterNet (NASA project) utilized the smart query tool Noesis as a testbed to test whether different ontologies (and different catalog searches) could be combined to match resources with user needs. NOESIS contains the upper level SWEET ontology that accepts plug in domain ontologies to refine user search queries, reducing the burden of multiple keyword searches. Another smart search interface was that developed for CUAHSI, HydroSeek, that uses a multi-layered concept search ontology, tagging variables names from any number of data sources to specific leaf and higher level concepts on which the search is executed. This approach has proven to be quite successful in mitigating semantic heterogeneity as the user does not need to know the semantic specifics of each data source system but just uses a set of common keywords to discover the data for a specific temporal and geospatial domain. This presentation will show tests with Noesis and Hydroseek lead to the conclusion that the construction of a complex, and highly heterogeneous water cycle ontology requires multiple ontology modules. To illustrate the complexity and heterogeneity of a water cycle ontology, Hydroseek successfully utilizes WaterOneFlow to integrate data across multiple different data collections, such as USGS NWIS. However,different methodologies are employed by the Earth Science, the Hydrological, and Hydraulic Engineering Communities, and each community employs models that require different input data. If a sub-domain ontology is created for each of these,describing water balance calculations, then the resulting structure of the semantic network describing these various terms can be rather complex, heterogeneous, and overlapping, and will require "mapping" between equivalent terms in the ontologies, along with the development of an upper level conceptual or domain ontology to utilize and link to those already in existence.

Buckets: Aggregative, Intelligent Agents for Publishing

NASA Technical Reports Server (NTRS)

Nelson, Michael L.; Maly, Kurt; Shen, Stewart N. T.; Zubair, Mohammad

1998-01-01

Buckets are an aggregative, intelligent construct for publishing in digital libraries. The goal of research projects is to produce information. This information is often instantiated in several forms, differentiated by semantic types (report, software, video, datasets, etc.). A given semantic type can be further differentiated by syntactic representations as well (PostScript version, PDF version, Word version, etc.). Although the information was created together and subtle relationships can exist between them, different semantic instantiations are generally segregated along currently obsolete media boundaries. Reports are placed in report archives, software might go into a software archive, but most of the data and supporting materials are likely to be kept in informal personal archives or discarded altogether. Buckets provide an archive-independent container construct in which all related semantic and syntactic data types and objects can be logically grouped together, archived, and manipulated as a single object. Furthermore, buckets are active archival objects and can communicate with each other, people, or arbitrary network services.

A framework for semantic interoperability in healthcare: a service oriented architecture based on health informatics standards.

PubMed

Ryan, Amanda; Eklund, Peter

2008-01-01

Healthcare information is composed of many types of varying and heterogeneous data. Semantic interoperability in healthcare is especially important when all these different types of data need to interact. Presented in this paper is a solution to interoperability in healthcare based on a standards-based middleware software architecture used in enterprise solutions. This architecture has been translated into the healthcare domain using a messaging and modeling standard which upholds the ideals of the Semantic Web (HL7 V3) combined with a well-known standard terminology of clinical terms (SNOMED CT).

Priming production: Neural evidence for enhanced automatic semantic activity preceding language production in schizophrenia.

PubMed

Kuperberg, Gina R; Delaney-Busch, Nathaniel; Fanucci, Kristina; Blackford, Trevor

2018-01-01

Lexico-semantic disturbances are considered central to schizophrenia. Clinically, their clearest manifestation is in language production. However, most studies probing their underlying mechanisms have used comprehension or categorization tasks. Here, we probed automatic semantic activity prior to language production in schizophrenia using event-related potentials (ERPs). 19 people with schizophrenia and 16 demographically-matched healthy controls named target pictures that were very quickly preceded by masked prime words. To probe automatic semantic activity prior to production, we measured the N400 ERP component evoked by these targets. To determine the origin of any automatic semantic abnormalities, we manipulated the type of relationship between prime and target such that they overlapped in (a) their semantic features (semantically related, e.g. "cake" preceding a < picture of a pie >, (b) their initial phonemes (phonemically related, e.g. "stomach" preceding a < picture of a starfish >), or (c) both their semantic features and their orthographic/phonological word form (identity related, e.g. "socks" preceding a < picture of socks >). For each of these three types of relationship, the same targets were paired with unrelated prime words (counterbalanced across lists). We contrasted ERPs and naming times to each type of related target with its corresponding unrelated target. People with schizophrenia showed abnormal N400 modulation prior to naming identity related (versus unrelated) targets: whereas healthy control participants produced a smaller amplitude N400 to identity related than unrelated targets, patients showed the opposite pattern, producing a larger N400 to identity related than unrelated targets. This abnormality was specific to the identity related targets. Just like healthy control participants, people with schizophrenia produced a smaller N400 to semantically related than to unrelated targets, and showed no difference in the N400 evoked by phonemically related and unrelated targets. There were no differences between the two groups in the pattern of naming times across conditions. People with schizophrenia can show abnormal neural activity associated with automatic semantic processing prior to language production. The specificity of this abnormality to the identity related targets suggests that that, rather than arising from abnormalities of either semantic features or lexical form alone, it may stem from disruptions of mappings (connections) between the meaning of words and their form.

Nonword Repetition and Vocabulary Knowledge as Predictors of Children's Phonological and Semantic Word Learning

ERIC Educational Resources Information Center

Adlof, Suzanne M.; Patten, Hannah

2017-01-01

Purpose: This study examined the unique and shared variance that nonword repetition and vocabulary knowledge contribute to children's ability to learn new words. Multiple measures of word learning were used to assess recall and recognition of phonological and semantic information. Method: Fifty children, with a mean age of 8 years (range 5-12…

The Development of Idiom Comprehension: An Investigation of Semantic and Contextual Processing Skills

ERIC Educational Resources Information Center

Cain, Kate; Towse, Andrea S.; Knight, Rachael S.

2009-01-01

Two experiments compared 7- and 8-year-olds' and 9- and 10-year-olds' ability to use semantic analysis and inference from context to understand idioms. We used a multiple-choice task and manipulated whether the idioms were transparent or opaque, familiar or novel, and presented with or without a supportive story context. Performance was compared…

Odour discrimination and identification are improved in early blindness.

PubMed

Cuevas, Isabel; Plaza, Paula; Rombaux, Philippe; De Volder, Anne G; Renier, Laurent

2009-12-01

Previous studies showed that early blind humans develop superior abilities in the use of their remaining senses, hypothetically due to a functional reorganization of the deprived visual brain areas. While auditory and tactile functions have been investigated for long, little is known about the effects of early visual deprivation on olfactory processing. However, blind humans make an extensive use of olfactory information in their daily life. Here we investigated olfactory discrimination and identification abilities in early blind subjects and age-matched sighted controls. Three levels of cuing were used in the identification task, i.e., free-identification (no cue), categorization (semantic cues) and multiple choice (semantic and phonological cues). Early blind subjects significantly outperformed the controls in odour discrimination, free-identification and categorization. In addition, the larger group difference was observed in the free-identification as compared to the categorization and the multiple choice conditions. This indicated that a better access to the semantic information from odour perception accounted for part of the improved olfactory performances in odour identification in the blind. We concluded that early blind subjects have both improved perceptual abilities and a better access to the information stored in semantic memory than sighted subjects.

Nonword Repetition and Vocabulary Knowledge as Predictors of Children's Phonological and Semantic Word Learning.

PubMed

Adlof, Suzanne M; Patten, Hannah

2017-03-01

This study examined the unique and shared variance that nonword repetition and vocabulary knowledge contribute to children's ability to learn new words. Multiple measures of word learning were used to assess recall and recognition of phonological and semantic information. Fifty children, with a mean age of 8 years (range 5-12 years), completed experimental assessments of word learning and norm-referenced assessments of receptive and expressive vocabulary knowledge and nonword repetition skills. Hierarchical multiple regression analyses examined the variance in word learning that was explained by vocabulary knowledge and nonword repetition after controlling for chronological age. Together with chronological age, nonword repetition and vocabulary knowledge explained up to 44% of the variance in children's word learning. Nonword repetition was the stronger predictor of phonological recall, phonological recognition, and semantic recognition, whereas vocabulary knowledge was the stronger predictor of verbal semantic recall. These findings extend the results of past studies indicating that both nonword repetition skill and existing vocabulary knowledge are important for new word learning, but the relative influence of each predictor depends on the way word learning is measured. Suggestions for further research involving typically developing children and children with language or reading impairments are discussed.

Cognitive Development and Reading: The Relation of Reading-Specific Multiple Classification Skill to Reading Comprehension in Elementary School Children.

ERIC Educational Resources Information Center

Cartwright, Kelly B.

2002-01-01

A reading-specific multiple classification task was designed that required children to classify printed words along phonological and semantic dimensions simultaneously. Reading-specific multiple classification skill made a unique contribution to children's reading comprehension over contributions made by age, domain-general multiple classification…

A Semantic Medical Multimedia Retrieval Approach Using Ontology Information Hiding

PubMed Central

Guo, Kehua; Zhang, Shigeng

2013-01-01

Searching useful information from unstructured medical multimedia data has been a difficult problem in information retrieval. This paper reports an effective semantic medical multimedia retrieval approach which can reflect the users' query intent. Firstly, semantic annotations will be given to the multimedia documents in the medical multimedia database. Secondly, the ontology that represented semantic information will be hidden in the head of the multimedia documents. The main innovations of this approach are cross-type retrieval support and semantic information preservation. Experimental results indicate a good precision and efficiency of our approach for medical multimedia retrieval in comparison with some traditional approaches. PMID:24082915

Visual and semantic processing of living things and artifacts: an FMRI study.

PubMed

Zannino, Gian Daniele; Buccione, Ivana; Perri, Roberta; Macaluso, Emiliano; Lo Gerfo, Emanuele; Caltagirone, Carlo; Carlesimo, Giovanni A

2010-03-01

We carried out an fMRI study with a twofold purpose: to investigate the relationship between networks dedicated to semantic and visual processing and to address the issue of whether semantic memory is subserved by a unique network or by different subsystems, according to semantic category or feature type. To achieve our goals, we administered a word-picture matching task, with within-category foils, to 15 healthy subjects during scanning. Semantic distance between the target and the foil and semantic domain of the target-foil pairs were varied orthogonally. Our results suggest that an amodal, undifferentiated network for the semantic processing of living things and artifacts is located in the anterolateral aspects of the temporal lobes; in fact, activity in this substrate was driven by semantic distance, not by semantic category. By contrast, activity in ventral occipito-temporal cortex was driven by category, not by semantic distance. We interpret the latter finding as the effect exerted by systematic differences between living things and artifacts at the level of their structural representations and possibly of their lower-level visual features. Finally, we attempt to reconcile contrasting data in the neuropsychological and functional imaging literature on semantic substrate and category specificity.

Selective Audiovisual Semantic Integration Enabled by Feature-Selective Attention

PubMed Central

Li, Yuanqing; Long, Jinyi; Huang, Biao; Yu, Tianyou; Wu, Wei; Li, Peijun; Fang, Fang; Sun, Pei

2016-01-01

An audiovisual object may contain multiple semantic features, such as the gender and emotional features of the speaker. Feature-selective attention and audiovisual semantic integration are two brain functions involved in the recognition of audiovisual objects. Humans often selectively attend to one or several features while ignoring the other features of an audiovisual object. Meanwhile, the human brain integrates semantic information from the visual and auditory modalities. However, how these two brain functions correlate with each other remains to be elucidated. In this functional magnetic resonance imaging (fMRI) study, we explored the neural mechanism by which feature-selective attention modulates audiovisual semantic integration. During the fMRI experiment, the subjects were presented with visual-only, auditory-only, or audiovisual dynamical facial stimuli and performed several feature-selective attention tasks. Our results revealed that a distribution of areas, including heteromodal areas and brain areas encoding attended features, may be involved in audiovisual semantic integration. Through feature-selective attention, the human brain may selectively integrate audiovisual semantic information from attended features by enhancing functional connectivity and thus regulating information flows from heteromodal areas to brain areas encoding the attended features. PMID:26759193

The Ins and Outs of Meaning: Behavioral and Neuroanatomical Dissociation of Semantically-Driven Word Retrieval and Multimodal Semantic Recognition in Aphasia

PubMed Central

Mirman, Daniel; Zhang, Yongsheng; Wang, Ze; Coslett, H. Branch; Schwartz, Myrna F.

2015-01-01

Theories about the architecture of language processing differ with regard to whether verbal and nonverbal comprehension share a functional and neural substrate and how meaning extraction in comprehension relates to the ability to use meaning to drive verbal production. We (re-)evaluate data from 17 cognitive-linguistic performance measures of 99 participants with chronic aphasia using factor analysis to establish functional components and support vector regression-based lesion-symptom mapping to determine the neural correlates of deficits on these functional components. The results are highly consistent with our previous findings: production of semantic errors is behaviorally and neuroanatomically distinct from verbal and nonverbal comprehension. Semantic errors were most strongly associated with left ATL damage whereas deficits on tests of verbal and non-verbal semantic recognition were most strongly associated with damage to deep white matter underlying the frontal lobe at the confluence of multiple tracts, including the inferior fronto-occipital fasciculus, the uncinate fasciculus, and the anterior thalamic radiations. These results suggest that traditional views based on grey matter hub(s) for semantic processing are incomplete and that the role of white matter in semantic cognition has been underappreciated. PMID:25681739

Semantically-Sensitive Macroprocessing

DTIC Science & Technology

1989-12-15

constr uct for protecting critical regions. Given the synchronization primitives P and V, we might implement the following transformation, where...By this we mean that the semantic model for the base language provides a primitive set of concepts, represented by data types and operations...the gener- ation of a (dynamic-) semantically equivalent program fragment ultimately expressible in terms of built-in primitives . Note that static

The Large-Scale Structure of Semantic Networks: Statistical Analyses and a Model of Semantic Growth

ERIC Educational Resources Information Center

Steyvers, Mark; Tenenbaum, Joshua B.

2005-01-01

We present statistical analyses of the large-scale structure of 3 types of semantic networks: word associations, WordNet, and Roget's Thesaurus. We show that they have a small-world structure, characterized by sparse connectivity, short average path lengths between words, and strong local clustering. In addition, the distributions of the number of…

Qualitative dynamics semantics for SBGN process description.

PubMed

Rougny, Adrien; Froidevaux, Christine; Calzone, Laurence; Paulevé, Loïc

2016-06-16

Qualitative dynamics semantics provide a coarse-grain modeling of networks dynamics by abstracting away kinetic parameters. They allow to capture general features of systems dynamics, such as attractors or reachability properties, for which scalable analyses exist. The Systems Biology Graphical Notation Process Description language (SBGN-PD) has become a standard to represent reaction networks. However, no qualitative dynamics semantics taking into account all the main features available in SBGN-PD had been proposed so far. We propose two qualitative dynamics semantics for SBGN-PD reaction networks, namely the general semantics and the stories semantics, that we formalize using asynchronous automata networks. While the general semantics extends standard Boolean semantics of reaction networks by taking into account all the main features of SBGN-PD, the stories semantics allows to model several molecules of a network by a unique variable. The obtained qualitative models can be checked against dynamical properties and therefore validated with respect to biological knowledge. We apply our framework to reason on the qualitative dynamics of a large network (more than 200 nodes) modeling the regulation of the cell cycle by RB/E2F. The proposed semantics provide a direct formalization of SBGN-PD networks in dynamical qualitative models that can be further analyzed using standard tools for discrete models. The dynamics in stories semantics have a lower dimension than the general one and prune multiple behaviors (which can be considered as spurious) by enforcing the mutual exclusiveness between the activity of different nodes of a same story. Overall, the qualitative semantics for SBGN-PD allow to capture efficiently important dynamical features of reaction network models and can be exploited to further refine them.

Intelligent services for discovery of complex geospatial features from remote sensing imagery

NASA Astrophysics Data System (ADS)

Yue, Peng; Di, Liping; Wei, Yaxing; Han, Weiguo

2013-09-01

Remote sensing imagery has been commonly used by intelligence analysts to discover geospatial features, including complex ones. The overwhelming volume of routine image acquisition requires automated methods or systems for feature discovery instead of manual image interpretation. The methods of extraction of elementary ground features such as buildings and roads from remote sensing imagery have been studied extensively. The discovery of complex geospatial features, however, is still rather understudied. A complex feature, such as a Weapon of Mass Destruction (WMD) proliferation facility, is spatially composed of elementary features (e.g., buildings for hosting fuel concentration machines, cooling towers, transportation roads, and fences). Such spatial semantics, together with thematic semantics of feature types, can be used to discover complex geospatial features. This paper proposes a workflow-based approach for discovery of complex geospatial features that uses geospatial semantics and services. The elementary features extracted from imagery are archived in distributed Web Feature Services (WFSs) and discoverable from a catalogue service. Using spatial semantics among elementary features and thematic semantics among feature types, workflow-based service chains can be constructed to locate semantically-related complex features in imagery. The workflows are reusable and can provide on-demand discovery of complex features in a distributed environment.

Semantic activation by Japanese kanji: evidence from event-related potentials.

PubMed

Hayashi, M; Kayamoto, Y; Tanaka, H; Yamada, J

1998-04-01

In a character-judgment paradigm, the subject quickly pressed a key when a hiragana (Japanese syllabary) appeared on a display and did nothing when a kanji (Japanese logograph) appeared. The amplitude of the N400 component was compared when four types of visual stimuli were used: (Type 1) single kanji--Grade 1- to 3-level words, (Type 2) single kanji--Grade 1- to 3-level bound morphemes, (Type 3) single kanji--high school- and college-level bound morphemes, and (Type 4) obsolete kanji. Analysis showed that N400 was largest in the temporal-occipital areas for the Type 1 stimuli and larger in the right parietal area for Type 2 than Type 3 stimuli. The analyses of N400 to semantic stimulations have been conducted and discussed in terms of their meaningfulness, age when writing of these kanji was mastered, and linguistic status (kanji versus nonkanji). Most interestingly, the Types 3 and 4 kanji did not activate semantic responses, showing that they did not function as linguistic units, i.e., kanji, in the mental lexicon.

A DNA-based semantic fusion model for remote sensing data.

PubMed

Sun, Heng; Weng, Jian; Yu, Guangchuang; Massawe, Richard H

2013-01-01

Semantic technology plays a key role in various domains, from conversation understanding to algorithm analysis. As the most efficient semantic tool, ontology can represent, process and manage the widespread knowledge. Nowadays, many researchers use ontology to collect and organize data's semantic information in order to maximize research productivity. In this paper, we firstly describe our work on the development of a remote sensing data ontology, with a primary focus on semantic fusion-driven research for big data. Our ontology is made up of 1,264 concepts and 2,030 semantic relationships. However, the growth of big data is straining the capacities of current semantic fusion and reasoning practices. Considering the massive parallelism of DNA strands, we propose a novel DNA-based semantic fusion model. In this model, a parallel strategy is developed to encode the semantic information in DNA for a large volume of remote sensing data. The semantic information is read in a parallel and bit-wise manner and an individual bit is converted to a base. By doing so, a considerable amount of conversion time can be saved, i.e., the cluster-based multi-processes program can reduce the conversion time from 81,536 seconds to 4,937 seconds for 4.34 GB source data files. Moreover, the size of result file recording DNA sequences is 54.51 GB for parallel C program compared with 57.89 GB for sequential Perl. This shows that our parallel method can also reduce the DNA synthesis cost. In addition, data types are encoded in our model, which is a basis for building type system in our future DNA computer. Finally, we describe theoretically an algorithm for DNA-based semantic fusion. This algorithm enables the process of integration of the knowledge from disparate remote sensing data sources into a consistent, accurate, and complete representation. This process depends solely on ligation reaction and screening operations instead of the ontology.

A DNA-Based Semantic Fusion Model for Remote Sensing Data

PubMed Central

Sun, Heng; Weng, Jian; Yu, Guangchuang; Massawe, Richard H.

2013-01-01

Semantic technology plays a key role in various domains, from conversation understanding to algorithm analysis. As the most efficient semantic tool, ontology can represent, process and manage the widespread knowledge. Nowadays, many researchers use ontology to collect and organize data's semantic information in order to maximize research productivity. In this paper, we firstly describe our work on the development of a remote sensing data ontology, with a primary focus on semantic fusion-driven research for big data. Our ontology is made up of 1,264 concepts and 2,030 semantic relationships. However, the growth of big data is straining the capacities of current semantic fusion and reasoning practices. Considering the massive parallelism of DNA strands, we propose a novel DNA-based semantic fusion model. In this model, a parallel strategy is developed to encode the semantic information in DNA for a large volume of remote sensing data. The semantic information is read in a parallel and bit-wise manner and an individual bit is converted to a base. By doing so, a considerable amount of conversion time can be saved, i.e., the cluster-based multi-processes program can reduce the conversion time from 81,536 seconds to 4,937 seconds for 4.34 GB source data files. Moreover, the size of result file recording DNA sequences is 54.51 GB for parallel C program compared with 57.89 GB for sequential Perl. This shows that our parallel method can also reduce the DNA synthesis cost. In addition, data types are encoded in our model, which is a basis for building type system in our future DNA computer. Finally, we describe theoretically an algorithm for DNA-based semantic fusion. This algorithm enables the process of integration of the knowledge from disparate remote sensing data sources into a consistent, accurate, and complete representation. This process depends solely on ligation reaction and screening operations instead of the ontology. PMID:24116207

(Pea)nuts and bolts of visual narrative: Structure and meaning in sequential image comprehension

PubMed Central

Cohn, Neil; Paczynski, Martin; Jackendoff, Ray; Holcomb, Phillip J.; Kuperberg, Gina R.

2012-01-01

Just as syntax differentiates coherent sentences from scrambled word strings, the comprehension of sequential images must also use a cognitive system to distinguish coherent narrative sequences from random strings of images. We conducted experiments analogous to two classic studies of language processing to examine the contributions of narrative structure and semantic relatedness to processing sequential images. We compared four types of comic strips: 1) Normal sequences with both structure and meaning, 2) Semantic Only sequences (in which the panels were related to a common semantic theme, but had no narrative structure), 3) Structural Only sequences (narrative structure but no semantic relatedness), and 4) Scrambled sequences of randomly-ordered panels. In Experiment 1, participants monitored for target panels in sequences presented panel-by-panel. Reaction times were slowest to panels in Scrambled sequences, intermediate in both Structural Only and Semantic Only sequences, and fastest in Normal sequences. This suggests that both semantic relatedness and narrative structure offer advantages to processing. Experiment 2 measured ERPs to all panels across the whole sequence. The N300/N400 was largest to panels in both the Scrambled and Structural Only sequences, intermediate in Semantic Only sequences and smallest in the Normal sequences. This implies that a combination of narrative structure and semantic relatedness can facilitate semantic processing of upcoming panels (as reflected by the N300/N400). Also, panels in the Scrambled sequences evoked a larger left-lateralized anterior negativity than panels in the Structural Only sequences. This localized effect was distinct from the N300/N400, and appeared despite the fact that these two sequence types were matched on local semantic relatedness between individual panels. These findings suggest that sequential image comprehension uses a narrative structure that may be independent of semantic relatedness. Altogether, we argue that the comprehension of visual narrative is guided by an interaction between structure and meaning. PMID:22387723

'I remember therefore I am, and I am therefore I remember': exploring the contributions of episodic and semantic self-knowledge to strength of identity.

PubMed

Haslam, Catherine; Jetten, Jolanda; Haslam, S Alexander; Pugliese, Cara; Tonks, James

2011-05-01

The present research explores the relationship between the two components of autobiographical memory--episodic and semantic self-knowledge--and identity strength in older adults living in the community and residential care. Participants (N= 32) completed the autobiographical memory interview and measures of personal identity strength and multiple group memberships. Contrary to previous research, autobiographical memory for all time periods (childhood, early adulthood, and recent life) in the semantic domain was associated with greater strength in personal identity. Further, we obtained support for the hypothesis that the relationship between episodic self-knowledge and identity strength would be mediated by knowledge of personal semantic facts. However, there was also support for a reverse mediation model indicating that a strong sense of identity is associated with semantic self-knowledge and through this may enhance self-relevant recollection. The discussion elaborates on these findings and we propose a self-knowledge and identity model (SKIM) whereby semantic self-knowledge mediates a bidirectional relationship between episodic self-knowledge and identity. ©2010 The British Psychological Society.

Enhancing biomedical text summarization using semantic relation extraction.

PubMed

Shang, Yue; Li, Yanpeng; Lin, Hongfei; Yang, Zhihao

2011-01-01

Automatic text summarization for a biomedical concept can help researchers to get the key points of a certain topic from large amount of biomedical literature efficiently. In this paper, we present a method for generating text summary for a given biomedical concept, e.g., H1N1 disease, from multiple documents based on semantic relation extraction. Our approach includes three stages: 1) We extract semantic relations in each sentence using the semantic knowledge representation tool SemRep. 2) We develop a relation-level retrieval method to select the relations most relevant to each query concept and visualize them in a graphic representation. 3) For relations in the relevant set, we extract informative sentences that can interpret them from the document collection to generate text summary using an information retrieval based method. Our major focus in this work is to investigate the contribution of semantic relation extraction to the task of biomedical text summarization. The experimental results on summarization for a set of diseases show that the introduction of semantic knowledge improves the performance and our results are better than the MEAD system, a well-known tool for text summarization.

Generalized dissociative amnesia: episodic, semantic and procedural memories lost and found.

PubMed

van der Hart, O; Nijenhuis, E

2001-10-01

This review tests Ribot's classic twofold categorization of generalized amnesia (GA) into Type I, total loss of episodic memory, and Type II, additional more or less extensive loss of semantic and/or procedural memory. It also explores his law of regression, according to which, cast in modern terms, recovery of lost procedural and semantic memories precedes recovery of episodic memory, as well as reported aetiological factors. Clinically and formally assessed cases of GA, published since 1845, were surveyed and further analysed. Over and above authentic episodic memory loss, cases differed widely in the extent of impairment of semantic and procedural memory. Recovery of semantic and procedural memory often preceded recovery of episodic memory. This particularly applied to authenticated trauma memories. To an extent, lost memories affected current functioning, and in some cases were associated with alternating dissociative personalities. Severe memory distortions upon memory recovery were not reported. Most cases were trauma or stress related, while in some cases the aetiology remained unknown. Contrary to the view expressed in DSM-IV, which states that dissociative amnesia pertains to an inability to recall personal information, GA may also involve loss and recovery of semantic and procedural memories. Since the loss of various memory types in GA is dimensional rather than categorical, Ribot's typological distinction does not hold. Some of the reviewed cases suggest a trauma-related aetiology. Generalized amnesia of varying degrees of severity can involve delayed retrieval of trauma memories, as well as the loss and delayed retrieval of the premorbid personality.

Feeling torn when everything seems right: semantic incongruence causes felt ambivalence.

PubMed

Gebauer, Jochen E; Maio, Gregory R; Pakizeh, Ali

2013-06-01

The co-occurrence of positive and negative attributes of an attitude object typically accounts for less than a quarter of the variance in felt ambivalence toward these objects, rendering this evaluative incongruence insufficient for explaining felt ambivalence. The present research tested whether another type of incongruence, semantic incongruence, also causes felt ambivalence. Semantic incongruence arises from inconsistencies in the descriptive content of attitude objects' attributes (e.g., attributes that are not mutually supportive), independent of these attributes' valences. Experiment 1 manipulated evaluative and semantic incongruence using valence norms and semantic norms. Both of these norm-based manipulations independently predicted felt ambivalence, and, in Experiment 2, they even did so over and above self-based incongruence (i.e., participants' idiosyncratic perceptions of evaluative and semantic incongruence). Experiments 3a and 3b revealed that aversive dissonant feelings play a role in the effects of evaluative incongruence, but not semantic incongruence, on felt ambivalence.

Representational Similarity of Body Parts in Human Occipitotemporal Cortex.

PubMed

Bracci, Stefania; Caramazza, Alfonso; Peelen, Marius V

2015-09-23

Regions in human lateral and ventral occipitotemporal cortices (OTC) respond selectively to pictures of the human body and its parts. What are the organizational principles underlying body part responses in these regions? Here we used representational similarity analysis (RSA) of fMRI data to test multiple possible organizational principles: shape similarity, physical proximity, cortical homunculus proximity, and semantic similarity. Participants viewed pictures of whole persons, chairs, and eight body parts (hands, arms, legs, feet, chests, waists, upper faces, and lower faces). The similarity of multivoxel activity patterns for all body part pairs was established in whole person-selective OTC regions. The resulting neural similarity matrices were then compared with similarity matrices capturing the hypothesized organizational principles. Results showed that the semantic similarity model best captured the neural similarity of body parts in lateral and ventral OTC, which followed an organization in three clusters: (1) body parts used as action effectors (hands, feet, arms, and legs), (2) noneffector body parts (chests and waists), and (3) face parts (upper and lower faces). Whole-brain RSA revealed, in addition to OTC, regions in parietal and frontal cortex in which neural similarity was related to semantic similarity. In contrast, neural similarity in occipital cortex was best predicted by shape similarity models. We suggest that the semantic organization of body parts in high-level visual cortex relates to the different functions associated with the three body part clusters, reflecting the unique processing and connectivity demands associated with the different types of information (e.g., action, social) different body parts (e.g., limbs, faces) convey. Significance statement: While the organization of body part representations in motor and somatosensory cortices has been well characterized, the principles underlying body part representations in visual cortex have not yet been explored. In the present fMRI study we used multivoxel pattern analysis and representational similarity analysis to characterize the organization of body maps in human occipitotemporal cortex (OTC). Results indicate that visual and shape dimensions do not fully account for the organization of body part representations in OTC. Instead, the representational structure of body maps in OTC appears strongly related to functional-semantic properties of body parts. We suggest that this organization reflects the unique processing and connectivity demands associated with the different types of information different body parts convey. Copyright © 2015 the authors 0270-6474/15/3512977-09$15.00/0.

High performance semantic factoring of giga-scale semantic graph databases.

DOE Office of Scientific and Technical Information (OSTI.GOV)

al-Saffar, Sinan; Adolf, Bob; Haglin, David

2010-10-01

As semantic graph database technology grows to address components ranging from extant large triple stores to SPARQL endpoints over SQL-structured relational databases, it will become increasingly important to be able to bring high performance computational resources to bear on their analysis, interpretation, and visualization, especially with respect to their innate semantic structure. Our research group built a novel high performance hybrid system comprising computational capability for semantic graph database processing utilizing the large multithreaded architecture of the Cray XMT platform, conventional clusters, and large data stores. In this paper we describe that architecture, and present the results of our deployingmore » that for the analysis of the Billion Triple dataset with respect to its semantic factors, including basic properties, connected components, namespace interaction, and typed paths.« less

Computing multiple aggregation levels and contextual features for road facilities recognition using mobile laser scanning data

NASA Astrophysics Data System (ADS)

Yang, Bisheng; Dong, Zhen; Liu, Yuan; Liang, Fuxun; Wang, Yongjun

2017-04-01

In recent years, updating the inventory of road infrastructures based on field work is labor intensive, time consuming, and costly. Fortunately, vehicle-based mobile laser scanning (MLS) systems provide an efficient solution to rapidly capture three-dimensional (3D) point clouds of road environments with high flexibility and precision. However, robust recognition of road facilities from huge volumes of 3D point clouds is still a challenging issue because of complicated and incomplete structures, occlusions and varied point densities. Most existing methods utilize point or object based features to recognize object candidates, and can only extract limited types of objects with a relatively low recognition rate, especially for incomplete and small objects. To overcome these drawbacks, this paper proposes a semantic labeling framework by combing multiple aggregation levels (point-segment-object) of features and contextual features to recognize road facilities, such as road surfaces, road boundaries, buildings, guardrails, street lamps, traffic signs, roadside-trees, power lines, and cars, for highway infrastructure inventory. The proposed method first identifies ground and non-ground points, and extracts road surfaces facilities from ground points. Non-ground points are segmented into individual candidate objects based on the proposed multi-rule region growing method. Then, the multiple aggregation levels of features and the contextual features (relative positions, relative directions, and spatial patterns) associated with each candidate object are calculated and fed into a SVM classifier to label the corresponding candidate object. The recognition performance of combining multiple aggregation levels and contextual features was compared with single level (point, segment, or object) based features using large-scale highway scene point clouds. Comparative studies demonstrated that the proposed semantic labeling framework significantly improves road facilities recognition precision (90.6%) and recall (91.2%), particularly for incomplete and small objects.

Hippocampal activation during episodic and semantic memory retrieval: comparing category production and category cued recall.

PubMed

Ryan, Lee; Cox, Christine; Hayes, Scott M; Nadel, Lynn

2008-01-01

Whether or not the hippocampus participates in semantic memory retrieval has been the focus of much debate in the literature. However, few neuroimaging studies have directly compared hippocampal activation during semantic and episodic retrieval tasks that are well matched in all respects other than the source of the retrieved information. In Experiment 1, we compared hippocampal fMRI activation during a classic semantic memory task, category production, and an episodic version of the same task, category cued recall. Left hippocampal activation was observed in both episodic and semantic conditions, although other regions of the brain clearly distinguished the two tasks. Interestingly, participants reported using retrieval strategies during the semantic retrieval task that relied on autobiographical and spatial information; for example, visualizing themselves in their kitchen while producing items for the category kitchen utensils. In Experiment 2, we considered whether the use of these spatial and autobiographical retrieval strategies could have accounted for the hippocampal activation observed in Experiment 1. Categories were presented that elicited one of three retrieval strategy types, autobiographical and spatial, autobiographical and nonspatial, and neither autobiographical nor spatial. Once again, similar hippocampal activation was observed for all three category types, regardless of the inclusion of spatial or autobiographical content. We conclude that the distinction between semantic and episodic memory is more complex than classic memory models suggest.

Hippocampal Activation during Episodic and Semantic Memory Retrieval: Comparing Category Production and Category Cued Recall

PubMed Central

Ryan, Lee; Cox, Christine; Hayes, Scott M.; Nadel, Lynn

2008-01-01

Whether or not the hippocampus participates in semantic memory retrieval has been the focus of much debate in the literature. However, few neuroimaging studies have directly compared hippocampal activation during semantic and episodic retrieval tasks that are well matched in all respects other than the source of the retrieved information. In Experiment 1, we compared hippocampal fMRI activation during a classic semantic memory task, category production, and an episodic version of the same task, category cued recall. Left hippocampal activation was observed in both episodic and semantic conditions, although other regions of the brain clearly distinguished the two tasks. Interestingly, participants reported using retrieval strategies during the semantic retrieval task that relied on autobiographical and spatial information; for example, visualizing themselves in their kitchen while producing items for the category kitchen utensils. In Experiment 2, we considered whether the use of these spatial and autobiographical retrieval strategies could have accounted for the hippocampal activation observed in Experiment 1. Categories were presented that elicited one of three retrieval strategy types, autobiographical and spatial, autobiographical and nonspatial, and neither autobiographical nor spatial. Once again, similar hippocampal activation was observed for all three category types, regardless of the inclusion of spatial or autobiographical content. We conclude that the distinction between semantic and episodic memory is more complex than classic memory models suggest. PMID:18420234

Semantic relations differentially impact associative recognition memory: electrophysiological evidence.

PubMed

Kriukova, Olga; Bridger, Emma; Mecklinger, Axel

2013-10-01

Though associative recognition memory is thought to rely primarily on recollection, recent research indicates that familiarity might also make a substantial contribution when to-be-learned items are integrated into a coherent structure by means of an existing semantic relation. It remains unclear how different types of semantic relations, such as categorical (e.g., dancer-singer) and thematic (e.g., dancer-stage) relations might affect associative recognition, however. Using event-related potentials (ERPs), we addressed this question by manipulating the type of semantic link between paired words in an associative recognition memory experiment. An early midfrontal old/new effect, typically linked to familiarity, was observed across the relation types. In contrast, a robust left parietal old/new effect was found in the categorical condition only, suggesting a clear contribution of recollection to associative recognition for this kind of pairs. One interpretation of this pattern is that familiarity was sufficiently diagnostic for associative recognition of thematic relations, which could result from the integrative nature of the thematic relatedness compared to the similarity-based nature of categorical pairs. The present study suggests that the extent to which recollection and familiarity are involved in associative recognition is at least in part determined by the properties of semantic relations between the paired associates. Copyright © 2013 Elsevier Inc. All rights reserved.

Action semantics: A unifying conceptual framework for the selective use of multimodal and modality-specific object knowledge.

PubMed

van Elk, Michiel; van Schie, Hein; Bekkering, Harold

2014-06-01

Our capacity to use tools and objects is often considered one of the hallmarks of the human species. Many objects greatly extend our bodily capabilities to act in the physical world, such as when using a hammer or a saw. In addition, humans have the remarkable capability to use objects in a flexible fashion and to combine multiple objects in complex actions. We prepare coffee, cook dinner and drive our car. In this review we propose that humans have developed declarative and procedural knowledge, i.e. action semantics that enables us to use objects in a meaningful way. A state-of-the-art review of research on object use is provided, involving behavioral, developmental, neuropsychological and neuroimaging studies. We show that research in each of these domains is characterized by similar discussions regarding (1) the role of object affordances, (2) the relation between goals and means in object use and (3) the functional and neural organization of action semantics. We propose a novel conceptual framework of action semantics to address these issues and to integrate the previous findings. We argue that action semantics entails both multimodal object representations and modality-specific sub-systems, involving manipulation knowledge, functional knowledge and representations of the sensory and proprioceptive consequences of object use. Furthermore, we argue that action semantics are hierarchically organized and selectively activated and used depending on the action intention of the actor and the current task context. Our framework presents an integrative account of multiple findings and perspectives on object use that may guide future studies in this interdisciplinary domain. Copyright © 2013 Elsevier B.V. All rights reserved.

Creating Vocabulary Item Types That Measure Students' Depth of Semantic Knowledge. Research Report. ETS RR-14-02

ERIC Educational Resources Information Center

Deane, Paul; Lawless, René R.; Li, Chen; Sabatini, John; Bejar, Isaac I.; O'Reilly, Tenaha

2014-01-01

We expect that word knowledge accumulates gradually. This article draws on earlier approaches to assessing depth, but focuses on one dimension: richness of semantic knowledge. We present results from a study in which three distinct item types were developed at three levels of depth: knowledge of common usage patterns, knowledge of broad topical…

Towards comprehensive syntactic and semantic annotations of the clinical narrative

PubMed Central

Albright, Daniel; Lanfranchi, Arrick; Fredriksen, Anwen; Styler, William F; Warner, Colin; Hwang, Jena D; Choi, Jinho D; Dligach, Dmitriy; Nielsen, Rodney D; Martin, James; Ward, Wayne; Palmer, Martha; Savova, Guergana K

2013-01-01

Objective To create annotated clinical narratives with layers of syntactic and semantic labels to facilitate advances in clinical natural language processing (NLP). To develop NLP algorithms and open source components. Methods Manual annotation of a clinical narrative corpus of 127 606 tokens following the Treebank schema for syntactic information, PropBank schema for predicate-argument structures, and the Unified Medical Language System (UMLS) schema for semantic information. NLP components were developed. Results The final corpus consists of 13 091 sentences containing 1772 distinct predicate lemmas. Of the 766 newly created PropBank frames, 74 are verbs. There are 28 539 named entity (NE) annotations spread over 15 UMLS semantic groups, one UMLS semantic type, and the Person semantic category. The most frequent annotations belong to the UMLS semantic groups of Procedures (15.71%), Disorders (14.74%), Concepts and Ideas (15.10%), Anatomy (12.80%), Chemicals and Drugs (7.49%), and the UMLS semantic type of Sign or Symptom (12.46%). Inter-annotator agreement results: Treebank (0.926), PropBank (0.891–0.931), NE (0.697–0.750). The part-of-speech tagger, constituency parser, dependency parser, and semantic role labeler are built from the corpus and released open source. A significant limitation uncovered by this project is the need for the NLP community to develop a widely agreed-upon schema for the annotation of clinical concepts and their relations. Conclusions This project takes a foundational step towards bringing the field of clinical NLP up to par with NLP in the general domain. The corpus creation and NLP components provide a resource for research and application development that would have been previously impossible. PMID:23355458

When Wine and Apple Both Help the Production of Grapes: ERP Evidence for Post-lexical Semantic Facilitation in Picture Naming

PubMed Central

Python, Grégoire; Fargier, Raphaël; Laganaro, Marina

2018-01-01

Background: Producing a word in referential naming requires to select the right word in our mental lexicon among co-activated semantically related words. The mechanisms underlying semantic context effects during speech planning are still controversial, particularly for semantic facilitation which investigation remains under-represented in contrast to the plethora of studies dealing with interference. Our aim is to study the time-course of semantic facilitation in picture naming, using a picture-word “interference” paradigm and event-related potentials (ERPs). Methods: We compared two different types of semantic relationships, associative and categorical, in a single word priming and a double word priming paradigm. The primes were presented visually with a long negative Stimulus Onset Asynchrony (SOA), which is expected to cause facilitation. Results: Shorter naming latencies were observed after both associative and categorical primes, as compared to unrelated primes, and even shorter latencies after two primes. Electrophysiological results showed relatively late modulations of waveform amplitudes for both types of primes (beginning ~330 ms post picture onset with a single prime and ~275 ms post picture onset with two primes), corresponding to a shift in latency of similar topographic maps across conditions. Conclusion: The present results are in favor of a post-lexical locus of semantic facilitation for associative and categorical priming in picture naming and confirm that semantic facilitation is as relevant as semantic interference to inform on word production. The post-lexical locus argued here might be related to self-monitoting or/and to modulations at the level of word-form planning, without excluding the participation of strategic processes. PMID:29692716

Distractor Modality Can Turn Semantic Interference into Semantic Facilitation in the Picture-Word Interference Task: Implications for Theories of Lexical Access in Speech Production

ERIC Educational Resources Information Center

Hantsch, Ansgar; Jescheniak, Jorg D.; Schriefers, Herbert

2009-01-01

A number of recent studies have questioned the idea that lexical selection during speech production is a competitive process. One type of evidence against selection by competition is the observation that in the picture-word interference task semantically related distractors may facilitate the naming of a picture, whereas the selection by…

The Use of Marking Rules in Semantic Systems. Working Papers of the Language Behavior Research Laboratory, No. 26.

ERIC Educational Resources Information Center

Geoghegan, William H.

This paper discusses the type of marking rule normally used in the production and interpretation of message forms for which semantic marking is possible. The structure and use of such rules is illustrated through a recent study of the semantics of personal address among the Balangingi' Samal, a Muslim group of the southern Philippines. The rule…

A service-oriented distributed semantic mediator: integrating multiscale biomedical information.

PubMed

Mora, Oscar; Engelbrecht, Gerhard; Bisbal, Jesus

2012-11-01

Biomedical research continuously generates large amounts of heterogeneous and multimodal data spread over multiple data sources. These data, if appropriately shared and exploited, could dramatically improve the research practice itself, and ultimately the quality of health care delivered. This paper presents DISMED (DIstributed Semantic MEDiator), an open source semantic mediator that provides a unified view of a federated environment of multiscale biomedical data sources. DISMED is a Web-based software application to query and retrieve information distributed over a set of registered data sources, using semantic technologies. It also offers a userfriendly interface specifically designed to simplify the usage of these technologies by non-expert users. Although the architecture of the software mediator is generic and domain independent, in the context of this paper, DISMED has been evaluated for managing biomedical environments and facilitating research with respect to the handling of scientific data distributed in multiple heterogeneous data sources. As part of this contribution, a quantitative evaluation framework has been developed. It consist of a benchmarking scenario and the definition of five realistic use-cases. This framework, created entirely with public datasets, has been used to compare the performance of DISMED against other available mediators. It is also available to the scientific community in order to evaluate progress in the domain of semantic mediation, in a systematic and comparable manner. The results show an average improvement in the execution time by DISMED of 55% compared to the second best alternative in four out of the five use-cases of the experimental evaluation.

Dissociative semantic breakdown in Alzheimer's disease: evidence from multiple category fluency test.

PubMed

Ting, Simon Kang Seng; Hameed, Shahul; Earnest, Arul; Tan, Eng-King

2013-07-01

Category-specific semantic dissociation particularly in terms of biological and non-biological dichotomy has been described in Alzheimer's disease (AD). We re-examine above finding by performing multiple superordinate category verbal fluency test in AD patients. We analyze the baseline neuropsychological assessment performance of food and animal fluency test of AD patients from a tertiary hospital that collected prospectively over 5 years period and correlation was calculated by Kappa test. The analysis is stratified according to literacy level (primary: 0-6 years education and secondary: >6 years education) and disease severity (MMSE score: mild 19-24, moderate 13-18 and severe <13). A total of 296 AD patients were analyzed and only fair to moderate agreement between food and animal category fluency test was found especially in the mild AD cases (primary: kappa 0.42; secondary: kappa 0.40). Kappa agreement level increases when disease progress especially in the secondary education group. Food category, which is a more relevant semantic knowledge to Singapore population, is generally more affected. Higher educated subjects appeared to have less semantic dissociation effect when disease progress. Despite less primed in daily life, biological category of semantic knowledge appears to be affected less during AD process in highly urbanized Singapore society. Brain appears to have special protective mechanism towards living things. However, education level seems have a modulation effect towards the biological protective mechanism. Copyright © 2012 Elsevier B.V. All rights reserved.

Transductive multi-view zero-shot learning.

PubMed

Fu, Yanwei; Hospedales, Timothy M; Xiang, Tao; Gong, Shaogang

2015-11-01

Most existing zero-shot learning approaches exploit transfer learning via an intermediate semantic representation shared between an annotated auxiliary dataset and a target dataset with different classes and no annotation. A projection from a low-level feature space to the semantic representation space is learned from the auxiliary dataset and applied without adaptation to the target dataset. In this paper we identify two inherent limitations with these approaches. First, due to having disjoint and potentially unrelated classes, the projection functions learned from the auxiliary dataset/domain are biased when applied directly to the target dataset/domain. We call this problem the projection domain shift problem and propose a novel framework, transductive multi-view embedding, to solve it. The second limitation is the prototype sparsity problem which refers to the fact that for each target class, only a single prototype is available for zero-shot learning given a semantic representation. To overcome this problem, a novel heterogeneous multi-view hypergraph label propagation method is formulated for zero-shot learning in the transductive embedding space. It effectively exploits the complementary information offered by different semantic representations and takes advantage of the manifold structures of multiple representation spaces in a coherent manner. We demonstrate through extensive experiments that the proposed approach (1) rectifies the projection shift between the auxiliary and target domains, (2) exploits the complementarity of multiple semantic representations, (3) significantly outperforms existing methods for both zero-shot and N-shot recognition on three image and video benchmark datasets, and (4) enables novel cross-view annotation tasks.

ODMSummary: A Tool for Automatic Structured Comparison of Multiple Medical Forms Based on Semantic Annotation with the Unified Medical Language System.

PubMed

Storck, Michael; Krumm, Rainer; Dugas, Martin

2016-01-01

Medical documentation is applied in various settings including patient care and clinical research. Since procedures of medical documentation are heterogeneous and developed further, secondary use of medical data is complicated. Development of medical forms, merging of data from different sources and meta-analyses of different data sets are currently a predominantly manual process and therefore difficult and cumbersome. Available applications to automate these processes are limited. In particular, tools to compare multiple documentation forms are missing. The objective of this work is to design, implement and evaluate the new system ODMSummary for comparison of multiple forms with a high number of semantically annotated data elements and a high level of usability. System requirements are the capability to summarize and compare a set of forms, enable to estimate the documentation effort, track changes in different versions of forms and find comparable items in different forms. Forms are provided in Operational Data Model format with semantic annotations from the Unified Medical Language System. 12 medical experts were invited to participate in a 3-phase evaluation of the tool regarding usability. ODMSummary (available at https://odmtoolbox.uni-muenster.de/summary/summary.html) provides a structured overview of multiple forms and their documentation fields. This comparison enables medical experts to assess multiple forms or whole datasets for secondary use. System usability was optimized based on expert feedback. The evaluation demonstrates that feedback from domain experts is needed to identify usability issues. In conclusion, this work shows that automatic comparison of multiple forms is feasible and the results are usable for medical experts.

A SEMantic and EPisodic Memory Test (SEMEP) Developed within the Embodied Cognition Framework: Application to Normal Aging, Alzheimer's Disease and Semantic Dementia.

PubMed

Vallet, Guillaume T; Hudon, Carol; Bier, Nathalie; Macoir, Joël; Versace, Rémy; Simard, Martine

2017-01-01

Embodiment has highlighted the importance of sensory-motor components in cognition. Perception and memory are thus very tightly bound together, and episodic and semantic memories should rely on the same grounded memory traces. Reduced perception should then directly reduce the ability to encode and retrieve an episodic memory, as in normal aging. Multimodal integration deficits, as in Alzheimer's disease, should lead to more severe episodic memory impairment. The present study introduces a new memory test developed to take into account these assumptions. The SEMEP (SEMantic-Episodic) memory test proposes to assess conjointly semantic and episodic knowledge across multiple tasks: semantic matching, naming, free recall, and recognition. The performance of young adults is compared to healthy elderly adults (HE), patients with Alzheimer's disease (AD), and patients with semantic dementia (SD). The results show specific patterns of performance between the groups. HE commit memory errors only for presented but not to be remembered items. AD patients present the worst episodic memory performance associated with intrusion errors (recall or recognition of items never presented). They were the only group to not benefit from a visual isolation (addition of a yellow background), a method known to increase the distinctiveness of the memory traces. Finally, SD patients suffer from the most severe semantic impairment. To conclude, confusion errors are common across all the elderly groups, whereas AD was the only group to exhibit regular intrusion errors and SD patients to show severe semantic impairment.

What can Written-Words Tell us About Lexical Retrieval in Speech Production?

PubMed Central

Navarrete, Eduardo; Mahon, Bradford Z.; Lorenzoni, Anna; Peressotti, Francesca

2016-01-01

In recent decades, researchers have exploited semantic context effects in picture naming tasks in order to investigate the mechanisms involved in the retrieval of words from the mental lexicon. In the blocked naming paradigm, participants name target pictures that are either blocked or not blocked by semantic category. In the continuous naming task, participants name a sequence of target pictures that are drawn from multiple semantic categories. Semantic context effects in both tasks are a highly reliable phenomenon. The empirical evidence is, however, sparse and inconsistent when the target stimuli are printed-words instead of pictures. In the first part of the present study we review the empirical evidence regarding semantic context effects with written-word stimuli in the blocked and continuous naming tasks. In the second part, we empirically test whether semantic context effects are transferred from picture naming trials to word reading trials, and from word reading trials to picture naming trials. The results indicate a transfer of semantic context effects from picture naming to subsequently read within-category words. There is no transfer of semantic effects from target words that were read to subsequently named within-category pictures. These results replicate previous findings (Navarrete et al., 2010) and are contrary to predictions from a recent theoretical analysis by Belke (2013). The empirical evidence reported in the literature together with the present results, are discussed in relation to current accounts of semantic context effects in speech production. PMID:26779090

The non-stop road from concrete to abstract: high concreteness causes the activation of long-range networks

PubMed Central

Weiss, Sabine; Müller, Horst M.

2013-01-01

Current grounding theories propose that sensory-motor brain systems are not only modulated by the comprehension of concrete but also partly of abstract language. In order to investigate whether concrete or abstract language elicits similar or distinct brain activity, neuronal synchronization patterns were investigated by means of long-range EEG coherence analysis. Participants performed a semantic judgment task with concrete and abstract sentences. EEG coherence between distant electrodes was analyzed in various frequencies before and during sentence processing using a bivariate AR-model with time-varying parameters. The theta frequency band (3–7 Hz) reflected common and different synchronization networks related to working memory processes and memory-related lexico-semantic retrieval during processing of both sentence types. In contrast, the beta1 band (13–18 Hz) showed prominent differences between both sentence types, whereby concrete sentences were associated with higher coherence implicating a more widespread range and intensity of mental simulation processes. The gamma band (35–40 Hz) reflected the sentences' congruency and indicated the more difficult integration of incongruent final nouns into the sentence context. Most importantly, findings support the notion that different cognitive operations during sentence processing are associated with multiple brain oscillations. PMID:24027515

UltiMatch-NL: A Web Service Matchmaker Based on Multiple Semantic Filters

PubMed Central

Mohebbi, Keyvan; Ibrahim, Suhaimi; Zamani, Mazdak; Khezrian, Mojtaba

2014-01-01

In this paper, a Semantic Web service matchmaker called UltiMatch-NL is presented. UltiMatch-NL applies two filters namely Signature-based and Description-based on different abstraction levels of a service profile to achieve more accurate results. More specifically, the proposed filters rely on semantic knowledge to extract the similarity between a given pair of service descriptions. Thus it is a further step towards fully automated Web service discovery via making this process more semantic-aware. In addition, a new technique is proposed to weight and combine the results of different filters of UltiMatch-NL, automatically. Moreover, an innovative approach is introduced to predict the relevance of requests and Web services and eliminate the need for setting a threshold value of similarity. In order to evaluate UltiMatch-NL, the repository of OWLS-TC is used. The performance evaluation based on standard measures from the information retrieval field shows that semantic matching of OWL-S services can be significantly improved by incorporating designed matching filters. PMID:25157872

ADEpedia: a scalable and standardized knowledge base of Adverse Drug Events using semantic web technology.

PubMed

Jiang, Guoqian; Solbrig, Harold R; Chute, Christopher G

2011-01-01

A source of semantically coded Adverse Drug Event (ADE) data can be useful for identifying common phenotypes related to ADEs. We proposed a comprehensive framework for building a standardized ADE knowledge base (called ADEpedia) through combining ontology-based approach with semantic web technology. The framework comprises four primary modules: 1) an XML2RDF transformation module; 2) a data normalization module based on NCBO Open Biomedical Annotator; 3) a RDF store based persistence module; and 4) a front-end module based on a Semantic Wiki for the review and curation. A prototype is successfully implemented to demonstrate the capability of the system to integrate multiple drug data and ontology resources and open web services for the ADE data standardization. A preliminary evaluation is performed to demonstrate the usefulness of the system, including the performance of the NCBO annotator. In conclusion, the semantic web technology provides a highly scalable framework for ADE data source integration and standard query service.

UltiMatch-NL: a Web service matchmaker based on multiple semantic filters.

PubMed

Mohebbi, Keyvan; Ibrahim, Suhaimi; Zamani, Mazdak; Khezrian, Mojtaba

2014-01-01

In this paper, a Semantic Web service matchmaker called UltiMatch-NL is presented. UltiMatch-NL applies two filters namely Signature-based and Description-based on different abstraction levels of a service profile to achieve more accurate results. More specifically, the proposed filters rely on semantic knowledge to extract the similarity between a given pair of service descriptions. Thus it is a further step towards fully automated Web service discovery via making this process more semantic-aware. In addition, a new technique is proposed to weight and combine the results of different filters of UltiMatch-NL, automatically. Moreover, an innovative approach is introduced to predict the relevance of requests and Web services and eliminate the need for setting a threshold value of similarity. In order to evaluate UltiMatch-NL, the repository of OWLS-TC is used. The performance evaluation based on standard measures from the information retrieval field shows that semantic matching of OWL-S services can be significantly improved by incorporating designed matching filters.

The Hippocampus Remains Activated over the Long Term for the Retrieval of Truly Episodic Memories

PubMed Central

Harand, Caroline; Bertran, Françoise; La Joie, Renaud; Landeau, Brigitte; Mézenge, Florence; Desgranges, Béatrice; Peigneux, Philippe; Eustache, Francis; Rauchs, Géraldine

2012-01-01

The role of the hippocampus in declarative memory consolidation is a matter of intense debate. We investigated the neural substrates of memory retrieval for recent and remote information using functional magnetic resonance imaging (fMRI). 18 young, healthy participants learned a series of pictures. Then, during two fMRI recognition sessions, 3 days and 3 months later, they had to determine whether they recognized or not each picture using the “Remember/Know” procedure. Presentation of the same learned images at both delays allowed us to track the evolution of memories and distinguish consistently episodic memories from those that were initially episodic and then became familiar or semantic over time and were retrieved without any contextual detail. Hippocampal activation decreased over time for initially episodic, later semantic memories, but remained stable for consistently episodic ones, at least in its posterior part. For both types of memories, neocortical activations were observed at both delays, notably in the ventromedial prefrontal and anterior cingulate cortices. These activations may reflect a gradual reorganization of memory traces within neural networks. Our data indicate maintenance and strengthening of hippocampal and cortico-cortical connections in the consolidation and retrieval of episodic memories over time, in line with the Multiple Trace theory (Nadel and Moscovitch, 1997). At variance, memories becoming semantic over time consolidate through strengthening of cortico-cortical connections and progressive disengagement of the hippocampus. PMID:22937055

A way toward analyzing high-content bioimage data by means of semantic annotation and visual data mining

NASA Astrophysics Data System (ADS)

Herold, Julia; Abouna, Sylvie; Zhou, Luxian; Pelengaris, Stella; Epstein, David B. A.; Khan, Michael; Nattkemper, Tim W.

2009-02-01

In the last years, bioimaging has turned from qualitative measurements towards a high-throughput and highcontent modality, providing multiple variables for each biological sample analyzed. We present a system which combines machine learning based semantic image annotation and visual data mining to analyze such new multivariate bioimage data. Machine learning is employed for automatic semantic annotation of regions of interest. The annotation is the prerequisite for a biological object-oriented exploration of the feature space derived from the image variables. With the aid of visual data mining, the obtained data can be explored simultaneously in the image as well as in the feature domain. Especially when little is known of the underlying data, for example in the case of exploring the effects of a drug treatment, visual data mining can greatly aid the process of data evaluation. We demonstrate how our system is used for image evaluation to obtain information relevant to diabetes study and screening of new anti-diabetes treatments. Cells of the Islet of Langerhans and whole pancreas in pancreas tissue samples are annotated and object specific molecular features are extracted from aligned multichannel fluorescence images. These are interactively evaluated for cell type classification in order to determine the cell number and mass. Only few parameters need to be specified which makes it usable also for non computer experts and allows for high-throughput analysis.

Goal-directed mechanisms that constrain retrieval predict subsequent memory for new "foil" information.

PubMed

Vogelsang, David A; Bonnici, Heidi M; Bergström, Zara M; Ranganath, Charan; Simons, Jon S

2016-08-01

To remember a previous event, it is often helpful to use goal-directed control processes to constrain what comes to mind during retrieval. Behavioral studies have demonstrated that incidental learning of new "foil" words in a recognition test is superior if the participant is trying to remember studied items that were semantically encoded compared to items that were non-semantically encoded. Here, we applied subsequent memory analysis to fMRI data to understand the neural mechanisms underlying the "foil effect". Participants encoded information during deep semantic and shallow non-semantic tasks and were tested in a subsequent blocked memory task to examine how orienting retrieval towards different types of information influences the incidental encoding of new words presented as foils during the memory test phase. To assess memory for foils, participants performed a further surprise old/new recognition test involving foil words that were encountered during the previous memory test blocks as well as completely new words. Subsequent memory effects, distinguishing successful versus unsuccessful incidental encoding of foils, were observed in regions that included the left inferior frontal gyrus and posterior parietal cortex. The left inferior frontal gyrus exhibited disproportionately larger subsequent memory effects for semantic than non-semantic foils, and significant overlap in activity during semantic, but not non-semantic, initial encoding and foil encoding. The results suggest that orienting retrieval towards different types of foils involves re-implementing the neurocognitive processes that were involved during initial encoding. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Controlled semantic cognition relies upon dynamic and flexible interactions between the executive 'semantic control' and hub-and-spoke 'semantic representation' systems.

PubMed

Chiou, Rocco; Humphreys, Gina F; Jung, JeYoung; Lambon Ralph, Matthew A

2018-06-01

Built upon a wealth of neuroimaging, neurostimulation, and neuropsychology data, a recent proposal set forth a framework termed controlled semantic cognition (CSC) to account for how the brain underpins the ability to flexibly use semantic knowledge (Lambon Ralph et al., 2017; Nature Reviews Neuroscience). In CSC, the 'semantic control' system, underpinned predominantly by the prefrontal cortex, dynamically monitors and modulates the 'semantic representation' system that consists of a 'hub' (anterior temporal lobe, ATL) and multiple 'spokes' (modality-specific areas). CSC predicts that unfamiliar and exacting semantic tasks should intensify communication between the 'control' and 'representation' systems, relative to familiar and less taxing tasks. In the present study, we used functional magnetic resonance imaging (fMRI) to test this hypothesis. Participants paired unrelated concepts by canonical colours (a less accustomed task - e.g., pairing ketchup with fire-extinguishers due to both being red) or paired well-related concepts by semantic relationship (a typical task - e.g., ketchup is related to mustard). We found the 'control' system was more engaged by atypical than typical pairing. While both tasks activated the ATL 'hub', colour pairing additionally involved occipitotemporal 'spoke' regions abutting areas of hue perception. Furthermore, we uncovered a gradient along the ventral temporal cortex, transitioning from the caudal 'spoke' zones preferring canonical colour processing to the rostral 'hub' zones preferring semantic relationship. Functional connectivity also differed between the tasks: Compared with semantic pairing, colour pairing relied more upon the inferior frontal gyrus, a key node of the control system, driving enhanced connectivity with occipitotemporal 'spoke'. Together, our findings characterise the interaction within the neural architecture of semantic cognition - the control system dynamically heightens its connectivity with relevant components of the representation system, in response to different semantic contents and difficulty levels. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Lions, tigers, and bears, oh sh!t: Semantics versus tabooness in speech production.

PubMed

White, Katherine K; Abrams, Lise; Koehler, Sarah M; Collins, Richard J

2017-04-01

While both semantic and highly emotional (i.e., taboo) words can interfere with speech production, different theoretical mechanisms have been proposed to explain why interference occurs. Two experiments investigated these theoretical approaches by comparing the magnitude of these two types of interference and the stages at which they occur during picture naming. Participants named target pictures superimposed with semantic, taboo, or unrelated distractor words that were presented at three different stimulus-onset asynchronies (SOA): -150 ms, 0 ms, or +150 ms. In addition, the duration of distractor presentation was manipulated across experiments, with distractors appearing for the duration of the picture (Experiment 1) or for 350 ms (Experiment 2). Taboo distractors interfered more than semantic distractors, i.e., slowed target naming times, at all SOAs. While distractor duration had no effect on type of interference at -150 or 0 SOAs, briefly presented distractors eliminated semantic interference but not taboo interference at +150 SOA. Discussion focuses on how existing speech production theories can explain interference from emotional distractors and the unique role that attention may play in taboo interference.

The representation of semantic knowledge in a child with Williams syndrome.

PubMed

Robinson, Sally J; Temple, Christine M

2009-05-01

This study investigated whether there are distinct types of semantic knowledge with distinct representational bases during development. The representation of semantic knowledge in a teenage child (S.T.) with Williams syndrome was explored for the categories of animals, fruit, and vegetables, manipulable objects, and nonmanipulable objects. S.T.'s lexical stores were of a normal size but the volume of "sensory feature" semantic knowledge she generated in oral descriptions was reduced. In visual recognition decisions, S.T. made more false positives to nonitems than did controls. Although overall naming of pictures was unimpaired, S.T. exhibited a category-specific anomia for nonmanipulable objects and impaired naming of visual-feature descriptions of animals. S.T.'s performance was interpreted as reflecting the impaired integration of distinctive features from perceptual input, which may impact upon nonmanipulable objects to a greater extent than the other knowledge categories. Performance was used to inform adult-based models of semantic representation, with category structure proposed to emerge due to differing degrees of dependency upon underlying knowledge types, feature correlations, and the acquisition of information from modality-specific processing modules.

A psycholinguistic database for traditional Chinese character naming.

PubMed

Chang, Ya-Ning; Hsu, Chun-Hsien; Tsai, Jie-Li; Chen, Chien-Liang; Lee, Chia-Ying

2016-03-01

In this study, we aimed to provide a large-scale set of psycholinguistic norms for 3,314 traditional Chinese characters, along with their naming reaction times (RTs), collected from 140 Chinese speakers. The lexical and semantic variables in the database include frequency, regularity, familiarity, consistency, number of strokes, homophone density, semantic ambiguity rating, phonetic combinability, semantic combinability, and the number of disyllabic compound words formed by a character. Multiple regression analyses were conducted to examine the predictive powers of these variables for the naming RTs. The results demonstrated that these variables could account for a significant portion of variance (55.8%) in the naming RTs. An additional multiple regression analysis was conducted to demonstrate the effects of consistency and character frequency. Overall, the regression results were consistent with the findings of previous studies on Chinese character naming. This database should be useful for research into Chinese language processing, Chinese education, or cross-linguistic comparisons. The database can be accessed via an online inquiry system (http://ball.ling.sinica.edu.tw/namingdatabase/index.html).

Impaired category fluency in medial temporal lobe amnesia: the role of episodic memory.

PubMed

Greenberg, Daniel L; Keane, Margaret M; Ryan, Lee; Verfaellie, Mieke

2009-09-02

Memory tasks are often classified as semantic or episodic, but recent research shows that these types of memory are highly interactive. Category fluency, for example, is generally considered to reflect retrieval from semantic memory, but behavioral evidence suggests that episodic memory is also involved: participants frequently draw on autobiographical experiences while generating exemplars of certain categories. Neuroimaging studies accordingly have reported increased medial temporal lobe (MTL) activation during exemplar generation. Studies of fluency in MTL amnesics have yielded mixed results but were not designed to determine the precise contributions of episodic memory. We addressed this issue by asking MTL amnesics and controls to generate exemplars of three types of categories. One type tended to elicit autobiographical and spatial retrieval strategies (AS). Another type elicited strategies that were autobiographical but nonspatial (AN). The third type elicited neither autobiographical nor spatial strategies (N). Amnesic patients and control participants generated exemplars for eight categories of each type. Patients were impaired on all category types but were more impaired on AS and AN categories. After covarying for phonemic fluency (total FAS score), the N category impairment was not significant, but the impairment on AS and AN categories remained. The same results were obtained for patients with lesions restricted to the MTL and those with more extensive lesions. We conclude that patients' episodic memory impairment hindered their performance on this putatively semantic task. This interaction between episodic and semantic memory might partially account for fluency deficits seen in aging, mild cognitive impairment, and Alzheimer's disease.

Social and Personal Factors in Semantic Infusion Projects

NASA Astrophysics Data System (ADS)

West, P.; Fox, P. A.; McGuinness, D. L.

2009-12-01

As part of our semantic data framework activities across multiple, diverse disciplines we required the involvement of domain scientists, computer scientists, software engineers, data managers, and often, social scientists. This involvement from a cross-section of disciplines turns out to be a social exercise as much as it is a technical and methodical activity. Each member of the team is used to different modes of working, expectations, vocabularies, levels of participation, and incentive and reward systems. We will examine how both roles and personal responsibilities play in the development of semantic infusion projects, and how an iterative development cycle can contribute to the successful completion of such a project.

The Relation between Thematic Role Computing and Semantic Relatedness Processing during On-Line Sentence Comprehension

PubMed Central

Li, Xiaoqing; Zhao, Haiyan; Lu, Yong

2014-01-01

Sentence comprehension involves timely computing different types of relations between its verbs and noun arguments, such as morphosyntactic, semantic, and thematic relations. Here, we used EEG technique to investigate the potential differences in thematic role computing and lexical-semantic relatedness processing during on-line sentence comprehension, and the interaction between these two types of processes. Mandarin Chinese sentences were used as materials. The basic structure of those sentences is “Noun+Verb+‘le’+a two-character word”, with the Noun being the initial argument. The verb disambiguates the initial argument as an agent or a patient. Meanwhile, the initial argument and the verb are highly or lowly semantically related. The ERPs at the verbs revealed that: relative to the agent condition, the patient condition evoked a larger N400 only when the argument and verb were lowly semantically related; however, relative to the high-relatedness condition, the low-relatedness condition elicited a larger N400 regardless of the thematic relation; although both thematic role variation and semantic relatedness variation elicited N400 effects, the N400 effect elicited by the former was broadly distributed and reached maximum over the frontal electrodes, and the N400 effect elicited by the latter had a posterior distribution. In addition, the brain oscillations results showed that, although thematic role variation (patient vs. agent) induced power decreases around the beta frequency band (15–30 Hz), semantic relatedness variation (low-relatedness vs. high-relatedness) induced power increases in the theta frequency band (4–7 Hz). These results suggested that, in the sentence context, thematic role computing is modulated by the semantic relatedness between the verb and its argument; semantic relatedness processing, however, is in some degree independent from the thematic relations. Moreover, our results indicated that, during on-line sentence comprehension, thematic role computing and semantic relatedness processing are mediated by distinct neural systems. PMID:24755643

Semantic Web technologies for the big data in life sciences.

PubMed

Wu, Hongyan; Yamaguchi, Atsuko

2014-08-01

The life sciences field is entering an era of big data with the breakthroughs of science and technology. More and more big data-related projects and activities are being performed in the world. Life sciences data generated by new technologies are continuing to grow in not only size but also variety and complexity, with great speed. To ensure that big data has a major influence in the life sciences, comprehensive data analysis across multiple data sources and even across disciplines is indispensable. The increasing volume of data and the heterogeneous, complex varieties of data are two principal issues mainly discussed in life science informatics. The ever-evolving next-generation Web, characterized as the Semantic Web, is an extension of the current Web, aiming to provide information for not only humans but also computers to semantically process large-scale data. The paper presents a survey of big data in life sciences, big data related projects and Semantic Web technologies. The paper introduces the main Semantic Web technologies and their current situation, and provides a detailed analysis of how Semantic Web technologies address the heterogeneous variety of life sciences big data. The paper helps to understand the role of Semantic Web technologies in the big data era and how they provide a promising solution for the big data in life sciences.

Improving life sciences information retrieval using semantic web technology.

PubMed

Quan, Dennis

2007-05-01

The ability to retrieve relevant information is at the heart of every aspect of research and development in the life sciences industry. Information is often distributed across multiple systems and recorded in a way that makes it difficult to piece together the complete picture. Differences in data formats, naming schemes and network protocols amongst information sources, both public and private, must be overcome, and user interfaces not only need to be able to tap into these diverse information sources but must also assist users in filtering out extraneous information and highlighting the key relationships hidden within an aggregated set of information. The Semantic Web community has made great strides in proposing solutions to these problems, and many efforts are underway to apply Semantic Web techniques to the problem of information retrieval in the life sciences space. This article gives an overview of the principles underlying a Semantic Web-enabled information retrieval system: creating a unified abstraction for knowledge using the RDF semantic network model; designing semantic lenses that extract contextually relevant subsets of information; and assembling semantic lenses into powerful information displays. Furthermore, concrete examples of how these principles can be applied to life science problems including a scenario involving a drug discovery dashboard prototype called BioDash are provided.

Unaware Memory in Hypothesis Generation Tasks

DTIC Science & Technology

1986-12-01

have been offered within the context of Tulving’s (1972) distinction between episodic and semantic memory systems (e.g., see Jacoby & - Witherspoon...in this direction (see Tulving, 1985) raise the possibility that neither episodic nor semantic memory systems can account for the type of unaware...material: Interactions with " episodic " and " semantic " memory . Conitive Psycholozv, 12, 227-251. Kolers, P. A. (1976). Reading a year later. Journal o

Visual Field Differences in Visual Word Recognition Can Emerge Purely from Perceptual Learning: Evidence from Modeling Chinese Character Pronunciation

ERIC Educational Resources Information Center

Hsiao, Janet Hui-wen

2011-01-01

In Chinese orthography, a dominant character structure exists in which a semantic radical appears on the left and a phonetic radical on the right (SP characters); a minority opposite arrangement also exists (PS characters). As the number of phonetic radical types is much greater than semantic radical types, in SP characters the information is…

A Characterization of Visual, Semantic and Auditory Memory in Children with Combination-Type Attention Deficit, Primarily Inattentive, and a Control Group

ERIC Educational Resources Information Center

Ramirez, Luz Angela; Arenas, Angela Maria; Henao, Gloria Cecilia

2005-01-01

Introduction: This investigation describes and compares characteristics of visual, semantic and auditory memory in a group of children diagnosed with combined-type attention deficit with hyperactivity, attention deficit predominating, and a control group. Method: 107 boys and girls were selected, from 7 to 11 years of age, all residents in the…

Nonword Repetition and Vocabulary Knowledge as Predictors of Children's Phonological and Semantic Word Learning

PubMed Central

Patten, Hannah

2017-01-01

Purpose This study examined the unique and shared variance that nonword repetition and vocabulary knowledge contribute to children's ability to learn new words. Multiple measures of word learning were used to assess recall and recognition of phonological and semantic information. Method Fifty children, with a mean age of 8 years (range 5–12 years), completed experimental assessments of word learning and norm-referenced assessments of receptive and expressive vocabulary knowledge and nonword repetition skills. Hierarchical multiple regression analyses examined the variance in word learning that was explained by vocabulary knowledge and nonword repetition after controlling for chronological age. Results Together with chronological age, nonword repetition and vocabulary knowledge explained up to 44% of the variance in children's word learning. Nonword repetition was the stronger predictor of phonological recall, phonological recognition, and semantic recognition, whereas vocabulary knowledge was the stronger predictor of verbal semantic recall. Conclusions These findings extend the results of past studies indicating that both nonword repetition skill and existing vocabulary knowledge are important for new word learning, but the relative influence of each predictor depends on the way word learning is measured. Suggestions for further research involving typically developing children and children with language or reading impairments are discussed. PMID:28241284

Abnormal dynamics of language in schizophrenia.

PubMed

Stephane, Massoud; Kuskowski, Michael; Gundel, Jeanette

2014-05-30

Language could be conceptualized as a dynamic system that includes multiple interactive levels (sub-lexical, lexical, sentence, and discourse) and components (phonology, semantics, and syntax). In schizophrenia, abnormalities are observed at all language elements (levels and components) but the dynamic between these elements remains unclear. We hypothesize that the dynamics between language elements in schizophrenia is abnormal and explore how this dynamic is altered. We, first, investigated language elements with comparable procedures in patients and healthy controls. Second, using measures of reaction time, we performed multiple linear regression analyses to evaluate the inter-relationships among language elements and the effect of group on these relationships. Patients significantly differed from controls with respect to sub-lexical/lexical, lexical/sentence, and sentence/discourse regression coefficients. The intercepts of the regression slopes increased in the same order above (from lower to higher levels) in patients but not in controls. Regression coefficients between syntax and both sentence level and discourse level semantics did not differentiate patients from controls. This study indicates that the dynamics between language elements is abnormal in schizophrenia. In patients, top-down flow of linguistic information might be reduced, and the relationship between phonology and semantics but not between syntax and semantics appears to be altered. Published by Elsevier Ireland Ltd.

Semantic Ambiguity: Do Multiple Meanings Inhibit or Facilitate Word Recognition?

ERIC Educational Resources Information Center

Haro, Juan; Ferré, Pilar

2018-01-01

It is not clear whether multiple unrelated meanings inhibit or facilitate word recognition. Some studies have found a disadvantage for words having multiple meanings with respect to unambiguous words in lexical decision tasks (LDT), whereas several others have shown a facilitation for such words. In the present study, we argue that these…

Lung cancer signature biomarkers: tissue specific semantic similarity based clustering of digital differential display (DDD) data.

PubMed

Srivastava, Mousami; Khurana, Pankaj; Sugadev, Ragumani

2012-11-02

The tissue-specific Unigene Sets derived from more than one million expressed sequence tags (ESTs) in the NCBI, GenBank database offers a platform for identifying significantly and differentially expressed tissue-specific genes by in-silico methods. Digital differential display (DDD) rapidly creates transcription profiles based on EST comparisons and numerically calculates, as a fraction of the pool of ESTs, the relative sequence abundance of known and novel genes. However, the process of identifying the most likely tissue for a specific disease in which to search for candidate genes from the pool of differentially expressed genes remains difficult. Therefore, we have used 'Gene Ontology semantic similarity score' to measure the GO similarity between gene products of lung tissue-specific candidate genes from control (normal) and disease (cancer) sets. This semantic similarity score matrix based on hierarchical clustering represents in the form of a dendrogram. The dendrogram cluster stability was assessed by multiple bootstrapping. Multiple bootstrapping also computes a p-value for each cluster and corrects the bias of the bootstrap probability. Subsequent hierarchical clustering by the multiple bootstrapping method (α = 0.95) identified seven clusters. The comparative, as well as subtractive, approach revealed a set of 38 biomarkers comprising four distinct lung cancer signature biomarker clusters (panel 1-4). Further gene enrichment analysis of the four panels revealed that each panel represents a set of lung cancer linked metastasis diagnostic biomarkers (panel 1), chemotherapy/drug resistance biomarkers (panel 2), hypoxia regulated biomarkers (panel 3) and lung extra cellular matrix biomarkers (panel 4). Expression analysis reveals that hypoxia induced lung cancer related biomarkers (panel 3), HIF and its modulating proteins (TGM2, CSNK1A1, CTNNA1, NAMPT/Visfatin, TNFRSF1A, ETS1, SRC-1, FN1, APLP2, DMBT1/SAG, AIB1 and AZIN1) are significantly down regulated. All down regulated genes in this panel were highly up regulated in most other types of cancers. These panels of proteins may represent signature biomarkers for lung cancer and will aid in lung cancer diagnosis and disease monitoring as well as in the prediction of responses to therapeutics.

A Method for Overcoming the Problem of Concept-Scale Interaction in Semantic Differential Research

ERIC Educational Resources Information Center

Bynner, John; Romney, David

1972-01-01

Data collected in a study of hospital staff attitudes to drug addicts and other types of patients are used to illustrate the problem of concept-scale interaction in semantic differential research. (Authors)

Alignment of the UMLS semantic network with BioTop: methodology and assessment.

PubMed

Schulz, Stefan; Beisswanger, Elena; van den Hoek, László; Bodenreider, Olivier; van Mulligen, Erik M

2009-06-15

For many years, the Unified Medical Language System (UMLS) semantic network (SN) has been used as an upper-level semantic framework for the categorization of terms from terminological resources in biomedicine. BioTop has recently been developed as an upper-level ontology for the biomedical domain. In contrast to the SN, it is founded upon strict ontological principles, using OWL DL as a formal representation language, which has become standard in the semantic Web. In order to make logic-based reasoning available for the resources annotated or categorized with the SN, a mapping ontology was developed aligning the SN with BioTop. The theoretical foundations and the practical realization of the alignment are being described, with a focus on the design decisions taken, the problems encountered and the adaptations of BioTop that became necessary. For evaluation purposes, UMLS concept pairs obtained from MEDLINE abstracts by a named entity recognition system were tested for possible semantic relationships. Furthermore, all semantic-type combinations that occur in the UMLS Metathesaurus were checked for satisfiability. The effort-intensive alignment process required major design changes and enhancements of BioTop and brought up several design errors that could be fixed. A comparison between a human curator and the ontology yielded only a low agreement. Ontology reasoning was also used to successfully identify 133 inconsistent semantic-type combinations. BioTop, the OWL DL representation of the UMLS SN, and the mapping ontology are available at http://www.purl.org/biotop/.

Episodic memory, semantic memory, and amnesia.

PubMed

Squire, L R; Zola, S M

1998-01-01

Episodic memory and semantic memory are two types of declarative memory. There have been two principal views about how this distinction might be reflected in the organization of memory functions in the brain. One view, that episodic memory and semantic memory are both dependent on the integrity of medial temporal lobe and midline diencephalic structures, predicts that amnesic patients with medial temporal lobe/diencephalic damage should be proportionately impaired in both episodic and semantic memory. An alternative view is that the capacity for semantic memory is spared, or partially spared, in amnesia relative to episodic memory ability. This article reviews two kinds of relevant data: 1) case studies where amnesia has occurred early in childhood, before much of an individual's semantic knowledge has been acquired, and 2) experimental studies with amnesic patients of fact and event learning, remembering and knowing, and remote memory. The data provide no compelling support for the view that episodic and semantic memory are affected differently in medial temporal lobe/diencephalic amnesia. However, episodic and semantic memory may be dissociable in those amnesic patients who additionally have severe frontal lobe damage.

The semantic-similarity effect in children: influence of long-term knowledge on verbal short-term memory.

PubMed

Monnier, Catherine; Bonthoux, Françoise

2011-11-01

The present research was designed to highlight the relation between children's categorical knowledge and their verbal short-term memory (STM) performance. To do this, we manipulated the categorical organization of the words composing lists to be memorized by 5- and 9-year-old children. Three types of word list were drawn up: semantically similar context-dependent (CD) lists, semantically similar context-independent (CI) lists, and semantically dissimilar lists. In line with the procedure used by Poirier and Saint-Aubin (1995), the dissimilar lists were produced using words from the semantically similar lists. Both 5- and 9-year-old children showed better recall for the semantically similar CD lists than they did for the unrelated lists. In the semantic similar CI condition, semantic similarity enhanced immediate serial recall only at age 9 but contributed to item information memory both at ages 5 and 9. These results, which indicate a semantic influence of long-term memory (LTM) on serial recall from age 5, are discussed in the light of current models of STM. Moreover, we suggest that differences between results at 5 and 9 years are compatible with pluralist models of development. ©2011 The British Psychological Society.

Enhancing Biomedical Text Summarization Using Semantic Relation Extraction

PubMed Central

Shang, Yue; Li, Yanpeng; Lin, Hongfei; Yang, Zhihao

2011-01-01

Automatic text summarization for a biomedical concept can help researchers to get the key points of a certain topic from large amount of biomedical literature efficiently. In this paper, we present a method for generating text summary for a given biomedical concept, e.g., H1N1 disease, from multiple documents based on semantic relation extraction. Our approach includes three stages: 1) We extract semantic relations in each sentence using the semantic knowledge representation tool SemRep. 2) We develop a relation-level retrieval method to select the relations most relevant to each query concept and visualize them in a graphic representation. 3) For relations in the relevant set, we extract informative sentences that can interpret them from the document collection to generate text summary using an information retrieval based method. Our major focus in this work is to investigate the contribution of semantic relation extraction to the task of biomedical text summarization. The experimental results on summarization for a set of diseases show that the introduction of semantic knowledge improves the performance and our results are better than the MEAD system, a well-known tool for text summarization. PMID:21887336

Recursion in aphasia.

PubMed

Bánréti, Zoltán

2010-11-01

This study investigates how aphasic impairment impinges on syntactic and/or semantic recursivity of human language. A series of tests has been conducted with the participation of five Hungarian speaking aphasic subjects and 10 control subjects. Photographs representing simple situations were presented to subjects and questions were asked about them. The responses are supposed to involve formal structural recursion, but they contain semantic-pragmatic operations instead, with 'theory of mind' type embeddings. Aphasic individuals tend to exploit the parallel between 'theory of mind' embeddings and syntactic-structural embeddings in order to avoid formal structural recursion. Formal structural recursion may be more impaired in Broca's aphasia and semantic recursivity may remain selectively unimpaired in this type of aphasia.

Recognition during recall failure: Semantic feature matching as a mechanism for recognition of semantic cues when recall fails.

PubMed

Cleary, Anne M; Ryals, Anthony J; Wagner, Samantha R

2016-01-01

Research suggests that a feature-matching process underlies cue familiarity-detection when cued recall with graphemic cues fails. When a test cue (e.g., potchbork) overlaps in graphemic features with multiple unrecalled studied items (e.g., patchwork, pitchfork, pocketbook, pullcork), higher cue familiarity ratings are given during recall failure of all of the targets than when the cue overlaps in graphemic features with only one studied target and that target fails to be recalled (e.g., patchwork). The present study used semantic feature production norms (McRae et al., Behavior Research Methods, Instruments, & Computers, 37, 547-559, 2005) to examine whether the same holds true when the cues are semantic in nature (e.g., jaguar is used to cue cheetah). Indeed, test cues (e.g., cedar) that overlapped in semantic features (e.g., a_tree, has_bark, etc.) with four unretrieved studied items (e.g., birch, oak, pine, willow) received higher cue familiarity ratings during recall failure than test cues that overlapped in semantic features with only two (also unretrieved) studied items (e.g., birch, oak), which in turn received higher familiarity ratings during recall failure than cues that did not overlap in semantic features with any studied items. These findings suggest that the feature-matching theory of recognition during recall failure can accommodate recognition of semantic cues during recall failure, providing a potential mechanism for conceptually-based forms of cue recognition during target retrieval failure. They also provide converging evidence for the existence of the semantic features envisaged in feature-based models of semantic knowledge representation and for those more concretely specified by the production norms of McRae et al. (Behavior Research Methods, Instruments, & Computers, 37, 547-559, 2005).

Personal semantics: Is it distinct from episodic and semantic memory? An electrophysiological study of memory for autobiographical facts and repeated events in honor of Shlomo Bentin.

PubMed

Renoult, Louis; Tanguay, Annick; Beaudry, Myriam; Tavakoli, Paniz; Rabipour, Sheida; Campbell, Kenneth; Moscovitch, Morris; Levine, Brian; Davidson, Patrick S R

2016-03-01

Declarative memory is thought to consist of two independent systems: episodic and semantic. Episodic memory represents personal and contextually unique events, while semantic memory represents culturally-shared, acontextual factual knowledge. Personal semantics refers to aspects of declarative memory that appear to fall somewhere in between the extremes of episodic and semantic. Examples include autobiographical knowledge and memories of repeated personal events. These two aspects of personal semantics have been studied little and rarely compared to both semantic and episodic memory. We recorded the event-related potentials (ERPs) of 27 healthy participants while they verified the veracity of sentences probing four types of questions: general (i.e., semantic) facts, autobiographical facts, repeated events, and unique (i.e., episodic) events. Behavioral results showed equivalent reaction times in all 4 conditions. True sentences were verified faster than false sentences, except for unique events for which no significant difference was observed. Electrophysiological results showed that the N400 (which is classically associated with retrieval from semantic memory) was maximal for general facts and the LPC (which is classically associated with retrieval from episodic memory) was maximal for unique events. For both ERP components, the two personal semantic conditions (i.e., autobiographical facts and repeated events) systematically differed from semantic memory. In addition, N400 amplitudes also differentiated autobiographical facts from unique events. Autobiographical facts and repeated events did not differ significantly from each other but their corresponding scalp distributions differed from those associated with general facts. Our results suggest that the neural correlates of personal semantics can be distinguished from those of semantic and episodic memory, and may provide clues as to how unique events are transformed to semantic memory. Copyright © 2015 Elsevier Ltd. All rights reserved.

What Klein's "Semantic Gradient" Does and Does Not Really Show: Decomposing Stroop Interference into Task and Informational Conflict Components.

PubMed

Levin, Yulia; Tzelgov, Joseph

2016-01-01

The present study suggests that the idea that Stroop interference originates from multiple components may gain theoretically from integrating two independent frameworks. The first framework is represented by the well-known notion of "semantic gradient" of interference and the second one is the distinction between two types of conflict - the task and the informational conflict - giving rise to the interference (MacLeod and MacDonald, 2000; Goldfarb and Henik, 2007). The proposed integration led to the conclusion that two (i.e., orthographic and lexical components) of the four theoretically distinct components represent task conflict, and the other two (i.e., indirect and direct informational conflict components) represent informational conflict. The four components were independently estimated in a series of experiments. The results confirmed the contribution of task conflict (estimated by a robust orthographic component) and of informational conflict (estimated by a strong direct informational conflict component) to Stroop interference. However, the performed critical review of the relevant literature (see General Discussion), as well as the results of the experiments reported, showed that the other two components expressing each type of conflict (i.e., the lexical component of task conflict and the indirect informational conflict) were small and unstable. The present analysis refines our knowledge of the origins of Stroop interference by providing evidence that each type of conflict has its major and minor contributions. The implications for cognitive control of an automatic reading process are also discussed.

What Klein’s “Semantic Gradient” Does and Does Not Really Show: Decomposing Stroop Interference into Task and Informational Conflict Components

PubMed Central

Levin, Yulia; Tzelgov, Joseph

2016-01-01

The present study suggests that the idea that Stroop interference originates from multiple components may gain theoretically from integrating two independent frameworks. The first framework is represented by the well-known notion of “semantic gradient” of interference and the second one is the distinction between two types of conflict – the task and the informational conflict – giving rise to the interference (MacLeod and MacDonald, 2000; Goldfarb and Henik, 2007). The proposed integration led to the conclusion that two (i.e., orthographic and lexical components) of the four theoretically distinct components represent task conflict, and the other two (i.e., indirect and direct informational conflict components) represent informational conflict. The four components were independently estimated in a series of experiments. The results confirmed the contribution of task conflict (estimated by a robust orthographic component) and of informational conflict (estimated by a strong direct informational conflict component) to Stroop interference. However, the performed critical review of the relevant literature (see General Discussion), as well as the results of the experiments reported, showed that the other two components expressing each type of conflict (i.e., the lexical component of task conflict and the indirect informational conflict) were small and unstable. The present analysis refines our knowledge of the origins of Stroop interference by providing evidence that each type of conflict has its major and minor contributions. The implications for cognitive control of an automatic reading process are also discussed. PMID:26955363

Semantic memory assessment in 15 patients with amyotrophic lateral sclerosis.

PubMed

Hervieu-Bègue, M; Rouaud, O; Graule Petot, A; Catteau, A; Giroud, M

2016-01-01

A total of 30 to 50% of amyotrophic lateral sclerosis patients suffer from cognitive disorders. The aim of the study is to characterize these disorders and to assess semantic memory in non-demented ALS patients. The secondary aim is to look for a link between disease type and neuropsychological characteristics. Patients were followed in an ALS center in Dijon. The following neuropsychological tests were used in this study: Folstein test, BREF test, verbal fluency, Isaac test, GRESEM test and TOP 30 test. Fifteen ALS patients were included. Nine of them (60%) were suffering from a semantic memory disorder. There was no correlation between ALS characteristics and the semantic memory disorder. This is the first study to reveal a semantic memory disorder in ALS. This result accentuates the hypothesis that ALS and semantic dementia are two phenotypes of the same degenerative process linked to TDP 43 proteinopathy. Copyright © 2016. Published by Elsevier Masson SAS.

Semantic Data Integration and Knowledge Management to Represent Biological Network Associations.

PubMed

Losko, Sascha; Heumann, Klaus

2017-01-01

The vast quantities of information generated by academic and industrial research groups are reflected in a rapidly growing body of scientific literature and exponentially expanding resources of formalized data, including experimental data, originating from a multitude of "-omics" platforms, phenotype information, and clinical data. For bioinformatics, the challenge remains to structure this information so that scientists can identify relevant information, to integrate this information as specific "knowledge bases," and to formalize this knowledge across multiple scientific domains to facilitate hypothesis generation and validation. Here we report on progress made in building a generic knowledge management environment capable of representing and mining both explicit and implicit knowledge and, thus, generating new knowledge. Risk management in drug discovery and clinical research is used as a typical example to illustrate this approach. In this chapter we introduce techniques and concepts (such as ontologies, semantic objects, typed relationships, contexts, graphs, and information layers) that are used to represent complex biomedical networks. The BioXM™ Knowledge Management Environment is used as an example to demonstrate how a domain such as oncology is represented and how this representation is utilized for research.

ODMSummary: A Tool for Automatic Structured Comparison of Multiple Medical Forms Based on Semantic Annotation with the Unified Medical Language System

PubMed Central

Krumm, Rainer; Dugas, Martin

2016-01-01

Introduction Medical documentation is applied in various settings including patient care and clinical research. Since procedures of medical documentation are heterogeneous and developed further, secondary use of medical data is complicated. Development of medical forms, merging of data from different sources and meta-analyses of different data sets are currently a predominantly manual process and therefore difficult and cumbersome. Available applications to automate these processes are limited. In particular, tools to compare multiple documentation forms are missing. The objective of this work is to design, implement and evaluate the new system ODMSummary for comparison of multiple forms with a high number of semantically annotated data elements and a high level of usability. Methods System requirements are the capability to summarize and compare a set of forms, enable to estimate the documentation effort, track changes in different versions of forms and find comparable items in different forms. Forms are provided in Operational Data Model format with semantic annotations from the Unified Medical Language System. 12 medical experts were invited to participate in a 3-phase evaluation of the tool regarding usability. Results ODMSummary (available at https://odmtoolbox.uni-muenster.de/summary/summary.html) provides a structured overview of multiple forms and their documentation fields. This comparison enables medical experts to assess multiple forms or whole datasets for secondary use. System usability was optimized based on expert feedback. Discussion The evaluation demonstrates that feedback from domain experts is needed to identify usability issues. In conclusion, this work shows that automatic comparison of multiple forms is feasible and the results are usable for medical experts. PMID:27736972

Addressing the Challenges of Multi-Domain Data Integration with the SemantEco Framework

NASA Astrophysics Data System (ADS)

Patton, E. W.; Seyed, P.; McGuinness, D. L.

2013-12-01

Data integration across multiple domains will continue to be a challenge with the proliferation of big data in the sciences. Data origination issues and how data are manipulated are critical to enable scientists to understand and consume disparate datasets as research becomes more multidisciplinary. We present the SemantEco framework as an exemplar for designing an integrative portal for data discovery, exploration, and interpretation that uses best practice W3C Recommendations. We use the Resource Description Framework (RDF) with extensible ontologies described in the Web Ontology Language (OWL) to provide graph-based data representation. Furthermore, SemantEco ingests data via the software package csv2rdf4lod, which generates data provenance using the W3C provenance recommendation (PROV). Our presentation will discuss benefits and challenges of semantic integration, their effect on runtime performance, and how the SemantEco framework assisted in identifying performance issues and improved query performance across multiple domains by an order of magnitude. SemantEco benefits from a semantic approach that provides an 'open world', which allows data to incrementally change just as it does in the real world. SemantEco modules may load new ontologies and data using the W3C's SPARQL Protocol and RDF Query Language via HTTP. Modules may also provide user interface elements for applications and query capabilities to support new use cases. Modules can associate with domains, which are first-class objects in SemantEco. This enables SemantEco to perform integration and reasoning both within and across domains on module-provided data. The SemantEco framework has been used to construct a web portal for environmental and ecological data. The portal includes water and air quality data from the U.S. Geological Survey (USGS) and Environmental Protection Agency (EPA) and species observation counts for birds and fish from the Avian Knowledge Network and the Santa Barbara Long Term Ecological Research, respectively. We provide regulation ontologies using OWL2 datatype facets to detect out-of-range measurements for environmental standards set by the EPA, i.a. Users adjust queries using module-defined facets and a map presents the resulting measurement sites. Custom icons identify sites that violate regulations, making them easy to locate. Selecting a site gives the option of charting spatially proximate data from different domains over time. Our portal currently provides 1.6 billion triples of scientific data in RDF. We segment data by ZIP code and reasoning over 2157 measurements with our EPA regulation ontology that contains 131 regulations takes 2.5 seconds on a 2.4 GHz Intel Core 2 Quad with 8 GB of RAM. SemantEco's modular design and reasoning capabilities make it an exemplar for building multidisciplinary data integration tools that provide data access to scientists and the general population alike. Its provenance tracking provides accountability and its reasoning services can assist users in interpreting data. Future work includes support for geographical queries using the Open Geospatial Consortium's GeoSPARQL standard.

Toward Webscale, Rule-Based Inference on the Semantic Web Via Data Parallelism

DTIC Science & Technology

2013-02-01

Another work distinct from its peers is the work on approximate reasoning by Rudolph et al. [34] in which multiple inference sys- tems were combined not...Workshop Scalable Semantic Web Knowledge Base Systems, 2010, pp. 17–31. [34] S. Rudolph , T. Tserendorj, and P. Hitzler, “What is approximate reasoning...2013] [55] M. Duerst and M. Suignard. (2005, Jan .). RFC 3987 – internationalized resource identifiers (IRIs). IETF. [Online]. Available: http

Semantically Transparent and Opaque Compounds in German Noun-Phrase Production: Evidence for Morphemes in Speaking.

PubMed

Lorenz, Antje; Zwitserlood, Pienie

2016-01-01

This study examines the lexical representation and processing of noun-noun compounds and their grammatical gender during speech production in German, a language that codes for grammatical gender (masculine, feminine, and neuter). Using a picture-word interference paradigm, participants produced determiner-compound noun phrases in response to pictures, while ignoring written distractor words. Compound targets were either semantically transparent (e.g., birdhouse) or opaque (e.g., hotdog), and their constituent nouns either had the same or a different gender (internal gender match). Effects of gender-congruent but otherwise unrelated distractor nouns, and of two morphologically related distractors corresponding to the first or second constituent were assessed relative to a completely unrelated, gender-incongruent distractor baseline. Both constituent distractors strongly facilitated compound naming, and these effects were independent of the targets' semantic transparency. This supports retrieval of constituent morphemes for semantically transparent and opaque compounds during speech production. Furthermore, gender congruency between compounds and distractors did not speed up naming in general, but interacted with gender match of the compounds' constituent nouns, and their semantic transparency. A significant gender-congruency effect was obtained with semantically transparent compounds, consisting of two constituent nouns of the same gender, only. In principle, this pattern is compatible with a multiple lemma representation account for semantically transparent, but not for opaque compounds. The data also fit with a more parsimonious, holistic representation for all compounds at the lemma level, when differences in co-activation patterns for semantically transparent and opaque compounds are considered.

Synonym extraction and abbreviation expansion with ensembles of semantic spaces.

PubMed

Henriksson, Aron; Moen, Hans; Skeppstedt, Maria; Daudaravičius, Vidas; Duneld, Martin

2014-02-05

Terminologies that account for variation in language use by linking synonyms and abbreviations to their corresponding concept are important enablers of high-quality information extraction from medical texts. Due to the use of specialized sub-languages in the medical domain, manual construction of semantic resources that accurately reflect language use is both costly and challenging, often resulting in low coverage. Although models of distributional semantics applied to large corpora provide a potential means of supporting development of such resources, their ability to isolate synonymy from other semantic relations is limited. Their application in the clinical domain has also only recently begun to be explored. Combining distributional models and applying them to different types of corpora may lead to enhanced performance on the tasks of automatically extracting synonyms and abbreviation-expansion pairs. A combination of two distributional models - Random Indexing and Random Permutation - employed in conjunction with a single corpus outperforms using either of the models in isolation. Furthermore, combining semantic spaces induced from different types of corpora - a corpus of clinical text and a corpus of medical journal articles - further improves results, outperforming a combination of semantic spaces induced from a single source, as well as a single semantic space induced from the conjoint corpus. A combination strategy that simply sums the cosine similarity scores of candidate terms is generally the most profitable out of the ones explored. Finally, applying simple post-processing filtering rules yields substantial performance gains on the tasks of extracting abbreviation-expansion pairs, but not synonyms. The best results, measured as recall in a list of ten candidate terms, for the three tasks are: 0.39 for abbreviations to long forms, 0.33 for long forms to abbreviations, and 0.47 for synonyms. This study demonstrates that ensembles of semantic spaces can yield improved performance on the tasks of automatically extracting synonyms and abbreviation-expansion pairs. This notion, which merits further exploration, allows different distributional models - with different model parameters - and different types of corpora to be combined, potentially allowing enhanced performance to be obtained on a wide range of natural language processing tasks.

Synonym extraction and abbreviation expansion with ensembles of semantic spaces

PubMed Central

2014-01-01

Background Terminologies that account for variation in language use by linking synonyms and abbreviations to their corresponding concept are important enablers of high-quality information extraction from medical texts. Due to the use of specialized sub-languages in the medical domain, manual construction of semantic resources that accurately reflect language use is both costly and challenging, often resulting in low coverage. Although models of distributional semantics applied to large corpora provide a potential means of supporting development of such resources, their ability to isolate synonymy from other semantic relations is limited. Their application in the clinical domain has also only recently begun to be explored. Combining distributional models and applying them to different types of corpora may lead to enhanced performance on the tasks of automatically extracting synonyms and abbreviation-expansion pairs. Results A combination of two distributional models – Random Indexing and Random Permutation – employed in conjunction with a single corpus outperforms using either of the models in isolation. Furthermore, combining semantic spaces induced from different types of corpora – a corpus of clinical text and a corpus of medical journal articles – further improves results, outperforming a combination of semantic spaces induced from a single source, as well as a single semantic space induced from the conjoint corpus. A combination strategy that simply sums the cosine similarity scores of candidate terms is generally the most profitable out of the ones explored. Finally, applying simple post-processing filtering rules yields substantial performance gains on the tasks of extracting abbreviation-expansion pairs, but not synonyms. The best results, measured as recall in a list of ten candidate terms, for the three tasks are: 0.39 for abbreviations to long forms, 0.33 for long forms to abbreviations, and 0.47 for synonyms. Conclusions This study demonstrates that ensembles of semantic spaces can yield improved performance on the tasks of automatically extracting synonyms and abbreviation-expansion pairs. This notion, which merits further exploration, allows different distributional models – with different model parameters – and different types of corpora to be combined, potentially allowing enhanced performance to be obtained on a wide range of natural language processing tasks. PMID:24499679

Semantic technologies in a decision support system

NASA Astrophysics Data System (ADS)

Wasielewska, K.; Ganzha, M.; Paprzycki, M.; Bǎdicǎ, C.; Ivanovic, M.; Lirkov, I.

2015-10-01

The aim of our work is to design a decision support system based on ontological representation of domain(s) and semantic technologies. Specifically, we consider the case when Grid / Cloud user describes his/her requirements regarding a "resource" as a class expression from an ontology, while the instances of (the same) ontology represent available resources. The goal is to help the user to find the best option with respect to his/her requirements, while remembering that user's knowledge may be "limited." In this context, we discuss multiple approaches based on semantic data processing, which involve different "forms" of user interaction with the system. Specifically, we consider: (a) ontological matchmaking based on SPARQL queries and class expression, (b) graph-based semantic closeness of instances representing user requirements (constructed from the class expression) and available resources, and (c) multicriterial analysis based on the AHP method, which utilizes expert domain knowledge (also ontologically represented).

A funny thing happened on the way to articulation: N400 attenuation despite behavioral interference in picture naming

PubMed Central

Blackford, Trevor; Holcomb, Phillip J.; Grainger, Jonathan; Kuperberg, Gina R.

2013-01-01

We measured Event-Related Potentials (ERPs) and naming times to picture targets preceded by masked words (stimulus onset asynchrony: 80 ms) that shared one of three different types of relationship with the names of the pictures: (1) Identity related, in which the prime was the name of the picture (“socks” – ), (2) Phonemic Onset related, in which the initial segment of the prime was the same as the name of the picture (“log” – ), and (3) Semantically related in which the prime was a co–category exemplar and associated with the name of the picture (“cake” – ). Each type of related picture target was contrasted with an Unrelated picture target, resulting in a 3 × 2 design that crossed Relationship Type between the word and the target picture (Identity, Phonemic Onset and Semantic) with Relatedness (Related and Unrelated). Modulation of the N400 component to related (versus unrelated) pictures was taken to reflect semantic processing at the interface between the picture's conceptual features and its lemma, while naming times reflected the end product of all stages of processing. Both attenuation of the N400 and shorter naming times were observed to pictures preceded by Identity related (versus Unrelated) words. No ERP effects within 600 ms, but shorter naming times, were observed to pictures preceded by Phonemic Onset related (versus Unrelated) words. An attenuated N400 (electrophysiological semantic priming) but longer naming times (behavioral semantic interference) were observed to pictures preceded by Semantically related (versus Unrelated) words. These dissociations between ERP modulation and naming times suggest that (a) phonemic onset priming occurred late, during encoding of the articulatory response, and (b) semantic behavioral interference was not driven by competition at the lemma level of representation, but rather occurred at a later stage of production. PMID:22245030

Spatio-Temporal Data Model for Integrating Evolving Nation-Level Datasets

NASA Astrophysics Data System (ADS)

Sorokine, A.; Stewart, R. N.

2017-10-01

Ability to easily combine the data from diverse sources in a single analytical workflow is one of the greatest promises of the Big Data technologies. However, such integration is often challenging as datasets originate from different vendors, governments, and research communities that results in multiple incompatibilities including data representations, formats, and semantics. Semantics differences are hardest to handle: different communities often use different attribute definitions and associate the records with different sets of evolving geographic entities. Analysis of global socioeconomic variables across multiple datasets over prolonged time is often complicated by the difference in how boundaries and histories of countries or other geographic entities are represented. Here we propose an event-based data model for depicting and tracking histories of evolving geographic units (countries, provinces, etc.) and their representations in disparate data. The model addresses the semantic challenge of preserving identity of geographic entities over time by defining criteria for the entity existence, a set of events that may affect its existence, and rules for mapping between different representations (datasets). Proposed model is used for maintaining an evolving compound database of global socioeconomic and environmental data harvested from multiple sources. Practical implementation of our model is demonstrated using PostgreSQL object-relational database with the use of temporal, geospatial, and NoSQL database extensions.

Parametric effects of syntactic-semantic conflict in Broca's area during sentence processing.

PubMed

Thothathiri, Malathi; Kim, Albert; Trueswell, John C; Thompson-Schill, Sharon L

2012-03-01

The hypothesized role of Broca's area in sentence processing ranges from domain-general executive function to domain-specific computation that is specific to certain syntactic structures. We examined this issue by manipulating syntactic structure and conflict between syntactic and semantic cues in a sentence processing task. Functional neuroimaging revealed that activation within several Broca's area regions of interest reflected the parametric variation in syntactic-semantic conflict. These results suggest that Broca's area supports sentence processing by mediating between multiple incompatible constraints on sentence interpretation, consistent with this area's well-known role in conflict resolution in other linguistic and non-linguistic tasks. Copyright © 2011 Elsevier Inc. All rights reserved.

Semantic memory is impaired in patients with unilateral anterior temporal lobe resection for temporal lobe epilepsy.

PubMed

Lambon Ralph, Matthew A; Ehsan, Sheeba; Baker, Gus A; Rogers, Timothy T

2012-01-01

Contemporary clinical and basic neuroscience studies have increasingly implicated the anterior temporal lobe regions, bilaterally, in the formation of coherent concepts. Mounting convergent evidence for the importance of the anterior temporal lobe in semantic memory is found in patients with bilateral anterior temporal lobe damage (e.g. semantic dementia), functional neuroimaging and repetitive transcranial magnetic stimulation studies. If this proposal is correct, then one might expect patients with anterior temporal lobe resection for long-standing temporal lobe epilepsy to be semantically impaired. Such patients, however, do not present clinically with striking comprehension deficits but with amnesia and variable anomia, leading some to conclude that semantic memory is intact in resection for temporal lobe epilepsy and thus casting doubt over the conclusions drawn from semantic dementia and linked basic neuroscience studies. Whilst there is a considerable neuropsychological literature on temporal lobe epilepsy, few studies have probed semantic memory directly, with mixed results, and none have undertaken the same type of systematic investigation of semantic processing that has been conducted with other patient groups. In this study, therefore, we investigated the semantic performance of 20 patients with resection for chronic temporal lobe epilepsy with a full battery of semantic assessments, including more sensitive measures of semantic processing. The results provide a bridge between the current clinical observations about resection for temporal lobe epilepsy and the expectations from semantic dementia and other neuroscience findings. Specifically, we found that on simple semantic tasks, the patients' accuracy fell in the normal range, with the exception that some patients with left resection for temporal lobe epilepsy had measurable anomia. Once the semantic assessments were made more challenging, by probing specific-level concepts, lower frequency/more abstract items or measuring reaction times on semantic tasks versus those on difficulty-matched non-semantic assessments, evidence of a semantic impairment was found in all individuals. We conclude by describing a unified, computationally inspired framework for capturing the variable degrees of semantic impairment found across different patient groups (semantic dementia, temporal lobe epilepsy, glioma and stroke) as well as semantic processing in neurologically intact participants.

Semantic memory is impaired in patients with unilateral anterior temporal lobe resection for temporal lobe epilepsy

PubMed Central

Ehsan, Sheeba; Baker, Gus A.; Rogers, Timothy T.

2012-01-01

Contemporary clinical and basic neuroscience studies have increasingly implicated the anterior temporal lobe regions, bilaterally, in the formation of coherent concepts. Mounting convergent evidence for the importance of the anterior temporal lobe in semantic memory is found in patients with bilateral anterior temporal lobe damage (e.g. semantic dementia), functional neuroimaging and repetitive transcranial magnetic stimulation studies. If this proposal is correct, then one might expect patients with anterior temporal lobe resection for long-standing temporal lobe epilepsy to be semantically impaired. Such patients, however, do not present clinically with striking comprehension deficits but with amnesia and variable anomia, leading some to conclude that semantic memory is intact in resection for temporal lobe epilepsy and thus casting doubt over the conclusions drawn from semantic dementia and linked basic neuroscience studies. Whilst there is a considerable neuropsychological literature on temporal lobe epilepsy, few studies have probed semantic memory directly, with mixed results, and none have undertaken the same type of systematic investigation of semantic processing that has been conducted with other patient groups. In this study, therefore, we investigated the semantic performance of 20 patients with resection for chronic temporal lobe epilepsy with a full battery of semantic assessments, including more sensitive measures of semantic processing. The results provide a bridge between the current clinical observations about resection for temporal lobe epilepsy and the expectations from semantic dementia and other neuroscience findings. Specifically, we found that on simple semantic tasks, the patients’ accuracy fell in the normal range, with the exception that some patients with left resection for temporal lobe epilepsy had measurable anomia. Once the semantic assessments were made more challenging, by probing specific-level concepts, lower frequency/more abstract items or measuring reaction times on semantic tasks versus those on difficulty-matched non-semantic assessments, evidence of a semantic impairment was found in all individuals. We conclude by describing a unified, computationally inspired framework for capturing the variable degrees of semantic impairment found across different patient groups (semantic dementia, temporal lobe epilepsy, glioma and stroke) as well as semantic processing in neurologically intact participants. PMID:22287382

Transfer-appropriate processing in the testing effect.

PubMed

Veltre, Mary T; Cho, Kit W; Neely, James H

2015-01-01

The testing effect is the finding that taking a review test enhances performance on a final test relative to restudying the material. The present experiment investigated transfer-appropriate processing in the testing effect using semantic and orthographic cues to evoke conceptual and data-driven processing, respectively. After a study phase, subjects either restudied the material or took a cued-recall test consisting of half semantic and half orthographic cues in which the correct response was given as feedback. A final, cued-recall test consisted of the identical cue, or a new cue that was of the same type or different type of cue (semantic/orthographic or orthographic/semantic) as that used for that target in the review test. Testing enhanced memory in all conditions. When the review cues and final-test cues were identical, final recall was higher for semantic than orthographic cues. Consistent with test-based transfer-appropriate processing, memory performance improved as the review and final cues became more similar. These results suggest that the testing effect could potentially be caused by the episodic retrieval processes in a final memory test overlapping more with the episodic retrieval processes in a review test than with the encoding operations performed during restudy.

Neural dynamics associated with semantic and episodic memory for faces: evidence from multiple frequency bands.

PubMed

Zion-Golumbic, Elana; Kutas, Marta; Bentin, Shlomo

2010-02-01

Prior semantic knowledge facilitates episodic recognition memory for faces. To examine the neural manifestation of the interplay between semantic and episodic memory, we investigated neuroelectric dynamics during the creation (study) and the retrieval (test) of episodic memories for famous and nonfamous faces. Episodic memory effects were evident in several EEG frequency bands: theta (4-8 Hz), alpha (9-13 Hz), and gamma (40-100 Hz). Activity in these bands was differentially modulated by preexisting semantic knowledge and by episodic memory, implicating their different functional roles in memory. More specifically, theta activity and alpha suppression were larger for old compared to new faces at test regardless of fame, but were both larger for famous faces during study. This pattern of selective semantic effects suggests that the theta and alpha responses, which are primarily associated with episodic memory, reflect utilization of semantic information only when it is beneficial for task performance. In contrast, gamma activity decreased between the first (study) and second (test) presentation of a face, but overall was larger for famous than nonfamous faces. Hence, the gamma rhythm seems to be primarily related to activation of preexisting neural representations that may contribute to the formation of new episodic traces. Taken together, these data provide new insights into the complex interaction between semantic and episodic memory for faces and the neural dynamics associated with mnemonic processes.

COEUS: “semantic web in a box” for biomedical applications

PubMed Central

2012-01-01

Background As the “omics” revolution unfolds, the growth in data quantity and diversity is bringing about the need for pioneering bioinformatics software, capable of significantly improving the research workflow. To cope with these computer science demands, biomedical software engineers are adopting emerging semantic web technologies that better suit the life sciences domain. The latter’s complex relationships are easily mapped into semantic web graphs, enabling a superior understanding of collected knowledge. Despite increased awareness of semantic web technologies in bioinformatics, their use is still limited. Results COEUS is a new semantic web framework, aiming at a streamlined application development cycle and following a “semantic web in a box” approach. The framework provides a single package including advanced data integration and triplification tools, base ontologies, a web-oriented engine and a flexible exploration API. Resources can be integrated from heterogeneous sources, including CSV and XML files or SQL and SPARQL query results, and mapped directly to one or more ontologies. Advanced interoperability features include REST services, a SPARQL endpoint and LinkedData publication. These enable the creation of multiple applications for web, desktop or mobile environments, and empower a new knowledge federation layer. Conclusions The platform, targeted at biomedical application developers, provides a complete skeleton ready for rapid application deployment, enhancing the creation of new semantic information systems. COEUS is available as open source at http://bioinformatics.ua.pt/coeus/. PMID:23244467

Domain or not domain? That is the question: longitudinal semantic deterioration in Alzheimer's disease.

PubMed

Moreno-Martínez, F Javier; Goñi-Imízcoz, Miguel; Spitznagel, Mary Beth

2011-10-01

Category specific semantic impairment (e.g. living versus nonliving things) has been reported in association with various pathologies, including herpes simplex encephalitis and semantic dementia. However, evidence is inconsistent regarding whether this effect exists in diseases progressively impacting diverse cortical regions, such as Alzheimer's disease (AD). Ceiling effects producing non-Gaussian distributions and poor control for confounds such as nuisance variables (e.g. familiarity) may contribute to this discrepancy. Fourteen AD patients were longitudinally studied examining category effects on three semantic tasks (picture naming, naming to description and word to picture matching) matched across domain on all known nuisance variables (NV). To address non-Gaussian distributions, we run bootstrap analyses to determine whether NV, semantic domain or control performance best predicted AD patient performance. Multiple hierarchical regression analyses revealed that, whilst NV accounted for most of the explained variance in patients in the three tasks, the influence of semantic domain was substantially lower. Individual logistic regression demonstrated a significant category effect in only a few patients and healthy controls. No significant qualitative changes were observed in patients over time. Our results confirm the importance of NVs as predictors of AD patient performance, suggesting that the role of semantic domain is not a useful predictor of the progressive deterioration in AD. Copyright © 2011 Elsevier Inc. All rights reserved.

Combinatorial semantics strengthens angular-anterior temporal coupling.

PubMed

Molinaro, Nicola; Paz-Alonso, Pedro M; Duñabeitia, Jon Andoni; Carreiras, Manuel

2015-04-01

The human semantic combinatorial system allows us to create a wide number of new meanings from a finite number of existing representations. The present study investigates the neural dynamics underlying the semantic processing of different conceptual constructions based on predictions from previous neuroanatomical models of the semantic processing network. In two experiments, participants read sentences for comprehension containing noun-adjective pairs in three different conditions: prototypical (Redundant), nonsense (Anomalous) and low-typical but composable (Contrastive). In Experiment 1 we examined the processing costs associated to reading these sentences and found a processing dissociation between Anomalous and Contrastive word pairs, compared to prototypical (Redundant) stimuli. In Experiment 2, functional connectivity results showed strong co-activation across conditions between inferior frontal gyrus (IFG) and posterior middle temporal gyrus (MTG), as well as between these two regions and middle frontal gyrus (MFG), anterior temporal cortex (ATC) and fusiform gyrus (FG), consistent with previous neuroanatomical models. Importantly, processing of low-typical (but composable) meanings relative to prototypical and anomalous constructions was associated with a stronger positive coupling between ATC and angular gyrus (AG). Our results underscore the critical role of IFG-MTG co-activation during semantic processing and how other relevant nodes within the semantic processing network come into play to handle visual-orthographic information, to maintain multiple lexical-semantic representations in working memory and to combine existing representations while creatively constructing meaning. Copyright © 2015 Elsevier Ltd. All rights reserved.

Ontology Alignment Architecture for Semantic Sensor Web Integration

PubMed Central

Fernandez, Susel; Marsa-Maestre, Ivan; Velasco, Juan R.; Alarcos, Bernardo

2013-01-01

Sensor networks are a concept that has become very popular in data acquisition and processing for multiple applications in different fields such as industrial, medicine, home automation, environmental detection, etc. Today, with the proliferation of small communication devices with sensors that collect environmental data, semantic Web technologies are becoming closely related with sensor networks. The linking of elements from Semantic Web technologies with sensor networks has been called Semantic Sensor Web and has among its main features the use of ontologies. One of the key challenges of using ontologies in sensor networks is to provide mechanisms to integrate and exchange knowledge from heterogeneous sources (that is, dealing with semantic heterogeneity). Ontology alignment is the process of bringing ontologies into mutual agreement by the automatic discovery of mappings between related concepts. This paper presents a system for ontology alignment in the Semantic Sensor Web which uses fuzzy logic techniques to combine similarity measures between entities of different ontologies. The proposed approach focuses on two key elements: the terminological similarity, which takes into account the linguistic and semantic information of the context of the entity's names, and the structural similarity, based on both the internal and relational structure of the concepts. This work has been validated using sensor network ontologies and the Ontology Alignment Evaluation Initiative (OAEI) tests. The results show that the proposed techniques outperform previous approaches in terms of precision and recall. PMID:24051523

Ontology alignment architecture for semantic sensor Web integration.

PubMed

Fernandez, Susel; Marsa-Maestre, Ivan; Velasco, Juan R; Alarcos, Bernardo

2013-09-18

Sensor networks are a concept that has become very popular in data acquisition and processing for multiple applications in different fields such as industrial, medicine, home automation, environmental detection, etc. Today, with the proliferation of small communication devices with sensors that collect environmental data, semantic Web technologies are becoming closely related with sensor networks. The linking of elements from Semantic Web technologies with sensor networks has been called Semantic Sensor Web and has among its main features the use of ontologies. One of the key challenges of using ontologies in sensor networks is to provide mechanisms to integrate and exchange knowledge from heterogeneous sources (that is, dealing with semantic heterogeneity). Ontology alignment is the process of bringing ontologies into mutual agreement by the automatic discovery of mappings between related concepts. This paper presents a system for ontology alignment in the Semantic Sensor Web which uses fuzzy logic techniques to combine similarity measures between entities of different ontologies. The proposed approach focuses on two key elements: the terminological similarity, which takes into account the linguistic and semantic information of the context of the entity's names, and the structural similarity, based on both the internal and relational structure of the concepts. This work has been validated using sensor network ontologies and the Ontology Alignment Evaluation Initiative (OAEI) tests. The results show that the proposed techniques outperform previous approaches in terms of precision and recall.

COEUS: "semantic web in a box" for biomedical applications.

PubMed

Lopes, Pedro; Oliveira, José Luís

2012-12-17

As the "omics" revolution unfolds, the growth in data quantity and diversity is bringing about the need for pioneering bioinformatics software, capable of significantly improving the research workflow. To cope with these computer science demands, biomedical software engineers are adopting emerging semantic web technologies that better suit the life sciences domain. The latter's complex relationships are easily mapped into semantic web graphs, enabling a superior understanding of collected knowledge. Despite increased awareness of semantic web technologies in bioinformatics, their use is still limited. COEUS is a new semantic web framework, aiming at a streamlined application development cycle and following a "semantic web in a box" approach. The framework provides a single package including advanced data integration and triplification tools, base ontologies, a web-oriented engine and a flexible exploration API. Resources can be integrated from heterogeneous sources, including CSV and XML files or SQL and SPARQL query results, and mapped directly to one or more ontologies. Advanced interoperability features include REST services, a SPARQL endpoint and LinkedData publication. These enable the creation of multiple applications for web, desktop or mobile environments, and empower a new knowledge federation layer. The platform, targeted at biomedical application developers, provides a complete skeleton ready for rapid application deployment, enhancing the creation of new semantic information systems. COEUS is available as open source at http://bioinformatics.ua.pt/coeus/.

Electrophysiological evidence for effects of color knowledge in object recognition.

PubMed

Lu, Aitao; Xu, Guiping; Jin, Hua; Mo, Lei; Zhang, Jijia; Zhang, John X

2010-01-29

Knowledge about the typical colors associated with familiar everyday objects (i.e., strawberries are red) is well-known to be represented in the conceptual semantic system. Evidence that such knowledge may also play a role in early perceptual processes for object recognition is scant. In the present ERP study, participants viewed a list of object pictures and detected infrequent stimulus repetitions. Results show that shortly after stimulus onset, ERP components indexing early perceptual processes, including N1, P2, and N2, differentiated between objects in their appropriate or congruent color from these objects in an inappropriate or incongruent color. Such congruence effect also occurred in N3 associated with semantic processing of pictures but not in N4 for domain-general semantic processing. Our results demonstrate a clear effect of color knowledge in early object recognition stages and support the following proposal-color as a surface property is stored in a multiple-memory system where pre-semantic perceptual and semantic conceptual representations interact during object recognition. (c) 2009 Elsevier Ireland Ltd. All rights reserved.

A fusion network for semantic segmentation using RGB-D data

NASA Astrophysics Data System (ADS)

Yuan, Jiahui; Zhang, Kun; Xia, Yifan; Qi, Lin; Dong, Junyu

2018-04-01

Semantic scene parsing is considerable in many intelligent field, including perceptual robotics. For the past few years, pixel-wise prediction tasks like semantic segmentation with RGB images has been extensively studied and has reached very remarkable parsing levels, thanks to convolutional neural networks (CNNs) and large scene datasets. With the development of stereo cameras and RGBD sensors, it is expected that additional depth information will help improving accuracy. In this paper, we propose a semantic segmentation framework incorporating RGB and complementary depth information. Motivated by the success of fully convolutional networks (FCN) in semantic segmentation field, we design a fully convolutional networks consists of two branches which extract features from both RGB and depth data simultaneously and fuse them as the network goes deeper. Instead of aggregating multiple model, our goal is to utilize RGB data and depth data more effectively in a single model. We evaluate our approach on the NYU-Depth V2 dataset, which consists of 1449 cluttered indoor scenes, and achieve competitive results with the state-of-the-art methods.

An analysis of multi-type relational interactions in FMA using graph motifs with disjointness constraints.

PubMed

Zhang, Guo-Qiang; Luo, Lingyun; Ogbuji, Chime; Joslyn, Cliff; Mejino, Jose; Sahoo, Satya S

2012-01-01

The interaction of multiple types of relationships among anatomical classes in the Foundational Model of Anatomy (FMA) can provide inferred information valuable for quality assurance. This paper introduces a method called Motif Checking (MOCH) to study the effects of such multi-relation type interactions for detecting logical inconsistencies as well as other anomalies represented by the motifs. MOCH represents patterns of multi-type interaction as small labeled (with multiple types of edges) sub-graph motifs, whose nodes represent class variables, and labeled edges represent relational types. By representing FMA as an RDF graph and motifs as SPARQL queries, fragments of FMA are automatically obtained as auditing candidates. Leveraging the scalability and reconfigurability of Semantic Web Technology, we performed exhaustive analyses of a variety of labeled sub-graph motifs. The quality assurance feature of MOCH comes from the distinct use of a subset of the edges of the graph motifs as constraints for disjointness, whereby bringing in rule-based flavor to the approach as well. With possible disjointness implied by antonyms, we performed manual inspection of the resulting FMA fragments and tracked down sources of abnormal inferred conclusions (logical inconsistencies), which are amendable for programmatic revision of the FMA. Our results demonstrate that MOCH provides a unique source of valuable information for quality assurance. Since our approach is general, it is applicable to any ontological system with an OWL representation.

An Analysis of Multi-type Relational Interactions in FMA Using Graph Motifs with Disjointness Constraints

PubMed Central

Zhang, Guo-Qiang; Luo, Lingyun; Ogbuji, Chime; Joslyn, Cliff; Mejino, Jose; Sahoo, Satya S

2012-01-01

The interaction of multiple types of relationships among anatomical classes in the Foundational Model of Anatomy (FMA) can provide inferred information valuable for quality assurance. This paper introduces a method called Motif Checking (MOCH) to study the effects of such multi-relation type interactions for detecting logical inconsistencies as well as other anomalies represented by the motifs. MOCH represents patterns of multi-type interaction as small labeled (with multiple types of edges) sub-graph motifs, whose nodes represent class variables, and labeled edges represent relational types. By representing FMA as an RDF graph and motifs as SPARQL queries, fragments of FMA are automatically obtained as auditing candidates. Leveraging the scalability and reconfigurability of Semantic Web Technology, we performed exhaustive analyses of a variety of labeled sub-graph motifs. The quality assurance feature of MOCH comes from the distinct use of a subset of the edges of the graph motifs as constraints for disjointness, whereby bringing in rule-based flavor to the approach as well. With possible disjointness implied by antonyms, we performed manual inspection of the resulting FMA fragments and tracked down sources of abnormal inferred conclusions (logical inconsistencies), which are amendable for programmatic revision of the FMA. Our results demonstrate that MOCH provides a unique source of valuable information for quality assurance. Since our approach is general, it is applicable to any ontological system with an OWL representation. PMID:23304382

Reliability in content analysis: The case of semantic feature norms classification.

PubMed

Bolognesi, Marianna; Pilgram, Roosmaryn; van den Heerik, Romy

2017-12-01

Semantic feature norms (e.g., STIMULUS: car → RESPONSE: ) are commonly used in cognitive psychology to look into salient aspects of given concepts. Semantic features are typically collected in experimental settings and then manually annotated by the researchers into feature types (e.g., perceptual features, taxonomic features, etc.) by means of content analyses-that is, by using taxonomies of feature types and having independent coders perform the annotation task. However, the ways in which such content analyses are typically performed and reported are not consistent across the literature. This constitutes a serious methodological problem that might undermine the theoretical claims based on such annotations. In this study, we first offer a review of some of the released datasets of annotated semantic feature norms and the related taxonomies used for content analysis. We then provide theoretical and methodological insights in relation to the content analysis methodology. Finally, we apply content analysis to a new dataset of semantic features and show how the method should be applied in order to deliver reliable annotations and replicable coding schemes. We tackle the following issues: (1) taxonomy structure, (2) the description of categories, (3) coder training, and (4) sustainability of the coding scheme-that is, comparison of the annotations provided by trained versus novice coders. The outcomes of the project are threefold: We provide methodological guidelines for semantic feature classification; we provide a revised and adapted taxonomy that can (arguably) be applied to both concrete and abstract concepts; and we provide a dataset of annotated semantic feature norms.

Memory for emotional words: The role of semantic relatedness, encoding task and affective valence.

PubMed

Ferré, Pilar; Fraga, Isabel; Comesaña, Montserrat; Sánchez-Casas, Rosa

2015-01-01

Emotional stimuli have been repeatedly demonstrated to be better remembered than neutral ones. The aim of the present study was to test whether this advantage in memory is mainly produced by the affective content of the stimuli or it can be rather accounted for by factors such as semantic relatedness or type of encoding task. The valence of the stimuli (positive, negative and neutral words that could be either semantically related or unrelated) as well as the type of encoding task (focused on either familiarity or emotionality) was manipulated. The results revealed an advantage in memory for emotional words (either positive or negative) regardless of semantic relatedness. Importantly, this advantage was modulated by the encoding task, as it was reliable only in the task which focused on emotionality. These findings suggest that congruity with the dimension attended at encoding might contribute to the superiority in memory for emotional words, thus offering us a more complex picture of the underlying mechanisms behind the advantage for emotional information in memory.

Semantic SenseLab: implementing the vision of the Semantic Web in neuroscience

PubMed Central

Samwald, Matthias; Chen, Huajun; Ruttenberg, Alan; Lim, Ernest; Marenco, Luis; Miller, Perry; Shepherd, Gordon; Cheung, Kei-Hoi

2011-01-01

Summary Objective Integrative neuroscience research needs a scalable informatics framework that enables semantic integration of diverse types of neuroscience data. This paper describes the use of the Web Ontology Language (OWL) and other Semantic Web technologies for the representation and integration of molecular-level data provided by several of SenseLab suite of neuroscience databases. Methods Based on the original database structure, we semi-automatically translated the databases into OWL ontologies with manual addition of semantic enrichment. The SenseLab ontologies are extensively linked to other biomedical Semantic Web resources, including the Subcellular Anatomy Ontology, Brain Architecture Management System, the Gene Ontology, BIRNLex and UniProt. The SenseLab ontologies have also been mapped to the Basic Formal Ontology and Relation Ontology, which helps ease interoperability with many other existing and future biomedical ontologies for the Semantic Web. In addition, approaches to representing contradictory research statements are described. The SenseLab ontologies are designed for use on the Semantic Web that enables their integration into a growing collection of biomedical information resources. Conclusion We demonstrate that our approach can yield significant potential benefits and that the Semantic Web is rapidly becoming mature enough to realize its anticipated promises. The ontologies are available online at http://neuroweb.med.yale.edu/senselab/ PMID:20006477

Semantic SenseLab: Implementing the vision of the Semantic Web in neuroscience.

PubMed

Samwald, Matthias; Chen, Huajun; Ruttenberg, Alan; Lim, Ernest; Marenco, Luis; Miller, Perry; Shepherd, Gordon; Cheung, Kei-Hoi

2010-01-01

Integrative neuroscience research needs a scalable informatics framework that enables semantic integration of diverse types of neuroscience data. This paper describes the use of the Web Ontology Language (OWL) and other Semantic Web technologies for the representation and integration of molecular-level data provided by several of SenseLab suite of neuroscience databases. Based on the original database structure, we semi-automatically translated the databases into OWL ontologies with manual addition of semantic enrichment. The SenseLab ontologies are extensively linked to other biomedical Semantic Web resources, including the Subcellular Anatomy Ontology, Brain Architecture Management System, the Gene Ontology, BIRNLex and UniProt. The SenseLab ontologies have also been mapped to the Basic Formal Ontology and Relation Ontology, which helps ease interoperability with many other existing and future biomedical ontologies for the Semantic Web. In addition, approaches to representing contradictory research statements are described. The SenseLab ontologies are designed for use on the Semantic Web that enables their integration into a growing collection of biomedical information resources. We demonstrate that our approach can yield significant potential benefits and that the Semantic Web is rapidly becoming mature enough to realize its anticipated promises. The ontologies are available online at http://neuroweb.med.yale.edu/senselab/. 2009 Elsevier B.V. All rights reserved.

Retrieval and Monitoring Processes during Visual Working Memory: An ERP Study of the Benefit of Visual Semantics

PubMed Central

Orme, Elizabeth; Brown, Louise A.; Riby, Leigh M.

2017-01-01

In this study, we examined electrophysiological indices of episodic remembering whilst participants recalled novel shapes, with and without semantic content, within a visual working memory paradigm. The components of interest were the parietal episodic (PE; 400–800 ms) and late posterior negativity (LPN; 500–900 ms), as these have previously been identified as reliable markers of recollection and post-retrieval monitoring, respectively. Fifteen young adults completed a visual matrix patterns task, assessing memory for low and high semantic visual representations. Matrices with either low semantic or high semantic content (containing familiar visual forms) were briefly presented to participants for study (1500 ms), followed by a retention interval (6000 ms) and finally a same/different recognition phase. The event-related potentials of interest were tracked from the onset of the recognition test stimuli. Analyses revealed equivalent amplitude for the earlier PE effect for the processing of both low and high semantic stimulus types. However, the LPN was more negative-going for the processing of the low semantic stimuli. These data are discussed in terms of relatively ‘pure’ and complete retrieval of high semantic items, where support can readily be recruited from semantic memory. However, for the low semantic items additional executive resources, as indexed by the LPN, are recruited when memory monitoring and uncertainty exist in order to recall previously studied items more effectively. PMID:28725203

Retrieval and Monitoring Processes during Visual Working Memory: An ERP Study of the Benefit of Visual Semantics.

PubMed

Orme, Elizabeth; Brown, Louise A; Riby, Leigh M

2017-01-01

In this study, we examined electrophysiological indices of episodic remembering whilst participants recalled novel shapes, with and without semantic content, within a visual working memory paradigm. The components of interest were the parietal episodic (PE; 400-800 ms) and late posterior negativity (LPN; 500-900 ms), as these have previously been identified as reliable markers of recollection and post-retrieval monitoring, respectively. Fifteen young adults completed a visual matrix patterns task, assessing memory for low and high semantic visual representations. Matrices with either low semantic or high semantic content (containing familiar visual forms) were briefly presented to participants for study (1500 ms), followed by a retention interval (6000 ms) and finally a same/different recognition phase. The event-related potentials of interest were tracked from the onset of the recognition test stimuli. Analyses revealed equivalent amplitude for the earlier PE effect for the processing of both low and high semantic stimulus types. However, the LPN was more negative-going for the processing of the low semantic stimuli. These data are discussed in terms of relatively 'pure' and complete retrieval of high semantic items, where support can readily be recruited from semantic memory. However, for the low semantic items additional executive resources, as indexed by the LPN, are recruited when memory monitoring and uncertainty exist in order to recall previously studied items more effectively.

Dynamic generation of a table of contents with consumer-friendly labels.

PubMed

Miller, Trudi; Leroy, Gondy; Wood, Elizabeth

2006-01-01

Consumers increasingly look to the Internet for health information, but available resources are too difficult for the majority to understand. Interactive tables of contents (TOC) can help consumers access health information by providing an easy to understand structure. Using natural language processing and the Unified Medical Language System (UMLS), we have automatically generated TOCs for consumer health information. The TOC are categorized according to consumer-friendly labels for the UMLS semantic types and semantic groups. Categorizing phrases by semantic types is significantly more correct and relevant. Greater correctness and relevance was achieved with documents that are difficult to read than those at an easier reading level. Pruning TOCs to use categories that consumers favor further increases relevancy and correctness while reducing structural complexity.

Dissociation of lexical syntax and semantics: evidence from focal cortical degeneration.

PubMed

Garrard, P; Carroll, E; Vinson, D; Vigliocco, G

2004-10-01

The question of whether information relevant to meaning (semantics) and structure (syntax) relies on a common language processor or on separate subsystems has proved difficult to address definitively because of the confounds involved in comparing the two types of information. At the sentence level syntactic and semantic judgments make different cognitive demands, while at the single word level, the most commonly used syntactic distinction (between nouns and verbs) is confounded with a fundamental semantic difference (between objects and actions). The present study employs a different syntactic contrast (between count nouns and mass nouns), which is crossed with a semantic difference (between naturally occurring and man-made substances) applying to words within a circumscribed semantic field (foodstuffs). We show, first, that grammaticality judgments of a patient with semantic dementia are indistinguishable from those of a group of age-matched controls, and are similar regardless of the status of his semantic knowledge about the item. In a second experiment we use the triadic task in a group of age-matched controls to show that similarity judgments are influenced not only by meaning (natural vs. manmade), but also implicitly by syntactic information (count vs. mass). Using the same task in a patient with semantic dementia we show that the semantic influences on the syntactic dimension are unlikely to account for this pattern in normals. These data are discussed in relation to modular vs. nonmodular models of language processing, and in particular to the semantic-syntactic distinction.

The relationship between semantic short-term memory and immediate serial recall of known and unknown words and nonwords: data from two Chinese individuals with aphasia.

PubMed

Wong, Winsy; Low, Sam-Po

2008-07-01

The present study investigated verbal recall of semantically preserved and degraded words and nonwords by taking into consideration the status of one's semantic short-term memory (STM). Two experiments were conducted on 2 Chinese individuals with aphasia. The first experiment showed that they had largely preserved phonological processing abilities accompanied by mild but comparable semantic processing deficits; however, their performance on STM tasks revealed a double dissociation. The second experiment found that the participant with more preserved semantic STM had better recall of known words and nonwords than of their unknown counterparts, whereas such effects were absent in the patient with severe semantic STM deficit. The results are compatible with models that assume separate phonological and semantic STM components, such as that of R. C. Martin, M. Lesch, and M. Bartha (1999). In addition, the distribution of error types was different from previous studies. This is discussed in terms of the methodology of the authors' experiments and current views regarding the nature of semantic STM and representations in the Chinese mental lexicon. (c) 2008 APA

Modulation of alpha oscillations is required for the suppression of semantic interference.

PubMed

Melnik, Natalia; Mapelli, Igor; Özkurt, Tolga Esat

2017-10-01

Recent findings on alpha band oscillations suggest their important role in memory consolidation and suppression of external distractors such as environmental noise. However, less attention was given to the phenomenon of internal distracting information being solely inherent to the stimuli content. Human memory may be prone to internal distractions caused by semantic relatedness between the meaning of words (e.g., atom, neutron, nucleus, etc.) to be encoded, i.e., semantic interference. Our study investigates the brain oscillatory dynamics behind the semantic interference phenomenon, whose possible outcome is known as false memories. In this direction, Deese-Roediger-McDermott word lists were appropriated for a modified Sternberg paradigm in auditory modality. Participants received semantically related and unrelated word lists via headphones while EEG data were acquired. Semantic interference triggered the false memory rates to be higher than those of other types of memory errors. Analysis demonstrated that the upper part of alpha band (∼10-12Hz) power decreases on parieto-occipital channels in the retention interval, prior to the probe item for semantically related condition. Our study elucidates the oscillatory mechanisms behind semantic interference by relying on alpha functional inhibition theory. Copyright © 2017 Elsevier Inc. All rights reserved.

Supporting Information Linking and Discovery Across Organizations Using the VIVO Semantic Web Software Suite

NASA Astrophysics Data System (ADS)

Mayernik, M. S.; Daniels, M. D.; Maull, K. E.; Khan, H.; Krafft, D. B.; Gross, M. B.; Rowan, L. R.

2016-12-01

Geosciences research is often conducted using distributed networks of researchers and resources. To better enable the discovery of the research output from the scientists and resources used within these organizations, UCAR, Cornell University, and UNAVCO are collaborating on the EarthCollab (http://earthcube.org/group/earthcollab) project which seeks to leverage semantic technologies to manage and link scientific data. As part of this effort, we have been exploring how to leverage information distributed across multiple research organizations. EarthCollab is using the VIVO semantic software suite to lookup and display Semantic Web information across our project partners.Our presentation will include a demonstration of linking between VIVO instances, discussing how to create linkages between entities in different VIVO instances where both entities describe the same person or resource. This discussion will explore how we designate the equivalence of these entities using "same as" assertions between identifiers representing these entities including URIs and ORCID IDs and how we have extended the base VIVO architecture to support the lookup of which entities in separate VIVO instances may be equivalent and to then display information from external linked entities. We will also discuss how these extensions can support other linked data lookups and sources of information.This VIVO cross-linking mechanism helps bring information from multiple VIVO instances together and helps users in navigating information spread-out between multiple VIVO instances. Challenges and open questions for this approach relate to how to display the information obtained from an external VIVO instance, both in order to preserve the brands of the internal and external systems and to handle discrepancies between ontologies, content, and/or VIVO versions.

Modality-specific selective attention attenuates multisensory integration.

PubMed

Mozolic, Jennifer L; Hugenschmidt, Christina E; Peiffer, Ann M; Laurienti, Paul J

2008-01-01

Stimuli occurring in multiple sensory modalities that are temporally synchronous or spatially coincident can be integrated together to enhance perception. Additionally, the semantic content or meaning of a stimulus can influence cross-modal interactions, improving task performance when these stimuli convey semantically congruent or matching information, but impairing performance when they contain non-matching or distracting information. Attention is one mechanism that is known to alter processing of sensory stimuli by enhancing perception of task-relevant information and suppressing perception of task-irrelevant stimuli. It is not known, however, to what extent attention to a single sensory modality can minimize the impact of stimuli in the unattended sensory modality and reduce the integration of stimuli across multiple sensory modalities. Our hypothesis was that modality-specific selective attention would limit processing of stimuli in the unattended sensory modality, resulting in a reduction of performance enhancements produced by semantically matching multisensory stimuli, and a reduction in performance decrements produced by semantically non-matching multisensory stimuli. The results from two experiments utilizing a cued discrimination task demonstrate that selective attention to a single sensory modality prevents the integration of matching multisensory stimuli that is normally observed when attention is divided between sensory modalities. Attention did not reliably alter the amount of distraction caused by non-matching multisensory stimuli on this task; however, these findings highlight a critical role for modality-specific selective attention in modulating multisensory integration.

Brain activation of semantic category-based grouping in multiple identity tracking task

PubMed Central

Wei, Liuqing; Lyu, Chuang; Hu, Siyuan; Li, Zhen

2017-01-01

Using Multiple Identity Tracking task and the functional magnetic resonance imaging (fMRI) technology, the present study aimed to isolate and visualize the functional anatomy of neural systems involved in the semantic category-based grouping process. Three experiment conditions were selected and compared: the category-based targets grouping (TG) condition, the targets-distractors grouping (TDG) condition and the homogenous condition. In the TG condition, observers could utilize the categorical distinction between targets and distractors, to construct a uniform presentation of targets, that is, to form a group of the targets to facilitate tracking. In the TDG condition, half the targets and half the distractors belonged to the same category. Observers had to inhibit the grouping of targets and distractors in one category to complete tracking. In the homogenous condition, where targets and distractors consisted of the same objects, no grouping could be formed. The “TG-Homogenous” contrast (p<0.01) revealed the activation of the left fusiform and the pars triangularis of inferior frontal gyrus (IFG). The “TG-TDG” contrast only revealed the activation of the left anterior cingulate gyrus (ACC). The fusiform and IFG pars triangularis might participate in the representation of semantic knowledge, IFG pars triangularis might relate intensely with the classification of semantic categories. The ACC might be responsible for the initiation and maintenance of grouping representation. PMID:28505166

The thematic hierarchy in sentence comprehension: A study on the interaction between verb class and word order in Spanish.

PubMed

Gattei, Carolina A; Dickey, Michael W; Wainselboim, Alejandro J; París, Luis

2015-01-01

Linking is the theory that captures the mapping of the semantic roles of lexical arguments to the syntactic functions of the phrases that realize them. At the sentence level, linking allows us to understand "who did what to whom" in an event. In Spanish, linking has been shown to interact with word order, verb class, and case marking. The current study aims to provide the first piece of experimental evidence about the interplay between word order and verb type in Spanish. We achieve this by adopting role and reference grammar and the extended argument dependency model. Two different types of clauses were examined in a self-paced reading task: clauses with object-experiencer psychological verbs and activity verbs. These types of verbs differ in the way that their syntactic and semantic structures are linked, and thus they provide interesting evidence on how information that belongs to the syntax-semantics interface might influence the predictive and integrative processes of sentence comprehension with alternative word orders. Results indicate that in Spanish, comprehension and processing speed is enhanced when the order of the constituents in the sentence mirrors their ranking on a semantic hierarchy that encodes a verb's lexical semantics. Moreover, results show that during online comprehension, predictive mechanisms based on argument hierarchization are used rapidly to inform the processing system. Our findings corroborate already existing cross-linguistic evidence on the issue and are briefly discussed in the light of other sentence-processing models.

ODMedit: uniform semantic annotation for data integration in medicine based on a public metadata repository.

PubMed

Dugas, Martin; Meidt, Alexandra; Neuhaus, Philipp; Storck, Michael; Varghese, Julian

2016-06-01

The volume and complexity of patient data - especially in personalised medicine - is steadily increasing, both regarding clinical data and genomic profiles: Typically more than 1,000 items (e.g., laboratory values, vital signs, diagnostic tests etc.) are collected per patient in clinical trials. In oncology hundreds of mutations can potentially be detected for each patient by genomic profiling. Therefore data integration from multiple sources constitutes a key challenge for medical research and healthcare. Semantic annotation of data elements can facilitate to identify matching data elements in different sources and thereby supports data integration. Millions of different annotations are required due to the semantic richness of patient data. These annotations should be uniform, i.e., two matching data elements shall contain the same annotations. However, large terminologies like SNOMED CT or UMLS don't provide uniform coding. It is proposed to develop semantic annotations of medical data elements based on a large-scale public metadata repository. To achieve uniform codes, semantic annotations shall be re-used if a matching data element is available in the metadata repository. A web-based tool called ODMedit ( https://odmeditor.uni-muenster.de/ ) was developed to create data models with uniform semantic annotations. It contains ~800,000 terms with semantic annotations which were derived from ~5,800 models from the portal of medical data models (MDM). The tool was successfully applied to manually annotate 22 forms with 292 data items from CDISC and to update 1,495 data models of the MDM portal. Uniform manual semantic annotation of data models is feasible in principle, but requires a large-scale collaborative effort due to the semantic richness of patient data. A web-based tool for these annotations is available, which is linked to a public metadata repository.

Automatic Scoring of Multiple Semantic Attributes With Multi-Task Feature Leverage: A Study on Pulmonary Nodules in CT Images.

PubMed

Sihong Chen; Jing Qin; Xing Ji; Baiying Lei; Tianfu Wang; Dong Ni; Jie-Zhi Cheng

2017-03-01

The gap between the computational and semantic features is the one of major factors that bottlenecks the computer-aided diagnosis (CAD) performance from clinical usage. To bridge this gap, we exploit three multi-task learning (MTL) schemes to leverage heterogeneous computational features derived from deep learning models of stacked denoising autoencoder (SDAE) and convolutional neural network (CNN), as well as hand-crafted Haar-like and HoG features, for the description of 9 semantic features for lung nodules in CT images. We regard that there may exist relations among the semantic features of "spiculation", "texture", "margin", etc., that can be explored with the MTL. The Lung Image Database Consortium (LIDC) data is adopted in this study for the rich annotation resources. The LIDC nodules were quantitatively scored w.r.t. 9 semantic features from 12 radiologists of several institutes in U.S.A. By treating each semantic feature as an individual task, the MTL schemes select and map the heterogeneous computational features toward the radiologists' ratings with cross validation evaluation schemes on the randomly selected 2400 nodules from the LIDC dataset. The experimental results suggest that the predicted semantic scores from the three MTL schemes are closer to the radiologists' ratings than the scores from single-task LASSO and elastic net regression methods. The proposed semantic attribute scoring scheme may provide richer quantitative assessments of nodules for better support of diagnostic decision and management. Meanwhile, the capability of the automatic association of medical image contents with the clinical semantic terms by our method may also assist the development of medical search engine.

Classification with an edge: Improving semantic image segmentation with boundary detection

NASA Astrophysics Data System (ADS)

Marmanis, D.; Schindler, K.; Wegner, J. D.; Galliani, S.; Datcu, M.; Stilla, U.

2018-01-01

We present an end-to-end trainable deep convolutional neural network (DCNN) for semantic segmentation with built-in awareness of semantically meaningful boundaries. Semantic segmentation is a fundamental remote sensing task, and most state-of-the-art methods rely on DCNNs as their workhorse. A major reason for their success is that deep networks learn to accumulate contextual information over very large receptive fields. However, this success comes at a cost, since the associated loss of effective spatial resolution washes out high-frequency details and leads to blurry object boundaries. Here, we propose to counter this effect by combining semantic segmentation with semantically informed edge detection, thus making class boundaries explicit in the model. First, we construct a comparatively simple, memory-efficient model by adding boundary detection to the SEGNET encoder-decoder architecture. Second, we also include boundary detection in FCN-type models and set up a high-end classifier ensemble. We show that boundary detection significantly improves semantic segmentation with CNNs in an end-to-end training scheme. Our best model achieves >90% overall accuracy on the ISPRS Vaihingen benchmark.

The use of a modified semantic features analysis approach in aphasia.

PubMed

Hashimoto, Naomi; Frome, Amber

2011-01-01

Several studies have reported improved naming using the semantic feature analysis (SFA) approach in individuals with aphasia. Whether the SFA can be modified and still produce naming improvements in aphasia is unknown. The present study was designed to address this question by using a modified version of the SFA approach. Three, rather than the typical six, features were used, and written along with verbal responses were allowed in an individual with both aphasia and apraxia of speech. A single-subject multiple-baseline design across behaviors was used to treat naming of single objects across three different semantic categories in a 72-year-old individual with aphasia and apraxia of speech. Stimulus generalization of training was measured by using photographs of trained items presented in natural contexts. Training of the three different categories resulted in improved naming. At a 6-week follow-up session, naming remained above pre-treatment levels but declines were noted compared to treatment levels. Generalization to the same trained items presented in different contexts was also demonstrated although declines in performance were also noted over time. Results of the study provide qualified support for the use of three features in promoting long-term improvement of naming in an individual with both aphasia and apraxia of speech. Future SFA studies should focus on whether it is the number or types of features used, aphasia severity, or length of treatment that are critical factors in rehabilitating naming deficits in aphasia. Copyright © 2011 Elsevier Inc. All rights reserved.

Matching Alternative Addresses: a Semantic Web Approach

NASA Astrophysics Data System (ADS)

Ariannamazi, S.; Karimipour, F.; Hakimpour, F.

2015-12-01

Rapid development of crowd-sourcing or volunteered geographic information (VGI) provides opportunities for authoritatives that deal with geospatial information. Heterogeneity of multiple data sources and inconsistency of data types is a key characteristics of VGI datasets. The expansion of cities resulted in the growing number of POIs in the OpenStreetMap, a well-known VGI source, which causes the datasets to outdate in short periods of time. These changes made to spatial and aspatial attributes of features such as names and addresses might cause confusion or ambiguity in the processes that require feature's literal information like addressing and geocoding. VGI sources neither will conform specific vocabularies nor will remain in a specific schema for a long period of time. As a result, the integration of VGI sources is crucial and inevitable in order to avoid duplication and the waste of resources. Information integration can be used to match features and qualify different annotation alternatives for disambiguation. This study enhances the search capabilities of geospatial tools with applications able to understand user terminology to pursuit an efficient way for finding desired results. Semantic web is a capable tool for developing technologies that deal with lexical and numerical calculations and estimations. There are a vast amount of literal-spatial data representing the capability of linguistic information in knowledge modeling, but these resources need to be harmonized based on Semantic Web standards. The process of making addresses homogenous generates a helpful tool based on spatial data integration and lexical annotation matching and disambiguating.

Expanding the Extent of a UMLS Semantic Type via Group Neighborhood Auditing

PubMed Central

Chen, Yan; Gu, Huanying; Perl, Yehoshua; Halper, Michael; Xu, Junchuan

2009-01-01

Objective Each Unified Medical Language System (UMLS) concept is assigned one or more semantic types (ST). A dynamic methodology for aiding an auditor in finding concepts that are missing the assignment of a given ST, S is presented. Design The first part of the methodology exploits the previously introduced Refined Semantic Network and accompanying refined semantic types (RST) to help narrow the search space for offending concepts. The auditing is focused in a neighborhood surrounding the extent of an RST, T (of S) called an envelope, consisting of parents and children of concepts in the extent. The audit moves outward as long as missing assignments are discovered. In the second part, concepts not reached previously are processed and reassigned T as needed during the processing of S's other RSTs. The set of such concepts is expanded in a similar way to that in the first part. Measurements The number of errors discovered is reported. To measure the methodology's efficiency, “error hit rates” (i.e., errors found in concepts examined) are computed. Results The methodology was applied to three STs: Experimental Model of Disease (EMD), Environmental Effect of Humans, and Governmental or Regulatory Activity. The EMD experienced the most drastic change. For its RST “EMD ∩ Neoplastic Process” (RST “EMD”) with only 33 (31) original concepts, 915 (134) concepts were found by the first (second) part to be missing the EMD assignment. Changes to the other two STs were smaller. Conclusion The results show that the proposed auditing methodology can help to effectively and efficiently identify concepts lacking the assignment of a particular semantic type. PMID:19567802

The Anterior Midline Field: Coercion or Decision Making?

ERIC Educational Resources Information Center

Pylkkanen, Liina; Martin, Andrea E.; McElree, Brian; Smart, Andrew

2009-01-01

To study the neural bases of semantic composition in language processing without confounds from syntactic composition, recent magnetoencephalography (MEG) studies have investigated the processing of constructions that exhibit some type of syntax-semantics mismatch. The most studied case of such a mismatch is "complement coercion;" expressions such…

WikiHyperGlossary (WHG): an information literacy technology for chemistry documents.

PubMed

Bauer, Michael A; Berleant, Daniel; Cornell, Andrew P; Belford, Robert E

2015-01-01

The WikiHyperGlossary is an information literacy technology that was created to enhance reading comprehension of documents by connecting them to socially generated multimedia definitions as well as semantically relevant data. The WikiHyperGlossary enhances reading comprehension by using the lexicon of a discipline to generate dynamic links in a document to external resources that can provide implicit information the document did not explicitly provide. Currently, the most common method to acquire additional information when reading a document is to access a search engine and browse the web. This may lead to skimming of multiple documents with the novice actually never returning to the original document of interest. The WikiHyperGlossary automatically brings information to the user within the current document they are reading, enhancing the potential for deeper document understanding. The WikiHyperGlossary allows users to submit a web URL or text to be processed against a chosen lexicon, returning the document with tagged terms. The selection of a tagged term results in the appearance of the WikiHyperGlossary Portlet containing a definition, and depending on the type of word, tabs to additional information and resources. Current types of content include multimedia enhanced definitions, ChemSpider query results, 3D molecular structures, and 2D editable structures connected to ChemSpider queries. Existing glossaries can be bulk uploaded, locked for editing and associated with multiple social generated definitions. The WikiHyperGlossary leverages both social and semantic web technologies to bring relevant information to a document. This can not only aid reading comprehension, but increases the users' ability to obtain additional information within the document. We have demonstrated a molecular editor enabled knowledge framework that can result in a semantic web inductive reasoning process, and integration of the WikiHyperGlossary into other software technologies, like the Jikitou Biomedical Question and Answer system. Although this work was developed in the chemical sciences and took advantage of open science resources and initiatives, the technology is extensible to other knowledge domains. Through the DeepLit (Deeper Literacy: Connecting Documents to Data and Discourse) startup, we seek to extend WikiHyperGlossary technologies to other knowledge domains, and integrate them into other knowledge acquisition workflows.

Mapping the Multiple Graded Contributions of the Anterior Temporal Lobe Representational Hub to Abstract and Social Concepts: Evidence from Distortion-corrected fMRI.

PubMed

Binney, Richard J; Hoffman, Paul; Lambon Ralph, Matthew A

2016-09-06

A growing body of recent convergent evidence indicates that the anterior temporal lobe (ATL) has connectivity-derived graded differences in semantic function: the ventrolateral region appears to be the transmodal, omni-category center-point of the hub whilst secondary contributions come from the peripheries of the hub in a manner that reflects their differential connectivity to different input/output modalities. One of the key challenges for this neurocognitive theory is how different types of concept, especially those with less reliance upon external sensory experience (such as abstract and social concepts), are coded across the graded ATL hub. We were able to answer this key question by using distortion-corrected fMRI to detect functional activations across the entire ATL region and thus to map the neural basis of social and psycholinguistically-matched abstract concepts. Both types of concept engaged a core left-hemisphere semantic network, including the ventrolateral ATL, prefrontal regions and posterior MTG. Additionally, we replicated previous findings of weaker differential activation of the superior and polar ATL for the processing of social stimuli, in addition to the stronger, omni-category activation observed in the vATL. These results are compatible with the view of the ATL as a graded transmodal substrate for the representation of coherent concepts. © The Author 2016. Published by Oxford University Press.

Mapping the Multiple Graded Contributions of the Anterior Temporal Lobe Representational Hub to Abstract and Social Concepts: Evidence from Distortion-corrected fMRI

PubMed Central

Binney, Richard J.; Hoffman, Paul; Lambon Ralph, Matthew A.

2016-01-01

A growing body of recent convergent evidence indicates that the anterior temporal lobe (ATL) has connectivity-derived graded differences in semantic function: the ventrolateral region appears to be the transmodal, omni-category center-point of the hub whilst secondary contributions come from the peripheries of the hub in a manner that reflects their differential connectivity to different input/output modalities. One of the key challenges for this neurocognitive theory is how different types of concept, especially those with less reliance upon external sensory experience (such as abstract and social concepts), are coded across the graded ATL hub. We were able to answer this key question by using distortion-corrected fMRI to detect functional activations across the entire ATL region and thus to map the neural basis of social and psycholinguistically-matched abstract concepts. Both types of concept engaged a core left-hemisphere semantic network, including the ventrolateral ATL, prefrontal regions and posterior MTG. Additionally, we replicated previous findings of weaker differential activation of the superior and polar ATL for the processing of social stimuli, in addition to the stronger, omni-category activation observed in the vATL. These results are compatible with the view of the ATL as a graded transmodal substrate for the representation of coherent concepts. PMID:27600844

Organizing Diverse, Distributed Project Information

NASA Technical Reports Server (NTRS)

Keller, Richard M.

2003-01-01

SemanticOrganizer is a software application designed to organize and integrate information generated within a distributed organization or as part of a project that involves multiple, geographically dispersed collaborators. SemanticOrganizer incorporates the capabilities of database storage, document sharing, hypermedia navigation, and semantic-interlinking into a system that can be customized to satisfy the specific information-management needs of different user communities. The program provides a centralized repository of information that is both secure and accessible to project collaborators via the World Wide Web. SemanticOrganizer's repository can be used to collect diverse information (including forms, documents, notes, data, spreadsheets, images, and sounds) from computers at collaborators work sites. The program organizes the information using a unique network-structured conceptual framework, wherein each node represents a data record that contains not only the original information but also metadata (in effect, standardized data that characterize the information). Links among nodes express semantic relationships among the data records. The program features a Web interface through which users enter, interlink, and/or search for information in the repository. By use of this repository, the collaborators have immediate access to the most recent project information, as well as to archived information. A key advantage to SemanticOrganizer is its ability to interlink information together in a natural fashion using customized terminology and concepts that are familiar to a user community.

Semantic Entity-Component State Management Techniques to Enhance Software Quality for Multimodal VR-Systems.

PubMed

Fischbach, Martin; Wiebusch, Dennis; Latoschik, Marc Erich

2017-04-01

Modularity, modifiability, reusability, and API usability are important software qualities that determine the maintainability of software architectures. Virtual, Augmented, and Mixed Reality (VR, AR, MR) systems, modern computer games, as well as interactive human-robot systems often include various dedicated input-, output-, and processing subsystems. These subsystems collectively maintain a real-time simulation of a coherent application state. The resulting interdependencies between individual state representations, mutual state access, overall synchronization, and flow of control implies a conceptual close coupling whereas software quality asks for a decoupling to develop maintainable solutions. This article presents five semantics-based software techniques that address this contradiction: Semantic grounding, code from semantics, grounded actions, semantic queries, and decoupling by semantics. These techniques are applied to extend the well-established entity-component-system (ECS) pattern to overcome some of this pattern's deficits with respect to the implied state access. A walk-through of central implementation aspects of a multimodal (speech and gesture) VR-interface is used to highlight the techniques' benefits. This use-case is chosen as a prototypical example of complex architectures with multiple interacting subsystems found in many VR, AR and MR architectures. Finally, implementation hints are given, lessons learned regarding maintainability pointed-out, and performance implications discussed.

Semantic-JSON: a lightweight web service interface for Semantic Web contents integrating multiple life science databases.

PubMed

Kobayashi, Norio; Ishii, Manabu; Takahashi, Satoshi; Mochizuki, Yoshiki; Matsushima, Akihiro; Toyoda, Tetsuro

2011-07-01

Global cloud frameworks for bioinformatics research databases become huge and heterogeneous; solutions face various diametric challenges comprising cross-integration, retrieval, security and openness. To address this, as of March 2011 organizations including RIKEN published 192 mammalian, plant and protein life sciences databases having 8.2 million data records, integrated as Linked Open or Private Data (LOD/LPD) using SciNetS.org, the Scientists' Networking System. The huge quantity of linked data this database integration framework covers is based on the Semantic Web, where researchers collaborate by managing metadata across public and private databases in a secured data space. This outstripped the data query capacity of existing interface tools like SPARQL. Actual research also requires specialized tools for data analysis using raw original data. To solve these challenges, in December 2009 we developed the lightweight Semantic-JSON interface to access each fragment of linked and raw life sciences data securely under the control of programming languages popularly used by bioinformaticians such as Perl and Ruby. Researchers successfully used the interface across 28 million semantic relationships for biological applications including genome design, sequence processing, inference over phenotype databases, full-text search indexing and human-readable contents like ontology and LOD tree viewers. Semantic-JSON services of SciNetS.org are provided at http://semanticjson.org.

Developing data aggregation applications from a community standard semantic resource (Invited)

NASA Astrophysics Data System (ADS)

Leadbetter, A.; Lowry, R. K.

2013-12-01

The semantic content of the NERC Vocabulary Server (NVS) has been developed over thirty years. It has been used to mark up metadata and data in a wide range of international projects, including the European Commission (EC) Framework Programme 7 projects SeaDataNet and The Open Service Network for Marine Environmental Data (NETMAR). Within the United States, the National Science Foundation projects Rolling Deck to Repository and Biological & Chemical Data Management Office (BCO-DMO) use concepts from NVS for markup. Further, typed relationships between NVS concepts and terms served by the Marine Metadata Interoperability Ontology Registry and Repository. The vast majority of the concepts publicly served from NVS (35% of ~82,000) form the British Oceanographic Data Centre (BODC) Parameter Usage Vocabulary (PUV). The PUV is instantiated on the NVS as a SKOS concept collection. These terms are used to describe the individual channels in data and metadata served by, for example, BODC, SeaDataNet and BCO-DMO. The PUV terms are designed to be very precise and may contain a high level of detail. Some users have reported that the PUV is difficult to navigate due to its size and complexity (a problem CSIRO have begun to address by deploying a SISSVoc interface to the NVS), and it has been difficult to aggregate data as multiple PUV terms can - with full validity - be used to describe the same data channels. Better approaches to data aggregation are required as a use case for the PUV from the EC European Marine Observation and Data Network (EMODnet) Chemistry project. One solution, proposed and demonstrated during the course of the NETMAR project, is to build new SKOS concept collections which formalise the desired aggregations for given applications, and uses typed relationships to state which PUV concepts contribute to a specific aggregation. Development of these new collections requires input from a group of experts in the application domain who can decide which PUV concepts it is acceptable to aggregate for a given application. Another approach, which has been developed as a use case for concept and data discovery and will be implemented as part of the EC/United States/Australian collaboration the Ocean Data Interoperability Platform, is to expose the well defined, but little publicised, semantic model which underpins each and every concept within the PUV. This will be done in a machine readable form, so that tools can be built to aggregate data and concepts by, for example, the measured parameter; the environmental sphere or compartment of the sampling; and the methodology of the analysis of the parameter. There is interesting work being developed by CSIRO which may be used in this approach. The importance of these data aggregations is growing as more data providers use terms from semantic resources to describe their data, and allows for aggregating data from numerous sources. This importance will grow as data become 'born semantic', i.e. when semantics are embedded with data from the point of collection. In this presentation we introduce a brief history of the development of the PUV; the use cases for data aggregation and discovery outlined above; and the semantic model from which the PUV is built; and the ideas for embedding semantics in data from the point of collection.

Semantically supporting data discovery, markup and aggregation in the European Marine Observation and Data Network (EMODnet)

NASA Astrophysics Data System (ADS)

Lowry, Roy; Leadbetter, Adam

2014-05-01

The semantic content of the NERC Vocabulary Server (NVS) has been developed over thirty years. It has been used to mark up metadata and data in a wide range of international projects, including the European Commission (EC) Framework Programme 7 projects SeaDataNet and The Open Service Network for Marine Environmental Data (NETMAR). Within the United States, the National Science Foundation projects Rolling Deck to Repository and Biological & Chemical Data Management Office (BCO-DMO) use concepts from NVS for markup. Further, typed relationships between NVS concepts and terms served by the Marine Metadata Interoperability Ontology Registry and Repository. The vast majority of the concepts publicly served from NVS (35% of ~82,000) form the British Oceanographic Data Centre (BODC) Parameter Usage Vocabulary (PUV). The PUV is instantiated on the NVS as a SKOS concept collection. These terms are used to describe the individual channels in data and metadata served by, for example, BODC, SeaDataNet and BCO-DMO. The PUV terms are designed to be very precise and may contain a high level of detail. Some users have reported that the PUV is difficult to navigate due to its size and complexity (a problem CSIRO have begun to address by deploying a SISSVoc interface to the NVS), and it has been difficult to aggregate data as multiple PUV terms can - with full validity - be used to describe the same data channels. Better approaches to data aggregation are required as a use case for the PUV from the EC European Marine Observation and Data Network (EMODnet) Chemistry project. One solution, proposed and demonstrated during the course of the NETMAR project, is to build new SKOS concept collections which formalise the desired aggregations for given applications, and uses typed relationships to state which PUV concepts contribute to a specific aggregation. Development of these new collections requires input from a group of experts in the application domain who can decide which PUV concepts it is acceptable to aggregate for a given application. Another approach, which has been developed as a use case for concept and data discovery and will be implemented as part of the EC/United States/Australian collaboration the Ocean Data Interoperability Platform, is to expose the well defined, but little publicised, semantic model which underpins each and every concept within the PUV. This will be done in a machine readable form, so that tools can be built to aggregate data and concepts by, for example, the measured parameter; the environmental sphere or compartment of the sampling; and the methodology of the analysis of the parameter. There is interesting work being developed by CSIRO which may be used in this approach. The importance of these data aggregations is growing as more data providers use terms from semantic resources to describe their data, and allows for aggregating data from numerous sources. This importance will grow as data become "born semantic", i.e. when semantics are embedded with data from the point of collection. In this presentation we introduce a brief history of the development of the PUV; the use cases for data aggregation and discovery outlined above; and the semantic model from which the PUV is built; and the ideas for embedding semantics in data from the point of collection.

Semantic Web Services Challenge, Results from the First Year. Series: Semantic Web And Beyond, Volume 8.

NASA Astrophysics Data System (ADS)

Petrie, C.; Margaria, T.; Lausen, H.; Zaremba, M.

Explores trade-offs among existing approaches. Reveals strengths and weaknesses of proposed approaches, as well as which aspects of the problem are not yet covered. Introduces software engineering approach to evaluating semantic web services. Service-Oriented Computing is one of the most promising software engineering trends because of the potential to reduce the programming effort for future distributed industrial systems. However, only a small part of this potential rests on the standardization of tools offered by the web services stack. The larger part of this potential rests upon the development of sufficient semantics to automate service orchestration. Currently there are many different approaches to semantic web service descriptions and many frameworks built around them. A common understanding, evaluation scheme, and test bed to compare and classify these frameworks in terms of their capabilities and shortcomings, is necessary to make progress in developing the full potential of Service-Oriented Computing. The Semantic Web Services Challenge is an open source initiative that provides a public evaluation and certification of multiple frameworks on common industrially-relevant problem sets. This edited volume reports on the first results in developing common understanding of the various technologies intended to facilitate the automation of mediation, choreography and discovery for Web Services using semantic annotations. Semantic Web Services Challenge: Results from the First Year is designed for a professional audience composed of practitioners and researchers in industry. Professionals can use this book to evaluate SWS technology for their potential practical use. The book is also suitable for advanced-level students in computer science.

Measuring content overlap during handoff communication using distributional semantics: An exploratory study.

PubMed

Abraham, Joanna; Kannampallil, Thomas G; Srinivasan, Vignesh; Galanter, William L; Tagney, Gail; Cohen, Trevor

2017-01-01

We develop and evaluate a methodological approach to measure the degree and nature of overlap in handoff communication content within and across clinical professions. This extensible, exploratory approach relies on combining techniques from conversational analysis and distributional semantics. We audio-recorded handoff communication of residents and nurses on the General Medicine floor of a large academic hospital (n=120 resident and n=120 nurse handoffs). We measured semantic similarity, a proxy for content overlap, between resident-resident and nurse-nurse communication using multiple steps: a qualitative conversational content analysis; an automated semantic similarity analysis using Reflective Random Indexing (RRI); and comparing semantic similarity generated by RRI analysis with human ratings of semantic similarity. There was significant association between the semantic similarity as computed by the RRI method and human rating (ρ=0.88). Based on the semantic similarity scores, content overlap was relatively higher for content related to patient active problems, assessment of active problems, patient-identifying information, past medical history, and medications/treatments. In contrast, content overlap was limited on content related to allergies, family-related information, code status, and anticipatory guidance. Our approach using RRI analysis provides new opportunities for characterizing the nature and degree of overlap in handoff communication. Although exploratory, this method provides a basis for identifying content that can be used for determining shared understanding across clinical professions. Additionally, this approach can inform the development of flexibly standardized handoff tools that reflect clinical content that are most appropriate for fostering shared understanding during transitions of care. Copyright © 2016 Elsevier Inc. All rights reserved.

Focal retrograde amnesia and the episodic-semantic distinction.

PubMed

Wheeler, M A; McMillan, C T

2001-03-01

This article reports a review of focal retrograde amnesia (FRA), or the phenomenon of organically based severe memory loss restricted to retrograde, or pretraumatic, memory. Cases of FRA are classified according to the type of memory loss: episodic, semantic, or both. A few different clusters of the disorder were identified. Lesions to either the anterior temporal lobes or the posterior/visual cortex can result in an FRA that devastates retrograde episodic memory, while having smaller effects on semantic memory. A number of left-hemisphere patients have FRA confined to semantic memory. There are several additional examples of FRA following minor cerebral trauma that disrupts either episodic memory alone or both episodic and semantic memory that are not accompanied by evidence of structural brain lesions. We discuss these different profiles of FRA and their implications for the understanding of memory retrieval.

Biology Question Generation from a Semantic Network

NASA Astrophysics Data System (ADS)

Zhang, Lishan

Science instructors need questions for use in exams, homework assignments, class discussions, reviews, and other instructional activities. Textbooks never have enough questions, so instructors must find them from other sources or generate their own questions. In order to supply instructors with biology questions, a semantic network approach was developed for generating open response biology questions. The generated questions were compared to professional authorized questions. To boost students' learning experience, adaptive selection was built on the generated questions. Bayesian Knowledge Tracing was used as embedded assessment of the student's current competence so that a suitable question could be selected based on the student's previous performance. A between-subjects experiment with 42 participants was performed, where half of the participants studied with adaptive selected questions and the rest studied with mal-adaptive order of questions. Both groups significantly improved their test scores, and the participants in adaptive group registered larger learning gains than participants in the control group. To explore the possibility of generating rich instructional feedback for machine-generated questions, a question-paragraph mapping task was identified. Given a set of questions and a list of paragraphs for a textbook, the goal of the task was to map the related paragraphs to each question. An algorithm was developed whose performance was comparable to human annotators. A multiple-choice question with high quality distractors (incorrect answers) can be pedagogically valuable as well as being much easier to grade than open-response questions. Thus, an algorithm was developed to generate good distractors for multiple-choice questions. The machine-generated multiple-choice questions were compared to human-generated questions in terms of three measures: question difficulty, question discrimination and distractor usefulness. By recruiting 200 participants from Amazon Mechanical Turk, it turned out that the two types of questions performed very closely on all the three measures.

Metaphor, Multiplicative Meaning and the Semiotic Construction of Scientific Knowledge

ERIC Educational Resources Information Center

Liu, Yu; Owyong, Yuet See Monica

2011-01-01

Scientific discourse is characterized by multi-semiotic construction and the resultant semantic expansions. To date, there remains a lack of analytical methods to explicate the multiplicative nature of meaning. Drawing on the theories of systemic functional linguistics, this article examines the meaning-making processes across language and…

Predicting Robust Vocabulary Growth from Measures of Incremental Learning

ERIC Educational Resources Information Center

Frishkoff, Gwen A.; Perfetti, Charles A.; Collins-Thompson, Kevyn

2011-01-01

We report a study of incremental learning of new word meanings over multiple episodes. A new method called MESA (Markov Estimation of Semantic Association) tracked this learning through the automated assessment of learner-generated definitions. The multiple word learning episodes varied in the strength of contextual constraint provided by…

Episodic and semantic memory in children with mesial temporal sclerosis.

PubMed

Rzezak, Patricia; Guimarães, Catarina; Fuentes, Daniel; Guerreiro, Marilisa M; Valente, Kette Dualibi Ramos

2011-07-01

The aim of this study was to analyze semantic and episodic memory deficits in children with mesial temporal sclerosis (MTS) and their correlation with clinical epilepsy variables. For this purpose, 19 consecutive children and adolescents with MTS (8 to 16 years old) were evaluated and their performance on five episodic memory tests (short- and long-term memory and learning) and four semantic memory tests was compared with that of 28 healthy volunteers. Patients performed worse on tests of immediate and delayed verbal episodic memory, visual episodic memory, verbal and visual learning, mental scanning for semantic clues, object naming, word definition, and repetition of sentences. Clinical variables such as early age at seizure onset, severity of epilepsy, and polytherapy impaired distinct types of memory. These data confirm that children with MTS have episodic memory deficits and add new information on semantic memory. The data also demonstrate that clinical variables contribute differently to episodic and semantic memory performance. Copyright © 2011 Elsevier Inc. All rights reserved.

High Performance Descriptive Semantic Analysis of Semantic Graph Databases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Joslyn, Cliff A.; Adolf, Robert D.; al-Saffar, Sinan

As semantic graph database technology grows to address components ranging from extant large triple stores to SPARQL endpoints over SQL-structured relational databases, it will become increasingly important to be able to understand their inherent semantic structure, whether codified in explicit ontologies or not. Our group is researching novel methods for what we call descriptive semantic analysis of RDF triplestores, to serve purposes of analysis, interpretation, visualization, and optimization. But data size and computational complexity makes it increasingly necessary to bring high performance computational resources to bear on this task. Our research group built a novel high performance hybrid system comprisingmore » computational capability for semantic graph database processing utilizing the large multi-threaded architecture of the Cray XMT platform, conventional servers, and large data stores. In this paper we describe that architecture and our methods, and present the results of our analyses of basic properties, connected components, namespace interaction, and typed paths such for the Billion Triple Challenge 2010 dataset.« less

Establishing semantic interoperability of biomedical metadata registries using extended semantic relationships.

PubMed

Park, Yu Rang; Yoon, Young Jo; Kim, Hye Hyeon; Kim, Ju Han

2013-01-01

Achieving semantic interoperability is critical for biomedical data sharing between individuals, organizations and systems. The ISO/IEC 11179 MetaData Registry (MDR) standard has been recognized as one of the solutions for this purpose. The standard model, however, is limited. Representing concepts consist of two or more values, for instance, are not allowed including blood pressure with systolic and diastolic values. We addressed the structural limitations of ISO/IEC 11179 by an integrated metadata object model in our previous research. In the present study, we introduce semantic extensions for the model by defining three new types of semantic relationships; dependency, composite and variable relationships. To evaluate our extensions in a real world setting, we measured the efficiency of metadata reduction by means of mapping to existing others. We extracted metadata from the College of American Pathologist Cancer Protocols and then evaluated our extensions. With no semantic loss, one third of the extracted metadata could be successfully eliminated, suggesting better strategy for implementing clinical MDRs with improved efficiency and utility.

Neural Basis of Semantic and Syntactic Interference in Sentence Comprehension

PubMed Central

Glaser, Yi G.; Martin, Randi C.; Van Dyke, Julie A.; Hamilton, A. Cris; Tan, Yingying

2013-01-01

According to the cue-based parsing approach (Lewis, Vasishth, & Van Dyke, 2006), sentence comprehension difficulty derives from interference from material that partially matches syntactic and semantic retrieval cues. In a 2 (low vs. high semantic interference) × 2 (low vs. high syntactic interference) fMRI study, greater activation was observed in left BA 44/45 for high versus low syntactic interference conditions following sentences and in BA 45/47 for high versus low semantic interference following comprehension questions. A conjunction analysis showed BA45 associated with both types of interference, while BA47 was associated with only semantic interference. Greater activation was also observed in the left STG in the high interference conditions. Importantly, the results for the LIFG could not be attributed to greater working memory capacity demands for high interference conditions. The results favor a fractionation of LIFG wherein BA45 is associated with post-retrieval selection and BA47 with controlled retrieval of semantic information. PMID:23933471

Semantic associative relations and conceptual processing.

PubMed

Di Giacomo, Dina; De Federicis, Lucia Serenella; Pistelli, Manuela; Fiorenzi, Daniela; Passafiume, Domenico

2012-02-01

We analysed the organisation of semantic network using associative mechanisms between different types of information and studied the progression of the use of these associative relations during development. We aimed to verify the linkage of concepts with the use of semantic associative relations. The goal of this study was to analyse the cognitive ability to use associative relations between various items when describing old and/or new concepts. We examined the performance of 100 subjects between the ages of 4 and 7 years on an experimental task using five associative relations based on verbal encoding. The results showed that children are able to use the five semantic associative relations at age 4, but performance with each of the different associative relations improves at different times during development. Functional and part/whole relations develop at an early age, whereas the superordinate relations develop later. Our study clarified the characteristics of the progression of semantic associations during development as well as the roles that associative relations play in the structure and improvement of the semantic store.

Semantic processing in native and second language: evidence from hemispheric differences in fine and coarse semantic coding.

PubMed

Faust, Miriam; Ben-Artzi, Elisheva; Vardi, Nili

2012-12-01

Previous studies suggest that whereas the left hemisphere (LH) is involved in fine semantic processing, the right hemisphere (RH) is uniquely engaged in coarse semantic coding including the comprehension of distinct types of language such as figurative language, lexical ambiguity and verbal humor (e.g., Chiarello, 2003; Faust, 2012). The present study examined the patterns of hemispheric involvement in fine/coarse semantic processing in native and non-native languages using a split visual field priming paradigm. Thirty native Hebrew speaking students made lexical decision judgments of Hebrew and English target words preceded by strongly, weakly, or unrelated primes. Results indicated that whereas for Hebrew pairs, priming effect for the weakly-related word pairs was obtained only for RH presented target words, for English pairs, no priming effect for the weakly-related pairs emerged for either LH or RH presented targets, suggesting that coarse semantic coding is much weaker for a non-native than native language. Copyright © 2012 Elsevier Inc. All rights reserved.

When bees hamper the production of honey: lexical interference from associates in speech production.

PubMed

Abdel Rahman, Rasha; Melinger, Alissa

2007-05-01

In this article, the authors explore semantic context effects in speaking. In particular, the authors investigate a marked discrepancy between categorically and associatively induced effects; only categorical relationships have been reported to cause interference in object naming. In Experiments 1 and 2, a variant of the semantic blocking paradigm was used to induce two different types of semantic context effects. Pictures were either named in the context of categorically related objects (e.g., animals: bee, cow, fish) or in the context of associatively related objects from different semantic categories (e.g., apiary: bee, honey, bee keeper). Semantic interference effects were observed in both conditions, relative to an unrelated context. Experiment 3 replicated the classic effects of categorical interference and associative facilitation in a picture-word interference paradigm with the material used in Experiment 2. These findings suggest that associates are active lexical competitors and that the microstructure of lexicalization is highly flexible and adjustable to the semantic context in which the utterance takes place.

The effects of self-instruction training on a deaf child's semantic and pragmatic production.

PubMed

Swanson, H L

1987-10-01

Effects of self-instruction training on the communication skills of a profoundly hearing-impaired child were studied. Self-instruction training included modeling a series of problem-solving steps in order to direct communication production. Communication production was operationalized as signed semantic and pragmatic functions. A multiple baseline was used to assess treatment and generalization (treatment variations of person and setting) effects. There was evidence to suggest that self-instruction was immediately effective on pragmatic behaviors but such behaviors were reduced when another person administered treatment. In contrast, self-instruction training had a gradual influence on semantic behaviors and those effects were maintained when treatment included a different person and setting. Implications of the clinical study were discussed.

Combined semantic and similarity search in medical image databases

NASA Astrophysics Data System (ADS)

Seifert, Sascha; Thoma, Marisa; Stegmaier, Florian; Hammon, Matthias; Kramer, Martin; Huber, Martin; Kriegel, Hans-Peter; Cavallaro, Alexander; Comaniciu, Dorin

2011-03-01

The current diagnostic process at hospitals is mainly based on reviewing and comparing images coming from multiple time points and modalities in order to monitor disease progression over a period of time. However, for ambiguous cases the radiologist deeply relies on reference literature or second opinion. Although there is a vast amount of acquired images stored in PACS systems which could be reused for decision support, these data sets suffer from weak search capabilities. Thus, we present a search methodology which enables the physician to fulfill intelligent search scenarios on medical image databases combining ontology-based semantic and appearance-based similarity search. It enabled the elimination of 12% of the top ten hits which would arise without taking the semantic context into account.

Interdependence of episodic and semantic memory: evidence from neuropsychology.

PubMed

Greenberg, Daniel L; Verfaellie, Mieke

2010-09-01

Tulving's (1972) theory of memory draws a distinction between general knowledge (semantic memory) and memory for events (episodic memory). Neuropsychological studies have generally examined each type of memory in isolation, but theorists have long argued that these two forms of memory are interdependent. Here we review several lines of neuropsychological research that have explored the interdependence of episodic and semantic memory. The studies show that these forms of memory can affect each other both at encoding and at retrieval. We suggest that theories of memory should be revised to account for all of the interdependencies between episodic and semantic memory; they should also incorporate forms of memory that do not fit neatly into either category.

Interdependence of episodic and semantic memory: Evidence from neuropsychology

PubMed Central

GREENBERG, DANIEL L.; VERFAELLIE, MIEKE

2010-01-01

Tulving's (1972) theory of memory draws a distinction between general knowledge (semantic memory) and memory for events (episodic memory). Neuropsychological studies have generally examined each type of memory in isolation, but theorists have long argued that these two forms of memory are interdependent. Here we review several lines of neuropsychological research that have explored the interdependence of episodic and semantic memory. The studies show that these forms of memory can affect each other both at encoding and at retrieval. We suggest that theories of memory should be revised to account for all of the interdependencies between episodic and semantic memory; they should also incorporate forms of memory that do not fit neatly into either category. PMID:20561378

Linguistic multi-criteria decision-making with representing semantics by programming

NASA Astrophysics Data System (ADS)

Yang, Wu-E.; Ma, Chao-Qun; Han, Zhi-Qiu

2017-01-01

A linguistic multi-criteria decision-making method is introduced. In this method, a maximising discrimination programming assigns the semanteme values to linguistic variables to represent their semantics. Incomplete preferences from using linguistic information are expressed by the constraints of the model. Such assignment can amplify the difference between alternatives. Thus, the discrimination of the decision model is increased, which facilitates the decision-maker to rank or order the alternatives for making a decision. We also discuss the parameter setting and its influence, and use an application example to illustrate the proposed method. Further, the results with three types of semantic structure highlight the ability of the method in handling different semantic structures.

Predication-based semantic indexing: permutations as a means to encode predications in semantic space.

PubMed

Cohen, Trevor; Schvaneveldt, Roger W; Rindflesch, Thomas C

2009-11-14

Corpus-derived distributional models of semantic distance between terms have proved useful in a number of applications. For both theoretical and practical reasons, it is desirable to extend these models to encode discrete concepts and the ways in which they are related to one another. In this paper, we present a novel vector space model that encodes semantic predications derived from MEDLINE by the SemRep system into a compact spatial representation. The associations captured by this method are of a different and complementary nature to those derived by traditional vector space models, and the encoding of predication types presents new possibilities for knowledge discovery and information retrieval.

Integrating Experiential and Distributional Data to Learn Semantic Representations

ERIC Educational Resources Information Center

Andrews, Mark; Vigliocco, Gabriella; Vinson, David

2009-01-01

The authors identify 2 major types of statistical data from which semantic representations can be learned. These are denoted as "experiential data" and "distributional data". Experiential data are derived by way of experience with the physical world and comprise the sensory-motor data obtained through sense receptors. Distributional data, by…

Congruent and Incongruent Semantic Context Influence Vowel Recognition

ERIC Educational Resources Information Center

Wotton, J. M.; Elvebak, R. L.; Moua, L. C.; Heggem, N. M.; Nelson, C. A.; Kirk, K. M.

2011-01-01

The influence of sentence context on the recognition of naturally spoken vowels degraded by reverberation and Gaussian noise was investigated. Target words were paired to have similar consonant sounds but different vowels (e.g., map/mop) and were embedded early in sentences which provided three types of semantic context. Fifty-eight…

Development of compositional and contextual communicable congruence in robots by using dynamic neural network models.

PubMed

Park, Gibeom; Tani, Jun

2015-12-01

The current study presents neurorobotics experiments on acquisition of skills for "communicable congruence" with human via learning. A dynamic neural network model which is characterized by its multiple timescale dynamics property was utilized as a neuromorphic model for controlling a humanoid robot. In the experimental task, the humanoid robot was trained to generate specific sequential movement patterns as responding to various sequences of imperative gesture patterns demonstrated by the human subjects by following predefined compositional semantic rules. The experimental results showed that (1) the adopted MTRNN can achieve generalization by learning in the lower feature perception level by using a limited set of tutoring patterns, (2) the MTRNN can learn to extract compositional semantic rules with generalization in its higher level characterized by slow timescale dynamics, (3) the MTRNN can develop another type of cognitive capability for controlling the internal contextual processes as situated to on-going task sequences without being provided with cues for explicitly indicating task segmentation points. The analysis on the dynamic property developed in the MTRNN via learning indicated that the aforementioned cognitive mechanisms were achieved by self-organization of adequate functional hierarchy by utilizing the constraint of the multiple timescale property and the topological connectivity imposed on the network configuration. These results of the current research could contribute to developments of socially intelligent robots endowed with cognitive communicative competency similar to that of human. Copyright © 2015 Elsevier Ltd. All rights reserved.

Transcranial Direct Current Stimulation Effects on Semantic Processing in Healthy Individuals.

PubMed

Joyal, Marilyne; Fecteau, Shirley

2016-01-01

Semantic processing allows us to use conceptual knowledge about the world. It has been associated with a large distributed neural network that includes the frontal, temporal and parietal cortices. Recent studies using transcranial direct current stimulation (tDCS) also contributed at investigating semantic processing. The goal of this article was to review studies investigating semantic processing in healthy individuals with tDCS and discuss findings from these studies in line with neuroimaging results. Based on functional magnetic resonance imaging studies assessing semantic processing, we predicted that tDCS applied over the inferior frontal gyrus, middle temporal gyrus, and posterior parietal cortex will impact semantic processing. We conducted a search on Pubmed and selected 27 articles in which tDCS was used to modulate semantic processing in healthy subjects. We analysed each article according to these criteria: demographic information, experimental outcomes assessing semantic processing, study design, and effects of tDCS on semantic processes. From the 27 reviewed studies, 8 found main effects of stimulation. In addition to these 8 studies, 17 studies reported an interaction between stimulus types and stimulation conditions (e.g. incoherent functional, but not instrumental, actions were processed faster when anodal tDCS was applied over the posterior parietal cortex as compared to sham tDCS). Results suggest that regions in the frontal, temporal, and parietal cortices are involved in semantic processing. tDCS can modulate some aspects of semantic processing and provide information on the functional roles of brain regions involved in this cognitive process. Copyright © 2016 Elsevier Inc. All rights reserved.

A semantic web framework to integrate cancer omics data with biological knowledge.

PubMed

Holford, Matthew E; McCusker, James P; Cheung, Kei-Hoi; Krauthammer, Michael

2012-01-25

The RDF triple provides a simple linguistic means of describing limitless types of information. Triples can be flexibly combined into a unified data source we call a semantic model. Semantic models open new possibilities for the integration of variegated biological data. We use Semantic Web technology to explicate high throughput clinical data in the context of fundamental biological knowledge. We have extended Corvus, a data warehouse which provides a uniform interface to various forms of Omics data, by providing a SPARQL endpoint. With the querying and reasoning tools made possible by the Semantic Web, we were able to explore quantitative semantic models retrieved from Corvus in the light of systematic biological knowledge. For this paper, we merged semantic models containing genomic, transcriptomic and epigenomic data from melanoma samples with two semantic models of functional data - one containing Gene Ontology (GO) data, the other, regulatory networks constructed from transcription factor binding information. These two semantic models were created in an ad hoc manner but support a common interface for integration with the quantitative semantic models. Such combined semantic models allow us to pose significant translational medicine questions. Here, we study the interplay between a cell's molecular state and its response to anti-cancer therapy by exploring the resistance of cancer cells to Decitabine, a demethylating agent. We were able to generate a testable hypothesis to explain how Decitabine fights cancer - namely, that it targets apoptosis-related gene promoters predominantly in Decitabine-sensitive cell lines, thus conveying its cytotoxic effect by activating the apoptosis pathway. Our research provides a framework whereby similar hypotheses can be developed easily.

What lies beneath: A comparison of reading aloud in pure alexia and semantic dementia

PubMed Central

Hoffman, Paul; Roberts, Daniel J.; Ralph, Matthew A. Lambon; Patterson, Karalyn E.

2014-01-01

Exaggerated effects of word length upon reading-aloud performance define pure alexia, but have also been observed in semantic dementia. Some researchers have proposed a reading-specific account, whereby performance in these two disorders reflects the same cause: impaired orthographic processing. In contrast, according to the primary systems view of acquired reading disorders, pure alexia results from a basic visual processing deficit, whereas degraded semantic knowledge undermines reading performance in semantic dementia. To explore the source of reading deficits in these two disorders, we compared the reading performance of 10 pure alexic and 10 semantic dementia patients, matched in terms of overall severity of reading deficit. The results revealed comparable frequency effects on reading accuracy, but weaker effects of regularity in pure alexia than in semantic dementia. Analysis of error types revealed a higher rate of letter-based errors and a lower rate of regularization responses in pure alexia than in semantic dementia. Error responses were most often words in pure alexia but most often nonwords in semantic dementia. Although all patients made some letter substitution errors, these were characterized by visual similarity in pure alexia and phonological similarity in semantic dementia. Overall, the data indicate that the reading deficits in pure alexia and semantic dementia arise from impairments of visual processing and knowledge of word meaning, respectively. The locus and mechanisms of these impairments are placed within the context of current connectionist models of reading. PMID:24702272

The MMI Semantic Framework: Rosetta Stones for Earth Sciences

NASA Astrophysics Data System (ADS)

Rueda, C.; Bermudez, L. E.; Graybeal, J.; Alexander, P.

2009-12-01

Semantic interoperability—the exchange of meaning among computer systems—is needed to successfully share data in Ocean Science and across all Earth sciences. The best approach toward semantic interoperability requires a designed framework, and operationally tested tools and infrastructure within that framework. Currently available technologies make a scientific semantic framework feasible, but its development requires sustainable architectural vision and development processes. This presentation outlines the MMI Semantic Framework, including recent progress on it and its client applications. The MMI Semantic Framework consists of tools, infrastructure, and operational and community procedures and best practices, to meet short-term and long-term semantic interoperability goals. The design and prioritization of the semantic framework capabilities are based on real-world scenarios in Earth observation systems. We describe some key uses cases, as well as the associated requirements for building the overall infrastructure, which is realized through the MMI Ontology Registry and Repository. This system includes support for community creation and sharing of semantic content, ontology registration, version management, and seamless integration of user-friendly tools and application programming interfaces. The presentation describes the architectural components for semantic mediation, registry and repository for vocabularies, ontology, and term mappings. We show how the technologies and approaches in the framework can address community needs for managing and exchanging semantic information. We will demonstrate how different types of users and client applications exploit the tools and services for data aggregation, visualization, archiving, and integration. Specific examples from OOSTethys (http://www.oostethys.org) and the Ocean Observatories Initiative Cyberinfrastructure (http://www.oceanobservatories.org) will be cited. Finally, we show how semantic augmentation of web services standards could be performed using framework tools.

Musical and verbal semantic memory: two distinct neural networks?

PubMed

Groussard, M; Viader, F; Hubert, V; Landeau, B; Abbas, A; Desgranges, B; Eustache, F; Platel, H

2010-02-01

Semantic memory has been investigated in numerous neuroimaging and clinical studies, most of which have used verbal or visual, but only very seldom, musical material. Clinical studies have suggested that there is a relative neural independence between verbal and musical semantic memory. In the present study, "musical semantic memory" is defined as memory for "well-known" melodies without any knowledge of the spatial or temporal circumstances of learning, while "verbal semantic memory" corresponds to general knowledge about concepts, again without any knowledge of the spatial or temporal circumstances of learning. Our aim was to compare the neural substrates of musical and verbal semantic memory by administering the same type of task in each modality. We used high-resolution PET H(2)O(15) to observe 11 young subjects performing two main tasks: (1) a musical semantic memory task, where the subjects heard the first part of familiar melodies and had to decide whether the second part they heard matched the first, and (2) a verbal semantic memory task with the same design, but where the material consisted of well-known expressions or proverbs. The musical semantic memory condition activated the superior temporal area and inferior and middle frontal areas in the left hemisphere and the inferior frontal area in the right hemisphere. The verbal semantic memory condition activated the middle temporal region in the left hemisphere and the cerebellum in the right hemisphere. We found that the verbal and musical semantic processes activated a common network extending throughout the left temporal neocortex. In addition, there was a material-dependent topographical preference within this network, with predominantly anterior activation during musical tasks and predominantly posterior activation during semantic verbal tasks. Copyright (c) 2009 Elsevier Inc. All rights reserved.

Measurements of auditory-verbal STM span in aphasia: effects of item, task, and lexical impairment.

PubMed

Martin, Nadine; Ayala, Jennifer

2004-06-01

In the first part of this study, we investigated effects of item and task type on span performance in a group of aphasic individuals with word processing and STM deficits. Group analyses revealed significant effects of item on span performance with span being greater for digits than for words. We also investigated associations between subjects' lexical-semantic and phonological processing abilities and performance on four measures of verbal span (digit and word span, each varied for type of response, verbal vs. pointing) as well as one measure of nonverbal span. We predicted and found that the patterns of association between verbal span tasks and lexical abilities reflected the integrity of language processes and representations deployed in each paradigm used to assess span. Performance on the pointing span task, which engages both lexical-semantic and phonological processes, correlated with measures of both lexical-semantic and phonological abilities. Performance on repetition span, which engages primarily input and output phonological processes, correlated with measures of phonological abilities but not measures of lexical-semantic abilities. However, when partial correlations were performed for two subject groups based on their relative preservation of lexical-semantic ability (less or more than phonological ability), repetition span correlated with lexical-semantic measures only in the subgroup with relatively impaired lexical-semantics. Additionally, performance on the nonverbal span task correlated with measures of phonological abilities, suggesting either a general cognitive deficit affecting verbal and nonverbal STM or possibly, the use of a verbal strategy to perform this task. Our discussion focuses on the interpretation of span measurements in clinical practice and research, as well as the implications of these data for theories of short-term memory and word processing.

Semantic relatedness for evaluation of course equivalencies

NASA Astrophysics Data System (ADS)

Yang, Beibei

Semantic relatedness, or its inverse, semantic distance, measures the degree of closeness between two pieces of text determined by their meaning. Related work typically measures semantics based on a sparse knowledge base such as WordNet or Cyc that requires intensive manual efforts to build and maintain. Other work is based on a corpus such as the Brown corpus, or more recently, Wikipedia. This dissertation proposes two approaches to applying semantic relatedness to the problem of suggesting transfer course equivalencies. Two course descriptions are given as input to feed the proposed algorithms, which output a value that can be used to help determine if the courses are equivalent. The first proposed approach uses traditional knowledge sources such as WordNet and corpora for courses from multiple fields of study. The second approach uses Wikipedia, the openly-editable encyclopedia, and it focuses on courses from a technical field such as Computer Science. This work shows that it is promising to adapt semantic relatedness to the education field for matching equivalencies between transfer courses. A semantic relatedness measure using traditional knowledge sources such as WordNet performs relatively well on non-technical courses. However, due to the "knowledge acquisition bottleneck," such a resource is not ideal for technical courses, which use an extensive and growing set of technical terms. To address the problem, this work proposes a Wikipedia-based approach which is later shown to be more correlated to human judgment compared to previous work.

Semantic ambiguity effects on traditional Chinese character naming: A corpus-based approach.

PubMed

Chang, Ya-Ning; Lee, Chia-Ying

2017-11-09

Words are considered semantically ambiguous if they have more than one meaning and can be used in multiple contexts. A number of recent studies have provided objective ambiguity measures by using a corpus-based approach and have demonstrated ambiguity advantages in both naming and lexical decision tasks. Although the predictive power of objective ambiguity measures has been examined in several alphabetic language systems, the effects in logographic languages remain unclear. Moreover, most ambiguity measures do not explicitly address how the various contexts associated with a given word relate to each other. To explore these issues, we computed the contextual diversity (Adelman, Brown, & Quesada, Psychological Science, 17; 814-823, 2006) and semantic ambiguity (Hoffman, Lambon Ralph, & Rogers, Behavior Research Methods, 45; 718-730, 2013) of traditional Chinese single-character words based on the Academia Sinica Balanced Corpus, where contextual diversity was used to evaluate the present semantic space. We then derived a novel ambiguity measure, namely semantic variability, by computing the distance properties of the distinct clusters grouped by the contexts that contained a given word. We demonstrated that semantic variability was superior to semantic diversity in accounting for the variance in naming response times, suggesting that considering the substructure of the various contexts associated with a given word can provide a relatively fine scale of ambiguity information for a word. All of the context and ambiguity measures for 2,418 Chinese single-character words are provided as supplementary materials.

The role of sleep spindles and slow-wave activity in integrating new information in semantic memory.

PubMed

Tamminen, Jakke; Lambon Ralph, Matthew A; Lewis, Penelope A

2013-09-25

Assimilating new information into existing knowledge is a fundamental part of consolidating new memories and allowing them to guide behavior optimally and is vital for conceptual knowledge (semantic memory), which is accrued over many years. Sleep is important for memory consolidation, but its impact upon assimilation of new information into existing semantic knowledge has received minimal examination. Here, we examined the integration process by training human participants on novel words with meanings that fell into densely or sparsely populated areas of semantic memory in two separate sessions. Overnight sleep was polysomnographically monitored after each training session and recall was tested immediately after training, after a night of sleep, and 1 week later. Results showed that participants learned equal numbers of both word types, thus equating amount and difficulty of learning across the conditions. Measures of word recognition speed showed a disadvantage for novel words in dense semantic neighborhoods, presumably due to interference from many semantically related concepts, suggesting that the novel words had been successfully integrated into semantic memory. Most critically, semantic neighborhood density influenced sleep architecture, with participants exhibiting more sleep spindles and slow-wave activity after learning the sparse compared with the dense neighborhood words. These findings provide the first evidence that spindles and slow-wave activity mediate integration of new information into existing semantic networks.

Orthographic versus semantic matching in visual search for words within lists.

PubMed

Léger, Laure; Rouet, Jean-François; Ros, Christine; Vibert, Nicolas

2012-03-01

An eye-tracking experiment was performed to assess the influence of orthographic and semantic distractor words on visual search for words within lists. The target word (e.g., "raven") was either shown to participants before the search (literal search) or defined by its semantic category (e.g., "bird", categorical search). In both cases, the type of words included in the list affected visual search times and eye movement patterns. In the literal condition, the presence of orthographic distractors sharing initial and final letters with the target word strongly increased search times. Indeed, the orthographic distractors attracted participants' gaze and were fixated for longer times than other words in the list. The presence of semantic distractors related to the target word also increased search times, which suggests that significant automatic semantic processing of nontarget words took place. In the categorical condition, semantic distractors were expected to have a greater impact on the search task. As expected, the presence in the list of semantic associates of the target word led to target selection errors. However, semantic distractors did not significantly increase search times any more, whereas orthographic distractors still did. Hence, the visual characteristics of nontarget words can be strong predictors of the efficiency of visual search even when the exact target word is unknown. The respective impacts of orthographic and semantic distractors depended more on the characteristics of lists than on the nature of the search task.

Abstraction and generalization in statistical learning: implications for the relationship between semantic types and episodic tokens

PubMed Central

2017-01-01

Statistical approaches to emergent knowledge have tended to focus on the process by which experience of individual episodes accumulates into generalizable experience across episodes. However, there is a seemingly opposite, but equally critical, process that such experience affords: the process by which, from a space of types (e.g. onions—a semantic class that develops through exposure to individual episodes involving individual onions), we can perceive or create, on-the-fly, a specific token (a specific onion, perhaps one that is chopped) in the absence of any prior perceptual experience with that specific token. This article reviews a selection of statistical learning studies that lead to the speculation that this process—the generation, on the basis of semantic memory, of a novel episodic representation—is itself an instance of a statistical, in fact associative, process. The article concludes that the same processes that enable statistical abstraction across individual episodes to form semantic memories also enable the generation, from those semantic memories, of representations that correspond to individual tokens, and of novel episodic facts about those tokens. Statistical learning is a window onto these deeper processes that underpin cognition. This article is part of the themed issue ‘New frontiers for statistical learning in the cognitive sciences’. PMID:27872378

Abstraction and generalization in statistical learning: implications for the relationship between semantic types and episodic tokens.

PubMed

Altmann, Gerry T M

2017-01-05

Statistical approaches to emergent knowledge have tended to focus on the process by which experience of individual episodes accumulates into generalizable experience across episodes. However, there is a seemingly opposite, but equally critical, process that such experience affords: the process by which, from a space of types (e.g. onions-a semantic class that develops through exposure to individual episodes involving individual onions), we can perceive or create, on-the-fly, a specific token (a specific onion, perhaps one that is chopped) in the absence of any prior perceptual experience with that specific token. This article reviews a selection of statistical learning studies that lead to the speculation that this process-the generation, on the basis of semantic memory, of a novel episodic representation-is itself an instance of a statistical, in fact associative, process. The article concludes that the same processes that enable statistical abstraction across individual episodes to form semantic memories also enable the generation, from those semantic memories, of representations that correspond to individual tokens, and of novel episodic facts about those tokens. Statistical learning is a window onto these deeper processes that underpin cognition.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Author(s).

Three more semantic serial position functions and a SIMPLE explanation.

PubMed

Kelley, Matthew R; Neath, Ian; Surprenant, Aimée M

2013-05-01

There are innumerable demonstrations of serial position functions-with characteristic primacy and recency effects-in episodic tasks, but there are only a handful of such demonstrations in semantic memory tasks, and those demonstrations have used only two types of stimuli. Here, we provide three more examples of serial position functions when recalling from semantic memory. Participants were asked to reconstruct the order of (1) two cartoon theme song lyrics, (2) the seven Harry Potter books, and (3) two sets of movies, and all three demonstrations yielded conventional-looking serial position functions with primacy and recency effects. The data were well-fit by SIMPLE, a local distinctiveness model of memory that was originally designed to account for serial position effects in short- and long-term episodic memory. According to SIMPLE, serial position functions in both episodic and semantic memory tasks arise from the same type of processing: Items that are more separated from their close neighbors in psychological space at the time of recall will be better remembered. We argue that currently available evidence suggests that serial position functions observed when recalling items that are presumably in semantic memory arise because of the same processes as those observed when recalling items that are presumably in episodic memory.

Bridging the semantic gap in sports

NASA Astrophysics Data System (ADS)

Li, Baoxin; Errico, James; Pan, Hao; Sezan, M. Ibrahim

2003-01-01

One of the major challenges facing current media management systems and the related applications is the so-called "semantic gap" between the rich meaning that a user desires and the shallowness of the content descriptions that are automatically extracted from the media. In this paper, we address the problem of bridging this gap in the sports domain. We propose a general framework for indexing and summarizing sports broadcast programs. The framework is based on a high-level model of sports broadcast video using the concept of an event, defined according to domain-specific knowledge for different types of sports. Within this general framework, we develop automatic event detection algorithms that are based on automatic analysis of the visual and aural signals in the media. We have successfully applied the event detection algorithms to different types of sports including American football, baseball, Japanese sumo wrestling, and soccer. Event modeling and detection contribute to the reduction of the semantic gap by providing rudimentary semantic information obtained through media analysis. We further propose a novel approach, which makes use of independently generated rich textual metadata, to fill the gap completely through synchronization of the information-laden textual data with the basic event segments. An MPEG-7 compliant prototype browsing system has been implemented to demonstrate semantic retrieval and summarization of sports video.

Time series patterns and language support in DBMS

NASA Astrophysics Data System (ADS)

Telnarova, Zdenka

2017-07-01

This contribution is focused on pattern type Time Series as a rich in semantics representation of data. Some example of implementation of this pattern type in traditional Data Base Management Systems is briefly presented. There are many approaches how to manipulate with patterns and query patterns. Crucial issue can be seen in systematic approach to pattern management and specific pattern query language which takes into consideration semantics of patterns. Query language SQL-TS for manipulating with patterns is shown on Time Series data.

Varieties of semantic ‘access’ deficit in Wernicke’s aphasia and semantic aphasia

PubMed Central

Robson, Holly; Lambon Ralph, Matthew A.; Jefferies, Elizabeth

2015-01-01

Comprehension deficits are common in stroke aphasia, including in cases with (i) semantic aphasia, characterized by poor executive control of semantic processing across verbal and non-verbal modalities; and (ii) Wernicke’s aphasia, associated with poor auditory–verbal comprehension and repetition, plus fluent speech with jargon. However, the varieties of these comprehension problems, and their underlying causes, are not well understood. Both patient groups exhibit some type of semantic ‘access’ deficit, as opposed to the ‘storage’ deficits observed in semantic dementia. Nevertheless, existing descriptions suggest that these patients might have different varieties of ‘access’ impairment—related to difficulty resolving competition (in semantic aphasia) versus initial activation of concepts from sensory inputs (in Wernicke’s aphasia). We used a case series design to compare patients with Wernicke’s aphasia and those with semantic aphasia on Warrington’s paradigmatic assessment of semantic ‘access’ deficits. In these verbal and non-verbal matching tasks, a small set of semantically-related items are repeatedly presented over several cycles so that the target on one trial becomes a distractor on another (building up interference and eliciting semantic ‘blocking’ effects). Patients with Wernicke’s aphasia and semantic aphasia were distinguished according to lesion location in the temporal cortex, but in each group, some individuals had additional prefrontal damage. Both of these aspects of lesion variability—one that mapped onto classical ‘syndromes’ and one that did not—predicted aspects of the semantic ‘access’ deficit. Both semantic aphasia and Wernicke’s aphasia cases showed multimodal semantic impairment, although as expected, the Wernicke’s aphasia group showed greater deficits on auditory-verbal than picture judgements. Distribution of damage in the temporal lobe was crucial for predicting the initially ‘beneficial’ effects of stimulus repetition: cases with Wernicke’s aphasia showed initial improvement with repetition of words and pictures, while in semantic aphasia, semantic access was initially good but declined in the face of competition from previous targets. Prefrontal damage predicted the ‘harmful’ effects of repetition: the ability to reselect both word and picture targets in the face of mounting competition was linked to left prefrontal damage in both groups. Therefore, patients with semantic aphasia and Wernicke’s aphasia have partially distinct impairment of semantic ‘access’ but, across these syndromes, prefrontal lesions produce declining comprehension with repetition in both verbal and non-verbal tasks. PMID:26454668

Varieties of semantic 'access' deficit in Wernicke's aphasia and semantic aphasia.

PubMed

Thompson, Hannah E; Robson, Holly; Lambon Ralph, Matthew A; Jefferies, Elizabeth

2015-12-01

Comprehension deficits are common in stroke aphasia, including in cases with (i) semantic aphasia, characterized by poor executive control of semantic processing across verbal and non-verbal modalities; and (ii) Wernicke's aphasia, associated with poor auditory-verbal comprehension and repetition, plus fluent speech with jargon. However, the varieties of these comprehension problems, and their underlying causes, are not well understood. Both patient groups exhibit some type of semantic 'access' deficit, as opposed to the 'storage' deficits observed in semantic dementia. Nevertheless, existing descriptions suggest that these patients might have different varieties of 'access' impairment-related to difficulty resolving competition (in semantic aphasia) versus initial activation of concepts from sensory inputs (in Wernicke's aphasia). We used a case series design to compare patients with Wernicke's aphasia and those with semantic aphasia on Warrington's paradigmatic assessment of semantic 'access' deficits. In these verbal and non-verbal matching tasks, a small set of semantically-related items are repeatedly presented over several cycles so that the target on one trial becomes a distractor on another (building up interference and eliciting semantic 'blocking' effects). Patients with Wernicke's aphasia and semantic aphasia were distinguished according to lesion location in the temporal cortex, but in each group, some individuals had additional prefrontal damage. Both of these aspects of lesion variability-one that mapped onto classical 'syndromes' and one that did not-predicted aspects of the semantic 'access' deficit. Both semantic aphasia and Wernicke's aphasia cases showed multimodal semantic impairment, although as expected, the Wernicke's aphasia group showed greater deficits on auditory-verbal than picture judgements. Distribution of damage in the temporal lobe was crucial for predicting the initially 'beneficial' effects of stimulus repetition: cases with Wernicke's aphasia showed initial improvement with repetition of words and pictures, while in semantic aphasia, semantic access was initially good but declined in the face of competition from previous targets. Prefrontal damage predicted the 'harmful' effects of repetition: the ability to reselect both word and picture targets in the face of mounting competition was linked to left prefrontal damage in both groups. Therefore, patients with semantic aphasia and Wernicke's aphasia have partially distinct impairment of semantic 'access' but, across these syndromes, prefrontal lesions produce declining comprehension with repetition in both verbal and non-verbal tasks. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain.

Reduced Short-Term Memory Span in Aphasia and Susceptibility to Interference: Contribution of Material-Specific Maintenance Deficits

PubMed Central

Barde, Laura H.F.; Schwartz, Myrna F.; Chrysikou, Evangelia G.; Thompson-Schill, Sharon L.

2010-01-01

Semantic short-term memory (STM) deficits have been traditionally defined as an inability to maintain semantic representations over a delay (R. Martin, Shelton & Yaffee, 1994). Yet some patients with semantic STM deficits make numerous intrusions of items from previously presented lists, thus presenting an interesting paradox: Why should an inability to maintain semantic representations produce an increase in intrusions from earlier lists? In this study, we investigated the relationship between maintenance deficits and susceptibility to interference in a group of 20 aphasic patients characterized with weak semantic or weak phonological STM. Patients and matched control participants performed a modified item-recognition task designed to elicit semantic or phonological interference from list items located one, two, or three trials back (Hamilton & R. Martin, 2007). Controls demonstrated significant effects of interference in both versions of the task. Interference in patients was predicted by the type and severity of their STM deficit; that is, shorter semantic spans were associated with greater semantic interference and shorter phonological spans were associated with greater phonological interference. We interpret these results through a new perspective, the reactivation hypothesis, and we discuss their importance for accounts emphasizing the contribution of maintenance mechanisms for STM impairments in aphasia as well as susceptibility to interference. PMID:19925813

Topographical gradients of semantics and phonology revealed by temporal lobe stimulation.

PubMed

Miozzo, Michele; Williams, Alicia C; McKhann, Guy M; Hamberger, Marla J

2017-02-01

Word retrieval is a fundamental component of oral communication, and it is well established that this function is supported by left temporal cortex. Nevertheless, the specific temporal areas mediating word retrieval and the particular linguistic processes these regions support have not been well delineated. Toward this end, we analyzed over 1000 naming errors induced by left temporal cortical stimulation in epilepsy surgery patients. Errors were primarily semantic (lemon → "pear"), phonological (horn → "corn"), non-responses, and delayed responses (correct responses after a delay), and each error type appeared predominantly in a specific region: semantic errors in mid-middle temporal gyrus (TG), phonological errors and delayed responses in middle and posterior superior TG, and non-responses in anterior inferior TG. To the extent that semantic errors, phonological errors and delayed responses reflect disruptions in different processes, our results imply topographical specialization of semantic and phonological processing. Specifically, results revealed an inferior-to-superior gradient, with more superior regions associated with phonological processing. Further, errors were increasingly semantically related to targets toward posterior temporal cortex. We speculate that detailed semantic input is needed to support phonological retrieval, and thus, the specificity of semantic input increases progressively toward posterior temporal regions implicated in phonological processing. Hum Brain Mapp 38:688-703, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

The Swedish BioFINDER 2 Study

ClinicalTrials.gov

2018-04-16

Dementia; Alzheimer Disease; Parkinson Disease; Lewy Body Disease; Parkinson-Dementia Syndrome; Frontotemporal Degeneration; Semantic Dementia; Progressive Nonfluent Aphasia; Progressive Supranuclear Palsy; Corticobasal Degeneration; Multiple System Atrophy; Mild Cognitive Impairment

Ontology patterns for complex topographic feature yypes

USGS Publications Warehouse

Varanka, Dalia E.

2011-01-01

Complex feature types are defined as integrated relations between basic features for a shared meaning or concept. The shared semantic concept is difficult to define in commonly used geographic information systems (GIS) and remote sensing technologies. The role of spatial relations between complex feature parts was recognized in early GIS literature, but had limited representation in the feature or coverage data models of GIS. Spatial relations are more explicitly specified in semantic technology. In this paper, semantics for topographic feature ontology design patterns (ODP) are developed as data models for the representation of complex features. In the context of topographic processes, component assemblages are supported by resource systems and are found on local landscapes. The topographic ontology is organized across six thematic modules that can account for basic feature types, resource systems, and landscape types. Types of complex feature attributes include location, generative processes and physical description. Node/edge networks model standard spatial relations and relations specific to topographic science to represent complex features. To demonstrate these concepts, data from The National Map of the U. S. Geological Survey was converted and assembled into ODP.

Semantic Enhancement for Enterprise Data Management

NASA Astrophysics Data System (ADS)

Ma, Li; Sun, Xingzhi; Cao, Feng; Wang, Chen; Wang, Xiaoyuan; Kanellos, Nick; Wolfson, Dan; Pan, Yue

Taking customer data as an example, the paper presents an approach to enhance the management of enterprise data by using Semantic Web technologies. Customer data is the most important kind of core business entity a company uses repeatedly across many business processes and systems, and customer data management (CDM) is becoming critical for enterprises because it keeps a single, complete and accurate record of customers across the enterprise. Existing CDM systems focus on integrating customer data from all customer-facing channels and front and back office systems through multiple interfaces, as well as publishing customer data to different applications. To make the effective use of the CDM system, this paper investigates semantic query and analysis over the integrated and centralized customer data, enabling automatic classification and relationship discovery. We have implemented these features over IBM Websphere Customer Center, and shown the prototype to our clients. We believe that our study and experiences are valuable for both Semantic Web community and data management community.

A case study of data integration for aquatic resources using semantic web technologies

USGS Publications Warehouse

Gordon, Janice M.; Chkhenkeli, Nina; Govoni, David L.; Lightsom, Frances L.; Ostroff, Andrea C.; Schweitzer, Peter N.; Thongsavanh, Phethala; Varanka, Dalia E.; Zednik, Stephan

2015-01-01

Use cases, information modeling, and linked data techniques are Semantic Web technologies used to develop a prototype system that integrates scientific observations from four independent USGS and cooperator data systems. The techniques were tested with a use case goal of creating a data set for use in exploring potential relationships among freshwater fish populations and environmental factors. The resulting prototype extracts data from the BioData Retrieval System, the Multistate Aquatic Resource Information System, the National Geochemical Survey, and the National Hydrography Dataset. A prototype user interface allows a scientist to select observations from these data systems and combine them into a single data set in RDF format that includes explicitly defined relationships and data definitions. The project was funded by the USGS Community for Data Integration and undertaken by the Community for Data Integration Semantic Web Working Group in order to demonstrate use of Semantic Web technologies by scientists. This allows scientists to simultaneously explore data that are available in multiple, disparate systems beyond those they traditionally have used.

Anatomy is strategy: Skilled reading differences associated with structural connectivity differences in the reading network

PubMed Central

Graves, William W.; Binder, Jeffrey R.; Desai, Rutvik H.; Humphries, Colin; Stengel, Benjamin C.; Seidenberg, Mark S.

2014-01-01

Are there multiple ways to be a skilled reader? To address this longstanding, unresolved question, we hypothesized that individual variability in using semantic information in reading aloud would be associated with neuroanatomical variation in pathways linking semantics and phonology. Left-hemisphere regions of interest for diffusion tensor imaging analysis were defined based on fMRI results, including two regions linked with semantic processing – angular gyrus (AG) and inferior temporal sulcus (ITS) – and two linked with phonological processing – posterior superior temporal gyrus (pSTG) and posterior middle temporal gyrus (pMTG). Effects of imageability (a semantic measure) on response times varied widely among individuals and covaried with the volume of pathways through the ITS and pMTG, and through AG and pSTG, partially overlapping the inferior longitudinal fasciculus and the posterior branch of the arcuate fasciculus. These results suggest strategy differences among skilled readers associated with structural variation in the neural reading network. PMID:24735993

Graph-Based Semantic Web Service Composition for Healthcare Data Integration.

PubMed

Arch-Int, Ngamnij; Arch-Int, Somjit; Sonsilphong, Suphachoke; Wanchai, Paweena

2017-01-01

Within the numerous and heterogeneous web services offered through different sources, automatic web services composition is the most convenient method for building complex business processes that permit invocation of multiple existing atomic services. The current solutions in functional web services composition lack autonomous queries of semantic matches within the parameters of web services, which are necessary in the composition of large-scale related services. In this paper, we propose a graph-based Semantic Web Services composition system consisting of two subsystems: management time and run time. The management-time subsystem is responsible for dependency graph preparation in which a dependency graph of related services is generated automatically according to the proposed semantic matchmaking rules. The run-time subsystem is responsible for discovering the potential web services and nonredundant web services composition of a user's query using a graph-based searching algorithm. The proposed approach was applied to healthcare data integration in different health organizations and was evaluated according to two aspects: execution time measurement and correctness measurement.

Graph-Based Semantic Web Service Composition for Healthcare Data Integration

PubMed Central

2017-01-01

Within the numerous and heterogeneous web services offered through different sources, automatic web services composition is the most convenient method for building complex business processes that permit invocation of multiple existing atomic services. The current solutions in functional web services composition lack autonomous queries of semantic matches within the parameters of web services, which are necessary in the composition of large-scale related services. In this paper, we propose a graph-based Semantic Web Services composition system consisting of two subsystems: management time and run time. The management-time subsystem is responsible for dependency graph preparation in which a dependency graph of related services is generated automatically according to the proposed semantic matchmaking rules. The run-time subsystem is responsible for discovering the potential web services and nonredundant web services composition of a user's query using a graph-based searching algorithm. The proposed approach was applied to healthcare data integration in different health organizations and was evaluated according to two aspects: execution time measurement and correctness measurement. PMID:29065602

CASAS: A tool for composing automatically and semantically astrophysical services

NASA Astrophysics Data System (ADS)

Louge, T.; Karray, M. H.; Archimède, B.; Knödlseder, J.

2017-07-01

Multiple astronomical datasets are available through internet and the astrophysical Distributed Computing Infrastructure (DCI) called Virtual Observatory (VO). Some scientific workflow technologies exist for retrieving and combining data from those sources. However selection of relevant services, automation of the workflows composition and the lack of user-friendly platforms remain a concern. This paper presents CASAS, a tool for semantic web services composition in astrophysics. This tool proposes automatic composition of astrophysical web services and brings a semantics-based, automatic composition of workflows. It widens the services choice and eases the use of heterogeneous services. Semantic web services composition relies on ontologies for elaborating the services composition; this work is based on Astrophysical Services ONtology (ASON). ASON had its structure mostly inherited from the VO services capacities. Nevertheless, our approach is not limited to the VO and brings VO plus non-VO services together without the need for premade recipes. CASAS is available for use through a simple web interface.

Differential interference effects of negative emotional states on subsequent semantic and perceptual processing

PubMed Central

Gorlick, Marissa A.; Mather, Mara

2012-01-01

Past studies have revealed that encountering negative events interferes with cognitive processing of subsequent stimuli. The present study investigated whether negative events affect semantic and perceptual processing differently. Presentation of negative pictures produced slower reaction times than neutral or positive pictures in tasks that require semantic processing, such as natural/man-made judgments about drawings of objects, commonness judgments about objects, and categorical judgments about pairs of words. In contrast, negative picture presentation did not slow down judgments in subsequent perceptual processing (e.g., color judgments about words, and size judgments about objects). The subjective arousal level of negative pictures did not modulate the interference effects on semantic/perceptual processing. These findings indicate that encountering negative emotional events interferes with semantic processing of subsequent stimuli more strongly than perceptual processing, and that not all types of subsequent cognitive processing are impaired by negative events. PMID:22142207

Differential interference effects of negative emotional states on subsequent semantic and perceptual processing.

PubMed

Sakaki, Michiko; Gorlick, Marissa A; Mather, Mara

2011-12-01

Past studies have revealed that encountering negative events interferes with cognitive processing of subsequent stimuli. The present study investigates whether negative events affect semantic and perceptual processing differently. Presentation of negative pictures produced slower reaction times than neutral or positive pictures in tasks that require semantic processing, such as natural or man-made judgments about drawings of objects, commonness judgments about objects, and categorical judgments about pairs of words. In contrast, negative picture presentation did not slow down judgments in subsequent perceptual processing (e.g., color judgments about words, size judgments about objects). The subjective arousal level of negative pictures did not modulate the interference effects on semantic or perceptual processing. These findings indicate that encountering negative emotional events interferes with semantic processing of subsequent stimuli more strongly than perceptual processing, and that not all types of subsequent cognitive processing are impaired by negative events. (c) 2011 APA, all rights reserved.

Shared neural processes support semantic control and action understanding

PubMed Central

Davey, James; Rueschemeyer, Shirley-Ann; Costigan, Alison; Murphy, Nik; Krieger-Redwood, Katya; Hallam, Glyn; Jefferies, Elizabeth

2015-01-01

Executive–semantic control and action understanding appear to recruit overlapping brain regions but existing evidence from neuroimaging meta-analyses and neuropsychology lacks spatial precision; we therefore manipulated difficulty and feature type (visual vs. action) in a single fMRI study. Harder judgements recruited an executive–semantic network encompassing medial and inferior frontal regions (including LIFG) and posterior temporal cortex (including pMTG). These regions partially overlapped with brain areas involved in action but not visual judgements. In LIFG, the peak responses to action and difficulty were spatially identical across participants, while these responses were overlapping yet spatially distinct in posterior temporal cortex. We propose that the co-activation of LIFG and pMTG allows the flexible retrieval of semantic information, appropriate to the current context; this might be necessary both for semantic control and understanding actions. Feature selection in difficult trials also recruited ventral occipital–temporal areas, not implicated in action understanding. PMID:25658631

PIDs, Types and the Semantic Web

NASA Astrophysics Data System (ADS)

Schwardmann, Ulrich

2017-04-01

PID Information Types are becoming a crucial role in scientific data management because they can provide state (what) and binding (where) information about digital objects as attributes of the PID. This is a similar but much more flexible approach than the well known mime type characterization, because both of these types concepts allow to decide about preconditions for processes in advance and before touching the data. One aspect of this is the need for standards and correctness of the used types to ensure reliability for the processes operating on the digital objects. This requires registries and schemas for PID InfoTypes and suggests an automated schema generation process. Such a process in combination with data type registries will be described in more detail in the intended talk. Another aspect of PID InfoTypes is its intrinsic grammar as subject-predicate-object triple, with the PID as subject, the type as predicate and its value (often again a PID) as object in this relation. Given the registration of types and the proposed syntactical rigidness of the value, guaranteed by the schema, together with the use of PIDs in subject and predicate, the type concept has the ability to overcome the fuzziness and lack of reliability of semantic web categories with its URL references and possibly changing locations and content. The intended talk will also describe this approach in more detail, discusses the differences to linked data and describes some necessary technological developments for the type concept to keep up with the possibilities currently provided by the semantic web.

Scene Semantic Segmentation from Indoor Rgb-D Images Using Encode-Decoder Fully Convolutional Networks

NASA Astrophysics Data System (ADS)

Wang, Z.; Li, T.; Pan, L.; Kang, Z.

2017-09-01

With increasing attention for the indoor environment and the development of low-cost RGB-D sensors, indoor RGB-D images are easily acquired. However, scene semantic segmentation is still an open area, which restricts indoor applications. The depth information can help to distinguish the regions which are difficult to be segmented out from the RGB images with similar color or texture in the indoor scenes. How to utilize the depth information is the key problem of semantic segmentation for RGB-D images. In this paper, we propose an Encode-Decoder Fully Convolutional Networks for RGB-D image classification. We use Multiple Kernel Maximum Mean Discrepancy (MK-MMD) as a distance measure to find common and special features of RGB and D images in the network to enhance performance of classification automatically. To explore better methods of applying MMD, we designed two strategies; the first calculates MMD for each feature map, and the other calculates MMD for whole batch features. Based on the result of classification, we use the full connect CRFs for the semantic segmentation. The experimental results show that our method can achieve a good performance on indoor RGB-D image semantic segmentation.

An agent-based peer-to-peer architecture for semantic discovery of manufacturing services across virtual enterprises

NASA Astrophysics Data System (ADS)

Zhang, Wenyu; Zhang, Shuai; Cai, Ming; Jian, Wu

2015-04-01

With the development of virtual enterprise (VE) paradigm, the usage of serviceoriented architecture (SOA) is increasingly being considered for facilitating the integration and utilisation of distributed manufacturing resources. However, due to the heterogeneous nature among VEs, the dynamic nature of a VE and the autonomous nature of each VE member, the lack of both sophisticated coordination mechanism in the popular centralised infrastructure and semantic expressivity in the existing SOA standards make the current centralised, syntactic service discovery method undesirable. This motivates the proposed agent-based peer-to-peer (P2P) architecture for semantic discovery of manufacturing services across VEs. Multi-agent technology provides autonomous and flexible problemsolving capabilities in dynamic and adaptive VE environments. Peer-to-peer overlay provides highly scalable coupling across decentralised VEs, each of which exhibiting as a peer composed of multiple agents dealing with manufacturing services. The proposed architecture utilises a novel, efficient, two-stage search strategy - semantic peer discovery and semantic service discovery - to handle the complex searches of manufacturing services across VEs through fast peer filtering. The operation and experimental evaluation of the prototype system are presented to validate the implementation of the proposed approach.

Regional Brain Dysfunction Associated with Semantic Errors in Comprehension.

PubMed

Shahid, Hinna; Sebastian, Rajani; Tippett, Donna C; Saxena, Sadhvi; Wright, Amy; Hanayik, Taylor; Breining, Bonnie; Bonilha, Leonardo; Fridriksson, Julius; Rorden, Chris; Hillis, Argye E

2018-02-01

Here we illustrate how investigation of individuals acutely after stroke, before structure/function reorganization through recovery or rehabilitation, can be helpful in answering questions about the role of specific brain regions in language functions. Although there is converging evidence from a variety of sources that the left posterior-superior temporal gyrus plays some role in spoken word comprehension, its precise role in this function has not been established. We hypothesized that this region is essential for distinguishing between semantically related words, because it is critical for linking the spoken word to the complete semantic representation. We tested this hypothesis in 127 individuals with 48 hours of acute ischemic stroke, before the opportunity for reorganization or recovery. We identified tissue dysfunction (acute infarct and/or hypoperfusion) in gray and white matter parcels of the left hemisphere, and we evaluated the association between rate of semantic errors in a word-picture verification tasks and extent of tissue dysfunction in each region. We found that after correcting for lesion volume and multiple comparisons, the rate of semantic errors correlated with the extent of tissue dysfunction in left posterior-superior temporal gyrus and retrolenticular white matter. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

[Schizophrenia and semantic priming effects].

PubMed

Lecardeur, L; Giffard, B; Eustache, F; Dollfus, S

2006-01-01

This article is a review of studies using the semantic priming paradigm to assess the functioning of semantic memory in schizophrenic patients. Semantic priming describes the phenomenon of increasing the speed with which a string of letters (the target) is recognized as a word (lexical decision task) by presenting to the subject a semantically related word (the prime) prior to the appearance of the target word. This semantic priming is linked to both automatic and controlled processes depending on experimental conditions (stimulus onset asynchrony (SOA), percentage of related words and explicit memory instructions). Automatic process observed with short SOA, low related word percentage and instructions asking only to process the target, could be linked to the "automatic spreading activation" through the semantic network. Controlled processes involve "semantic matching" (the number of related and unrelated pairs influences the subjects decision) and "expectancy" (the prime leads the subject to generate an expectancy set of potential target to the prime). These processes can be observed whatever the SOA for the former and with long SOA for the later, but both with only high related word percentage and explicit memory instructions. Studies evaluating semantic priming effects in schizophrenia show conflicting results: schizophrenic patients can present hyperpriming (semantic priming effect is larger in patients than in controls), hypopriming (semantic priming effect is lower in patients than in controls) or equal semantic priming effects compared to control subjects. These results could be associated to a global impairment of controlled processes in schizophrenia, essentially to a dysfunction of semantic matching process. On the other hand, efficiency of semantic automatic spreading activation process is controversial. These discrepancies could be linked to the different experimental conditions used (duration of SOA, proportion of related pairs and instructions), which influence on the degree of involvement of controlled processes and therefore prevent to really assess its functioning. In addition, manipulations of the relation between prime and target (semantic distance, type of semantic relation and strength of semantic relation) seem to influence reaction times. However, the relation between prime and target (mediated priming) frequently used could not be the most relevant relation to understand the way of spreading of activation in semantic network in patients with schizophrenia. Finally, patients with formal thought disorders present particularly high priming effects relative to controls. These abnormal semantic priming effects could reflect a dysfunction of automatic spreading activation process and consequently an exaggerated diffusion of activation in the semantic network. In the future, the inclusion of different groups schizophrenic subjects could allow us to determine whether semantic memory disorders are pathognomonic or specific of a particular group of patients with schizophrenia.

Adapting Semantic Natural Language Processing Technology to Address Information Overload in Influenza Epidemic Management

PubMed Central

Keselman, Alla; Rosemblat, Graciela; Kilicoglu, Halil; Fiszman, Marcelo; Jin, Honglan; Shin, Dongwook; Rindflesch, Thomas C.

2013-01-01

Explosion of disaster health information results in information overload among response professionals. The objective of this project was to determine the feasibility of applying semantic natural language processing (NLP) technology to addressing this overload. The project characterizes concepts and relationships commonly used in disaster health-related documents on influenza pandemics, as the basis for adapting an existing semantic summarizer to the domain. Methods include human review and semantic NLP analysis of a set of relevant documents. This is followed by a pilot-test in which two information specialists use the adapted application for a realistic information seeking task. According to the results, the ontology of influenza epidemics management can be described via a manageable number of semantic relationships that involve concepts from a limited number of semantic types. Test users demonstrate several ways to engage with the application to obtain useful information. This suggests that existing semantic NLP algorithms can be adapted to support information summarization and visualization in influenza epidemics and other disaster health areas. However, additional research is needed in the areas of terminology development (as many relevant relationships and terms are not part of existing standardized vocabularies), NLP, and user interface design. PMID:24311971

Semantic Similarity Measures for the Generation of Science Tests in Basque

ERIC Educational Resources Information Center

Aldabe, Itziar; Maritxalar, Montse

2014-01-01

The work we present in this paper aims to help teachers create multiple-choice science tests. We focus on a scientific vocabulary-learning scenario taking place in a Basque-language educational environment. In this particular scenario, we explore the option of automatically generating Multiple-Choice Questions (MCQ) by means of Natural Language…

Neuropsychological Predictors of Math Calculation and Reasoning in School-Aged Children

ERIC Educational Resources Information Center

Schneider, Dana Lynn

2012-01-01

After multiple reviews of the literature, which documented that multiple cognitive processes may be involved in mathematics ability and disability, Geary (1993) proposed a model that included three subtypes of math disability: Semantic, Procedural, and Visuospatial. A review of the extant literature produced three studies that examined Geary's…

Auditory Training with Multiple Talkers and Passage-Based Semantic Cohesion

ERIC Educational Resources Information Center

Casserly, Elizabeth D.; Barney, Erin C.

2017-01-01

Purpose: Current auditory training methods typically result in improvements to speech recognition abilities in quiet, but learner gains may not extend to other domains in speech (e.g., recognition in noise) or self-assessed benefit. This study examined the potential of training involving multiple talkers and training emphasizing discourse-level…

A Practical Methodology for the Systematic Development of Multiple Choice Tests.

ERIC Educational Resources Information Center

Blumberg, Phyllis; Felner, Joel

Using Guttman's facet design analysis, four parallel forms of a multiple-choice test were developed. A mapping sentence, logically representing the universe of content of a basic cardiology course, specified the facets of the course and the semantic structural units linking them. The facets were: cognitive processes, disease priority, specific…

Collocational Processing in Light of the Phraseological Continuum Model: Does Semantic Transparency Matter?

ERIC Educational Resources Information Center

Gyllstad, Henrik; Wolter, Brent

2016-01-01

The present study investigates whether two types of word combinations (free combinations and collocations) differ in terms of processing by testing Howarth's Continuum Model based on word combination typologies from a phraseological tradition. A visual semantic judgment task was administered to advanced Swedish learners of English (n = 27) and…

Semantic Connection or Visual Connection: Investigating the True Source of Confusion

ERIC Educational Resources Information Center

Ishii, Tomoko

2015-01-01

It has been repeatedly argued among vocabulary researchers that semantically related words should not be taught simultaneously because they can interfere with each other. However, the question of what types of relatedness cause interference has rarely been examined carefully. In addition, there are disagreements among the past studies that have…

A Left Cerebral Hemisphere's Superiority in Processing Spatial-Categorical Information in a Non-Verbal Semantic Format

ERIC Educational Resources Information Center

Suegami, Takashi; Laeng, Bruno

2013-01-01

It has been shown that the left and right cerebral hemispheres (LH and RH) respectively process qualitative or "categorical" spatial relations and metric or "coordinate" spatial relations. However, categorical spatial information could be thought as divided into two types: semantically-coded and visuospatially-coded categorical information. We…

A Schema Theory Account of Some Cognitive Processes in Complex Learning. Technical Report No. 81.

ERIC Educational Resources Information Center

Munro, Allen; Rigney, Joseph W.

Procedural semantics models have diminished the distinction between data structures and procedures in computer simulations of human intelligence. This development has theoretical consequences for models of cognition. One type of procedural semantics model, called schema theory, is presented, and a variety of cognitive processes are explained in…

Perspective: Semantic Data Management for the Home

DTIC Science & Technology

2009-02-01

stored. For example, one view might be “all files with type=music and artist= Beatles stored on Liz’s iPod” and another “all files with owner=Liz...semantic naming structures and search tech- niques from a rich history of previous work. The Seman- tic Filesystem [12] proposed the use of attribute

Medical Image Analysis by Cognitive Information Systems - a Review.

PubMed

Ogiela, Lidia; Takizawa, Makoto

2016-10-01

This publication presents a review of medical image analysis systems. The paradigms of cognitive information systems will be presented by examples of medical image analysis systems. The semantic processes present as it is applied to different types of medical images. Cognitive information systems were defined on the basis of methods for the semantic analysis and interpretation of information - medical images - applied to cognitive meaning of medical images contained in analyzed data sets. Semantic analysis was proposed to analyzed the meaning of data. Meaning is included in information, for example in medical images. Medical image analysis will be presented and discussed as they are applied to various types of medical images, presented selected human organs, with different pathologies. Those images were analyzed using different classes of cognitive information systems. Cognitive information systems dedicated to medical image analysis was also defined for the decision supporting tasks. This process is very important for example in diagnostic and therapy processes, in the selection of semantic aspects/features, from analyzed data sets. Those features allow to create a new way of analysis.

Studies on semantic priming effects in right hemisphere stroke: A systematic review

PubMed Central

Müller, Juliana de Lima; de Salles, Jerusa Fumagalli

2013-01-01

The role of the right cerebral hemisphere (RH) associated with semantic priming effects (SPEs) must be better understood, since the consequences of RH damage on SPE are not yet well established. OBJECTIVE The aim of this article was to investigate studies analyzing SPEs in patients affected by stroke in the RH through a systematic review, verifying whether there are deficits in SPEs, and whether performance varies depending on the type of semantic processing evaluated or stimulus in the task. METHODS A search was conducted on the LILACS, PUBMED and PSYCINFO databases. RESULTS Out of the initial 27 studies identified, 11 remained in the review. Difficulties in SPEs were shown in five studies. Performance does not seem to vary depending on the type of processing, but on the type of stimulus used. CONCLUSION This ability should be evaluated in individuals that have suffered a stroke in the RH in order to provide treatments that will contribute to their recovery PMID:29213834

Linking Somatic and Symbolic Representation in Semantic Memory: The Dynamic Multilevel Reactivation Framework

PubMed Central

Reilly, Jamie; Peelle, Jonathan E; Garcia, Amanda; Crutch, Sebastian J

2016-01-01

Biological plausibility is an essential constraint for any viable model of semantic memory. Yet, we have only the most rudimentary understanding of how the human brain conducts abstract symbolic transformations that underlie word and object meaning. Neuroscience has evolved a sophisticated arsenal of techniques for elucidating the architecture of conceptual representation. Nevertheless, theoretical convergence remains elusive. Here we describe several contrastive approaches to the organization of semantic knowledge, and in turn we offer our own perspective on two recurring questions in semantic memory research: 1) to what extent are conceptual representations mediated by sensorimotor knowledge (i.e., to what degree is semantic memory embodied)? 2) How might an embodied semantic system represent abstract concepts such as modularity, symbol, or proposition? To address these questions, we review the merits of sensorimotor (i.e., embodied) and amodal (i.e., disembodied) semantic theories and address the neurobiological constraints underlying each. We conclude that the shortcomings of both perspectives in their extreme forms necessitate a hybrid middle ground. We accordingly propose the Dynamic Multilevel Reactivation Framework, an integrative model premised upon flexible interplay between sensorimotor and amodal symbolic representations mediated by multiple cortical hubs. We discuss applications of the Dynamic Multilevel Reactivation Framework to abstract and concrete concept representation and describe how a multidimensional conceptual topography based on emotion, sensation, and magnitude can successfully frame a semantic space containing meanings for both abstract and concrete words. The consideration of ‘abstract conceptual features’ does not diminish the role of logical and/or executive processing in activating, manipulating and using information stored in conceptual representations. Rather, it proposes that the material on which these processes operate necessarily combine pure sensorimotor information and higher-order cognitive dimensions involved in symbolic representation. PMID:27294419

Linking somatic and symbolic representation in semantic memory: the dynamic multilevel reactivation framework.

PubMed

Reilly, Jamie; Peelle, Jonathan E; Garcia, Amanda; Crutch, Sebastian J

2016-08-01

Biological plausibility is an essential constraint for any viable model of semantic memory. Yet, we have only the most rudimentary understanding of how the human brain conducts abstract symbolic transformations that underlie word and object meaning. Neuroscience has evolved a sophisticated arsenal of techniques for elucidating the architecture of conceptual representation. Nevertheless, theoretical convergence remains elusive. Here we describe several contrastive approaches to the organization of semantic knowledge, and in turn we offer our own perspective on two recurring questions in semantic memory research: (1) to what extent are conceptual representations mediated by sensorimotor knowledge (i.e., to what degree is semantic memory embodied)? (2) How might an embodied semantic system represent abstract concepts such as modularity, symbol, or proposition? To address these questions, we review the merits of sensorimotor (i.e., embodied) and amodal (i.e., disembodied) semantic theories and address the neurobiological constraints underlying each. We conclude that the shortcomings of both perspectives in their extreme forms necessitate a hybrid middle ground. We accordingly propose the Dynamic Multilevel Reactivation Framework-an integrative model predicated upon flexible interplay between sensorimotor and amodal symbolic representations mediated by multiple cortical hubs. We discuss applications of the dynamic multilevel reactivation framework to abstract and concrete concept representation and describe how a multidimensional conceptual topography based on emotion, sensation, and magnitude can successfully frame a semantic space containing meanings for both abstract and concrete words. The consideration of 'abstract conceptual features' does not diminish the role of logical and/or executive processing in activating, manipulating and using information stored in conceptual representations. Rather, it proposes that the materials upon which these processes operate necessarily combine pure sensorimotor information and higher-order cognitive dimensions involved in symbolic representation.

Double dissociation of semantic categories in Alzheimer's disease.

PubMed

Gonnerman, L M; Andersen, E S; Devlin, J T; Kempler, D; Seidenberg, M S

1997-04-01

Data that demonstrate distinct patterns of semantic impairment in Alzheimer's disease (AD) are presented. Findings suggest that while groups of mild-moderate patients may not display category specific impairments, some individual patients do show selective impairment of either natural kinds or artifacts. We present a model of semantic organization in which category specific impairments arise from damage to distributed features underlying different types of categories. We incorporate the crucial notions of intercorrelations and distinguishing features, allowing us to demonstrate (1) how category specific impairments can result from widespread damage and (2) how selective deficits in AD reflect different points in the progression of impairment. The different patterns of impairment arise from an interaction between the nature of the semantic categories and the progression of damage.

The impact of impaired semantic knowledge on spontaneous iconic gesture production

PubMed Central

Cocks, Naomi; Dipper, Lucy; Pritchard, Madeleine; Morgan, Gary

2013-01-01

Background Previous research has found that people with aphasia produce more spontaneous iconic gesture than control participants, especially during word-finding difficulties. There is some evidence that impaired semantic knowledge impacts on the diversity of gestural handshapes, as well as the frequency of gesture production. However, no previous research has explored how impaired semantic knowledge impacts on the frequency and type of iconic gestures produced during fluent speech compared with those produced during word-finding difficulties. Aims To explore the impact of impaired semantic knowledge on the frequency and type of iconic gestures produced during fluent speech and those produced during word-finding difficulties. Methods & Procedures A group of 29 participants with aphasia and 29 control participants were video recorded describing a cartoon they had just watched. All iconic gestures were tagged and coded as either “manner,” “path only,” “shape outline” or “other”. These gestures were then separated into either those occurring during fluent speech or those occurring during a word-finding difficulty. The relationships between semantic knowledge and gesture frequency and form were then investigated in the two different conditions. Outcomes & Results As expected, the participants with aphasia produced a higher frequency of iconic gestures than the control participants, but when the iconic gestures produced during word-finding difficulties were removed from the analysis, the frequency of iconic gesture was not significantly different between the groups. While there was not a significant relationship between the frequency of iconic gestures produced during fluent speech and semantic knowledge, there was a significant positive correlation between semantic knowledge and the proportion of word-finding difficulties that contained gesture. There was also a significant positive correlation between the speakers' semantic knowledge and the proportion of gestures that were produced during fluent speech that were classified as “manner”. Finally while not significant, there was a positive trend between semantic knowledge of objects and the production of “shape outline” gestures during word-finding difficulties for objects. Conclusions The results indicate that impaired semantic knowledge in aphasia impacts on both the iconic gestures produced during fluent speech and those produced during word-finding difficulties but in different ways. These results shed new light on the relationship between impaired language and iconic co-speech gesture production and also suggest that analysis of iconic gesture may be a useful addition to clinical assessment. PMID:24058228

Semantic-JSON: a lightweight web service interface for Semantic Web contents integrating multiple life science databases

PubMed Central

Kobayashi, Norio; Ishii, Manabu; Takahashi, Satoshi; Mochizuki, Yoshiki; Matsushima, Akihiro; Toyoda, Tetsuro

2011-01-01

Global cloud frameworks for bioinformatics research databases become huge and heterogeneous; solutions face various diametric challenges comprising cross-integration, retrieval, security and openness. To address this, as of March 2011 organizations including RIKEN published 192 mammalian, plant and protein life sciences databases having 8.2 million data records, integrated as Linked Open or Private Data (LOD/LPD) using SciNetS.org, the Scientists' Networking System. The huge quantity of linked data this database integration framework covers is based on the Semantic Web, where researchers collaborate by managing metadata across public and private databases in a secured data space. This outstripped the data query capacity of existing interface tools like SPARQL. Actual research also requires specialized tools for data analysis using raw original data. To solve these challenges, in December 2009 we developed the lightweight Semantic-JSON interface to access each fragment of linked and raw life sciences data securely under the control of programming languages popularly used by bioinformaticians such as Perl and Ruby. Researchers successfully used the interface across 28 million semantic relationships for biological applications including genome design, sequence processing, inference over phenotype databases, full-text search indexing and human-readable contents like ontology and LOD tree viewers. Semantic-JSON services of SciNetS.org are provided at http://semanticjson.org. PMID:21632604

A semantic web framework to integrate cancer omics data with biological knowledge

PubMed Central

2012-01-01

Background The RDF triple provides a simple linguistic means of describing limitless types of information. Triples can be flexibly combined into a unified data source we call a semantic model. Semantic models open new possibilities for the integration of variegated biological data. We use Semantic Web technology to explicate high throughput clinical data in the context of fundamental biological knowledge. We have extended Corvus, a data warehouse which provides a uniform interface to various forms of Omics data, by providing a SPARQL endpoint. With the querying and reasoning tools made possible by the Semantic Web, we were able to explore quantitative semantic models retrieved from Corvus in the light of systematic biological knowledge. Results For this paper, we merged semantic models containing genomic, transcriptomic and epigenomic data from melanoma samples with two semantic models of functional data - one containing Gene Ontology (GO) data, the other, regulatory networks constructed from transcription factor binding information. These two semantic models were created in an ad hoc manner but support a common interface for integration with the quantitative semantic models. Such combined semantic models allow us to pose significant translational medicine questions. Here, we study the interplay between a cell's molecular state and its response to anti-cancer therapy by exploring the resistance of cancer cells to Decitabine, a demethylating agent. Conclusions We were able to generate a testable hypothesis to explain how Decitabine fights cancer - namely, that it targets apoptosis-related gene promoters predominantly in Decitabine-sensitive cell lines, thus conveying its cytotoxic effect by activating the apoptosis pathway. Our research provides a framework whereby similar hypotheses can be developed easily. PMID:22373303

A Semi-Supervised Learning Algorithm for Predicting Four Types MiRNA-Disease Associations by Mutual Information in a Heterogeneous Network.

PubMed

Zhang, Xiaotian; Yin, Jian; Zhang, Xu

2018-03-02

Increasing evidence suggests that dysregulation of microRNAs (miRNAs) may lead to a variety of diseases. Therefore, identifying disease-related miRNAs is a crucial problem. Currently, many computational approaches have been proposed to predict binary miRNA-disease associations. In this study, in order to predict underlying miRNA-disease association types, a semi-supervised model called the network-based label propagation algorithm is proposed to infer multiple types of miRNA-disease associations (NLPMMDA) by mutual information derived from the heterogeneous network. The NLPMMDA method integrates disease semantic similarity, miRNA functional similarity, and Gaussian interaction profile kernel similarity information of miRNAs and diseases to construct a heterogeneous network. NLPMMDA is a semi-supervised model which does not require verified negative samples. Leave-one-out cross validation (LOOCV) was implemented for four known types of miRNA-disease associations and demonstrated the reliable performance of our method. Moreover, case studies of lung cancer and breast cancer confirmed effective performance of NLPMMDA to predict novel miRNA-disease associations and their association types.

A Complex Network Approach to Distributional Semantic Models

PubMed Central

Utsumi, Akira

2015-01-01

A number of studies on network analysis have focused on language networks based on free word association, which reflects human lexical knowledge, and have demonstrated the small-world and scale-free properties in the word association network. Nevertheless, there have been very few attempts at applying network analysis to distributional semantic models, despite the fact that these models have been studied extensively as computational or cognitive models of human lexical knowledge. In this paper, we analyze three network properties, namely, small-world, scale-free, and hierarchical properties, of semantic networks created by distributional semantic models. We demonstrate that the created networks generally exhibit the same properties as word association networks. In particular, we show that the distribution of the number of connections in these networks follows the truncated power law, which is also observed in an association network. This indicates that distributional semantic models can provide a plausible model of lexical knowledge. Additionally, the observed differences in the network properties of various implementations of distributional semantic models are consistently explained or predicted by considering the intrinsic semantic features of a word-context matrix and the functions of matrix weighting and smoothing. Furthermore, to simulate a semantic network with the observed network properties, we propose a new growing network model based on the model of Steyvers and Tenenbaum. The idea underlying the proposed model is that both preferential and random attachments are required to reflect different types of semantic relations in network growth process. We demonstrate that this model provides a better explanation of network behaviors generated by distributional semantic models. PMID:26295940

Text Mining the History of Medicine.

PubMed

Thompson, Paul; Batista-Navarro, Riza Theresa; Kontonatsios, Georgios; Carter, Jacob; Toon, Elizabeth; McNaught, John; Timmermann, Carsten; Worboys, Michael; Ananiadou, Sophia

2016-01-01

Historical text archives constitute a rich and diverse source of information, which is becoming increasingly readily accessible, due to large-scale digitisation efforts. However, it can be difficult for researchers to explore and search such large volumes of data in an efficient manner. Text mining (TM) methods can help, through their ability to recognise various types of semantic information automatically, e.g., instances of concepts (places, medical conditions, drugs, etc.), synonyms/variant forms of concepts, and relationships holding between concepts (which drugs are used to treat which medical conditions, etc.). TM analysis allows search systems to incorporate functionality such as automatic suggestions of synonyms of user-entered query terms, exploration of different concepts mentioned within search results or isolation of documents in which concepts are related in specific ways. However, applying TM methods to historical text can be challenging, according to differences and evolutions in vocabulary, terminology, language structure and style, compared to more modern text. In this article, we present our efforts to overcome the various challenges faced in the semantic analysis of published historical medical text dating back to the mid 19th century. Firstly, we used evidence from diverse historical medical documents from different periods to develop new resources that provide accounts of the multiple, evolving ways in which concepts, their variants and relationships amongst them may be expressed. These resources were employed to support the development of a modular processing pipeline of TM tools for the robust detection of semantic information in historical medical documents with varying characteristics. We applied the pipeline to two large-scale medical document archives covering wide temporal ranges as the basis for the development of a publicly accessible semantically-oriented search system. The novel resources are available for research purposes, while the processing pipeline and its modules may be used and configured within the Argo TM platform.

Text Mining the History of Medicine

PubMed Central

Thompson, Paul; Batista-Navarro, Riza Theresa; Kontonatsios, Georgios; Carter, Jacob; Toon, Elizabeth; McNaught, John; Timmermann, Carsten; Worboys, Michael; Ananiadou, Sophia

2016-01-01

Historical text archives constitute a rich and diverse source of information, which is becoming increasingly readily accessible, due to large-scale digitisation efforts. However, it can be difficult for researchers to explore and search such large volumes of data in an efficient manner. Text mining (TM) methods can help, through their ability to recognise various types of semantic information automatically, e.g., instances of concepts (places, medical conditions, drugs, etc.), synonyms/variant forms of concepts, and relationships holding between concepts (which drugs are used to treat which medical conditions, etc.). TM analysis allows search systems to incorporate functionality such as automatic suggestions of synonyms of user-entered query terms, exploration of different concepts mentioned within search results or isolation of documents in which concepts are related in specific ways. However, applying TM methods to historical text can be challenging, according to differences and evolutions in vocabulary, terminology, language structure and style, compared to more modern text. In this article, we present our efforts to overcome the various challenges faced in the semantic analysis of published historical medical text dating back to the mid 19th century. Firstly, we used evidence from diverse historical medical documents from different periods to develop new resources that provide accounts of the multiple, evolving ways in which concepts, their variants and relationships amongst them may be expressed. These resources were employed to support the development of a modular processing pipeline of TM tools for the robust detection of semantic information in historical medical documents with varying characteristics. We applied the pipeline to two large-scale medical document archives covering wide temporal ranges as the basis for the development of a publicly accessible semantically-oriented search system. The novel resources are available for research purposes, while the processing pipeline and its modules may be used and configured within the Argo TM platform. PMID:26734936

The Effect of Pinyin Input Experience on the Link Between Semantic and Phonology of Chinese Character in Digital Writing.

PubMed

Chen, Jingjun; Luo, Rong; Liu, Huashan

2017-08-01

With the development of ICT, digital writing is becoming much more common in people's life. Differently from keyboarding alphabets directly to input English words, keyboarding Chinese character is always through typing phonetic alphabets and then identify the glyph provided by Pinyin input-method software while in this process which do not need users to produce orthography spelling, thus it is different from traditional written language production model based on handwriting process. Much of the research in this domain has found that using Pinyin input method is beneficial to Chinese characters recognition, but only a small part explored the effects of individual's Pinyin input experience on the Chinese characters production process. We ask whether using Pinyin input-method will strengthen the semantic-phonology linkage or semantic-orthography linkage in Chinese character mental lexicon. Through recording the RT and accuracy of participants completing semantic-syllable and semantic-glyph consistency judgments, the results found the accuracy of semantic-syllable consistency judgments in high Pinyin input experienced group was higher than that in low-experienced group, and RT was reversed. There were no significant differences on semantic-glyph consistency judgments between the two groups. We conclude that using Pinyin input method in Chinese digital writing can strengthen the semantic-phonology linkage while do not weakening the semantic-orthography linkage in mental lexicon at the same time, which means that Pinyin input method is beneficial to lexical processing involving Chinese cognition.

Surface errors without semantic impairment in acquired dyslexia: a voxel-based lesion–symptom mapping study

PubMed Central

Pillay, Sara B.; Humphries, Colin J.; Gross, William L.; Graves, William W.; Book, Diane S.

2016-01-01

Patients with surface dyslexia have disproportionate difficulty pronouncing irregularly spelled words (e.g. pint), suggesting impaired use of lexical-semantic information to mediate phonological retrieval. Patients with this deficit also make characteristic ‘regularization’ errors, in which an irregularly spelled word is mispronounced by incorrect application of regular spelling-sound correspondences (e.g. reading plaid as ‘played’), indicating over-reliance on sublexical grapheme–phoneme correspondences. We examined the neuroanatomical correlates of this specific error type in 45 patients with left hemisphere chronic stroke. Voxel-based lesion–symptom mapping showed a strong positive relationship between the rate of regularization errors and damage to the posterior half of the left middle temporal gyrus. Semantic deficits on tests of single-word comprehension were generally mild, and these deficits were not correlated with the rate of regularization errors. Furthermore, the deep occipital-temporal white matter locus associated with these mild semantic deficits was distinct from the lesion site associated with regularization errors. Thus, in contrast to patients with surface dyslexia and semantic impairment from anterior temporal lobe degeneration, surface errors in our patients were not related to a semantic deficit. We propose that these patients have an inability to link intact semantic representations with phonological representations. The data provide novel evidence for a post-semantic mechanism mediating the production of surface errors, and suggest that the posterior middle temporal gyrus may compute an intermediate representation linking semantics with phonology. PMID:26966139

Mandarin-Speaking Children's Speech Recognition: Developmental Changes in the Influences of Semantic Context and F0 Contours.

PubMed

Zhou, Hong; Li, Yu; Liang, Meng; Guan, Connie Qun; Zhang, Linjun; Shu, Hua; Zhang, Yang

2017-01-01

The goal of this developmental speech perception study was to assess whether and how age group modulated the influences of high-level semantic context and low-level fundamental frequency ( F 0 ) contours on the recognition of Mandarin speech by elementary and middle-school-aged children in quiet and interference backgrounds. The results revealed different patterns for semantic and F 0 information. One the one hand, age group modulated significantly the use of F 0 contours, indicating that elementary school children relied more on natural F 0 contours than middle school children during Mandarin speech recognition. On the other hand, there was no significant modulation effect of age group on semantic context, indicating that children of both age groups used semantic context to assist speech recognition to a similar extent. Furthermore, the significant modulation effect of age group on the interaction between F 0 contours and semantic context revealed that younger children could not make better use of semantic context in recognizing speech with flat F 0 contours compared with natural F 0 contours, while older children could benefit from semantic context even when natural F 0 contours were altered, thus confirming the important role of F 0 contours in Mandarin speech recognition by elementary school children. The developmental changes in the effects of high-level semantic and low-level F 0 information on speech recognition might reflect the differences in auditory and cognitive resources associated with processing of the two types of information in speech perception.

Naming unique entities in the semantic variant of primary progressive aphasia and Alzheimer's disease: Towards a better understanding of the semantic impairment.

PubMed

Montembeault, M; Brambati, S M; Joubert, S; Boukadi, M; Chapleau, M; Laforce, R Jr; Wilson, M A; Macoir, J; Rouleau, I

2017-01-27

While the semantic variant of primary progressive aphasia (svPPA) is characterized by a predominant semantic memory impairment, episodic memory impairments are the clinical hallmark of Alzheimer's disease (AD). However, AD patients also present with semantic deficits, which are more severe for semantically unique entities (e.g. a famous person) than for common concepts (e.g. a beaver). Previous studies in these patient populations have largely focused on famous-person naming. Therefore, we aimed to evaluate if these impairments also extend to other semantically unique entities such as famous places and famous logos. In this study, 13 AD patients, 9 svPPA patients, and 12 cognitively unimpaired elderly subjects (CTRL) were tested with a picture-naming test of non-unique entities (Boston Naming Test) and three experimental tests of semantically unique entities assessing naming of famous persons, places, and logos. Both clinical groups were overall more impaired at naming semantically unique entities than non-unique entities. Naming impairments in AD and svPPA extended to the other types of semantically unique entities, since a CTRL>AD>svPPA pattern was found on the performance of all naming tests. Naming famous places and famous persons appeared to be most impaired in svPPA, and both specific and general semantic knowledge for these entities were affected in these patients. Although AD patients were most significantly impaired on famous-person naming, only their specific semantic knowledge was impaired, while general knowledge was preserved. Post-hoc neuroimaging analyses also showed that famous-person naming impairments in AD correlated with atrophy in the temporo-parietal junction, a region functionally associated with lexical access. In line with previous studies, svPPA patients' impairment in both naming and semantic knowledge suggest a more profound semantic impairment, while naming impairments in AD may arise to a greater extent from impaired lexical access, even though semantic impairment for specific knowledge is also present. These results highlight the critical importance of developing and using a variety of semantically-unique-entity naming tests in neuropsychological assessments of patients with neurodegenerative diseases, which may unveil different patterns of lexical-semantic deficits. Copyright © 2016 Elsevier Ltd. All rights reserved.

Assessing the Role of Experimental Evidence for Interface Judgment: Licensing of Negative Polarity Items, Scalar Readings, and Focus

PubMed Central

Giannakidou, Anastasia; Etxeberria, Urtzi

2018-01-01

This paper reviews a series of experimental studies that address what we call “interface judgment,” which is the complex judgment involving integration from multiple levels of grammatical representation such as the syntax-semantics and prosody-semantics interface. We first discuss the results from the ERP literature connected to NPI licensing in different languages, paying particular attention to the N400 and the P600 as neural correlates of this specific phenomenon and focusing on the study by Xiang et al. (2016). The results of this study show evidence that there are two distinct NPI licensing mechanisms, i.e., licensing and rescuing, in line with Giannakidou (1998, 2006). Then we discuss an acceptability judgment task on Greek NPIs which supports the negativity as a scale hypothesis (Zwarts, 1995, 1996; Giannakidou, 1998). For the semantics-prosody interface judgment, we discuss two types of findings on two different phenomena and languages: (i) the study by Giannakidou and Yoon (2016) on scalar and non-scalar NPIs in Greek and Korean, which serves as the foundation for Chatzikonstantinou's (2016) study of production data showing distinct prosodic properties in emphatic (scalar) and non-emphatic (non-scalar) Greek NPIs; (ii) a (production and perception) study by Etxeberria and Irurtzun (2015) on the prosodic disambiguation of the scalar/non-scalar readings of sentences containing the focus particle “ere” in Basque. The main conclusion of the paper is that experimental methods of the kind discussed in the paper are useful in establishing physical, quantitative correlates of interface judgment. PMID:29515470

Neural differences between the processing of musical meaning conveyed by direction of pitch change and natural music in congenital amusia.

PubMed

Zhou, Linshu; Liu, Fang; Jing, Xiaoyi; Jiang, Cunmei

2017-02-01

Music is a unique communication system for human beings. Iconic musical meaning is one dimension of musical meaning, which emerges from musical information resembling sounds of objects, qualities of objects, or qualities of abstract concepts. The present study investigated whether congenital amusia, a disorder of musical pitch perception, impacts the processing of iconic musical meaning. With a cross-modal semantic priming paradigm, target images were primed by semantically congruent or incongruent musical excerpts, which were characterized by direction (upward or downward) of pitch change (Experiment 1), or were selected from natural music (Experiment 2). Twelve Mandarin-speaking amusics and 12 controls performed a recognition (implicit) and a semantic congruency judgment (explicit) task while their EEG waveforms were recorded. Unlike controls, amusics failed to elicit an N400 effect when musical meaning was represented by direction of pitch change, regardless of the nature of the tasks (implicit versus explicit). However, the N400 effect in response to musical meaning in natural musical excerpts was observed for both the groups in both types of tasks. These results indicate that amusics are able to process iconic musical meaning through multiple acoustic cues in natural musical excerpts, but not through the direction of pitch change. This is the first study to investigate the processing of musical meaning in congenital amusia, providing evidence in support of the "melodic contour deafness hypothesis" with regard to iconic musical meaning processing in this disorder. Copyright © 2017 Elsevier Ltd. All rights reserved.

Do Adults Show an Effect of Delayed First Language Acquisition When Calculating Scalar Implicatures?

PubMed

Davidson, Kathryn; Mayberry, Rachel I

Language acquisition involves learning not only grammatical rules and a lexicon, but also what someone is intending to convey with their utterance: the semantic/pragmatic component of language. In this paper we separate the contributions of linguistic development and cognitive maturity to the acquisition of the semantic/pragmatic component of language by comparing deaf adults who had either early or late first exposure to their first language (ASL). We focus on the particular type of meaning at the semantic/pragmatic interface called scalar implicature , for which preschool-age children typically differ from adults. Children's behavior has been attributed to either their not knowing appropriate linguistic alternatives to consider or to cognitive developmental differences between children and adults. Unlike children, deaf adults with late language exposure are cognitively mature, although they never fully acquire some complex linguistic structures, and thus serve as a test for the role of language in such interpretations. Our results indicate an overall high performance by late learners, especially when implicatures are not based on conventionalized items. However, compared to early language learners, late language learners compute fewer implicatures when conventionalized linguistic alternatives are involved (e.g. ). We conclude that (i) in general, Gricean pragmatic reasoning does not seem to be impacted by delayed first language acquisition and can account for multiple quantity implicatures, but (ii) the creation of a scale based on lexical items can lead to ease in alternative creation that may be advantageously learned early in life, and that this may be one of several factors contributing to differences between adults and children on scalar implicature tasks.

Role of Grammatical Gender and Semantics in German Word Production

ERIC Educational Resources Information Center

Vigliocco, Gabriella; Vinson, David P.; Indefrey, Peter; Levelt, Willem J. M.; Hellwig, Frauke

2004-01-01

Semantic substitution errors (e.g., saying "arm" when "leg" is intended) are among the most common types of errors occurring during spontaneous speech. It has been shown that grammatical gender of German target nouns is preserved in the errors (E. Mane, 1999). In 3 experiments, the authors explored different accounts of the grammatical gender…

"Big Brown Dog" or "Brown Big Dog?" An Electrophysiological Study of Semantic Constraints on Prenominal Adjective Order

ERIC Educational Resources Information Center

Kemmerer, David; Weber-Fox, Christine; Price, Karen; Zdanczyk, Cynthia; Way, Heather

2007-01-01

Event-related brain potentials (ERPs) were recorded while participants read and made acceptability judgments about sentences containing three types of adjective sequences: (1) normal sequences--e.g., "Jennifer rode a huge gray elephant"; (2) reversed sequences that violate grammatical-semantic constraints on linear order--e.g., *"Jennifer rode a…

Semantic Markup for Literary Scholars: How Descriptive Markup Affects the Study and Teaching of Literature.

ERIC Educational Resources Information Center

Campbell, D. Grant

2002-01-01

Describes a qualitative study which investigated the attitudes of literary scholars towards the features of semantic markup for primary texts in XML format. Suggests that layout is a vital part of the reading process which implies that the standardization of DTDs (Document Type Definitions) should extend to styling as well. (Author/LRW)

Semantic Interaction in Early and Late Bilinguals: All Words Are Not Created Equally

ERIC Educational Resources Information Center

Gathercole, Virginia C. Mueller; Moawad, Ruba Abdelmatloub

2010-01-01

This study examines L1-L2 interaction in semantic categorization in early and late L2 learners. Word categories that overlapped but were not identical in Arabic and English were tested. Words always showed a "wider" range of application in one language, "narrower" in the other. Three types of categories--"classical", "radial", and…

Semantic Categorization of Placement Verbs in L1 and L2 Danish and Spanish

ERIC Educational Resources Information Center

Cadierno, Teresa; Ibarretxe-Antuñano, Iraide; Hijazo-Gascón, Alberto

2016-01-01

This study investigates semantic categorization of the meaning of placement verbs by Danish and Spanish native speakers and two groups of intermediate second language (L2) learners (Danish learners of L2 Spanish and Spanish learners of L2 Danish). Participants described 31 video clips picturing different types of placement events. Cluster analyses…

Semantic querying of relational data for clinical intelligence: a semantic web services-based approach

PubMed Central

2013-01-01

Background Clinical Intelligence, as a research and engineering discipline, is dedicated to the development of tools for data analysis for the purposes of clinical research, surveillance, and effective health care management. Self-service ad hoc querying of clinical data is one desirable type of functionality. Since most of the data are currently stored in relational or similar form, ad hoc querying is problematic as it requires specialised technical skills and the knowledge of particular data schemas. Results A possible solution is semantic querying where the user formulates queries in terms of domain ontologies that are much easier to navigate and comprehend than data schemas. In this article, we are exploring the possibility of using SADI Semantic Web services for semantic querying of clinical data. We have developed a prototype of a semantic querying infrastructure for the surveillance of, and research on, hospital-acquired infections. Conclusions Our results suggest that SADI can support ad-hoc, self-service, semantic queries of relational data in a Clinical Intelligence context. The use of SADI compares favourably with approaches based on declarative semantic mappings from data schemas to ontologies, such as query rewriting and RDFizing by materialisation, because it can easily cope with situations when (i) some computation is required to turn relational data into RDF or OWL, e.g., to implement temporal reasoning, or (ii) integration with external data sources is necessary. PMID:23497556

When is best-worst best? A comparison of best-worst scaling, numeric estimation, and rating scales for collection of semantic norms.

PubMed

Hollis, Geoff; Westbury, Chris

2018-02-01

Large-scale semantic norms have become both prevalent and influential in recent psycholinguistic research. However, little attention has been directed towards understanding the methodological best practices of such norm collection efforts. We compared the quality of semantic norms obtained through rating scales, numeric estimation, and a less commonly used judgment format called best-worst scaling. We found that best-worst scaling usually produces norms with higher predictive validities than other response formats, and does so requiring less data to be collected overall. We also found evidence that the various response formats may be producing qualitatively, rather than just quantitatively, different data. This raises the issue of potential response format bias, which has not been addressed by previous efforts to collect semantic norms, likely because of previous reliance on a single type of response format for a single type of semantic judgment. We have made available software for creating best-worst stimuli and scoring best-worst data. We also made available new norms for age of acquisition, valence, arousal, and concreteness collected using best-worst scaling. These norms include entries for 1,040 words, of which 1,034 are also contained in the ANEW norms (Bradley & Lang, Affective norms for English words (ANEW): Instruction manual and affective ratings (pp. 1-45). Technical report C-1, the center for research in psychophysiology, University of Florida, 1999).

Parsing GML data based on integrative GML syntactic and semantic schemas database

NASA Astrophysics Data System (ADS)

Miao, Lizhi; Zhang, Shuliang; Lu, Guonian; Gao, Xiaoli; Jiao, Donglai; Gan, Jiayan

2007-06-01

This paper proposes a new method to parse various application schemas of Geography Markup Language (GML) for understanding syntax and semantic of their element and type in order to implement uniform interpretation of the same GML instance data among diverse users. The proposed method generates an Integrative GML Syntactic and Semantic Schemas Database (IGSSSDB) from GML3.1 core schemas and corresponding application schema. This paper parses GML data based on IGSSSDB, which is composed of syntactic and semantic information, nesting information and mapping rules of GML core schemas and application schemas. Three kinds of relational tables are designed for storing information from schemas when constructing IGSSSDB. Those are info tables for schemas included and namespace imported in application schemas, tables for information related to schemas and catalog tables of core schemas. In relational tables, we propose to use homologous regular expression to describe model of elements and complex types in schemas, which can ensure model complete and readable. Based on IGSSSDB, we design and develop many APIs to implement GML data parsing, and can process syntactic and semantic information of GML data from diverse fields and users. At the latter part of this paper, test study is implemented to show that the proposed method is feasible and appropriate for parsing GML data. Also, it founds a good basis for future GML data studies such as storage, index and query etc.

Quantum games as quantum types

NASA Astrophysics Data System (ADS)

Delbecque, Yannick

In this thesis, we present a new model for higher-order quantum programming languages. The proposed model is an adaptation of the probabilistic game semantics developed by Danos and Harmer [DH02]: we expand it with quantum strategies which enable one to represent quantum states and quantum operations. Some of the basic properties of these strategies are established and then used to construct denotational semantics for three quantum programming languages. The first of these languages is a formalisation of the measurement calculus proposed by Danos et al. [DKP07]. The other two are new: they are higher-order quantum programming languages. Previous attempts to define a denotational semantics for higher-order quantum programming languages have failed. We identify some of the key reasons for this and base the design of our higher-order languages on these observations. The game semantics proposed in this thesis is the first denotational semantics for a lambda-calculus equipped with quantum types and with extra operations which allow one to program quantum algorithms. The results presented validate the two different approaches used in the design of these two new higher-order languages: a first one where quantum states are used through references and a second one where they are introduced as constants in the language. The quantum strategies presented in this thesis allow one to understand the constraints that must be imposed on quantum type systems with higher-order types. The most significant constraint is the fact that abstraction over part of the tensor product of many unknown quantum states must not be allowed. Quantum strategies are a new mathematical model which describes the interaction between classical and quantum data using system-environment dialogues. The interactions between the different parts of a quantum system are described using the rich structure generated by composition of strategies. This approach has enough generality to be put in relation with other work in quantum computing. Quantum strategies could thus be useful for other purposes than the study of quantum programming languages.

Teaching graphic symbol combinations to children with limited speech during shared story reading.

PubMed

Tönsing, Kerstin M; Dada, Shakila; Alant, Erna

2014-12-01

The aim of this study was to determine the effect of an intervention strategy on the production of graphic symbol combinations in children with limited speech. Four children between the ages of 6;5 and 10;8 (years;months) with limited speech participated in the study. A single-subject, multiple probe design across three different types of semantic relations was used. Generalization to untrained exemplars was also monitored. Results were mixed across the four participants: two participants learned to combine symbols across different types of relations, maintained these skills post intervention, and generalized their skills to untrained combinations; and two participants showed less consistent evidence of learning. The effects, as measured during structured probes, were strong for one participant, moderate for another, and inconclusive for the two others. Responses during shared story reading suggested that the measurement probes might have underestimated participants' ability to combine symbols.

Centrality-based Selection of Semantic Resources for Geosciences

NASA Astrophysics Data System (ADS)

Cerba, Otakar; Jedlicka, Karel

2017-04-01

Semantical questions intervene almost in all disciplines dealing with geographic data and information, because relevant semantics is crucial for any way of communication and interaction among humans as well as among machines. But the existence of such a large number of different semantic resources (such as various thesauri, controlled vocabularies, knowledge bases or ontologies) makes the process of semantics implementation much more difficult and complicates the use of the advantages of semantics. This is because in many cases users are not able to find the most suitable resource for their purposes. The research presented in this paper introduces a methodology consisting of an analysis of identical relations in Linked Data space, which covers a majority of semantic resources, to find a suitable resource of semantic information. Identical links interconnect representations of an object or a concept in various semantic resources. Therefore this type of relations is considered to be crucial from the view of Linked Data, because these links provide new additional information, including various views on one concept based on different cultural or regional aspects (so-called social role of Linked Data). For these reasons it is possible to declare that one reasonable criterion for feasible semantic resources for almost all domains, including geosciences, is their position in a network of interconnected semantic resources and level of linking to other knowledge bases and similar products. The presented methodology is based on searching of mutual connections between various instances of one concept using "follow your nose" approach. The extracted data on interconnections between semantic resources are arranged to directed graphs and processed by various metrics patterned on centrality computing (degree, closeness or betweenness centrality). Semantic resources recommended by the research could be used for providing semantically described keywords for metadata records or as names of items in data models. Such an approach enables much more efficient data harmonization, integration, sharing and exploitation. * * * * This publication was supported by the project LO1506 of the Czech Ministry of Education, Youth and Sports. This publication was supported by project Data-Driven Bioeconomy (DataBio) from the ICT-15-2016-2017, Big Data PPP call.

Semantic definitions of space flight control center languages using the hierarchical graph technique

NASA Technical Reports Server (NTRS)

Zaghloul, M. E.; Truszkowski, W.

1981-01-01

In this paper a method is described by which the semantic definitions of the Goddard Space Flight Control Center Command Languages can be specified. The semantic modeling facility used is an extension of the hierarchical graph technique, which has a major benefit of supporting a variety of data structures and a variety of control structures. It is particularly suited for the semantic descriptions of such types of languages where the detailed separation between the underlying operating system and the command language system is system dependent. These definitions were used in the definition of the Systems Test and Operation Language (STOL) of the Goddard Space Flight Center which is a command language that provides means for the user to communicate with payloads, application programs, and other ground system elements.

Do you remember? How caregivers question their spouses who have Alzheimer's disease and the impact on communication.

PubMed

Small, Jeff A; Perry, JoAnn

2005-02-01

This study examined the types of questions caregivers use and their outcomes when conversing with their spouse with Alzheimer's disease (AD). Of particular interest was caregivers' use of yes-no and open-ended questions and the demands they make on the memory of the person with AD. It was hypothesized that communication between caregivers and their spouses would be more successful when caregivers used yes-no rather than open-ended questions; however, it was also predicted that a more positive communication outcome would occur when caregivers used open-ended questions that requested information from semantic rather than episodic memory. Eighteen caregivers and their spouses diagnosed with AD were audiotaped while they conversed for approximately 10 min on a topic of their choosing. The conversations were transcribed and coded according to the occurrence of questions, the type of question (yes-no, choice, or open-ended), the type of memory required to respond to a question (semantic or episodic), and the outcome of a response to a question (communication breakdown). The results indicated that caregivers used yes-no and open-ended questions to a similar extent, whereas episodic questions were used almost twice as frequently as semantic questions. Communication was more successful when caregivers used yes-no compared with open-ended questions and when questions placed demands on semantic rather than episodic memory. The findings from this study suggest that caregivers can reduce communication problems by avoiding the use of questions that depend on episodic memory. In addition, while yes-no questions were associated with more favorable outcomes than open-ended questions, the latter do not need to be avoided if they refer to information that draws only on semantic memory.

The role of semantic and phonological factors in word recognition: an ERP cross-modal priming study of derivational morphology.

PubMed

Kielar, Aneta; Joanisse, Marc F

2011-01-01

Theories of morphological processing differ on the issue of how lexical and grammatical information are stored and accessed. A key point of contention is whether complex forms are decomposed during recognition (e.g., establish+ment), compared to forms that cannot be analyzed into constituent morphemes (e.g., apartment). In the present study, we examined these issues with respect to English derivational morphology by measuring ERP responses during a cross-modal priming lexical decision task. ERP priming effects for semantically and phonologically transparent derived words (government-govern) were compared to those of semantically opaque derived words (apartment-apart) as well as "quasi-regular" items that represent intermediate cases of morphological transparency (dresser-dress). Additional conditions independently manipulated semantic and phonological relatedness in non-derived words (semantics: couch-sofa; phonology: panel-pan). The degree of N400 ERP priming to morphological forms varied depending on the amount of semantic and phonological overlap between word types, rather than respecting a bivariate distinction between derived and opaque forms. Moreover, these effects could not be accounted for by semantic or phonological relatedness alone. The findings support the theory that morphological relatedness is graded rather than absolute, and depend on the joint contribution of form and meaning overlap. Copyright © 2010 Elsevier Ltd. All rights reserved.

Is semantic verbal fluency impairment explained by executive function deficits in schizophrenia?

PubMed

Berberian, Arthur A; Moraes, Giovanna V; Gadelha, Ary; Brietzke, Elisa; Fonseca, Ana O; Scarpato, Bruno S; Vicente, Marcella O; Seabra, Alessandra G; Bressan, Rodrigo A; Lacerda, Acioly L

2016-04-19

To investigate if verbal fluency impairment in schizophrenia reflects executive function deficits or results from degraded semantic store or inefficient search and retrieval strategies. Two groups were compared: 141 individuals with schizophrenia and 119 healthy age and education-matched controls. Both groups performed semantic and phonetic verbal fluency tasks. Performance was evaluated using three scores, based on 1) number of words generated; 2) number of clustered/related words; and 3) switching score. A fourth performance score based on the number of clusters was also measured. SZ individuals produced fewer words than controls. After controlling for the total number of words produced, a difference was observed between the groups in the number of cluster-related words generated in the semantic task. In both groups, the number of words generated in the semantic task was higher than that generated in the phonemic task, although a significant group vs. fluency type interaction showed that subjects with schizophrenia had disproportionate semantic fluency impairment. Working memory was positively associated with increased production of words within clusters and inversely correlated with switching. Semantic fluency impairment may be attributed to an inability (resulting from reduced cognitive control) to distinguish target signal from competing noise and to maintain cues for production of memory probes.

Design and Applications of a GeoSemantic Framework for Integration of Data and Model Resources in Hydrologic Systems

NASA Astrophysics Data System (ADS)

Elag, M.; Kumar, P.

2016-12-01

Hydrologists today have to integrate resources such as data and models, which originate and reside in multiple autonomous and heterogeneous repositories over the Web. Several resource management systems have emerged within geoscience communities for sharing long-tail data, which are collected by individual or small research groups, and long-tail models, which are developed by scientists or small modeling communities. While these systems have increased the availability of resources within geoscience domains, deficiencies remain due to the heterogeneity in the methods, which are used to describe, encode, and publish information about resources over the Web. This heterogeneity limits our ability to access the right information in the right context so that it can be efficiently retrieved and understood without the Hydrologist's mediation. A primary challenge of the Web today is the lack of the semantic interoperability among the massive number of resources, which already exist and are continually being generated at rapid rates. To address this challenge, we have developed a decentralized GeoSemantic (GS) framework, which provides three sets of micro-web services to support (i) semantic annotation of resources, (ii) semantic alignment between the metadata of two resources, and (iii) semantic mediation among Standard Names. Here we present the design of the framework and demonstrate its application for semantic integration between data and models used in the IML-CZO. First we show how the IML-CZO data are annotated using the Semantic Annotation Services. Then we illustrate how the Resource Alignment Services and Knowledge Integration Services are used to create a semantic workflow among TopoFlow model, which is a spatially-distributed hydrologic model and the annotated data. Results of this work are (i) a demonstration of how the GS framework advances the integration of heterogeneous data and models of water-related disciplines by seamless handling of their semantic heterogeneity, (ii) an introduction of new paradigm for reusing existing and new standards as well as tools and models without the need of their implementation in the Cyberinfrastructures of water-related disciplines, and (iii) an investigation of a methodology by which distributed models can be coupled in a workflow using the GS services.

A case study: semantic integration of gene-disease associations for type 2 diabetes mellitus from literature and biomedical data resources.

PubMed

Rebholz-Schuhmann, Dietrich; Grabmüller, Christoph; Kavaliauskas, Silvestras; Croset, Samuel; Woollard, Peter; Backofen, Rolf; Filsell, Wendy; Clark, Dominic

2014-07-01

In the Semantic Enrichment of the Scientific Literature (SESL) project, researchers from academia and from life science and publishing companies collaborated in a pre-competitive way to integrate and share information for type 2 diabetes mellitus (T2DM) in adults. This case study exposes benefits from semantic interoperability after integrating the scientific literature with biomedical data resources, such as UniProt Knowledgebase (UniProtKB) and the Gene Expression Atlas (GXA). We annotated scientific documents in a standardized way, by applying public terminological resources for diseases and proteins, and other text-mining approaches. Eventually, we compared the genetic causes of T2DM across the data resources to demonstrate the benefits from the SESL triple store. Our solution enables publishers to distribute their content with little overhead into remote data infrastructures, such as into any Virtual Knowledge Broker. Copyright © 2013. Published by Elsevier Ltd.

Effects of saccadic bilateral eye movements on episodic and semantic autobiographical memory fluency.

PubMed

Parker, Andrew; Parkin, Adam; Dagnall, Neil

2013-01-01

Performing a sequence of fast saccadic horizontal eye movements has been shown to facilitate performance on a range of cognitive tasks, including the retrieval of episodic memories. One explanation for these effects is based on the hypothesis that saccadic eye movements increase hemispheric interaction, and that such interactions are important for particular types of memory. The aim of the current research was to assess the effect of horizontal saccadic eye movements on the retrieval of both episodic autobiographical memory (event/incident based memory) and semantic autobiographical memory (fact based memory) over recent and more distant time periods. It was found that saccadic eye movements facilitated the retrieval of episodic autobiographical memories (over all time periods) but not semantic autobiographical memories. In addition, eye movements did not enhance the retrieval of non-autobiographical semantic memory. This finding illustrates a dissociation between the episodic and semantic characteristics of personal memory and is considered within the context of hemispheric contributions to episodic memory performance.

Semantic Segmentation of Building Elements Using Point Cloud Hashing

NASA Astrophysics Data System (ADS)

Chizhova, M.; Gurianov, A.; Hess, M.; Luhmann, T.; Brunn, A.; Stilla, U.

2018-05-01

For the interpretation of point clouds, the semantic definition of extracted segments from point clouds or images is a common problem. Usually, the semantic of geometrical pre-segmented point cloud elements are determined using probabilistic networks and scene databases. The proposed semantic segmentation method is based on the psychological human interpretation of geometric objects, especially on fundamental rules of primary comprehension. Starting from these rules the buildings could be quite well and simply classified by a human operator (e.g. architect) into different building types and structural elements (dome, nave, transept etc.), including particular building parts which are visually detected. The key part of the procedure is a novel method based on hashing where point cloud projections are transformed into binary pixel representations. A segmentation approach released on the example of classical Orthodox churches is suitable for other buildings and objects characterized through a particular typology in its construction (e.g. industrial objects in standardized enviroments with strict component design allowing clear semantic modelling).

Effects of Saccadic Bilateral Eye Movements on Episodic and Semantic Autobiographical Memory Fluency

PubMed Central

Parker, Andrew; Parkin, Adam; Dagnall, Neil

2013-01-01

Performing a sequence of fast saccadic horizontal eye movements has been shown to facilitate performance on a range of cognitive tasks, including the retrieval of episodic memories. One explanation for these effects is based on the hypothesis that saccadic eye movements increase hemispheric interaction, and that such interactions are important for particular types of memory. The aim of the current research was to assess the effect of horizontal saccadic eye movements on the retrieval of both episodic autobiographical memory (event/incident based memory) and semantic autobiographical memory (fact based memory) over recent and more distant time periods. It was found that saccadic eye movements facilitated the retrieval of episodic autobiographical memories (over all time periods) but not semantic autobiographical memories. In addition, eye movements did not enhance the retrieval of non-autobiographical semantic memory. This finding illustrates a dissociation between the episodic and semantic characteristics of personal memory and is considered within the context of hemispheric contributions to episodic memory performance. PMID:24133435

Comparison of affective and semantic priming in different SOA.

PubMed

Jiang, Zhongqing; Qu, Yuhong; Xiao, Yanli; Wu, Qi; Xia, Likun; Li, Wenhui; Liu, Ying

2016-11-01

Researchers have been at odds on whether affective or semantic priming is faster or stronger. The present study selects a series of facial expression photos and words, which have definite emotional meaning or gender meaning, to set up experiment including both affective and semantic priming. The intensity of emotion and gender information in the prime as well as the strength of emotional or semantic (in gender) relationship between the prime and the target is matched. Three groups of participants are employed separately in our experiment varied with stimulus onset asynchrony (SOA) as 50, 250 or 500 ms. The results show that the difference between two types of priming effect is revealed when the SOA is at 50 ms, in which the affective priming effect is presented when the prime has negative emotion. It indicates that SOA can affect the comparison between the affective and semantic priming, and the former takes the priority in the automatic processing level.

Semantic information extracting system for classification of radiological reports in radiology information system (RIS)

NASA Astrophysics Data System (ADS)

Shi, Liehang; Ling, Tonghui; Zhang, Jianguo

2016-03-01

Radiologists currently use a variety of terminologies and standards in most hospitals in China, and even there are multiple terminologies being used for different sections in one department. In this presentation, we introduce a medical semantic comprehension system (MedSCS) to extract semantic information about clinical findings and conclusion from free text radiology reports so that the reports can be classified correctly based on medical terms indexing standards such as Radlex or SONMED-CT. Our system (MedSCS) is based on both rule-based methods and statistics-based methods which improve the performance and the scalability of MedSCS. In order to evaluate the over all of the system and measure the accuracy of the outcomes, we developed computation methods to calculate the parameters of precision rate, recall rate, F-score and exact confidence interval.

The interplay of episodic and semantic memory in guiding repeated search in scenes.

PubMed

Võ, Melissa L-H; Wolfe, Jeremy M

2013-02-01

It seems intuitive to think that previous exposure or interaction with an environment should make it easier to search through it and, no doubt, this is true in many real-world situations. However, in a recent study, we demonstrated that previous exposure to a scene does not necessarily speed search within that scene. For instance, when observers performed as many as 15 searches for different objects in the same, unchanging scene, the speed of search did not decrease much over the course of these multiple searches (Võ & Wolfe, 2012). Only when observers were asked to search for the same object again did search become considerably faster. We argued that our naturalistic scenes provided such strong "semantic" guidance-e.g., knowing that a faucet is usually located near a sink-that guidance by incidental episodic memory-having seen that faucet previously-was rendered less useful. Here, we directly manipulated the availability of semantic information provided by a scene. By monitoring observers' eye movements, we found a tight coupling of semantic and episodic memory guidance: Decreasing the availability of semantic information increases the use of episodic memory to guide search. These findings have broad implications regarding the use of memory during search in general and particularly during search in naturalistic scenes. Copyright © 2012 Elsevier B.V. All rights reserved.

Unitary vs multiple semantics: PET studies of word and picture processing.

PubMed

Bright, P; Moss, H; Tyler, L K

2004-06-01

In this paper we examine a central issue in cognitive neuroscience: are there separate conceptual representations associated with different input modalities (e.g., Paivio, 1971, 1986; Warrington & Shallice, 1984) or do inputs from different modalities converge on to the same set of representations (e.g., Caramazza, Hillis, Rapp, & Romani, 1990; Lambon Ralph, Graham, Patterson, & Hodges, 1999; Rapp, Hillis, & Caramazza, 1993)? We present an analysis of four PET studies (three semantic categorisation tasks and one lexical decision task), two of which employ words as stimuli and two of which employ pictures. Using conjunction analyses, we found robust semantic activation, common to both input modalities in anterior and medial aspects of the left fusiform gyrus, left parahippocampal and perirhinal cortices, and left inferior frontal gyrus (BA 47). There were modality-specific activations in both temporal poles (words) and occipitotemporal cortices (pictures). We propose that the temporal poles are involved in processing both words and pictures, but their engagement might be primarily determined by the level of specificity at which an object is processed. Activation in posterior temporal regions associated with picture processing most likely reflects intermediate, pre-semantic stages of visual processing. Our data are most consistent with a hierarchically structured, unitary system of semantic representations for both verbal and visual modalities, subserved by anterior regions of the inferior temporal cortex.

Dynamic information processing states revealed through neurocognitive models of object semantics

PubMed Central

Clarke, Alex

2015-01-01

Recognising objects relies on highly dynamic, interactive brain networks to process multiple aspects of object information. To fully understand how different forms of information about objects are represented and processed in the brain requires a neurocognitive account of visual object recognition that combines a detailed cognitive model of semantic knowledge with a neurobiological model of visual object processing. Here we ask how specific cognitive factors are instantiated in our mental processes and how they dynamically evolve over time. We suggest that coarse semantic information, based on generic shared semantic knowledge, is rapidly extracted from visual inputs and is sufficient to drive rapid category decisions. Subsequent recurrent neural activity between the anterior temporal lobe and posterior fusiform supports the formation of object-specific semantic representations – a conjunctive process primarily driven by the perirhinal cortex. These object-specific representations require the integration of shared and distinguishing object properties and support the unique recognition of objects. We conclude that a valuable way of understanding the cognitive activity of the brain is though testing the relationship between specific cognitive measures and dynamic neural activity. This kind of approach allows us to move towards uncovering the information processing states of the brain and how they evolve over time. PMID:25745632

What we talk about when we talk about access deficits

PubMed Central

Mirman, Daniel; Britt, Allison E.

2014-01-01

Semantic impairments have been divided into storage deficits, in which the semantic representations themselves are damaged, and access deficits, in which the representations are intact but access to them is impaired. The behavioural phenomena that have been associated with access deficits include sensitivity to cueing, sensitivity to presentation rate, performance inconsistency, negative serial position effects, sensitivity to number and strength of competitors, semantic blocking effects, disordered selection between strong and weak competitors, correlation between semantic deficits and executive function deficits and reduced word frequency effects. Four general accounts have been proposed for different subsets of these phenomena: abnormal refractoriness, too much activation, impaired competitive selection and deficits of semantic control. A combination of abnormal refractoriness and impaired competitive selection can account for most of the behavioural phenomena, but there remain several open questions. In particular, it remains unclear whether access deficits represent a single syndrome, a syndrome with multiple subtypes or a variable collection of phenomena, whether the underlying deficit is domain-general or domain-specific, whether it is owing to disorders of inhibition, activation or selection, and the nature of the connection (if any) between access phenomena in aphasia and in neurologically intact controls. Computational models offer a promising approach to answering these questions. PMID:24324232

Listening to accented speech in a second language: First language and age of acquisition effects.

PubMed

Larraza, Saioa; Samuel, Arthur G; Oñederra, Miren Lourdes

2016-11-01

Bilingual speakers must acquire the phonemic inventory of 2 languages and need to recognize spoken words cross-linguistically; a demanding job potentially made even more difficult due to dialectal variation, an intrinsic property of speech. The present work examines how bilinguals perceive second language (L2) accented speech and where accommodation to dialectal variation takes place. Dialectal effects were analyzed at different levels: An AXB discrimination task tapped phonetic-phonological representations, an auditory lexical-decision task tested for effects in accessing the lexicon, and an auditory priming task looked for semantic processing effects. Within that central focus, the goal was to see whether perceptual adjustment at a given level is affected by 2 main linguistic factors: bilinguals' first language and age of acquisition of the L2. Taking advantage of the cross-linguistic situation of the Basque language, bilinguals with different first languages (Spanish or French) and ages of acquisition of Basque (simultaneous, early, or late) were tested. Our use of multiple tasks with multiple types of bilinguals demonstrates that in spite of very similar discrimination capacity, French-Basque versus Spanish-Basque simultaneous bilinguals' performance on lexical access significantly differed. Similarly, results of the early and late groups show that the mapping of phonetic-phonological information onto lexical representations is a more demanding process that accentuates non-native processing difficulties. L1 and AoA effects were more readily overcome in semantic processing; accented variants regularly created priming effects in the different groups of bilinguals. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks

PubMed Central

Meng, Qinggang; Deng, Su; Huang, Hongbin; Wu, Yahui; Badii, Atta

2017-01-01

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic. PMID:28245222

Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks.

PubMed

Wu, Jibing; Meng, Qinggang; Deng, Su; Huang, Hongbin; Wu, Yahui; Badii, Atta

2017-01-01

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic.

Developmental changes in the neural influence of sublexical information on semantic processing.

PubMed

Lee, Shu-Hui; Booth, James R; Chou, Tai-Li

2015-07-01

Functional magnetic resonance imaging (fMRI) was used to examine the developmental changes in a group of normally developing children (aged 8-12) and adolescents (aged 13-16) during semantic processing. We manipulated association strength (i.e. a global reading unit) and semantic radical (i.e. a local reading unit) to explore the interaction of lexical and sublexical semantic information in making semantic judgments. In the semantic judgment task, two types of stimuli were used: visually-similar (i.e. shared a semantic radical) versus visually-dissimilar (i.e. did not share a semantic radical) character pairs. Participants were asked to indicate if two Chinese characters, arranged according to association strength, were related in meaning. The results showed greater developmental increases in activation in left angular gyrus (BA 39) in the visually-similar compared to the visually-dissimilar pairs for the strong association. There were also greater age-related increases in angular gyrus for the strong compared to weak association in the visually-similar pairs. Both of these results suggest that shared semantics at the sublexical level facilitates the integration of overlapping features at the lexical level in older children. In addition, there was a larger developmental increase in left posterior middle temporal gyrus (BA 21) for the weak compared to strong association in the visually-dissimilar pairs, suggesting conflicting sublexical information placed greater demands on access to lexical representations in the older children. All together, these results suggest that older children are more sensitive to sublexical information when processing lexical representations. Copyright © 2015 Elsevier Ltd. All rights reserved.

Research in Knowledge Representation for Natural Language Understanding.

DTIC Science & Technology

1984-09-01

TYPE OF REPORT & PERIOO COVERED RESEARCH IN KNOWLEDGE REPRESENTATION Annual Report FOR NATURAL LANGUAGE UNDERSTANDING 9/1/83 - 8/31/84 S. PERFORMING...nhaber) Artificial intelligence, natural language understanding , knowledge representation, semantics, semantic networks, KL-TWO, NIKL, belief and...attempting to understand and react to a complex, evolving situation. This report summarizes our research in knowledge representation and natural language

Retrograde Amnesia for Episodic and Semantic Memories in Amnestic Mild Cognitive Impairment.

PubMed

De Simone, Maria Stefania; Fadda, Lucia; Perri, Roberta; De Tollis, Massimo; Aloisi, Marta; Caltagirone, Carlo; Carlesimo, Giovanni Augusto

2017-01-01

Retrograde amnesia (RA), which includes loss of memory for past personal events (autobiographical RA) and for acquired knowledge (semantic RA), has been largely documented in patients with amnestic mild cognitive impairment (aMCI). However, previous studies have produced controversial results particularly concerning the temporal extent of memory impairment. Here we investigated whether, with the onset of hippocampal pathology, age of memory acquisition and retrieval frequency play different roles in modulating the progressive loss of semantic and episodic contents of retrograde memory respectively. For this purpose, aMCI patients and healthy controls were tested for the ability to recall semantic and autobiographical information related to famous public events as a function of both age of acquisition and retrieval frequency. In aMCI patients, we found that the impairment in recollecting past personal incidents was modulated by the combined action of memory age and retrieval frequency, because older and more frequently retrieved episodes are less susceptible to loss than more recent and less frequently retrieved ones. On the other side, we found that the loss of semantic information depended only on memory age, because the remoteness of the trace allows for better preservation of the memory. Our results provide evidence that the loss of the two components of retrograde memory is regulated by different mechanisms. This supports the view that diverse neural mechanisms are involved in episodic and semantic memory trace storage and retrieval, as postulated by the Multiple Trace Theory.

Semantic Mappings and Locality of Nursing Diagnostic Concepts in UMLS

PubMed Central

Kim, Tae Youn; Coenen, Amy; Hardiker, Nicholas

2011-01-01

One solution for enhancing the interoperability between nursing information systems, given the availability of multiple nursing terminologies, is to cross-map existing nursing concepts. The Unified Medical Language System (UMLS) developed and distributed by the National Library of Medicine (NLM) is a knowledge resource containing cross-mappings of various terminologies in a unified framework. While the knowledge resource has been available for the last two decades, little research on the representation of nursing terminologies in UMLS has been conducted. As a first step, UMLS semantic mappings and concept locality were examined for nursing diagnostic concepts or problems selected from three terminologies (i.e., CCC, ICNP, and NANDA-I) along with corresponding SNOMED CT concepts. The evaluation of UMLS semantic mappings was conducted by measuring the proportion of concordance between UMLS and human expert mappings. The semantic locality of nursing diagnostic concepts was assessed by examining the associations of select concepts and the placement of the nursing concepts on the Semantic Network and Group. The study found that the UMLS mappings of CCC and NANDA-I concepts to SNOMED CT were highly concordant to expert mappings. The level of concordance in mappings of ICNP to SNOMED CT, CCC and NANDA-I within UMLS was relatively low, indicating the need for further research and development. Likewise, the semantic locality of ICNP concepts could be further improved. Various stakeholders need to collaborate to enhance the NLM knowledge resource and the interoperability of nursing data within the discipline as well as across health-related disciplines. PMID:21951759

Semantic-syntactic partial word knowledge growth through reading.

PubMed

Wagovich, Stacy A; Hill, Margaret S; Petroski, Gregory F

2015-02-01

Incidental reading provides a powerful opportunity for partial word knowledge growth in the school-age years. The extent to which children of differing language abilities can use reading experiences to glean partial knowledge of words is not well understood. The purpose of this study was to compare semantic-syntactic partial word knowledge growth of children with higher language skills (HL group; overall language standard scores of 85 or higher) to that of children with relatively lower language skills (LL group; overall receptive or expressive standard score below 85). Thirty-two children, 16 per group, silently read stories containing unfamiliar nouns and verbs 3 times over a 1-week period. Semantic-syntactic partial word knowledge growth was assessed after each reading and 2-3 days later to assess retention. Over time, both groups showed significant partial word knowledge growth, with the HL group showing significantly more growth. In addition, both groups retained knowledge several days later. Regardless of language skill level, children benefit from multiple exposures to unfamiliar words in reading in their development and retention of semantic-syntactic partial word knowledge growth.

Anterograde and retrograde amnesia in a person with bilateral fornix lesions following removal of a colloid cyst.

PubMed

Poreh, Amir; Winocur, Gordon; Moscovitch, Morris; Backon, Matti; Goshen, Elinor; Ram, Zvi; Feldman, Zeev

2006-01-01

AD, a 45-year-old man, presented with a severe and global anterograde amnesia following surgery for removal of a colloid cyst. Structural neuroimaging confirmed bilateral lesions to the fornix and a small lesion in the basal forebrain. Testing for remote episodic memory of autobiographical events, and for remote semantic memory of personal and public events, and of famous people, revealed that AD had a severe retrograde amnesia for autobiographical episodes that covered his entire lifetime, and a time-limited retrograde amnesia for semantic memory. Because the fornix and basal forebrain lesions disrupted major afferent and efferent pathways of the hippocampus, it was concluded that the integrity of the hippocampus and its projections are needed to retain and/or recover autobiographical memories no matter how old they are. By contrast, hippocampal contribution to semantic memory is time-limited. These findings were interpreted as consistent with Multiple Trace Theory, which holds that the hippocampal system is essential for recovering contextually rich memories no matter how old they are, but is not needed for recovering semantic memories.

A Semantic Sensor Web for Environmental Decision Support Applications

PubMed Central

Gray, Alasdair J. G.; Sadler, Jason; Kit, Oles; Kyzirakos, Kostis; Karpathiotakis, Manos; Calbimonte, Jean-Paul; Page, Kevin; García-Castro, Raúl; Frazer, Alex; Galpin, Ixent; Fernandes, Alvaro A. A.; Paton, Norman W.; Corcho, Oscar; Koubarakis, Manolis; De Roure, David; Martinez, Kirk; Gómez-Pérez, Asunción

2011-01-01

Sensing devices are increasingly being deployed to monitor the physical world around us. One class of application for which sensor data is pertinent is environmental decision support systems, e.g., flood emergency response. For these applications, the sensor readings need to be put in context by integrating them with other sources of data about the surrounding environment. Traditional systems for predicting and detecting floods rely on methods that need significant human resources. In this paper we describe a semantic sensor web architecture for integrating multiple heterogeneous datasets, including live and historic sensor data, databases, and map layers. The architecture provides mechanisms for discovering datasets, defining integrated views over them, continuously receiving data in real-time, and visualising on screen and interacting with the data. Our approach makes extensive use of web service standards for querying and accessing data, and semantic technologies to discover and integrate datasets. We demonstrate the use of our semantic sensor web architecture in the context of a flood response planning web application that uses data from sensor networks monitoring the sea-state around the coast of England. PMID:22164110

Semantic Interoperability Almost Without Using The Same Vocabulary: Is It Possible?

NASA Astrophysics Data System (ADS)

Krisnadhi, A. A.

2016-12-01

Semantic interoperability, which is a key requirement in realizing cross-repository data integration, is often understood as using the same ontology or vocabulary. Consequently, within a particular domain, one can easily assume that there has to be one unifying domain ontology covering as many vocabulary terms in the domain as possible in order to realize any form of data integration across multiple data sources. Furthermore, the desire to provide very precise definition of those many terms led to the development of huge, foundational and domain ontologies that are comprehensive, but too complicated, restrictive, monolithic, and difficult to use and reuse, which cause common data providers to avoid using them. This problem is especially true in a domain as diverse as geosciences as it is virtually impossible to reach an agreement to the semantics of many terms (e.g., there are hundreds of definitions of forest used throughout the world). To overcome this challenge, modular ontology architecture has emerged in recent years, fueled among others, by advances in the ontology design pattern research. Each ontology pattern models only one key notion. It can act as a small module of a larger ontology. Such a module is developed in such a way that it is largely independent of how other notions in the same domain are modeled. This leads to an increased reusability. Furthermore, an ontology formed out of such modules would have an improved understandability over large, monolithic ontologies. Semantic interoperability in the aforementioned architecture is not achieved by enforcing the use of the same vocabulary, but rather, promoting alignment to the same ontology patterns. In this work, we elaborate how this architecture realizes the above idea. In particular, we describe how multiple data sources with differing perspectives and vocabularies can interoperate through this architecture. Building the solution upon semantic technologies such as Linked Data and the Web Ontology Language (OWL), we demonstrate how a data integration solution based on this idea can be realized over different data repositories.

Spatio-Semantic Comparison of Large 3d City Models in Citygml Using a Graph Database

NASA Astrophysics Data System (ADS)

Nguyen, S. H.; Yao, Z.; Kolbe, T. H.

2017-10-01

A city may have multiple CityGML documents recorded at different times or surveyed by different users. To analyse the city's evolution over a given period of time, as well as to update or edit the city model without negating modifications made by other users, it is of utmost importance to first compare, detect and locate spatio-semantic changes between CityGML datasets. This is however difficult due to the fact that CityGML elements belong to a complex hierarchical structure containing multi-level deep associations, which can basically be considered as a graph. Moreover, CityGML allows multiple syntactic ways to define an object leading to syntactic ambiguities in the exchange format. Furthermore, CityGML is capable of including not only 3D urban objects' graphical appearances but also their semantic properties. Since to date, no known algorithm is capable of detecting spatio-semantic changes in CityGML documents, a frequent approach is to replace the older models completely with the newer ones, which not only costs computational resources, but also loses track of collaborative and chronological changes. Thus, this research proposes an approach capable of comparing two arbitrarily large-sized CityGML documents on both semantic and geometric level. Detected deviations are then attached to their respective sources and can easily be retrieved on demand. As a result, updating a 3D city model using this approach is much more efficient as only real changes are committed. To achieve this, the research employs a graph database as the main data structure for storing and processing CityGML datasets in three major steps: mapping, matching and updating. The mapping process transforms input CityGML documents into respective graph representations. The matching process compares these graphs and attaches edit operations on the fly. Found changes can then be executed using the Web Feature Service (WFS), the standard interface for updating geographical features across the web.

Using a high-dimensional graph of semantic space to model relationships among words

PubMed Central

Jackson, Alice F.; Bolger, Donald J.

2014-01-01

The GOLD model (Graph Of Language Distribution) is a network model constructed based on co-occurrence in a large corpus of natural language that may be used to explore what information may be present in a graph-structured model of language, and what information may be extracted through theoretically-driven algorithms as well as standard graph analysis methods. The present study will employ GOLD to examine two types of relationship between words: semantic similarity and associative relatedness. Semantic similarity refers to the degree of overlap in meaning between words, while associative relatedness refers to the degree to which two words occur in the same schematic context. It is expected that a graph structured model of language constructed based on co-occurrence should easily capture associative relatedness, because this type of relationship is thought to be present directly in lexical co-occurrence. However, it is hypothesized that semantic similarity may be extracted from the intersection of the set of first-order connections, because two words that are semantically similar may occupy similar thematic or syntactic roles across contexts and thus would co-occur lexically with the same set of nodes. Two versions the GOLD model that differed in terms of the co-occurence window, bigGOLD at the paragraph level and smallGOLD at the adjacent word level, were directly compared to the performance of a well-established distributional model, Latent Semantic Analysis (LSA). The superior performance of the GOLD models (big and small) suggest that a single acquisition and storage mechanism, namely co-occurrence, can account for associative and conceptual relationships between words and is more psychologically plausible than models using singular value decomposition (SVD). PMID:24860525

Using a high-dimensional graph of semantic space to model relationships among words.

PubMed

Jackson, Alice F; Bolger, Donald J

2014-01-01

The GOLD model (Graph Of Language Distribution) is a network model constructed based on co-occurrence in a large corpus of natural language that may be used to explore what information may be present in a graph-structured model of language, and what information may be extracted through theoretically-driven algorithms as well as standard graph analysis methods. The present study will employ GOLD to examine two types of relationship between words: semantic similarity and associative relatedness. Semantic similarity refers to the degree of overlap in meaning between words, while associative relatedness refers to the degree to which two words occur in the same schematic context. It is expected that a graph structured model of language constructed based on co-occurrence should easily capture associative relatedness, because this type of relationship is thought to be present directly in lexical co-occurrence. However, it is hypothesized that semantic similarity may be extracted from the intersection of the set of first-order connections, because two words that are semantically similar may occupy similar thematic or syntactic roles across contexts and thus would co-occur lexically with the same set of nodes. Two versions the GOLD model that differed in terms of the co-occurence window, bigGOLD at the paragraph level and smallGOLD at the adjacent word level, were directly compared to the performance of a well-established distributional model, Latent Semantic Analysis (LSA). The superior performance of the GOLD models (big and small) suggest that a single acquisition and storage mechanism, namely co-occurrence, can account for associative and conceptual relationships between words and is more psychologically plausible than models using singular value decomposition (SVD).

Closed-Loop Lifecycle Management of Service and Product in the Internet of Things: Semantic Framework for Knowledge Integration.

PubMed

Yoo, Min-Jung; Grozel, Clément; Kiritsis, Dimitris

2016-07-08

This paper describes our conceptual framework of closed-loop lifecycle information sharing for product-service in the Internet of Things (IoT). The framework is based on the ontology model of product-service and a type of IoT message standard, Open Messaging Interface (O-MI) and Open Data Format (O-DF), which ensures data communication. (1) BACKGROUND: Based on an existing product lifecycle management (PLM) methodology, we enhanced the ontology model for the purpose of integrating efficiently the product-service ontology model that was newly developed; (2) METHODS: The IoT message transfer layer is vertically integrated into a semantic knowledge framework inside which a Semantic Info-Node Agent (SINA) uses the message format as a common protocol of product-service lifecycle data transfer; (3) RESULTS: The product-service ontology model facilitates information retrieval and knowledge extraction during the product lifecycle, while making more information available for the sake of service business creation. The vertical integration of IoT message transfer, encompassing all semantic layers, helps achieve a more flexible and modular approach to knowledge sharing in an IoT environment; (4) Contribution: A semantic data annotation applied to IoT can contribute to enhancing collected data types, which entails a richer knowledge extraction. The ontology-based PLM model enables as well the horizontal integration of heterogeneous PLM data while breaking traditional vertical information silos; (5) CONCLUSION: The framework was applied to a fictive case study with an electric car service for the purpose of demonstration. For the purpose of demonstrating the feasibility of the approach, the semantic model is implemented in Sesame APIs, which play the role of an Internet-connected Resource Description Framework (RDF) database.

Closed-Loop Lifecycle Management of Service and Product in the Internet of Things: Semantic Framework for Knowledge Integration

PubMed Central

Yoo, Min-Jung; Grozel, Clément; Kiritsis, Dimitris

2016-01-01

This paper describes our conceptual framework of closed-loop lifecycle information sharing for product-service in the Internet of Things (IoT). The framework is based on the ontology model of product-service and a type of IoT message standard, Open Messaging Interface (O-MI) and Open Data Format (O-DF), which ensures data communication. (1) Background: Based on an existing product lifecycle management (PLM) methodology, we enhanced the ontology model for the purpose of integrating efficiently the product-service ontology model that was newly developed; (2) Methods: The IoT message transfer layer is vertically integrated into a semantic knowledge framework inside which a Semantic Info-Node Agent (SINA) uses the message format as a common protocol of product-service lifecycle data transfer; (3) Results: The product-service ontology model facilitates information retrieval and knowledge extraction during the product lifecycle, while making more information available for the sake of service business creation. The vertical integration of IoT message transfer, encompassing all semantic layers, helps achieve a more flexible and modular approach to knowledge sharing in an IoT environment; (4) Contribution: A semantic data annotation applied to IoT can contribute to enhancing collected data types, which entails a richer knowledge extraction. The ontology-based PLM model enables as well the horizontal integration of heterogeneous PLM data while breaking traditional vertical information silos; (5) Conclusion: The framework was applied to a fictive case study with an electric car service for the purpose of demonstration. For the purpose of demonstrating the feasibility of the approach, the semantic model is implemented in Sesame APIs, which play the role of an Internet-connected Resource Description Framework (RDF) database. PMID:27399717

A PDP model of the simultaneous perception of multiple objects

NASA Astrophysics Data System (ADS)

Henderson, Cynthia M.; McClelland, James L.

2011-06-01

Illusory conjunctions in normal and simultanagnosic subjects are two instances where the visual features of multiple objects are incorrectly 'bound' together. A connectionist model explores how multiple objects could be perceived correctly in normal subjects given sufficient time, but could give rise to illusory conjunctions with damage or time pressure. In this model, perception of two objects benefits from lateral connections between hidden layers modelling aspects of the ventral and dorsal visual pathways. As with simultanagnosia, simulations of dorsal lesions impair multi-object recognition. In contrast, a large ventral lesion has minimal effect on dorsal functioning, akin to dissociations between simple object manipulation (retained in visual form agnosia and semantic dementia) and object discrimination (impaired in these disorders) [Hodges, J.R., Bozeat, S., Lambon Ralph, M.A., Patterson, K., and Spatt, J. (2000), 'The Role of Conceptual Knowledge: Evidence from Semantic Dementia', Brain, 123, 1913-1925; Milner, A.D., and Goodale, M.A. (2006), The Visual Brain in Action (2nd ed.), New York: Oxford]. It is hoped that the functioning of this model might suggest potential processes underlying dorsal and ventral contributions to the correct perception of multiple objects.

Similar autobiographical memory impairment in long-term secondary progressive multiple sclerosis and Alzheimer's disease.

PubMed

Müller, S; Saur, R; Greve, B; Melms, A; Hautzinger, M; Fallgatter, A J; Leyhe, T

2013-02-01

Memory disturbance is a common symptom of multiple sclerosis (MS), but little is known about autobiographical memory deficits in the long-term course of different MS subtypes. Inflammatory activity and demyelination is pronounced in relapsing-remitting multiple sclerosis (RRMS) whereas, similar to Alzheimer's disease, neurodegeneration affecting autobiographical memory-associated areas is seen in secondary progressive multiple sclerosis (SPMS). In light of distinct disease mechanisms, we evaluated autobiographical memory in different MS subtypes and hypothesized similarities between elderly patients with SPMS and Alzheimer's disease. We used the Autobiographical Memory Interview to assess episodic and semantic autobiographical memory in 112 education- and gender-matched participants, including healthy controls and patients with RRMS, SPMS, amnesic mild cognitive impairment (aMCI) and early Alzheimer's dementia (AD). Patients with SPMS, AD, and aMCI, but not with RRMS, exhibited a pattern of episodic autobiographical memory impairment that followed Ribot's Law; older memories were better preserved than more recent memories. In contrast to aMCI and AD, neither SPMS nor RRMS was associated with semantic autobiographical memory impairment. Our neuropsychological findings suggest that episodic autobiographical memory is affected in long-term patients with SPMS, possibly due to neurodegenerative processes in functional relevant brain regions.

Autobiographically significant concepts: more episodic than semantic in nature? An electrophysiological investigation of overlapping types of memory.

PubMed

Renoult, Louis; Davidson, Patrick S R; Schmitz, Erika; Park, Lillian; Campbell, Kenneth; Moscovitch, Morris; Levine, Brian

2015-01-01

A common assertion is that semantic memory emerges from episodic memory, shedding the distinctive contexts associated with episodes over time and/or repeated instances. Some semantic concepts, however, may retain their episodic origins or acquire episodic information during life experiences. The current study examined this hypothesis by investigating the ERP correlates of autobiographically significant (AS) concepts, that is, semantic concepts that are associated with vivid episodic memories. We inferred the contribution of semantic and episodic memory to AS concepts using the amplitudes of the N400 and late positive component, respectively. We compared famous names that easily brought to mind episodic memories (high AS names) against equally famous names that did not bring such recollections to mind (low AS names) on a semantic task (fame judgment) and an episodic task (recognition memory). Compared with low AS names, high AS names were associated with increased amplitude of the late positive component in both tasks. Moreover, in the recognition task, this effect of AS was highly correlated with recognition confidence. In contrast, the N400 component did not differentiate the high versus low AS names but, instead, was related to the amount of general knowledge participants had regarding each name. These results suggest that semantic concepts high in AS, such as famous names, have an episodic component and are associated with similar brain processes to those that are engaged by episodic memory. Studying AS concepts may provide unique insights into how episodic and semantic memory interact.

Effects of Semantic Context and Fundamental Frequency Contours on Mandarin Speech Recognition by Second Language Learners.

PubMed

Zhang, Linjun; Li, Yu; Wu, Han; Li, Xin; Shu, Hua; Zhang, Yang; Li, Ping

2016-01-01

Speech recognition by second language (L2) learners in optimal and suboptimal conditions has been examined extensively with English as the target language in most previous studies. This study extended existing experimental protocols (Wang et al., 2013) to investigate Mandarin speech recognition by Japanese learners of Mandarin at two different levels (elementary vs. intermediate) of proficiency. The overall results showed that in addition to L2 proficiency, semantic context, F0 contours, and listening condition all affected the recognition performance on the Mandarin sentences. However, the effects of semantic context and F0 contours on L2 speech recognition diverged to some extent. Specifically, there was significant modulation effect of listening condition on semantic context, indicating that L2 learners made use of semantic context less efficiently in the interfering background than in quiet. In contrast, no significant modulation effect of listening condition on F0 contours was found. Furthermore, there was significant interaction between semantic context and F0 contours, indicating that semantic context becomes more important for L2 speech recognition when F0 information is degraded. None of these effects were found to be modulated by L2 proficiency. The discrepancy in the effects of semantic context and F0 contours on L2 speech recognition in the interfering background might be related to differences in processing capacities required by the two types of information in adverse listening conditions.

Interoperable cross-domain semantic and geospatial framework for automatic change detection

NASA Astrophysics Data System (ADS)

Kuo, Chiao-Ling; Hong, Jung-Hong

2016-01-01

With the increasingly diverse types of geospatial data established over the last few decades, semantic interoperability in integrated applications has attracted much interest in the field of Geographic Information System (GIS). This paper proposes a new strategy and framework to process cross-domain geodata at the semantic level. This framework leverages the semantic equivalence of concepts between domains through bridge ontology and facilitates the integrated use of different domain data, which has been long considered as an essential superiority of GIS, but is impeded by the lack of understanding about the semantics implicitly hidden in the data. We choose the task of change detection to demonstrate how the introduction of ontology concept can effectively make the integration possible. We analyze the common properties of geodata and change detection factors, then construct rules and summarize possible change scenario for making final decisions. The use of topographic map data to detect changes in land use shows promising success, as far as the improvement of efficiency and level of automation is concerned. We believe the ontology-oriented approach will enable a new way for data integration across different domains from the perspective of semantic interoperability, and even open a new dimensionality for the future GIS.

SCALEUS: Semantic Web Services Integration for Biomedical Applications.

PubMed

Sernadela, Pedro; González-Castro, Lorena; Oliveira, José Luís

2017-04-01

In recent years, we have witnessed an explosion of biological data resulting largely from the demands of life science research. The vast majority of these data are freely available via diverse bioinformatics platforms, including relational databases and conventional keyword search applications. This type of approach has achieved great results in the last few years, but proved to be unfeasible when information needs to be combined or shared among different and scattered sources. During recent years, many of these data distribution challenges have been solved with the adoption of semantic web. Despite the evident benefits of this technology, its adoption introduced new challenges related with the migration process, from existent systems to the semantic level. To facilitate this transition, we have developed Scaleus, a semantic web migration tool that can be deployed on top of traditional systems in order to bring knowledge, inference rules, and query federation to the existent data. Targeted at the biomedical domain, this web-based platform offers, in a single package, straightforward data integration and semantic web services that help developers and researchers in the creation process of new semantically enhanced information systems. SCALEUS is available as open source at http://bioinformatics-ua.github.io/scaleus/ .

The Nature and Neural Correlates of Semantic Association versus Conceptual Similarity

PubMed Central

Jackson, Rebecca L.; Hoffman, Paul; Pobric, Gorana; Lambon Ralph, Matthew A.

2015-01-01

The ability to represent concepts and the relationships between them is critical to human cognition. How does the brain code relationships between items that share basic conceptual properties (e.g., dog and wolf) while simultaneously representing associative links between dissimilar items that co-occur in particular contexts (e.g., dog and bone)? To clarify the neural bases of these semantic components in neurologically intact participants, both types of semantic relationship were investigated in an fMRI study optimized for anterior temporal lobe (ATL) coverage. The clear principal finding was that the same core semantic network (ATL, superior temporal sulcus, ventral prefrontal cortex) was equivalently engaged when participants made semantic judgments on the basis of association or conceptual similarity. Direct comparisons revealed small, weaker differences for conceptual similarity > associative decisions (e.g., inferior prefrontal cortex) and associative > conceptual similarity (e.g., ventral parietal cortex) which appear to reflect graded differences in task difficulty. Indeed, once reaction time was entered as a covariate into the analysis, no associative versus category differences remained. The paper concludes with a discussion of how categorical/feature-based and associative relationships might be represented within a single, unified semantic system. PMID:25636912

Won't get fooled again: An event-related potential study of task and repetition effects on the semantic processing of items without semantics.

PubMed

Laszlo, Sarah; Stites, Mallory; Federmeier, Kara D

2012-01-01

A growing body of evidence suggests that semantic access is obligatory. Several studies have demonstrated that brain activity associated with semantic processing, measured in the N400 component of the event-related brain potential (ERP), is elicited even by meaningless, orthographically illegal strings, suggesting that semantic access is not gated by lexicality. However, the downstream consequences of that activity vary by item type, exemplified by the typical finding that N400 activity is reduced by repetition for words and pronounceable nonwords but not for illegal strings. We propose that this lack of repetition effect for illegal strings is caused not by lack of contact with semantics, but by the unrefined nature of that contact under conditions in which illegal strings can be readily categorised as task-irrelevant. To test this, we collected ERPs from participants performing a modified Lexical Decision Task, in which the presence of orthographically illegal acronyms rendered meaningless illegal strings more difficult lures than normal. Confirming our hypothesis, under these conditions illegal strings elicited robust N400 repetition effects, quantitatively and qualitatively similar to those elicited by words, pseudowords, and acronyms.

A Survey of Data Semantization in Internet of Things

PubMed Central

Shi, Feifei; Zhu, Tao

2018-01-01

With the development of Internet of Things (IoT), more and more sensors, actuators and mobile devices have been deployed into our daily lives. The result is that tremendous data are produced and it is urgent to dig out hidden information behind these volumous data. However, IoT data generated by multi-modal sensors or devices show great differences in formats, domains and types, which poses challenges for machines to process and understand. Therefore, adding semantics to Internet of Things becomes an overwhelming tendency. This paper provides a systematic review of data semantization in IoT, including its backgrounds, processing flows, prevalent techniques, applications, existing challenges and open issues. It surveys development status of adding semantics to IoT data, mainly referring to sensor data and points out current issues and challenges that are worth further study. PMID:29361772

A Survey of Data Semantization in Internet of Things.

PubMed

Shi, Feifei; Li, Qingjuan; Zhu, Tao; Ning, Huansheng

2018-01-22

With the development of Internet of Things (IoT), more and more sensors, actuators and mobile devices have been deployed into our daily lives. The result is that tremendous data are produced and it is urgent to dig out hidden information behind these volumous data. However, IoT data generated by multi-modal sensors or devices show great differences in formats, domains and types, which poses challenges for machines to process and understand. Therefore, adding semantics to Internet of Things becomes an overwhelming tendency. This paper provides a systematic review of data semantization in IoT, including its backgrounds, processing flows, prevalent techniques, applications, existing challenges and open issues. It surveys development status of adding semantics to IoT data, mainly referring to sensor data and points out current issues and challenges that are worth further study.

Comparing different types of source memory attributes in dementia of Alzheimer's type.

PubMed

Mammarella, Nicola; Fairfield, Beth; Di Domenico, Alberto

2012-04-01

Source monitoring (SM) refers to our ability to discriminate between memories from different sources. Twenty healthy high-cognitive functioning older adults, 20 healthy low-cognitive functioning older adults, and 20 older adults with dementia of Alzheimer's type (DAT) were asked to perform a series of SM tasks that varied in terms of the to-be-remembered source attribute (perceptual, spatial, temporal, semantic, social, and affective details). Results indicated that older DAT adults had greater difficulty in SM compared to the healthy control groups, especially with spatial and semantic details. Data are discussed in terms of the SM framework and suggest that poor memory for some types of source information may be considered as an important indicator of clinical memory function when assessing for the presence and severity of dementia.

Potential role of monkey inferior parietal neurons coding action semantic equivalences as precursors of parts of speech.

PubMed

Yamazaki, Yumiko; Yokochi, Hiroko; Tanaka, Michio; Okanoya, Kazuo; Iriki, Atsushi

2010-01-01

The anterior portion of the inferior parietal cortex possesses comprehensive representations of actions embedded in behavioural contexts. Mirror neurons, which respond to both self-executed and observed actions, exist in this brain region in addition to those originally found in the premotor cortex. We found that parietal mirror neurons responded differentially to identical actions embedded in different contexts. Another type of parietal mirror neuron represents an inverse and complementary property of responding equally to dissimilar actions made by itself and others for an identical purpose. Here, we propose a hypothesis that these sets of inferior parietal neurons constitute a neural basis for encoding the semantic equivalence of various actions across different agents and contexts. The neurons have mirror neuron properties, and they encoded generalization of agents, differentiation of outcomes, and categorization of actions that led to common functions. By integrating the activities of these mirror neurons with various codings, we further suggest that in the ancestral primates' brains, these various representations of meaningful action led to the gradual establishment of equivalence relations among the different types of actions, by sharing common action semantics. Such differential codings of the components of actions might represent precursors to the parts of protolanguage, such as gestural communication, which are shared among various members of a society. Finally, we suggest that the inferior parietal cortex serves as an interface between this action semantics system and other higher semantic systems, through common structures of action representation that mimic language syntax.

Potential role of monkey inferior parietal neurons coding action semantic equivalences as precursors of parts of speech

PubMed Central

Yamazaki, Yumiko; Yokochi, Hiroko; Tanaka, Michio; Okanoya, Kazuo; Iriki, Atsushi

2010-01-01

The anterior portion of the inferior parietal cortex possesses comprehensive representations of actions embedded in behavioural contexts. Mirror neurons, which respond to both self-executed and observed actions, exist in this brain region in addition to those originally found in the premotor cortex. We found that parietal mirror neurons responded differentially to identical actions embedded in different contexts. Another type of parietal mirror neuron represents an inverse and complementary property of responding equally to dissimilar actions made by itself and others for an identical purpose. Here, we propose a hypothesis that these sets of inferior parietal neurons constitute a neural basis for encoding the semantic equivalence of various actions across different agents and contexts. The neurons have mirror neuron properties, and they encoded generalization of agents, differentiation of outcomes, and categorization of actions that led to common functions. By integrating the activities of these mirror neurons with various codings, we further suggest that in the ancestral primates' brains, these various representations of meaningful action led to the gradual establishment of equivalence relations among the different types of actions, by sharing common action semantics. Such differential codings of the components of actions might represent precursors to the parts of protolanguage, such as gestural communication, which are shared among various members of a society. Finally, we suggest that the inferior parietal cortex serves as an interface between this action semantics system and other higher semantic systems, through common structures of action representation that mimic language syntax. PMID:20119879

Chemical Entity Semantic Specification: Knowledge representation for efficient semantic cheminformatics and facile data integration

PubMed Central

2011-01-01

Background Over the past several centuries, chemistry has permeated virtually every facet of human lifestyle, enriching fields as diverse as medicine, agriculture, manufacturing, warfare, and electronics, among numerous others. Unfortunately, application-specific, incompatible chemical information formats and representation strategies have emerged as a result of such diverse adoption of chemistry. Although a number of efforts have been dedicated to unifying the computational representation of chemical information, disparities between the various chemical databases still persist and stand in the way of cross-domain, interdisciplinary investigations. Through a common syntax and formal semantics, Semantic Web technology offers the ability to accurately represent, integrate, reason about and query across diverse chemical information. Results Here we specify and implement the Chemical Entity Semantic Specification (CHESS) for the representation of polyatomic chemical entities, their substructures, bonds, atoms, and reactions using Semantic Web technologies. CHESS provides means to capture aspects of their corresponding chemical descriptors, connectivity, functional composition, and geometric structure while specifying mechanisms for data provenance. We demonstrate that using our readily extensible specification, it is possible to efficiently integrate multiple disparate chemical data sources, while retaining appropriate correspondence of chemical descriptors, with very little additional effort. We demonstrate the impact of some of our representational decisions on the performance of chemically-aware knowledgebase searching and rudimentary reaction candidate selection. Finally, we provide access to the tools necessary to carry out chemical entity encoding in CHESS, along with a sample knowledgebase. Conclusions By harnessing the power of Semantic Web technologies with CHESS, it is possible to provide a means of facile cross-domain chemical knowledge integration with full preservation of data correspondence and provenance. Our representation builds on existing cheminformatics technologies and, by the virtue of RDF specification, remains flexible and amenable to application- and domain-specific annotations without compromising chemical data integration. We conclude that the adoption of a consistent and semantically-enabled chemical specification is imperative for surviving the coming chemical data deluge and supporting systems science research. PMID:21595881

Chemical Entity Semantic Specification: Knowledge representation for efficient semantic cheminformatics and facile data integration.

PubMed

Chepelev, Leonid L; Dumontier, Michel

2011-05-19

Over the past several centuries, chemistry has permeated virtually every facet of human lifestyle, enriching fields as diverse as medicine, agriculture, manufacturing, warfare, and electronics, among numerous others. Unfortunately, application-specific, incompatible chemical information formats and representation strategies have emerged as a result of such diverse adoption of chemistry. Although a number of efforts have been dedicated to unifying the computational representation of chemical information, disparities between the various chemical databases still persist and stand in the way of cross-domain, interdisciplinary investigations. Through a common syntax and formal semantics, Semantic Web technology offers the ability to accurately represent, integrate, reason about and query across diverse chemical information. Here we specify and implement the Chemical Entity Semantic Specification (CHESS) for the representation of polyatomic chemical entities, their substructures, bonds, atoms, and reactions using Semantic Web technologies. CHESS provides means to capture aspects of their corresponding chemical descriptors, connectivity, functional composition, and geometric structure while specifying mechanisms for data provenance. We demonstrate that using our readily extensible specification, it is possible to efficiently integrate multiple disparate chemical data sources, while retaining appropriate correspondence of chemical descriptors, with very little additional effort. We demonstrate the impact of some of our representational decisions on the performance of chemically-aware knowledgebase searching and rudimentary reaction candidate selection. Finally, we provide access to the tools necessary to carry out chemical entity encoding in CHESS, along with a sample knowledgebase. By harnessing the power of Semantic Web technologies with CHESS, it is possible to provide a means of facile cross-domain chemical knowledge integration with full preservation of data correspondence and provenance. Our representation builds on existing cheminformatics technologies and, by the virtue of RDF specification, remains flexible and amenable to application- and domain-specific annotations without compromising chemical data integration. We conclude that the adoption of a consistent and semantically-enabled chemical specification is imperative for surviving the coming chemical data deluge and supporting systems science research.

Neural bases of event knowledge and syntax integration in comprehension of complex sentences.

PubMed

Malaia, Evie; Newman, Sharlene

2015-01-01

Comprehension of complex sentences is necessarily supported by both syntactic and semantic knowledge, but what linguistic factors trigger a readers' reliance on a specific system? This functional neuroimaging study orthogonally manipulated argument plausibility and verb event type to investigate cortical bases of the semantic effect on argument comprehension during reading. The data suggest that telic verbs facilitate online processing by means of consolidating the event schemas in episodic memory and by easing the computation of syntactico-thematic hierarchies in the left inferior frontal gyrus. The results demonstrate that syntax-semantics integration relies on trade-offs among a distributed network of regions for maximum comprehension efficiency.

GOSAP: Gene Ontology-Based Semantic Alignment of Biological Pathways.

PubMed

Gamalielsson, Jonas; Olsson, Bjorn

2008-01-01

We present a new method for semantic comparison of biological pathways, aiming to discover evolutionary conservation of pathways between species. Our method uses all three sub-ontologies of Gene Ontology (GO) and a measure of semantic similarity to calculate match scores between gene products. These scores are used for finding local pairwise pathway alignments. This approach has the advantage of being applicable to all types of pathways where nodes are gene products, e.g., regulatory pathways, signalling pathways and metabolic enzyme-to-enzyme pathways. We demonstrate the usefulness of the method using regulatory and metabolic pathways from E. coli and S. cerevisiae as examples.

Looking for Structure: Is the Two-Word Stage of Language Development in Apes and Human Children the Same or Different?

ERIC Educational Resources Information Center

Patkowski, Mark

2014-01-01

Previously published corpora of two-word utterances by three chimpanzees and three human children were compared to determine whether, as has been claimed, apes possess the same basic syntactic and semantic capacities as 2-year old children. Some similarities were observed in the type of semantic relations expressed by the two groups; however,…

Comprehension of Concrete and Abstract Words in Patients with Selective Anterior Temporal Lobe Resection and in Patients with Selective Amygdalo-Hippocampectomy

ERIC Educational Resources Information Center

Loiselle, Magalie; Rouleau, Isabelle; Nguyen, Dang Khoa; Dubeau, Francois; Macoir, Joel; Whatmough, Christine; Lepore, Franco; Joubert, Sven

2012-01-01

The role of the anterior temporal lobe (ATL) in semantic memory is now firmly established. There is still controversy, however, regarding the specific role of this region in processing various types of concepts. There have been reports of patients suffering from semantic dementia (SD), a neurodegenerative condition in which the ATL is damaged…

Conceptual Model Formalization in a Semantic Interoperability Service Framework: Transforming Relational Database Schemas to OWL.

PubMed

Bravo, Carlos; Suarez, Carlos; González, Carolina; López, Diego; Blobel, Bernd

2014-01-01

Healthcare information is distributed through multiple heterogeneous and autonomous systems. Access to, and sharing of, distributed information sources are a challenging task. To contribute to meeting this challenge, this paper presents a formal, complete and semi-automatic transformation service from Relational Databases to Web Ontology Language. The proposed service makes use of an algorithm that allows to transform several data models of different domains by deploying mainly inheritance rules. The paper emphasizes the relevance of integrating the proposed approach into an ontology-based interoperability service to achieve semantic interoperability.

Statechart Analysis with Symbolic PathFinder

NASA Technical Reports Server (NTRS)

Pasareanu, Corina S.

2012-01-01

We report here on our on-going work that addresses the automated analysis and test case generation for software systems modeled using multiple Statechart formalisms. The work is motivated by large programs such as NASA Exploration, that involve multiple systems that interact via safety-critical protocols and are designed with different Statechart variants. To verify these safety-critical systems, we have developed Polyglot, a framework for modeling and analysis of model-based software written using different Statechart formalisms. Polyglot uses a common intermediate representation with customizable Statechart semantics and leverages the analysis and test generation capabilities of the Symbolic PathFinder tool. Polyglot is used as follows: First, the structure of the Statechart model (expressed in Matlab Stateflow or Rational Rhapsody) is translated into a common intermediate representation (IR). The IR is then translated into Java code that represents the structure of the model. The semantics are provided as "pluggable" modules.

["Prisms of Perception": multiple readings of mass media health messages in Northeast Brazil].

PubMed

Diógenes, Kátia Castelo Branco Machado; Nations, Marilyn

2011-12-01

This anthropological study from February 2009 to November 2010 revealed the comprehension and cultural critique of three mass media health campaigns in Northeast Brazil. Twenty-four ethnographic interviews were conducted, exploring the iconographic and semantic content of the campaigns in the Dendê community in Fortaleza, Ceará State, Brazil. The authors used Content Analysis; Systems of Signs, Significance, and Actions; and Contextualized Semantic Interpretation. There is a gap between the elaboration and reception of messages. Multiple interpretations occur (proximal reading, kaleidoscope of comprehension, and distant reading), depending on the reader's cognitive proximity to (or detachment from) the message. This "perceptual plasticity" arises from the creativity of popular imagination. Health professionals who hear rather than dismiss the "recipient's" subjective voice, which re-signifies authoritative messages, can penetrate the perception of the recipient's "visual world". In the context of poverty, this re-framing is essential for people to comprehend and proactively defend their own health.

Semantic preview benefit during reading.

PubMed

Hohenstein, Sven; Kliegl, Reinhold

2014-01-01

Word features in parafoveal vision influence eye movements during reading. The question of whether readers extract semantic information from parafoveal words was studied in 3 experiments by using a gaze-contingent display change technique. Subjects read German sentences containing 1 of several preview words that were replaced by a target word during the saccade to the preview (boundary paradigm). In the 1st experiment the preview word was semantically related or unrelated to the target. Fixation durations on the target were shorter for semantically related than unrelated previews, consistent with a semantic preview benefit. In the 2nd experiment, half the sentences were presented following the rules of German spelling (i.e., previews and targets were printed with an initial capital letter), and the other half were presented completely in lowercase. A semantic preview benefit was obtained under both conditions. In the 3rd experiment, we introduced 2 further preview conditions, an identical word and a pronounceable nonword, while also manipulating the text contrast. Whereas the contrast had negligible effects, fixation durations on the target were reliably different for all 4 types of preview. Semantic preview benefits were greater for pretarget fixations closer to the boundary (large preview space) and, although not as consistently, for long pretarget fixation durations (long preview time). The results constrain theoretical proposals about eye movement control in reading. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Older and Wiser: Older Adults’ Episodic Word Memory Benefits from Sentence Study Contexts

PubMed Central

Matzen, Laura E.; Benjamin, Aaron S.

2013-01-01

A hallmark of adaptive cognition is the ability to modulate learning in response to the demands posed by different types of tests and different types of materials. Here we evaluate how older adults process words and sentences differently by examining patterns of memory errors. In two experiments, we explored younger and older adults’ sensitivity to lures on a recognition test following study of words in these two types of contexts. Among the studied words were compound words such as “blackmail” and “jailbird” that were related to conjunction lures (e.g. “blackbird”) and semantic lures (e.g. “criminal”). Participants engaged in a recognition test that included old items, conjunction lures, semantic lures, and unrelated new items. In both experiments, younger and older adults had the same general pattern of memory errors: more incorrect endorsements of semantic than conjunction lures following sentence study and more incorrect endorsements of conjunction than semantic lures following list study. The similar pattern reveals that older and younger adults responded to the constraints of the two different study contexts in similar ways. However, while younger and older adults showed similar levels of memory performance for the list study context, the sentence study context elicited superior memory performance in the older participants. It appears as though memory tasks that take advantage of greater expertise in older adults--in this case, greater experience with sentence processing--can reveal superior memory performance in the elderly. PMID:23834493

The use of semantic- and phonological-based feature approaches to treat naming deficits in aphasia.

PubMed

Hashimoto, Naomi

2012-06-01

The aim of the study was to compare approaches highlighting either semantic or phonological features to treat naming deficits in aphasia. Treatment focused on improving picture naming. An alternating treatments design was used with a multiple baseline design across stimuli to examine effects of both approaches in two participants with varying degrees of anomia. The features approaches were modified in that three, rather than six, features were used. Significant differential effects were found across participants; this appeared to be a function of each participant's strengths or preferences over the course of treatment. Modest generalization effects were obtained for one participant. Naming error analyses revealed patterns suggestive of increased lexical access for both participants. These findings provide evidence that using a modified features-based protocol can improve naming when incorporating both semantic and phonological feature cues. Naming error patterns can provide additional evidence of improved naming during treatment.

A novel adaptive Cuckoo search for optimal query plan generation.

PubMed

Gomathi, Ramalingam; Sharmila, Dhandapani

2014-01-01

The emergence of multiple web pages day by day leads to the development of the semantic web technology. A World Wide Web Consortium (W3C) standard for storing semantic web data is the resource description framework (RDF). To enhance the efficiency in the execution time for querying large RDF graphs, the evolving metaheuristic algorithms become an alternate to the traditional query optimization methods. This paper focuses on the problem of query optimization of semantic web data. An efficient algorithm called adaptive Cuckoo search (ACS) for querying and generating optimal query plan for large RDF graphs is designed in this research. Experiments were conducted on different datasets with varying number of predicates. The experimental results have exposed that the proposed approach has provided significant results in terms of query execution time. The extent to which the algorithm is efficient is tested and the results are documented.

The SeaHorn Verification Framework

NASA Technical Reports Server (NTRS)

Gurfinkel, Arie; Kahsai, Temesghen; Komuravelli, Anvesh; Navas, Jorge A.

2015-01-01

In this paper, we present SeaHorn, a software verification framework. The key distinguishing feature of SeaHorn is its modular design that separates the concerns of the syntax of the programming language, its operational semantics, and the verification semantics. SeaHorn encompasses several novelties: it (a) encodes verification conditions using an efficient yet precise inter-procedural technique, (b) provides flexibility in the verification semantics to allow different levels of precision, (c) leverages the state-of-the-art in software model checking and abstract interpretation for verification, and (d) uses Horn-clauses as an intermediate language to represent verification conditions which simplifies interfacing with multiple verification tools based on Horn-clauses. SeaHorn provides users with a powerful verification tool and researchers with an extensible and customizable framework for experimenting with new software verification techniques. The effectiveness and scalability of SeaHorn are demonstrated by an extensive experimental evaluation using benchmarks from SV-COMP 2015 and real avionics code.

Semantic effects in sentence recall: the contribution of immediate vs delayed recall in language assessment.

PubMed

Polišenská, Kamila; Chiat, Shula; Comer, Amanda; McKenzie, Kirsty

2014-01-01

Sentence recall is increasingly used to assess language. It is widely debated what the task is actually testing, but one rarely explored aspect is the contribution of semantics to sentence recall. The few studies that have examined the role of semantics in sentence recall have employed an 'intrusion paradigm', following Potter and Lombardi (1990), and their paradigm relies on interference errors with conclusions based on an analysis of error patterns. We have instead manipulated the semantic plausibility of whole sentences to investigate the effects of semantics on immediate and delayed sentence recall. In Study 1, adults recalled semantically plausible and implausible sentences either immediately or after distracter tasks varying in lexical retrieval demands (backward counting and picture naming). Results revealed significant effects of plausibility, delay, and a significant interaction indicating increasing reliance on semantics as the demands of the distracter tasks increased. Study 2, conducted with 6-year-old children, employed delay conditions that were modified to avoid floor effects (delay with silence and forward counting) and a similar pattern of results emerged. This novel methodology provided robust evidence showing the effectiveness of delayed recall in the assessment of semantics and the effectiveness of immediate recall in the assessment of morphosyntax. The findings from our study clarify the linguistic mechanisms involved in immediate and delayed sentence recall, with implications for the use of recall tasks in language assessment. The reader will be able to: (i) define the difference between immediate and delayed sentence recall and different types of distractors, (ii) explain the utility of immediate and delayed recall sentence recall in language assessment, (iii) discuss suitability of delayed recall for the assessment of semantics. Copyright © 2014 Elsevier Inc. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rios Velazquez, E; Parmar, C; Narayan, V

Purpose: To compare the complementary value of quantitative radiomic features to that of radiologist-annotated semantic features in predicting EGFR mutations in lung adenocarcinomas. Methods: Pre-operative CT images of 258 lung adenocarcinoma patients were available. Tumors were segmented using the sing-click ensemble segmentation algorithm. A set of radiomic features was extracted using 3D-Slicer. Test-retest reproducibility and unsupervised dimensionality reduction were applied to select a subset of reproducible and independent radiomic features. Twenty semantic annotations were scored by an expert radiologist, describing the tumor, surrounding tissue and associated findings. Minimum-redundancy-maximum-relevance (MRMR) was used to identify the most informative radiomic and semantic featuresmore » in 172 patients (training-set, temporal split). Radiomic, semantic and combined radiomic-semantic logistic regression models to predict EGFR mutations were evaluated in and independent validation dataset of 86 patients using the area under the receiver operating curve (AUC). Results: EGFR mutations were found in 77/172 (45%) and 39/86 (45%) of the training and validation sets, respectively. Univariate AUCs showed a similar range for both feature types: radiomics median AUC = 0.57 (range: 0.50 – 0.62); semantic median AUC = 0.53 (range: 0.50 – 0.64, Wilcoxon p = 0.55). After MRMR feature selection, the best-performing radiomic, semantic, and radiomic-semantic logistic regression models, for EGFR mutations, showed a validation AUC of 0.56 (p = 0.29), 0.63 (p = 0.063) and 0.67 (p = 0.004), respectively. Conclusion: Quantitative volumetric and textural Radiomic features complement the qualitative and semi-quantitative radiologist annotations. The prognostic value of informative qualitative semantic features such as cavitation and lobulation is increased with the addition of quantitative textural features from the tumor region.« less

Knowledge-based approaches to the maintenance of a large controlled medical terminology.

PubMed Central

Cimino, J J; Clayton, P D; Hripcsak, G; Johnson, S B

1994-01-01

OBJECTIVE: Develop a knowledge-based representation for a controlled terminology of clinical information to facilitate creation, maintenance, and use of the terminology. DESIGN: The Medical Entities Dictionary (MED) is a semantic network, based on the Unified Medical Language System (UMLS), with a directed acyclic graph to represent multiple hierarchies. Terms from four hospital systems (laboratory, electrocardiography, medical records coding, and pharmacy) were added as nodes in the network. Additional knowledge about terms, added as semantic links, was used to assist in integration, harmonization, and automated classification of disparate terminologies. RESULTS: The MED contains 32,767 terms and is in active clinical use. Automated classification was successfully applied to terms for laboratory specimens, laboratory tests, and medications. One benefit of the approach has been the automated inclusion of medications into multiple pharmacologic and allergenic classes that were not present in the pharmacy system. Another benefit has been the reduction of maintenance efforts by 90%. CONCLUSION: The MED is a hybrid of terminology and knowledge. It provides domain coverage, synonymy, consistency of views, explicit relationships, and multiple classification while preventing redundancy, ambiguity (homonymy) and misclassification. PMID:7719786

Neural Substrates of Semantic Prospection – Evidence from the Dementias

PubMed Central

Irish, Muireann; Eyre, Nadine; Dermody, Nadene; O’Callaghan, Claire; Hodges, John R.; Hornberger, Michael; Piguet, Olivier

2016-01-01

The ability to envisage personally relevant events at a future time point represents an incredibly sophisticated cognitive endeavor and one that appears to be intimately linked to episodic memory integrity. Far less is known regarding the neurocognitive mechanisms underpinning the capacity to envisage non-personal future occurrences, known as semantic future thinking. Moreover the degree of overlap between the neural substrates supporting episodic and semantic forms of prospection remains unclear. To this end, we sought to investigate the capacity for episodic and semantic future thinking in Alzheimer’s disease (n = 15) and disease-matched behavioral-variant frontotemporal dementia (n = 15), neurodegenerative disorders characterized by significant medial temporal lobe (MTL) and frontal pathology. Participants completed an assessment of past and future thinking across personal (episodic) and non-personal (semantic) domains, as part of a larger neuropsychological battery investigating episodic and semantic processing, and their performance was contrasted with 20 age- and education-matched healthy older Controls. Participants underwent whole-brain T1-weighted structural imaging and voxel-based morphometry analysis was conducted to determine the relationship between gray matter integrity and episodic and semantic future thinking. Relative to Controls, both patient groups displayed marked future thinking impairments, extending across episodic and semantic domains. Analyses of covariance revealed that while episodic future thinking deficits could be explained solely in terms of episodic memory proficiency, semantic prospection deficits reflected the interplay between episodic and semantic processing. Distinct neural correlates emerged for each form of future simulation with differential involvement of prefrontal, lateral temporal, and medial temporal regions. Notably, the hippocampus was implicated irrespective of future thinking domain, with the suggestion of lateralization effects depending on the type of information being simulated. Whereas episodic future thinking related to right hippocampal integrity, semantic future thinking was found to relate to left hippocampal integrity. Our findings support previous observations of significant MTL involvement for semantic forms of prospection and point to distinct neurocognitive mechanisms which must be functional to support future-oriented forms of thought across personal and non-personal contexts. PMID:27252632

Did you or I say pretty, rude or brief? An ERP study of the effects of speaker's identity on emotional word processing.

PubMed

Pinheiro, Ana P; Rezaii, Neguine; Nestor, Paul G; Rauber, Andréia; Spencer, Kevin M; Niznikiewicz, Margaret

2016-02-01

During speech comprehension, multiple cues need to be integrated at a millisecond speed, including semantic information, as well as voice identity and affect cues. A processing advantage has been demonstrated for self-related stimuli when compared with non-self stimuli, and for emotional relative to neutral stimuli. However, very few studies investigated self-other speech discrimination and, in particular, how emotional valence and voice identity interactively modulate speech processing. In the present study we probed how the processing of words' semantic valence is modulated by speaker's identity (self vs. non-self voice). Sixteen healthy subjects listened to 420 prerecorded adjectives differing in voice identity (self vs. non-self) and semantic valence (neutral, positive and negative), while electroencephalographic data were recorded. Participants were instructed to decide whether the speech they heard was their own (self-speech condition), someone else's (non-self speech), or if they were unsure. The ERP results demonstrated interactive effects of speaker's identity and emotional valence on both early (N1, P2) and late (Late Positive Potential - LPP) processing stages: compared with non-self speech, self-speech with neutral valence elicited more negative N1 amplitude, self-speech with positive valence elicited more positive P2 amplitude, and self-speech with both positive and negative valence elicited more positive LPP. ERP differences between self and non-self speech occurred in spite of similar accuracy in the recognition of both types of stimuli. Together, these findings suggest that emotion and speaker's identity interact during speech processing, in line with observations of partially dependent processing of speech and speaker information. Copyright © 2016. Published by Elsevier Inc.

Arbitrary and semantic associations in subjective memory impairment and amnestic mild cognitive impairment among Taiwanese individuals: A cross-sectional study.

PubMed

Chang, Hsin-Te; Chen, Ta-Fu; Cheng, Ting-Wen; Lai, Ya-Mei; Hua, Mau-Sun

2018-05-01

Researchers have recently proposed a preclinical stage of dementia of Alzheimer's type (DAT), referred to as subjective memory impairment (SMI), with the aim of developing methods for the early detection of DAT and subsequent intervention. It has been proposed that the objective memory functions of individuals with SMI are normal; however, arbitrary and semantic associations are both used to describe the processes of memory. No previous studies have investigated these processes among individuals with SMI. Cross-sectional analysis was used to compare the memory function of individuals with SMI, amnestic mild cognitive impairment (aMCI), or DAT. One hundred and eighty-three participants were recruited from the Memory Clinic of National Taiwan University Hospital and communities in northern Taiwan, including individuals with no memory complaints (HC, n = 30) and individuals with SMI (n = 61), aMCI-single domain (n = 24), aMCI-multiple domain (n = 33), or DAT (n = 35). The Word Sequence Learning Test (WSLT) was used to assess the formation of arbitrary associations and the Logical Memory subtest of the Wechsler Memory Scale-Third Edition was used to assess the formation of semantic associations. Compared to the HC group, the SMI group performed poorly only on the WSLT, whereas the other groups performed poorly on both of the memory tasks. This study demonstrated that SMI individuals tend to perform poorly in the formation of arbitrary associations. Our findings suggest that tasks requiring arbitrary associations may provide greater sensitivity in the detection cognitive changes associated with preclinical DAT. Copyright © 2017. Published by Elsevier B.V.

Ontology Design Patterns: Bridging the Gap Between Local Semantic Use Cases and Large-Scale, Long-Term Data Integration

NASA Astrophysics Data System (ADS)

Shepherd, Adam; Arko, Robert; Krisnadhi, Adila; Hitzler, Pascal; Janowicz, Krzysztof; Chandler, Cyndy; Narock, Tom; Cheatham, Michelle; Schildhauer, Mark; Jones, Matt; Raymond, Lisa; Mickle, Audrey; Finin, Tim; Fils, Doug; Carbotte, Suzanne; Lehnert, Kerstin

2015-04-01

Integrating datasets for new use cases is one of the common drivers for adopting semantic web technologies. Even though linked data principles enables this type of activity over time, the task of reconciling new ontological commitments for newer use cases can be daunting. This situation was faced by the Biological and Chemical Oceanography Data Management Office (BCO-DMO) as it sought to integrate its existing linked data with other data repositories to address newer scientific use cases as a partner in the GeoLink Project. To achieve a successful integration with other GeoLink partners, BCO-DMO's metadata would need to be described using the new ontologies developed by the GeoLink partners - a situation that could impact semantic inferencing, pre-existing software and external users of BCO-DMO's linked data. This presentation describes the process of how GeoLink is bridging the gap between local, pre-existing ontologies to achieve scientific metadata integration for all its partners through the use of ontology design patterns. GeoLink, an NSF EarthCube Building Block, brings together experts from the geosciences, computer science, and library science in an effort to improve discovery and reuse of data and knowledge. Its participating repositories include content from field expeditions, laboratory analyses, journal publications, conference presentations, theses/reports, and funding awards that span scientific studies from marine geology to marine ecology and biogeochemistry to paleoclimatology. GeoLink's outcomes include a set of reusable ontology design patterns (ODPs) that describe core geoscience concepts, a network of Linked Data published by participating repositories using those ODPs, and tools to facilitate discovery of related content in multiple repositories.

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs.

PubMed

Chen, Liang-Chieh; Papandreou, George; Kokkinos, Iasonas; Murphy, Kevin; Yuille, Alan L

2018-04-01

In this work we address the task of semantic image segmentation with Deep Learning and make three main contributions that are experimentally shown to have substantial practical merit. First, we highlight convolution with upsampled filters, or 'atrous convolution', as a powerful tool in dense prediction tasks. Atrous convolution allows us to explicitly control the resolution at which feature responses are computed within Deep Convolutional Neural Networks. It also allows us to effectively enlarge the field of view of filters to incorporate larger context without increasing the number of parameters or the amount of computation. Second, we propose atrous spatial pyramid pooling (ASPP) to robustly segment objects at multiple scales. ASPP probes an incoming convolutional feature layer with filters at multiple sampling rates and effective fields-of-views, thus capturing objects as well as image context at multiple scales. Third, we improve the localization of object boundaries by combining methods from DCNNs and probabilistic graphical models. The commonly deployed combination of max-pooling and downsampling in DCNNs achieves invariance but has a toll on localization accuracy. We overcome this by combining the responses at the final DCNN layer with a fully connected Conditional Random Field (CRF), which is shown both qualitatively and quantitatively to improve localization performance. Our proposed "DeepLab" system sets the new state-of-art at the PASCAL VOC-2012 semantic image segmentation task, reaching 79.7 percent mIOU in the test set, and advances the results on three other datasets: PASCAL-Context, PASCAL-Person-Part, and Cityscapes. All of our code is made publicly available online.

Community cyberinfrastructure for Advanced Microbial Ecology Research and Analysis: the CAMERA resource

PubMed Central

Sun, Shulei; Chen, Jing; Li, Weizhong; Altintas, Ilkay; Lin, Abel; Peltier, Steve; Stocks, Karen; Allen, Eric E.; Ellisman, Mark; Grethe, Jeffrey; Wooley, John

2011-01-01

The Community Cyberinfrastructure for Advanced Microbial Ecology Research and Analysis (CAMERA, http://camera.calit2.net/) is a database and associated computational infrastructure that provides a single system for depositing, locating, analyzing, visualizing and sharing data about microbial biology through an advanced web-based analysis portal. CAMERA collects and links metadata relevant to environmental metagenome data sets with annotation in a semantically-aware environment allowing users to write expressive semantic queries against the database. To meet the needs of the research community, users are able to query metadata categories such as habitat, sample type, time, location and other environmental physicochemical parameters. CAMERA is compliant with the standards promulgated by the Genomic Standards Consortium (GSC), and sustains a role within the GSC in extending standards for content and format of the metagenomic data and metadata and its submission to the CAMERA repository. To ensure wide, ready access to data and annotation, CAMERA also provides data submission tools to allow researchers to share and forward data to other metagenomics sites and community data archives such as GenBank. It has multiple interfaces for easy submission of large or complex data sets, and supports pre-registration of samples for sequencing. CAMERA integrates a growing list of tools and viewers for querying, analyzing, annotating and comparing metagenome and genome data. PMID:21045053

Community cyberinfrastructure for Advanced Microbial Ecology Research and Analysis: the CAMERA resource.

PubMed

Sun, Shulei; Chen, Jing; Li, Weizhong; Altintas, Ilkay; Lin, Abel; Peltier, Steve; Stocks, Karen; Allen, Eric E; Ellisman, Mark; Grethe, Jeffrey; Wooley, John

2011-01-01

The Community Cyberinfrastructure for Advanced Microbial Ecology Research and Analysis (CAMERA, http://camera.calit2.net/) is a database and associated computational infrastructure that provides a single system for depositing, locating, analyzing, visualizing and sharing data about microbial biology through an advanced web-based analysis portal. CAMERA collects and links metadata relevant to environmental metagenome data sets with annotation in a semantically-aware environment allowing users to write expressive semantic queries against the database. To meet the needs of the research community, users are able to query metadata categories such as habitat, sample type, time, location and other environmental physicochemical parameters. CAMERA is compliant with the standards promulgated by the Genomic Standards Consortium (GSC), and sustains a role within the GSC in extending standards for content and format of the metagenomic data and metadata and its submission to the CAMERA repository. To ensure wide, ready access to data and annotation, CAMERA also provides data submission tools to allow researchers to share and forward data to other metagenomics sites and community data archives such as GenBank. It has multiple interfaces for easy submission of large or complex data sets, and supports pre-registration of samples for sequencing. CAMERA integrates a growing list of tools and viewers for querying, analyzing, annotating and comparing metagenome and genome data.

Beneficial effects of semantic memory support on older adults' episodic memory: Differential patterns of support of item and associative information.

PubMed

Mohanty, Praggyan Pam; Naveh-Benjamin, Moshe; Ratneshwar, Srinivasan

2016-02-01

The effects of two types of semantic memory support-meaningfulness of an item and relatedness between items-in mitigating age-related deficits in item and associative, memory are examined in a marketing context. In Experiment 1, participants studied less (vs. more) meaningful brand logo graphics (pictures) paired with meaningful brand names (words) and later were assessed by item (old/new) and associative (intact/recombined) memory recognition tests. Results showed that meaningfulness of items eliminated age deficits in item memory, while equivalently boosting associative memory for older and younger adults. Experiment 2, in which related and unrelated brand logo graphics and brand name pairs served as stimuli, revealed that relatedness between items eliminated age deficits in associative memory, while improving to the same degree item memory in older and younger adults. Experiment 2 also provided evidence for a probable boundary condition that could reconcile seemingly contradictory extant results. Overall, these experiments provided evidence that although the two types of semantic memory support can improve both item and associative memory in older and younger adults, older adults' memory deficits can be eliminated when the type of support provided is compatible with the type of information required to perform well on the test. (c) 2016 APA, all rights reserved).

Investigating Mixture Interactions of Astringent Stimuli Using the Isobole Approach

PubMed Central

Fleming, Erin E.; Ziegler, Gregory R.

2016-01-01

Abstract Astringents (alum, malic acid, tannic acid) representing 3 broad classes (multivalent salts, organic acids, and polyphenols) were characterized alone, and as 2- and 3-component mixtures using isoboles. In experiment 1, participants rated 7 attributes (“astringency,” the sub-qualities “drying,” “roughing,” and “puckering,” and the side tastes “bitterness,” “sourness,” and “sweetness”) using direct scaling. Quality specific power functions were calculated for each stimulus. In experiment 2, the same participants characterized 2- and 3-component mixtures. Multiple factor analysis (MFA) and hierarchical clustering on attribute ratings across stimuli indicate “astringency” is highly related to “bitterness” as well as “puckering,” and the subqualities “drying” and “roughing” are somewhat redundant. Moreover, power functions were used to calculate indices of interaction (I) for each attribute/mixture combination. For “astringency,” there was evidence of antagonism, regardless of the type of mixture. Conversely, for subqualities, the pattern of interaction depended on the mixture type. Alum/tannic acid and tannic acid/malic acid mixtures showed evidence of synergy for “drying” and “roughing”; alum/malic acid mixtures showed evidence of antagonism for “drying,” “roughing,” and “puckering.” Collectively, these data clarify some semantic ambiguity regarding astringency and its subqualities, as well as the nature of interactions of among different types of astringents. Present data are not inconsistent with the idea that astringency arises from multiple mechanisms, although it remains to be determined whether the synergy observed here might reflect simultaneous activation of these multiple mechanisms. PMID:27252355

Autobiographical memory and well-being in aging: The central role of semantic self-images.

PubMed

Rathbone, Clare J; Holmes, Emily A; Murphy, Susannah E; Ellis, Judi A

2015-05-01

Higher levels of well-being are associated with longer life expectancies and better physical health. Previous studies suggest that processes involving the self and autobiographical memory are related to well-being, yet these relationships are poorly understood. The present study tested 32 older and 32 younger adults using scales measuring well-being and the affective valence of two types of autobiographical memory: episodic autobiographical memories and semantic self-images. Results showed that valence of semantic self-images, but not episodic autobiographical memories, was highly correlated with well-being, particularly in older adults. In contrast, well-being in older adults was unrelated to performance across a range of standardised memory tasks. These results highlight the role of semantic self-images in well-being, and have implications for the development of therapeutic interventions for well-being in aging. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Semantic Theme Analysis of Pilot Incident Reports

NASA Technical Reports Server (NTRS)

Thirumalainambi, Rajkumar

2009-01-01

Pilots report accidents or incidents during take-off, on flight and landing to airline authorities and Federal aviation authority as well. The description of pilot reports for an incident contains technical terms related to Flight instruments and operations. Normal text mining approaches collect keywords from text documents and relate them among documents that are stored in database. Present approach will extract specific theme analysis of incident reports and semantically relate hierarchy of terms assigning weights of themes. Once the theme extraction has been performed for a given document, a unique key can be assigned to that document to cross linking the documents. Semantic linking will be used to categorize the documents based on specific rules that can help an end-user to analyze certain types of accidents. This presentation outlines the architecture of text mining for pilot incident reports for autonomous categorization of pilot incident reports using semantic theme analysis.

Un Marco Abierto: Un Manual de Matematicas y Ciencas Utilizando Inteligencias Multiples Disenado para Estudiantes Bilingues de Educacion General y Especial (An Open Framework: A Math and Science Manual Utilizing Multiple Intelligences Designed for Bilingual Students in General and Special Education).

ERIC Educational Resources Information Center

New York City Board of Education, Brooklyn, NY. Office of Bilingual Education.

This manual incorporates a Multiple Intelligences perspective into its presentation of themes and lesson ideas for Spanish-English bilingual elementary school students in grades 4-8 and is designed for both gifted and special education uses. Each unit includes practice activities, semantic maps to illustrate and help organize ideas as well as…

Porting Social Media Contributions with SIOC

NASA Astrophysics Data System (ADS)

Bojars, Uldis; Breslin, John G.; Decker, Stefan

Social media sites, including social networking sites, have captured the attention of millions of users as well as billions of dollars in investment and acquisition. To better enable a user's access to multiple sites, portability between social media sites is required in terms of both (1) the personal profiles and friend networks and (2) a user's content objects expressed on each site. This requires representation mechanisms to interconnect both people and objects on the Web in an interoperable, extensible way. The Semantic Web provides the required representation mechanisms for portability between social media sites: it links people and objects to record and represent the heterogeneous ties that bind each to the other. The FOAF (Friend-of-a-Friend) initiative provides a solution to the first requirement, and this paper discusses how the SIOC (Semantically-Interlinked Online Communities) project can address the latter. By using agreed-upon Semantic Web formats like FOAF and SIOC to describe people, content objects, and the connections that bind them together, social media sites can interoperate and provide portable data by appealing to some common semantics. In this paper, we will discuss the application of Semantic Web technology to enhance current social media sites with semantics and to address issues with portability between social media sites. It has been shown that social media sites can serve as rich data sources for SIOC-based applications such as the SIOC Browser, but in the other direction, we will now show how SIOC data can be used to represent and port the diverse social media contributions (SMCs) made by users on heterogeneous sites.

Exploiting semantic linkages among multiple sources for semantic information retrieval

NASA Astrophysics Data System (ADS)

Li, JianQiang; Yang, Ji-Jiang; Liu, Chunchen; Zhao, Yu; Liu, Bo; Shi, Yuliang

2014-07-01

The vision of the Semantic Web is to build a global Web of machine-readable data to be consumed by intelligent applications. As the first step to make this vision come true, the initiative of linked open data has fostered many novel applications aimed at improving data accessibility in the public Web. Comparably, the enterprise environment is so different from the public Web that most potentially usable business information originates in an unstructured form (typically in free text), which poses a challenge for the adoption of semantic technologies in the enterprise environment. Considering that the business information in a company is highly specific and centred around a set of commonly used concepts, this paper describes a pilot study to migrate the concept of linked data into the development of a domain-specific application, i.e. the vehicle repair support system. The set of commonly used concepts, including the part name of a car and the phenomenon term on the car repairing, are employed to build the linkage between data and documents distributed among different sources, leading to the fusion of documents and data across source boundaries. Then, we describe the approaches of semantic information retrieval to consume these linkages for value creation for companies. The experiments on two real-world data sets show that the proposed approaches outperform the best baseline 6.3-10.8% and 6.4-11.1% in terms of top five and top 10 precisions, respectively. We believe that our pilot study can serve as an important reference for the development of similar semantic applications in an enterprise environment.

Oxytocin Modulates Semantic Integration in Speech Comprehension.

PubMed

Ye, Zheng; Stolk, Arjen; Toni, Ivan; Hagoort, Peter

2017-02-01

Listeners interpret utterances by integrating information from multiple sources including word level semantics and world knowledge. When the semantics of an expression is inconsistent with their knowledge about the world, the listener may have to search through the conceptual space for alternative possible world scenarios that can make the expression more acceptable. Such cognitive exploration requires considerable computational resources and might depend on motivational factors. This study explores whether and how oxytocin, a neuropeptide known to influence social motivation by reducing social anxiety and enhancing affiliative tendencies, can modulate the integration of world knowledge and sentence meanings. The study used a between-participant double-blind randomized placebo-controlled design. Semantic integration, indexed with magnetoencephalography through the N400m marker, was quantified while 45 healthy male participants listened to sentences that were either congruent or incongruent with facts of the world, after receiving intranasally delivered oxytocin or placebo. Compared with congruent sentences, world knowledge incongruent sentences elicited a stronger N400m signal from the left inferior frontal and anterior temporal regions and medial pFC (the N400m effect) in the placebo group. Oxytocin administration significantly attenuated the N400m effect at both sensor and cortical source levels throughout the experiment, in a state-like manner. Additional electrophysiological markers suggest that the absence of the N400m effect in the oxytocin group is unlikely due to the lack of early sensory or semantic processing or a general downregulation of attention. These findings suggest that oxytocin drives listeners to resolve challenges of semantic integration, possibly by promoting the cognitive exploration of alternative possible world scenarios.

Concepts, Control, and Context: A Connectionist Account of Normal and Disordered Semantic Cognition

PubMed Central

2018-01-01

Semantic cognition requires conceptual representations shaped by verbal and nonverbal experience and executive control processes that regulate activation of knowledge to meet current situational demands. A complete model must also account for the representation of concrete and abstract words, of taxonomic and associative relationships, and for the role of context in shaping meaning. We present the first major attempt to assimilate all of these elements within a unified, implemented computational framework. Our model combines a hub-and-spoke architecture with a buffer that allows its state to be influenced by prior context. This hybrid structure integrates the view, from cognitive neuroscience, that concepts are grounded in sensory-motor representation with the view, from computational linguistics, that knowledge is shaped by patterns of lexical co-occurrence. The model successfully codes knowledge for abstract and concrete words, associative and taxonomic relationships, and the multiple meanings of homonyms, within a single representational space. Knowledge of abstract words is acquired through (a) their patterns of co-occurrence with other words and (b) acquired embodiment, whereby they become indirectly associated with the perceptual features of co-occurring concrete words. The model accounts for executive influences on semantics by including a controlled retrieval mechanism that provides top-down input to amplify weak semantic relationships. The representational and control elements of the model can be damaged independently, and the consequences of such damage closely replicate effects seen in neuropsychological patients with loss of semantic representation versus control processes. Thus, the model provides a wide-ranging and neurally plausible account of normal and impaired semantic cognition. PMID:29733663

Semantic representation in the white matter pathway

PubMed Central

Fang, Yuxing; Wang, Xiaosha; Zhong, Suyu; Song, Luping; Han, Zaizhu; Gong, Gaolang

2018-01-01

Object conceptual processing has been localized to distributed cortical regions that represent specific attributes. A challenging question is how object semantic space is formed. We tested a novel framework of representing semantic space in the pattern of white matter (WM) connections by extending the representational similarity analysis (RSA) to structural lesion pattern and behavioral data in 80 brain-damaged patients. For each WM connection, a neural representational dissimilarity matrix (RDM) was computed by first building machine-learning models with the voxel-wise WM lesion patterns as features to predict naming performance of a particular item and then computing the correlation between the predicted naming score and the actual naming score of another item in the testing patients. This correlation was used to build the neural RDM based on the assumption that if the connection pattern contains certain aspects of information shared by the naming processes of these two items, models trained with one item should also predict naming accuracy of the other. Correlating the neural RDM with various cognitive RDMs revealed that neural patterns in several WM connections that connect left occipital/middle temporal regions and anterior temporal regions associated with the object semantic space. Such associations were not attributable to modality-specific attributes (shape, manipulation, color, and motion), to peripheral picture-naming processes (picture visual similarity, phonological similarity), to broad semantic categories, or to the properties of the cortical regions that they connected, which tended to represent multiple modality-specific attributes. That is, the semantic space could be represented through WM connection patterns across cortical regions representing modality-specific attributes. PMID:29624578

Tools for Testing Denotational Semantic Definitions of Programming Languages.

DTIC Science & Technology

1983-05-01

16. DISTRIBUTION STATEMENT (of this Report) This document is approved for public release and sale : distribution is unlimited. 17. DISTRIBUTION...decl Itun ...type_deci prodjtype_decl sumjype..decl Iseq .. type..deci I pkgspec I pkg...body I use..clause type...decl: (TDECL typejid type..def

Effects of level of processing at encoding and types of retrieval task in mild cognitive impairment and normal aging.

PubMed

Froger, Charlotte; Taconnat, Laurence; Landré, Lionel; Beigneux, Katia; Isingrini, Michel

2009-04-01

A total of 16 young (M = 27.25 years), 13 healthy elderly (M = 75.38 years), and 10 older adults with probable mild cognitive impairment (MCI; M = 78.6 years) carried out a task under two different encoding conditions (shallow vs. semantic) and two retrieval conditions (free recall vs. recognition). For the shallow condition, participants had to decide whether the first or last letter of each word in a list was "E." For the semantic condition, they had to decide whether each word represented a concrete or abstract entity. The MCI group was only able to benefit from semantic encoding to the same extent as the healthy older adults in the recognition task, whereas the younger and healthy older adults benefited in both retrieval tasks. These results suggest that the MCI group required cognitive support at retrieval to make effective use of semantic processing carried out at encoding. In the discussion, we suggest that adults with MCI engage more in deep processing, using the semantic network, than hitherto thought.

The contribution of the left anterior ventrolateral temporal lobe to the retrieval of personal semantics.

PubMed

Grilli, Matthew D; Bercel, John J; Wank, Aubrey A; Rapcsak, Steven Z

2018-06-04

Autobiographical facts and personal trait knowledge are conceptualized as distinct types of personal semantics, but the cognitive and neural mechanisms that separate them remain underspecified. One distinction may be their level of specificity, with autobiographical facts reflecting idiosyncratic conceptual knowledge and personal traits representing basic level category knowledge about the self. Given the critical role of the left anterior ventrolateral temporal lobe (AVTL) in the storage and retrieval of semantic information about unique entities, we hypothesized that knowledge of autobiographical facts may depend on the integrity of this region to a greater extent than personal traits. To provide neuropsychological evidence relevant to this issue, we investigated personal semantics, semantic knowledge of non-personal unique entities, and episodic memory in two individuals with well-defined left (MK) versus right (DW) AVTL lesions. Relative to controls, MK demonstrated preserved personal trait knowledge but impaired "experience-far" (i.e., spatiotemporal independent) autobiographical fact knowledge, semantic memory for non-personal unique entities, and episodic memory. In contrast, both experience-far autobiographical facts and personal traits were spared in DW, whereas episodic memory and aspects of semantic memory for non-personal unique entities were impaired. These findings support the notion that autobiographical facts and personal traits have distinct cognitive features and neural mechanisms. They also suggest a common organizing principle for personal and non-personal semantics, namely the specificity of such knowledge to an entity, which is reflected in the contribution of the left AVTL to retrieval. Copyright © 2018 Elsevier Ltd. All rights reserved.

The word processing deficit in semantic dementia: all categories are equal, but some categories are more equal than others.

PubMed

Pulvermüller, Friedemann; Cooper-Pye, Elisa; Dine, Clare; Hauk, Olaf; Nestor, Peter J; Patterson, Karalyn

2010-09-01

It has been claimed that semantic dementia (SD), the temporal variant of fronto-temporal dementia, is characterized by an across-the-board deficit affecting all types of conceptual knowledge. We here confirm this generalized deficit but also report differential degrees of impairment in processing specific semantic word categories in a case series of SD patients (N = 11). Within the domain of words with strong visually grounded meaning, the patients' lexical decision accuracy was more impaired for color-related than for form-related words. Likewise, within the domain of action verbs, the patients' performance was worse for words referring to face movements and speech acts than for words semantically linked to actions performed with the hand and arm. Psycholinguistic properties were matched between the stimulus groups entering these contrasts; an explanation for the differential degrees of impairment must therefore involve semantic features of the words in the different conditions. Furthermore, this specific pattern of deficits cannot be captured by classic category distinctions such as nouns versus verbs or living versus nonliving things. Evidence from previous neuroimaging research indicates that color- and face/speech-related words, respectively, draw most heavily on anterior-temporal and inferior-frontal areas, the structures most affected in SD. Our account combines (a) the notion of an anterior-temporal amodal semantic "hub" to explain the profound across-the-board deficit in SD word processing, with (b) a semantic topography model of category-specific circuits whose cortical distributions reflect semantic features of the words and concepts represented.

Verbal Fluency Performance in Amnestic MCI and Older Adults with Cognitive Complaints

PubMed Central

Nutter-Upham, Katherine E.; Saykin, Andrew J.; Rabin, Laura A.; Roth, Robert M.; Wishart, Heather A.; Pare, Nadia; Flashman, Laura A.

2009-01-01

Verbal fluency tests are employed regularly during neuropsychological assessments of older adults, and deficits are a common finding in patients with Alzheimer’s disease (AD). Little extant research, however, has investigated verbal fluency ability and subtypes in preclinical stages of neurodegenerative disease. We examined verbal fluency performance in 107 older adults with amnestic mild cognitive impairment (MCI, n = 37), cognitive complaints (CC, n = 37) despite intact neuropsychological functioning, and demographically-matched healthy controls (HC, n = 33). Participants completed fluency tasks with letter, semantic category, and semantic switching constraints. Both phonemic and semantic fluency were statistically (but not clinically) reduced in amnestic MCI relative to cognitively intact older adults, indicating subtle changes in both the quality of the semantic store and retrieval slowing. Investigation of the underlying constructs of verbal fluency yielded two factors: Switching (including switching and shifting tasks) and Production (including letter, category, and action naming tasks), and both factors discriminated MCI from HC albeit to different degrees. Correlational findings further suggested that all fluency tasks involved executive control to some degree, while those with an added executive component (i.e., switching and shifting) were less dependent on semantic knowledge. Overall, our findings highlight the importance of including multiple verbal fluency tests in assessment batteries targeting preclinical dementia populations and suggest that individual fluency tasks may tap specific cognitive processes. PMID:18339515

On the universal structure of human lexical semantics

PubMed Central

Sutton, Logan; Smith, Eric; Moore, Cristopher; Wilkins, Jon F.; Maddieson, Ian; Croft, William

2016-01-01

How universal is human conceptual structure? The way concepts are organized in the human brain may reflect distinct features of cultural, historical, and environmental background in addition to properties universal to human cognition. Semantics, or meaning expressed through language, provides indirect access to the underlying conceptual structure, but meaning is notoriously difficult to measure, let alone parameterize. Here, we provide an empirical measure of semantic proximity between concepts using cross-linguistic dictionaries to translate words to and from languages carefully selected to be representative of worldwide diversity. These translations reveal cases where a particular language uses a single “polysemous” word to express multiple concepts that another language represents using distinct words. We use the frequency of such polysemies linking two concepts as a measure of their semantic proximity and represent the pattern of these linkages by a weighted network. This network is highly structured: Certain concepts are far more prone to polysemy than others, and naturally interpretable clusters of closely related concepts emerge. Statistical analysis of the polysemies observed in a subset of the basic vocabulary shows that these structural properties are consistent across different language groups, and largely independent of geography, environment, and the presence or absence of a literary tradition. The methods developed here can be applied to any semantic domain to reveal the extent to which its conceptual structure is, similarly, a universal attribute of human cognition and language use. PMID:26831113

Semantic Web and Inferencing Technologies for Department of Defense Systems

DTIC Science & Technology

2014-10-01

contact report for a specific type of aircraft . Intra-domain-specific metadata in the threat data domain might be used to categorize the contact...DEFENSE SYSTEMS by Duane Davis October 2014 Approved for public release; distribution is unlimited Prepared for: The NPS Center for Multi-INT...TITLE AND SUBTITLE Semantic Web and Inferencing Technologies for Department of Defense Systems 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c

Chemical markup, XML, and the world wide web. 6. CMLReact, an XML vocabulary for chemical reactions.

PubMed

Holliday, Gemma L; Murray-Rust, Peter; Rzepa, Henry S

2006-01-01

A set of components (CMLReact) for managing chemical and biochemical reactions has been added to CML. These can be combined to support most of the strategies for the formal representation of reactions. The elements, attributes, and types are formally defined as XMLSchema components, and their semantics are developed. New syntax and semantics in CML are reported and illustrated with 10 examples.